The Future of Education (According to AI)

The Future of Education (According to AI)
Jared O'Leary
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In this episode I ask Bard and ChatGPT what the future of education looks like and probe these platforms to get a pulse on what computer science education looks like according to responses from large language models.

  • AI like chat GPT and Bard have been

    described as autocorrect on steroids but

    before the game sentience and end all of

    humanity as we know it we can use large

    language models like Chachi bati and

    Bard to simulate how a typical person

    within a field might respond to some

    different questions today I'm going to

    ask some questions from Bard and chat

    GPT to kind of like get a general

    understanding of what the discourse is

    around some questions about the future

    of Education as well as some questions

    around Computer Science Education now if

    you're not interested in all the

    questions that I'm about to ask I do

    include time to stamp so you can

    actually jump to a specific question

    that might interest you you can also

    leave a comment in the YouTube

    description if you are interested in

    sharing your own thoughts and what you

    think about the future of Education or

    just computer science education in

    general what did you agree with and what

    did you disagree with in particular now

    the first question that I asked AI was

    what will teaching and learning look

    like 10 years from now now most of the

    responses that are received kind of came

    across as if like a marketing person

    would kind of write something that they

    don't necessarily know a lot about so it

    skims the surface levels of

    understandings of a topic area without

    actually diving deep into it it's

    basically like a blog post that like

    some kind of marketer might write that

    really doesn't do much other than

    improve SEO which is search engine

    optimization so Bard responded to this

    question by saying that there's going to

    be more of a focus on personalized

    learning so students are going to have

    more control over what they're going to

    be able to do over the classroom I hope

    that's the case that's something I've

    been arguing for for years on this

    podcast as well as just in the

    presentations of Publications I do but

    if there was more personalized learning

    fantastic that'd be phenomenal win for

    all the students out there the next

    thing that Bard mentioned was that

    there's going to be more emphasis on

    critical thinking and problem solving

    such as engaging in project-based

    learning and problem-based learning now

    this I definitely see being more of a

    focus because there's going to be a lot

    more questioning in terms of was this

    actually said by this person or was it

    generated by AI is this video of

    somebody like robbing a bank actually

    somebody robbing the bank or is this

    just generated by AI Etc so I see there

    being a lot more going on with critical

    thinking and then problem solving in

    general is just something that's kind of

    very important for a variety of reasons

    I also mentioned that there's going to

    be more collaboration and teamwork as

    well as more use of techno technology

    which was kind of like a yeah well I

    mean duh but the last thing that Bard

    mentioned is that there's gonna be more

    of a focus on global citizenship so this

    was interesting because I was talking

    about how being able to look at things

    from different cultures and perspectives

    not just from like a local sense or from

    like a national sense but globally now I

    do see this as being a potential future

    like with the increase in abilities of

    real-time translations in particular

    we're going to be able to assist with

    more Global discussions so like I'm very

    slowly learning Japanese but there are

    some apps on my phone where I can like

    just speak into it and then it'll

    translate it immediately to somebody in

    Japanese and vice versa they can speak

    Japanese and it'll translate it to me in

    English because of this I do see more of

    a focus on global collaboration and

    communication among students and

    teachers Etc likely going to be

    asynchronous just because of like time

    zone differences and whatnot and like

    when students go to or attend school but

    that is quite frankly really cool like I

    like that idea that we're going to be

    able to have students on one part of the

    world be able to speak into some kind of

    a technology and it's going to translate

    it to other students on another part of

    the world so while most of these

    responses were pretty generic let's see

    what chat GPT has to say so chat chat

    gbt also mentioned that there's going to

    be more of a focus on personalized

    learning but these responses in general

    for all these questions chat GPT had a

    better response than Bard did Bard was

    much more of that like marketing

    response and then chatgpt actually

    sounded like the person sort of knew

    what they were talking about most of the

    time so for example on personalized

    learning it says quote adaptive Learning

    Systems AI tutors and intelligent

    educational software could be utilized

    to create personalized learning paths

    for students catering to their strengths

    weaknesses and interests end quote which

    by the way all these responses I include

    in their entirety in the show notes for

    episode 191 this particular episode so

    make sure you check that out if you want

    to actually see like all of these

    responses from Bard and chat DBT just

    click on the little plus sign and it'll

    expand it so this is a very important

    point so it elaborates on what

    personalized learning looks like I do

    agree that there are some abilities to

    have more adaptive Learning Systems Etc

    that are going to be able to make it so

    students can kind of go at their own

    pace however I've done several episodes

    that talks about a concept known as

    rhizomatic learning for example on

    episode 150 which is titled fostering

    intersectional identities through

    rhizomatic learning as well as episode

    with Catherine bornhurst John Stapleton

    and Katie Henry these episodes and more

    kind of talk about how you can engage in

    individualized learning within group

    spaces so if you're interested in that

    check out those episodes Linked In the

    show notes and the next thing that chat

    GPT mentioned was Blended learning

    environments so this is specifically for

    fostering Global Connections among

    students and Educators this was a really

    interesting idea so it's talking about

    how yeah we're going to have more

    in-person and virtual spaces kind of

    like a hybrid of the two maybe a combo

    of the two but it's specifically in

    connection with like Global Connections

    with other students and teachers that I

    thought was an interesting take on that

    the next thing that Chachi D mentioned

    for this question was an emphasis on

    critical thinking and problem solving

    okay this is basically the same thing

    that Bard mentioned the next one was

    lifelong learning and upskilling this

    one was a really interesting idea so

    specifically talking about how with the

    changes in technology and like jobs just

    constantly evolving in terms of like

    what's available the markets where

    there's needs Etc there's going to be a

    need for an emphasis on lifelong

    learning and upskilling so the ability

    to learn new skills or different skills

    than what you may have learned in school

    there's already a lot of discussions

    about whether or not college is useful

    and whether or not you should get a

    degree or just like jump into a field

    and I do see this as a kind of like

    trickling down into well do we really

    need to focus on like learning this

    particular concept of practice in this

    domain like in computer science when 20

    years from now that domain might not

    even exist as we know it today perhaps

    instead we should focus on the lifelong

    learning and again the upskilling and

    that I think is a really interesting

    idea that Bard did not mention that I do

    think that Educators and the education

    system could really benefit from

    exploring more the next thing that

    Chachi BT mentioned was collaboration

    and project-based learning as well as

    gamification and immersive experiences

    in particular it elaborates and says

    that virtual reality and augmented

    reality are going to become more of a

    norm Within teaching and learning in the

    next 10 years and that is something that

    I agree with and kind of wish that it

    was expanded upon in some of the other

    responses by Bard because this is

    something that is going to potentially

    have a drastic impact on the future of

    learning the next thing that chat gbt

    mentioned was more of a focus on

    data-driven education I'd argue we

    already have a huge Focus or too much of

    a focus if I dare say on data-driven

    education specifically data-driven

    education when it comes to standardized

    tests we spend way too much time on that

    preparing for it taking those tests Etc

    rather than just actually like creating

    learning exploring Etc so I agree that

    unfortunately that is likely going to be

    a big part of the future in the next 10

    years of education but I don't think we

    should focus on that so if you want to

    learn more about that check out some of

    the podcast episodes that have come

    before this there's over 190 of them so

    there's a lot to learn from from the

    different guests and unpacking

    scholarship episodes and the last thing

    that chat GPT mentioned was also just

    like that cultural and Global awareness

    now this was interesting to see these

    responses in particular I really like

    the pro coach of focusing on lifelong

    learning and upskilling out of the

    responses that was probably my favorite

    one to really focus on aside from

    personalized learning which obviously

    I've talked about many many times on the

    other podcast episodes now I followed up

    with both of the AI and asked the

    question how is that different from

    today now again because the large

    language models are basically

    summarizing discourse across a wide

    range of different sources this is kind

    of just giving you a pulse on the

    thoughts around education or the future

    of education so when it comes to

    personalized learning art mentioned

    quote today students typically learn in

    one size fits all classroom setting in

    over their own learning paths and they

    will be able to learn at their own pace

    and in their own way this will be

    facilitated by the use of educational

    Technologies such as adaptive learning

    software and online learning platforms

    end quote I totally agree with that I do

    see that being more of a future but

    again you can do all of that without

    actually having to use technology so

    check out the rhizomatic learning

    podcast episodes Linked In the show

    notes when it came to critical thinking

    and problem solving Bard mentioned that

    many schools focus on basically rote

    learning and memorizing fats Etc and I

    do know that some schools do that

    especially the traditional schools like

    the private schools but when it came to

    collaboration and teamwork Bard

    mentioned that many students work

    individually on projects I personally

    prefer them but I'd argue that the way

    that they're describing collaboration

    and teamwork it's actually not going to

    just be human human collaboration but

    also human to AI collaboration so being

    able to collaborate with AI to kind of

    like come up with a project idea or

    refine some code or to create something

    new Etc I'm predicting that in the

    future of Education there are going to

    be many collaborations with human Nai

    not just human to human that wasn't

    actually mentioned by Bard and then

    again these are just like a lot of

    generic responses and whatnot so when it

    came to the global citizenship there's

    basically saying they're going to learn

    about different cultures and

    perspectives I mean we're kind of

    already doing that in at least most of

    the United States general education

    curriculum like that does happen but I

    would argue that with the use of

    technology and whatnot instead of just

    focusing on learning about different

    cultures and perspectives we're actually

    going to collaborate with communicate

    with directly with the assistance of

    like technology that will allow us to

    translate across different languages Etc

    now when it came to chat gpt's response

    again these were generally better

    responses than barger's responses but

    there wasn't really anything that stood

    out as like oh yeah that's a really

    interesting point I really like that

    um I should talk about that on podcast

    so I'm just going to skip over that but

    again you can actually read the entire

    response from every one of these

    questions that I ask at the show notes

    which is found at jaredeliry.com alright

    so the next question that I asked both

    the AI is what is the role of artificial

    intelligence in teaching and learning so

    Bart mentioned that AI can be used for

    personalized learning as well as

    adaptive learning could be used as a

    virtual tutor you can use it to assess

    something or you can use it for research

    so AI can be used to kind of like come

    up with new teaching methods which is

    something that the AI recommended I'm

    not really sure what that means but it

    sounds interesting so perhaps what I

    could do is just like ask Bard hey what

    are some potential teaching methods that

    can be used or developed through Ai and

    then maybe I can follow up with that on

    a future podcast or something cat GPT

    also mentioned that personalized

    learning was going to be a big focus of

    that intersection of learning and

    artificial intelligence also mentioned

    intelligent tutoring specifically

    pointing out that tutors that are AI can

    be available 24 7 can provide more

    one-on-one feedback that is immediately

    on demand rather than having to wait

    like oh the tutor or teacher is helping

    somebody else in the classroom I just

    have to kind of wait to be able to help

    Etc I mean one of the ways that I kind

    of worked around that as somebody who

    previously worked in the classroom ever

    grade kindergarten through doctoral

    student is when I'd be working in a

    class and I would have like up on the

    board like okay first check like the

    documentation like read through the the

    documents for their coding platform

    using to see if they can answer your

    question then the next two steps are to

    ask some peers so ask somebody next to

    you and then maybe get up ask somebody

    else in the room and then the final step

    is to ask me if I was available if I was

    not available then you keep repeating

    steps one through three which is to

    check the of documentation and then ask

    some peers for help that way it wasn't

    so that like a kid was just like sitting

    there with her hand raised just kind of

    like waiting forever and then eventually

    they were able to actually be able to

    work with me on something because again

    when you have like sometimes I had 35

    kids in a class sometimes when I'm

    working with somebody on a coding

    project like it might be in a lengthy

    discussion where it's like oh well let's

    try this let's try and figure out what

    the bug is let's talk about this blah

    blah and so several minutes might go by

    or even 20 minutes or whatever so it's

    important to have some kind of a system

    in place now again peers might not

    always be able to provide a good answer

    so it might be helpful to have ai to

    kind of be like a tutor I totally

    understand that and interestingly a

    couple weeks ago in episode 188 which is

    titled studying the effect of AI code

    generators on supporting novice Learners

    in introductory programming that

    particular publication actually found

    out that students who learned with AI

    specifically learning how to code

    outperform students who did not learn

    with AI when they didn't use AI on a

    test so when they were just like writing

    out lines of Code by hand without any

    assistance of AI they actually performed

    it if they had originally learned it

    with AI so that is a fascinating finding

    and I'm curious if it can be replicated

    or reproduced in other contexts and

    whatnot so stay tuned folks we'll find

    out now again chat chippy mentioned that

    AI will be helpful for automated grading

    and feedback this can save some time for

    teachers so they can focus on working

    with students one-on-one rather than

    just like focusing on the assignment

    itself however I would argue that a

    teacher learns a lot when they are

    actually going through and Grading

    different things and learning about oh

    here's a misconception that I'm noticing

    and if you were to just hand that over

    to an AI and then AI just assigns some

    kind of a score and gives you feedback

    to the student if you are not the one

    who's actually grading things you're not

    going to be able to notice those

    patterns over time where you're like oh

    Johnny consistently for the past like

    four weeks have had issues with this

    very same thing across several different

    projects Etc so I would argue that it

    might help with grading and feedback but

    it might not necessarily help provide

    context for a teach to understand and

    identify those problems unless they're

    actively looking at the data and going

    oh I'm noticing some patterns right here

    so perhaps if hey I were to kind of

    summarize those patterns and then send

    them to the teacher then maybe they'd be

    able to better assist them one-on-one

    now another thing that the chat GPT

    mentioned was that AI would be helpful

    for natural language processing so this

    was interesting so here's a quote from

    this little paragraph quote AI powered

    chat Bots or virtual assistants can

    engage in conversations with students

    answering questions providing

    explanations and engaging in interactive

    dialogue end quote I am wondering out

    loud if we have chat Bots that are like

    voice activated kind of like Alexa or uh

    text based if that is going to actually

    improve speaking as well as reading

    abilities as students especially if they

    are English language Learners or

    emergent bilingual students I do see

    that as a potential way for students to

    be able to kind of like practice their

    reading practice their Writing Practice

    their speaking Etc and to do so where

    they can actually get feedback because

    like there are many times like when

    you're working with a student when they

    like say something and like the grammar

    is incorrect and you kind of like

    rephrase it back to them without like

    calling them out on it but an AI might

    be able to go like oh the way that you

    phrase this here's how you're actually

    supposed to say it or Etc like if you

    were asking for that from Ai and again

    this is something that can happen in

    real time 24 7 rather than having to

    rely on a tutor who's going to be there

    in person Etc now from what I was

    mentioning earlier with automated

    grading and feedback chat gbt did

    elaborate that data analysis and

    learning analytics would be helpful for

    quote helping identify patterns Trends

    and insights end quote so if it's

    combined with the automated grading and

    feedback and you're actually able to

    look at the patterns over time that I

    think that would be helpful for

    educators even for students to go oh I'm

    noticing that I'm having trouble with

    blah perhaps I should spend more time on

    blah that's something I do with like my

    drumming and whatnot is I will look at

    okay what is going well what are the

    things that are consistently

    inconsistent or consistently not

    sounding good now I need to find some

    different approaches different ways that

    I can actually work on those

    inconsistencies or problems with my own

    playing same thing applies with many

    other things like I've done that with

    martial arts I've done that with Video

    Games Etc trying to find the weaknesses

    of the areas of improvement and then

    finding ways that you can actually

    practice just that thing in isolation to

    improve it over time that could be

    helpful for educators as well as for

    students and I do think AI is going to

    be useful with that now here's another

    interesting one from chat GPT this is on

    intelligent content creation quote AI

    can assist in generating educational

    content such as automated lesson plans

    quizzes or interactive simulations it

    can also provide assistance in creating

    adaptive learning materials that adjust

    to individual student needs end quote

    that is really interesting and in fact

    we put that to the test a little bit

    later so I actually do ask both the AI

    to create some lesson plans and there's

    a bit of controversy in there that we'll

    talk about when we get to that but you

    can actually jump to that by clicking

    the description as I do include

    timestamps to each one of the questions

    that I ask and then the last thing that

    chat GPT mentioned is that virtual

    reality and augmented reality can be

    used to kind of like simulate real world

    scenarios experiences Etc now one

    interesting thing that chat GPT ends

    with is the following little paragraph

    quote it's important to note that while

    AI has the potential to enhance teaching

    and learning it is not intended to

    replace human Educators rather AI can

    complement and support teachers by

    automating routine tasks providing

    insights and offering personalized

    assistance thereby enabling Educators to

    focus on individualized instruction

    mentoring and fostering human Connection

    in the classroom end quote that is a

    really interesting thing that it adds at

    the very end of this now I have seen

    some business people in particular kind

    of talk about how AI is going to replace

    Educators and there's not going to be

    needs for them I completely disagree

    with that I know I'm a bit biased

    because like again I've worked with

    evergrade kindergarten through doctoral

    student but I don't see Educators going

    away or that Personal Touch I do see it

    being used in collaboration or being

    able to assist but having somebody there

    in person is just so much better because

    you're actually able to get to know the

    student as an individual at least if

    you're teaching that way as opposed to

    teaching to the group or to like the

    group mean or medium but I don't know

    maybe 10 years from now I'll be like uh

    actually Jared computers have completely

    replaced teachers because as I mentioned

    in that other podcast episode I did find

    that AI that was used in collaboration

    with learning actually performed better

    than students who did not learn with the

    collaboration of AI but again no no

    we'll see now the next question that I

    ask about the AI is why are teachers

    leaving the field and what can be done

    to prevent that so Bard mentioned that

    the average teacher salary in the United

    States is 61 730 which is considered to

    be low pay and quite frankly that was

    more than I was making as somebody with

    a doctorate 10 years of experience and

    they gave me 44

    classroom

    rolling in that money they also

    mentioned that there's a heavy workload

    there's a lack of support there's

    unreleased students and parent

    involvement is not happening I would

    argue that there's sometimes too much

    involvement from parents who think they

    know everything about their student and

    don't see all the bad things the

    students are doing behind their back but

    I also understand that some of the

    schools that I've worked at did not have

    enough parent involvement at home

    especially if the parents are having to

    work multiple jobs now again much like a

    marketing person trying to respond for

    an expert Bard mentions well we can fix

    these by increasing teacher pay reducing

    teacher workload by reducing the class

    sizes allowing for more planning time

    allowing for more professional

    development we can provide more support

    through the axis of more technology

    smaller class sizes we can also develop

    positive relationships with students

    quote teachers can develop positive

    relationships with students by being

    fair and consistent showing respect and

    being approachable end quote I would

    argue with somebody again who's worked

    with ever-grade kindergarten through

    doctoral students that students are the

    least of the problems that I had in

    education yeah of course there's going

    to be some outbursts or some students

    who are going to fight each other every

    now and then but then you just step in

    you knock one of them out and then it'll

    never happen again because no one will

    want to mess with with you that was a

    joke but this idea that like

    education is going to be so much better

    if like you just approach students with

    respect and be consistent like teachers

    aren't leaving the field because

    students are unruly there are so many

    like issues in education educational

    policy so many influences from parents

    from policy makers from community

    members Etc who are just making it so

    that it's unbearable to be in the

    classroom not to mention you know it's

    not safe to be in the classroom because

    random people are coming into the school

    or even sometimes students with weapons

    like it's a scary time to be an educator

    and again you're not getting paid much

    so I get the sentiment but if that's the

    general discourse that that's kind of

    blaming the teachers which again I would

    argue that is all the external

    influences on the educator not the

    educator itself that is the problem for

    the majority of the time yeah I've

    worked with some teachers who like

    clearly didn't want to be there but I

    mean given all the stresses the low pay

    etc etc like I get why you wouldn't want

    to put a lot of effort into it again

    somebody with a doctorate and 10 years

    of experience I made forty four thousand

    one hundred and eighty six dollars I've

    presented over a hundred times I have

    over a dozen Publications I've won

    multiple International teaching and

    research Awards and I was making less

    than fifty thousand dollars a year and

    I've seen some people on social media be

    like yeah well if you want to make more

    then how about you get more degrees and

    how about you just like perform well I

    did and I still made less than fifty

    thousand dollars a year but I'll end

    that rant right there now another thing

    that Bard mentioned is that we can

    encourage more parental involvement and

    I would argue that in lower income

    schools again parents don't necessarily

    have time for that all right so let's

    take a look at what chat gbt said so

    it's very similar so it's saying that

    teachers are leaving the field because

    of low salaries heavy workload and

    stress a lack of support and

    professional development again they

    mentioned classroom management

    challenges that there's diverse student

    needs disruptive behaviors a lack of

    resources so it was a little bit blaming

    the Educators but also expanding it

    saying hey there's a lack of resources

    and there's so many things you have to

    consider when teaching like if there's

    IEPs or 504 plans Etc and I totally get

    that so this was a little bit more

    nuanced than Bard's explanation was so I

    like this response a little bit better

    and the last thing that chat GPT

    mentioned is that policy changes and

    standardized testings are some of the

    reasons why teachers leaving and I agree

    a lot of what you focus on in the

    classroom is not necessarily students

    which is kind of a shame because that's

    why like I went into education into the

    field is to be able to help other kids

    but you have so many outside factors

    that you have to consider I have to

    prepare you for the test rather than you

    know just focusing on things you

    actually want to learn and again

    developing lifelong learning and

    upscaling Etc now chat GPT mentions that

    we can address this by having

    competitive compensation we can have a

    more supportive work environment reduce

    the administrative burden such as like

    administrative tasks and paperwork which

    yeah that would be nice I had to do

    lunch duty playground Duty Bus duty all

    sorts of other stuff which honestly is

    such a waste of my time again given my

    background like when I left the

    classroom I went to a non-profit and

    made curricular content and professional

    development that made that organization

    several million dollars because of the

    content that I personally made or led

    the team of and so instead of making

    several million dollars worth of content

    I was monitoring the bus and making sure

    that kids weren't jumping off the

    playground Etc like that is just kind of

    a waste of time and you could hire

    somebody at minimum wage to do that

    rather than taking away from my time to

    be able to create educational content

    and resources that help students but

    that is my own little rant on that

    another thing that chat CPT mentions is

    that you can focus on professional

    development and growth now this is

    something that I mentioned in other

    episodes is that there is very little

    money and time set aside for

    professional development and growth that

    usually occurs like on those Wednesday

    half days where like students get out

    early and teachers end up staying way

    later than they should because they have

    like several hours of meetings after

    school ends if you are lucky enough to

    get professional development during the

    school day that means that you're going

    to have to hire several if not dozens

    and dozens of substitute teachers during

    that day to replace that time when the

    teachers are leaving in the classroom

    and now somebody's got to be in there to

    like support the students but it's not

    going to be as high quality I mean I've

    had so many Subs who literally just like

    sat on their phone in there it didn't

    matter what kind of lesson plan you gave

    them they would literally do nothing in

    the class be like I don't know today's a

    game day have fun so while you might be

    able to have the funds to pay for the

    supports that you would need to be able

    to do the professional development it's

    going to have a negative impact on

    students so like there's really no win

    there when you're doing this

    unfortunately another thing that chat

    gbt mentions is that we need more

    teacher voice and collaboration

    especially when it comes to like

    policies and decision making I agree

    with that sentiment so there there is

    not enough like discussion with policy

    makers like I had a policy maker come

    into a district that I worked in and

    this person literally to the minute had

    their their entire like hour-long thing

    planned out they had I'm gonna spend

    three minutes in this classroom and then

    we're going to spend one minute walking

    to the next classroom another five

    minutes in this other classroom blah

    blah blah blah blah now I didn't

    actually teach at the school but I was

    asked to come into that school and act

    like I was a teacher there because again

    I was teaching in a completely different

    School in the same district they asked

    me to come over there simulate what my

    classroom looked like in that school I

    taught the kids like the week before for

    several days trying to help them I get

    caught up to what my students were doing

    in my actual classes students then were

    in there showcasing the projects that

    they worked on in their class and then

    they had a list of pre-approved

    questions that students could ask this

    policy maker so a student would be like

    reading from a script basically saying

    what do you think about the future of

    education and then the policy maker

    would say their little buzz line for a

    moment and then within five minutes they

    were gone and then after that I never

    saw those students again because I went

    back to my actual School my actual

    classes and those kids just kind of

    continued to do their own thing so

    policy makers who actually come into the

    classroom sometimes and at least this

    case come into an artificial classroom

    and then policy makers walk away from

    this going yeah this school was amazing

    like look how great this was these kids

    like asked such well-informed questions

    that you know were pre-approved by my PR

    team and look at all the fancy stuff

    they have on the walls that they

    certainly didn't put up the week before

    I actually arrived there so not only

    should like policymakers actually walk

    into a class classroom to see what it's

    like on a normal day and not just these

    like scripted PR stunts but they should

    actually like go in and figure out what

    it's like to be a substitute for a day

    or to teach for a day because you know

    what it's a lot harder than the looks

    there's an idea called the

    apprenticeship of observation which is

    basically a fancy way of saying hey

    you've been in school for maybe 13 plus

    years if you were in K-12 and you have

    observed somebody you've been

    apprenticed by all these Educators that

    you have had you've looked at it and

    gone I know how to teach I know what's

    going on even though you've never asked

    the teacher what are you thinking why

    are you doing it this way and not this

    way how is it that you would just

    adjusted this lesson based off of what

    students responded with blah blah blah

    blah you've observed but you don't

    understand the thinking behind it so

    this creates an issue where policy

    makers think they know what they're

    talking about because they've observed

    people teaching for decades and then

    they go oh I know how to do that as well

    I know it's best here's what worked for

    me but what they don't see is somebody

    like myself who has literally worked

    with 1000 of students individually can

    go well no the way that I'm teaching you

    policymaker is going to be different

    than I teach the person next to you

    based off of their own needs their own

    understandings their perspectives Etc so

    long rant to basically say yeah there

    needs to be way more teacher voice and

    collaboration with people who have all

    this external influence on what goes on

    inside of the classroom because quite

    frankly those people don't know what

    they're talking about because they

    haven't actually sat down and spoken

    with Educators and they haven't actually

    been in a classroom and experienced

    things from a teacher's perspective I'll

    end their aunt there if you want to hear

    more on these perspectives check out the

    my website now the last thing that chat

    GPT mentioned is teacher well-being and

    mental health support this is something

    that I have over emphasized on this

    particular podcast each year I release

    an episode that is specifically on

    burnout that takes all of the responses

    from guests and says here's how these

    individuals try and prevent burnout

    working in the field of Education or as

    a researcher Etc so make sure you check

    out the links in the show notes for

    those episodes if that is interesting to

    you now the next question I ask both the

    AI is how much should a public

    elementary school computer science

    educator be paid in Arizona with 10

    years of experience and a Doctorate in

    Education now Bard laughingly said that

    the median salary for elementary school

    teachers is 56 590 in 2020 and that

    somebody with those experiences that I

    just described should be making a salary

    of seventy five thousand dollars or more

    now again I have my contract here that

    said that in the 2016-2017 school year I

    was making 44

    it's described on there today in today's

    dollars I would be making if I had zero

    experience forty nine thousand dollars

    with a PhD in education or a maximum

    again maximum of sixty one thousand

    dollars with the 10 plus years of

    experience that I have because they do

    not count above 10 years but they do

    account for the PHD so I would be making

    sixty one thousand dollars if I was

    still in the classroom but Bard is

    suggesting that I should be making

    seventy five thousand dollars or more

    because of that experience in education

    and as a researcher etcbt on the other

    hand had a response that basically said

    hey I don't really have access to

    real-time data on salary so here are

    some ways that you can figure that out

    on your own you can check out the

    Department of Education you can go to

    school district websites or you can go

    to a teachers union and I agree that is

    how I'm able to find the the salary

    information but it really kind of makes

    me laugh it's just like so far off how

    much the educator will be making in the

    classroom if I was making seventy five

    thousand dollars a year as an educator

    that would have been sweet but again I

    was making Thirty one thousand dollars

    lesser than that now I took the same

    question and I applied it to a private

    elementary school educator so like in a

    charter school and so for chat GPT again

    it just basically said hey I can't

    really figure that out but here are some

    ways that you can do that but Bard said

    that the salary range can be from fifty

    thousand to a hundred thousand dollars

    or more and that the median salary for a

    elementary school teacher in private

    schools was 72 000 now this is

    fascinating because a lot of charter

    schools a lot of private schools you

    don't actually need to be certified to

    become an educator in the school you

    could literally have never taught a day

    in your life never have a single degree

    in education and you could just say hey

    I have like a master's degree in

    computer science I'm going to Now teach

    your computer science class and then be

    like cool here's 72 000 or whatever so

    you could potentially make more with

    less experience by working in a charter

    or private school obviously mileage may

    vary Etc depending on what school you're

    working at let me know in the comments

    on YouTube If you uh agree or disagree

    with that that private school Educators

    with potentially less experience should

    be getting paid more or less than public

    school teachers who have more experience

    in background in education alright so

    those were some of the questions that

    were like broadly talking about

    education now I want to narrow down to

    talk about well Computer Science

    Education in particular because this

    podcast does focus on Computer Science

    Education all right so the question that

    I ask is what are the top five

    pedagogies for teaching computer science

    Bard responded with project-based

    learning problem-based learning

    approaches to computational thinking

    which is apparently some kind of a

    framework I've literally never heard of

    this so it may be a hallucination and

    just like coming up with computational

    thinking and turning it into a framework

    I even searched for it and I couldn't

    find stuff on it just generic stuff

    about computational thinking the fourth

    amount was inductive inquiry and then

    the last one was experiential learning

    now if you want to like again see what

    each of these are I do include them in

    the show notes oddly enough Bard

    responded with like here are some more

    tips like on how to teach computer

    science so one is to make things more

    relevant one is to use more visuals make

    it fun provide feedback and celebrate

    successes again it just just reads as if

    it was written by somebody who's like on

    a marketing team who's never taught in a

    day in their life but has read some

    educational blogs about how to teach

    computer science like if you look at the

    make it fun it just has two sentences

    and it says computer science should be

    fun an exclamation point this can be

    done by using games puzzles and other

    activities okay and now I'm a phenomenal

    educator thanks for that advice chat GPT

    on the other hand had very similar

    things these answers were more detailed

    and less of a blog post from a marketing

    team but again it had some of the

    similar ideas just with like more Nuance

    to them so so the suggestions are to use

    project-based learning inquiry-based

    learning Collaborative Learning flipped

    classrooms and game-based learning but

    one of the things that I really

    appreciate at the end of this is the

    following quote it's important to note

    that these pedagogical approaches can be

    combined or adapted based on the

    specific needs of students the learning

    objectives and the available resources

    effective computer science instruction

    often involves a blend of these

    pedagogies along with integration of

    Technology tools formative assessment

    strategies and differentiation to meet

    the needs of Learners end quote that was

    actually a really good solid like

    explanation of this I've talked about

    this multiple times on the podcast

    episodes that have come before this that

    a multi-perspectable approach to

    education is the way that I highly

    recommend Educators approach things

    approach things from many different

    perspectives because what works for one

    student or group of students might not

    work for another student or groups of

    students so if you can approach things

    from many different ways have many

    different paths Etc then this can be

    very helpful so I'm actually happy to

    see that chat gbt mentioned that in the

    response on here for the top five

    pedagogies for teaching computer science

    now I followed up with each of the AI

    and asked can you elaborate on how each

    of these pedagogies elicit will be

    beneficial for learning asking this a

    Bard made it so that there were some

    better answers for these different

    approaches and kind of focused more on

    how it actually would help students the

    chap gbt gave four reasons for each of

    the five pedagogies for why that it

    would be useful for the students so chat

    CPT again gave a significantly better

    response to this and again if you want

    to read what these like responses are

    then check them out in the show notes

    now one of the things is not discussed

    enough quite frankly are the downsides

    for using different pedagoges so I asked

    both Bard and chat gbt what are the

    downsides for each of the pedagogies

    that they listed now Bard provided some

    of the downsides and they also actually

    provided some suggestions for how to

    mitigate each of these downsides which

    is something that I didn't ask for and

    then chatgpt had some more nuances for

    their answers than Bard did and

    basically answered the questions now

    here's like an example of how it

    responded to this so for example in

    Collaborative Learning quote unequal

    conditions in Collaborative Learning

    some students May contribute more or

    less than others leading to imbalances

    in workload and potential frustration

    among group members conflict resolution

    collaborative settings may present

    challenges related to conflicts or

    disagreements among students teachers

    must facilitate effective communication

    conflict resolution and Equitable

    participation individual accountability

    ensuring that each student is

    accountable for their learning and

    actively engaged in group activities can

    be challenging in Collaborative Learning

    environments end quote and again this is

    like all things that I was kind of

    ranting about earlier with Collaborative

    Learning so that I felt like was

    actually a pretty solid response as well

    as like some of the discussions on

    game-based learning like having done

    Publications and research on like video

    games and learning and whatnot like I

    agree that game-based learning can be

    really cool but there are some

    significant downsides that are often not

    discussed so chat cpt's response to

    game-based learning and the downsides of

    it was actually like pretty nuanced was

    was pretty good which again you can find

    in the show notes so the next question

    I'm asked both the AI was how could

    teachers make computer science classes

    more Equitable so Bart mentioned that we

    could use a variety of teaching methods

    we could provide individualized support

    we could use culturally relevant

    examples create a welcoming environment

    and be a role model they also provided

    some additional tips for it which was

    kind of like weird how it was phrased

    but they said to be aware of your own

    biases create a space for students to

    share their experiences provide

    opportunities for students to

    collaborate and celebrate students

    successes by making them I like feel

    like they belong now let's go back to

    the beware of your own biases this was

    interesting quote teachers should be

    aware of their own biases and how they

    might be affecting their teaching for

    example teachers who are not familiar

    with coding might be more likely to call

    on students who they think are good at

    coding even if those students are not

    from underrepresented groups end quote

    so this was actually like a pretty

    decent response like I'm surprised that

    it did mention that and like I actually

    would advise that other Educators become

    more aware of their own biases is

    something that I actively try and do but

    again it's one of those things where

    it's like what 10 years from now am I

    going to be appalled that I'm I believe

    or think now and obviously I don't know

    that so stay tuned folks chatgpt had

    again some more nuances and whatnot but

    the different recommendations that they

    get gave for making classes more

    Equitable was to have an inclusive

    curriculum and instruction addressing

    stereotypes and bias improving access

    and infrastructure having a more

    supportive classroom environment and

    Community engagement and Outreach all

    these have like three to four different

    suggestions on how you can do that for

    each one of these so for example on your

    inclusive curriculum and instruction

    chat GPT mentioned quote select diverse

    and inclusive learning resources

    materials and examples that represent a

    range of cultural perspectives and

    backgrounds incorporate projects coding

    exercises and problem solving tasks that

    relate to students's interests and

    experiences ensuring relevance and

    engagement for all Learners use multiple

    instructional strategies and modalities

    to accommodate diverse learning styles

    and preferences provide clear and

    structured instructions to support

    students who may require additional

    guidance or clarification end quote all

    of those I agree with I like honestly

    I'm kind of surprised at how well the

    chat GPT in particular can provide a

    pretty decent answer for some questions

    like honestly a lot of the responses

    that I'm getting here could have been

    found in like educational journals for

    like practitioners it's not quite at the

    Nuance yet of an academic based

    publication like for researchers and

    Scholars and whatnot but I imagine in

    that depending on the prompts that you

    give it and the writing styles that you

    ask it to write in it might be able to

    elaborate on this like hey can you write

    this from like a graduate student's

    perspective as opposed to like

    undergraduate's perspective now I wanted

    to get into some more provocative

    questions so I ask a question why should

    all students learn computer science

    because I've talked about on this

    podcast even though I love computer

    science Computer Science Education I

    don't think everyone should learn any

    subject area same thing with like music

    my bachelor's Masters and PhD are all in

    music education but I don't think

    everyone should do music or music

    education I think it depends on like

    what your interests are and what you

    want to do but I also think that there

    shouldn't be required classes in general

    so I wanted to see what would AI kind of

    summarize as why people think students

    should learn computer science now this

    was very like markety very buzzwordy so

    it's talking about computer science as a

    foundational skill it can be a creative

    field that it's a problem-solving field

    it's collaborative and it's fun but it

    also said computer science can solve

    quote real world problems such as

    climate change or poverty end quote I'm

    looking forward to the day when computer

    science solves climate change and

    poverty but I'm not holding my breath on

    that now Chachi PT on the other hand

    said that students should learn computer

    science because of digital literacy and

    essential skills problem solving and

    critical thinking there are career

    opportunities you can engage in

    creativity and Innovation because of

    computational thinking and algorithmic

    mindsets because of empowering digital

    citizenship interdisciplinary

    connections technological literacy and

    adaptability as well as addressing

    equity and access all of these in my

    opinion were very buzzwordy and didn't

    really have much substance to the

    thoughts behind them so for example A

    Bard's response to why computer science

    is a foundational skill it says quote

    computer science is a foundational skill

    that is essential for success in today's

    world computers are used in almost every

    aspect of Our Lives from work to school

    to entertainment by learning computer

    science students can develop the skills

    they need to be successful in the 21st

    century end quote that was a whole lot

    of nothing it sounds great like some

    kind of like a CEO executive or whatever

    is going to be like yeah this is why we

    should learn this thing but if you

    substitute the word computer science

    with technology or computer or phone or

    whatever it works just as well like

    nothing about computer science Concepts

    and practices was actually mentioned in

    there and Chachi BT's response it does

    say that you can figure out how things

    work and to have a better understanding

    of like digital tools and whatnot so

    that's at least some nuance and it's not

    just talking about computers at large

    but having like been on some Grant

    reviews and whatnot for like the

    Department of Education for several

    million dollars sometimes I've seen some

    of the applications where people will

    talk about computer science as if it's

    just using a computer like conflating

    the idea that learning how to use

    PowerPoint is going to help you learn

    and understand computer science those

    are two very different things in my

    opinion so again this was very buzzwordy

    and didn't really have much substance to

    it now trying to probe it a little bit

    more because I like to probe the general

    discourse around computer science and

    why it's like the most important thing

    in the world for some people and why

    everyone in the world apparently needs

    to learn it I asked the question for the

    AI should someone learn computer science

    if they are not going to be a

    professional computer scientist and so

    both the AI said yes but they just

    listed off basically saying some of the

    same stuff like Bard was like it's a

    foundational skill you need to learn how

    to use computers it's a creative thing

    it's problem solving it's collaborative

    and it's fun then it ended with this

    quote quote even if you don't want to be

    professional computer scientist learning

    computer science can still help you in

    your career many jobs now require some

    level of computer skills and learning

    computer science can give you a

    Competitive Edge additionally computer

    science can help you develop critical

    thinking problem solving and

    communication skills that are valuable

    in any field if you're interested in

    learning more about computer science

    there are many resources available

    online and in libraries you can also

    take classes at local community college

    or university with a little effort you

    can learn the basics of computer science

    and start using these skills to improve

    your life end quote again that was a

    nothing Burger there was like really no

    substance to that but that right there

    kind of summarizes like the general

    discourse that I I often see discussed

    with like technology in education

    computer science Educators take it one

    step further and actually talk about

    okay well instead of just using devices

    which is basically all Bard was talking

    about you can learn how to program those

    devices which is useful for upcoming

    jobs and that's mainly the argument that

    is used I like to focus on the other

    side of things balance things out a

    little bit more and say yeah you can

    also use it for leisure like I propose

    to my wife by modding the video game

    Minecraft I added our dogs to it I added

    custom purple armor because that's her

    favorite color all sorts of like fun

    things into it I'll include a link in

    the show notes if you want to see the

    video of some of the stuff that I added

    into it and it was great I loved it I

    did it for fun well and you know to get

    married but then there are other like

    games and like tools that I made for

    myself and none of it was made for money

    or monetary gain Etc so yeah you can

    focus on that side of things the career

    side of things but also you can focus on

    well if you're not gonna like do this as

    a profession you can still do this for

    fun you can engage in modding video

    games if you want to just like do that

    in your leisure or just create apps that

    would be helpful for you in your

    everyday life again chat CPT basically

    responded with yes it's important and

    here are some reasons why and they were

    like fairly generic reasons again you

    can engage in problem solving yeah well

    is computer science the best way to

    engage in problem solving that would be

    relevant to that individual learner

    who's not actually interested in

    computer science maybe maybe not though

    there are other ways you can engage in

    problem solving and all the other things

    that are listed on here without actually

    using computers so I followed up with

    both the AI and asked okay well what

    prevents students from being interested

    in computer science I responded by

    saying that there are perceptions that

    computer science can be difficult that

    there's a lack of female role models or

    lack of diversity and that there are

    negative stereotypes that it's like

    boring in a solitary field Etc so

    provide some suggestions on things that

    can be done to address those and you can

    check those out in the show notes now

    chat GPT had a several more examples of

    what prevents students from being

    interested in computer science so

    mentions that there's a lack of

    awareness unlike the potential careers

    you can have in compete with computer

    science as well as like the different

    concepts and it's real world

    applications of computer science also

    talks about different stereotypes and

    perceived incompatibility limited role

    models and representation inadequate

    preparation perceived Notions of

    difficulty a lack of engaging in

    relevant curriculum there are gender and

    cultural biases and then there's a

    limited access to resources and

    opportunities such as like technology

    quality instruction extracurricular

    resources

    etc etc I do agree with all these These

    are are different reasons why people

    might not be interested in computer

    science but I'd also like to add that

    some students are not interested in

    computer science because they're more

    interested in other areas so for example

    if you are a computer science educator

    why did you go into this field as

    opposed to other fields that other

    people went into I went into music

    education and now have been in computer

    science education for the better part of

    the last decade so I'm technically in

    two Fields simultaneously but I've also

    as of like January have been working on

    gaming stuff as a streamer as a content

    creator and whatnot for my YouTube

    channel Channel and my website so I

    technically have had like three distinct

    careers but that's three out of the

    millions of other careers and domains I

    could have gone into so same thing for

    this like just because a student is not

    interested in computer science it

    doesn't necessarily mean that they have

    to be in my opinion it's okay if they're

    interested in other areas like cool you

    want to be a physical therapist then be

    the best physical therapist you can be

    cool if you want to be a dentist then be

    the best dentist you can be if you want

    to be a therapist be the best therapist

    you can be and computer science may or

    may not intersect with that but it's

    okay if it doesn't in my opinion and you

    can disagree with me in the comment

    section on YouTube now the next question

    that I ask AI is how can teachers learn

    how to teach computer science classes if

    they don't have a background in computer

    science I was curious honestly if like

    the responses from Bard and chat GPT

    would kind of align with some of the

    different approaches that I use because

    I use several different perspectives

    again the multi-perspective approach try

    and look at learning from many different

    angles and whatnot so Bard mentions you

    can take a computer science class you

    can read computer science books and

    articles you can attend computer science

    conferences and workshops I'd argue that

    csda is a fantastic way to do that you

    can also connect with other teachers who

    are teaching computer science you can

    use online resources like Khan Academy

    code.org and scratch which there are a

    lot of podcasts that are dedicated to

    talking about scratch so check those out

    in the show notes and then it provides

    some suggestions for learning how to

    teach it so start small use Hands-On

    activities and be patient I agree with

    all those you can start small like focus

    on a specific project that is

    interesting to you you don't necessarily

    have to start with a course but say I

    want to be able to do X Y or Z and in

    order to do that I'm gonna need to learn

    a b and c where can I go to learn a b

    and c so that way I can do X Y or Z

    Etc if you approach it that way with a

    very specific project that is

    interesting to you you might be more

    likely to stick with it in the long haul

    rather than signing up for a course and

    going wow it's going to take like six

    weeks to get to something I'm actually

    interested in so instead I'm just gonna

    you know not learn this thing I also

    agree with the Hands-On activities like

    there are so many times that I watched a

    video and then I went and actually tried

    it in an IDE so a development

    environment where I was like oh wow I

    don't actually understand this thing I

    thought I understood this concept and

    then when I actually tried to do it like

    I completely failed and so then you've

    got to watch more videos or read more

    documentation to figure out why it

    didn't work because the instructor of

    that particular video or resource that

    you did go through didn't actually

    mention all the ways that it could go

    wrong and then be patient totally agree

    with that like it takes time don't beat

    yourself up if you aren't uh completely

    fluent in whatever programming languages

    within like the first week especially if

    you know you're working full time now

    chat GPT mentioned that okay if somebody

    who is new to computer science and wants

    to learn how to do computer science in

    the classroom you can do professional

    development workshops and courses you

    can do some online resources and

    tutorials like CS unplugged scratch and

    co.org were specifically mentioned you

    can engage in collaboration and

    networking I'd argue the csta community

    is a great way that you can do that

    there's discussion boards Etc there's

    also your local chapters check out the

    interview with Jason bour which is

    episode 82 and is titled Lessons Learned

    From csta chapters across the United

    States with Jason bour if you want to

    learn more about that I also mentioned

    Partnerships and mentoring this was

    interesting so this was like partnering

    with like a local business University or

    like industry professionals to have

    people come in and kind of like provide

    some guest instruction or lectures Etc

    or kind of like Mentor you through this

    process so that way you can learn on

    your own I do know some people who like

    doing stuff like that who are in the

    field and want to show you oh you want

    to learn about CS content knowledge I

    can help you with that you can't

    necessarily help you with how to teach

    it but I can help you with how to learn

    computer science and then you can figure

    out how to teach it they also mentioned

    there are many curriculum and resources

    that can align with this you can engage

    in peer learning and communities of

    practice but I kind of Wonder okay how

    is that different than collaboration and

    networking and then the last thing that

    chat GPD mentions is continuous learning

    and reflection I totally agree with that

    like it's never going to end if you're

    going into any kind of tech related or

    even steam or STEM related field it's

    likely going to be changing quite

    frequently then you're going to need to

    be able to continue to learn and improve

    as an educator and reflect on what's

    working well what can you improve Etc

    and you can do that at the end of like

    each lesson or day or unit project

    semester year Etc like having those

    different periods can kind of reflect on

    the micro like the daily or the lesson

    that happened as well as the macro like

    how did the unit go or how did the

    semester go and kind of making smaller

    and larger changes I think is generally

    beneficial for educators to engage in I

    highly recommend doing that all right

    another question that I ask the AI is

    what is computational thinking and why

    is it being taught now Bart's response

    was quite frankly not very good but at

    the beginning it says quote

    conversational thinking is a

    problem-solving approach that uses

    abstraction decomposition pattern

    recognition algorithms and evaluation it

    is a way of thinking that can be used to

    solve problems in any domain not just

    computer science end quote that is a

    very generic high level statement on

    what computational thinking is but the

    rest of the responses quite frankly

    didn't really do a great job explaining

    it so let's go to chat GPT chatgpt

    describes computational thinking as

    quote a problem-solving approach

    inspired by the principles used in

    computer science it involves breaking

    down complex problems into smaller more

    manageable components formulating

    algorithms or step-by-step procedures to

    solve them and utilizing logical and

    systematic thinking to arrive at

    Solutions computational thinking

    encompasses a set of skills and

    strategies that are transferable across

    various domains not just limited to

    computer science end quote then it goes

    on to say well here are some of like the

    main aspects of computational thinking

    there's decomposition pattern

    recognition abstraction algorithmic

    design algorithmic evaluation and that

    is being taught in schools because it

    helps with problem-solving skills

    because of digital literacy and

    technological understanding because it

    helps prepare for future careers because

    of critical and logical thinking because

    of creativity and Innovation integration

    with course subjects and future proofing

    students again with all of these like

    there's like a paragraph for each one of

    those things that I just quickly read

    off and you can read the whole thing in

    the show notes additional thinking is

    one of those terms that like so many

    people just get really uptight about

    like they have their one way of

    understanding this term and it's likely

    not in alignment with everybody else's

    understanding of that term because of

    that there's just constant budding of

    heads back and forth well what is it is

    it thinking is it a literacy is it a set

    of tools is it a process is it a

    framework blah blah blah blah and

    because there's really no one consensus

    on this I'm curious if your

    understanding of computational thinking

    aligned with either Bard's short

    definition or chat gpt's definition as

    well as the different

    aspects of computational thinking what

    was left out what was included that

    you're like yeah that totally lines or I

    disagree with that now I wanted to dive

    a little bit deeper with this idea of

    computational thinking so I asked AI to

    list five examples of computational

    thinking and in this scenario Bart

    actually did better with this so thank

    you Bart I appreciate you please spare

    me when you take over the world so

    here's an example decomposition quote

    breaking down a problem into smaller

    more manageable steps for example if you

    were trying to program a robot to walk

    you might break the problem down into

    steps like moving the legs moving the

    arms and balancing the body end quote

    now these examples are provided for

    pattern recognition abstraction

    algorithms and evaluation so if you want

    to see what the examples are for each

    one of those they're actually pretty

    decent chat GPT also provided some good

    examples of computational thinking so

    saying creating a recipe solving a

    Sudoku puzzle planning a route

    developing an app or conducting data

    analysis and so for each one of these

    they list like a sentence or two kind of

    explaining how each one of those

    examples is an example of computational

    thinking according to our future AI

    overlords the next question that I asked

    AI is write me a lesson that teaches an

    elementary student how to create a short

    scratch.mit.edu story this was

    fascinating folks as somebody who has

    developed over 100 lesson plans that's

    used by hundreds of thousands of

    students and thousands of teachers

    around the world this was something that

    I did professionally for the past like

    six or so years before I decided to

    leave that organization to be able to

    create content on my website and YouTube

    channel like this podcast as well as all

    the gaming and drumming stuff most of my

    lesson plans averaged maybe about 12

    Pages worth of content because there was

    so much information provided for that

    range of like experienced educator or

    somebody who is brand new to not only

    teaching but also brand new to computer

    science so there's a ton of resources

    and and what not to try and support them

    I would argue that these lesson plans

    are great for an intermediate to

    Advanced Computer Science educator who

    has taught computer science for a couple

    years and I was like yeah I got this I

    understand it just give me some of the

    the main points and I'll be able to

    figure this out the lesson plans that

    both Bart and chap GPT would not be

    helpful for somebody who's brand new to

    computer science they look at this and

    go okay well how do I do that or wait

    what what am I supposed to do here

    before a typical educator the fact that

    this was able to just like pump out a

    lesson plan that had objectives and

    materials introduction brainstorming

    storyboarding a coding session a testing

    session sharing it had assessments it

    had extensions conclusions Etc all of

    that to be popped out of an AI within a

    matter of moments was quite frankly

    impressive because I spent months just

    working on individual releases of like

    Junior literally months of full-time

    work just working on that and then AI is

    able to just like pump out an outline

    really fast like if I had said hey can

    you write this for somebody who's never

    taught computer science before or never

    taught a day in their life what would AI

    be able to do like 10 years from now

    would they be able to get the same level

    of quality and level of detail that I

    had with the 12 Pages or so on average

    of lesson plan content that I created

    for each one of the projects we'll find

    out I wouldn't be surprised if it can do

    that but that being said this stuff was

    very generic like if we look at the

    assessment for Bard it says that quote

    students will be assessed on their

    ability to create a short scratch story

    they will be evaluated on their

    creativity their coding skills and their

    ability to follow instructions end quote

    Yeah and how are you going to do that

    what about their creativity what

    specifically in their coding skills are

    you looking at and what instructions are

    they being asked to follow in their

    particular projects so there's like zero

    support in all of that that's just

    something that is just like oh yeah

    we're gonna do this thing and an

    administrator is going to be like cool

    how are you going to do that it's not

    going to go over well other examples of

    just like generic stuff that I would say

    is like not great advice was like in the

    introduction Bard mentioned quote

    introduce scratch to students and

    explain that it is a programming

    language that can be used to create

    interactive stories games and animations

    show students some examples of scratch

    project that have been created by other

    students end quote okay like what kinds

    of scratch projects like if I were

    writing that I'd say show students

    examples of stories that were created in

    scratch and here is a link to a studio

    that has like 10 different stories as

    examples that you can share with your

    students from simple to complex

    something like that would have been nice

    in this kind of lesson plan but again

    for just creating an outline really fast

    prior curriculum developer still I would

    probably go into this and just be like

    write me out an outline for something

    I'm not familiar with and then I can

    fill in the blanks with like oh a new

    teacher might need more support here or

    there so I do see a lot of like people

    using this in the future now chat CPT on

    the other hand had some interesting

    little improvements to it like for the

    introduction you're going to spend about

    you view you're going to spend about

    five minutes on this and you're going to

    quote show them how to access

    scratch.mit.edu and introduce the

    different components such as the stage

    Sprites and blocks in quote then it goes

    on to say specific blocks that you're

    even going to point out like the wind

    green flag has clicked the say and the

    weight block which all three of those

    are fantastic things that you would use

    in an actual story in scratch so like

    hands down chat GPT is like pretty solid

    for giving you a very like Bare Bones

    lesson plan on scratch but Bard was just

    more of like a generic lesson plan and

    it wasn't really clear if Byrd actually

    knew what scratch was other than a

    coding platform Chachi PT also expanded

    this and so it had that like the

    introduction okay here's what scratches

    then it had a brainstorming and planning

    phase which is for 10 minutes then it

    had creating the story for 20 minutes

    and it like showed you here's how to use

    the broadcast here's when the when the

    green flag is clicked like it it had

    some nuances in there I was like all

    right we're getting closer we're getting

    warmer but then it had adding an

    interactivity for like a 10 minute

    section so this is talking about like

    how to make a more complicated story

    with programming so not just like making

    it so that when you press a green flag

    it just like does does this thing and

    your story is over but actually making

    it so that you can have like different

    choices that affect the plot that was a

    really cool addition that chat gbt added

    that makes things much more creative and

    much more interactive for the user and

    for the student and whatnot who would

    create this so again you can see this

    like full lesson plans for both Bard and

    chap gbt in the show notes here's where

    things get really interesting I then had

    the exact same prompt but I added with

    the words about algorithmic bias so the

    prompt to both Bard and Chachi PT was

    write me a lesson that teaches an

    elementary student how to create a short

    scratch.mit.edu story about algorithmic

    bias here is what Bard said quote I'm

    unable to help as I am only a language

    model and don't have the ability to

    process and understand that end quote

    that's it nothing else is provided other

    than that single sentence jat gbt on the

    other hand provided basically a very

    similar lesson plan as was previously

    written without the words about rhythmic

    a bias but it included some comments in

    here like quote show examples of

    algorithmic bias in real life scenarios

    such as biased facial recognition

    systems or gender biased job application

    algorithms end quote that is actually

    like two really good examples that are

    often discussed in computer science so

    this was nice that chat gbt was actually

    able to include that whereas Bard was

    not able to do that or was unwilling to

    do that which is fascinating because I

    then took that exact same sentence and

    added in a little bit more after that

    original sentence and we get write me a

    lesson plan that teaches an elementary

    student how to create a short scratch

    that mit.edu story about algorithmic

    bias that's all the same while

    encouraging students to incorporate

    their own interests needs desires Etc in

    the story suddenly with that addition in

    there Bard was actually able to create a

    lesson plan until it again populates out

    the lesson plan specifically about all

    the algorithmic bias and ads and stuff

    like quote encourage them to think about

    their own interests needs and desires

    when coming up with ideas some possible

    story ideas include a story about a

    student who is denied a loan because of

    their race or gender a story about a job

    applicant who is not hired because of

    their age or disability a story about a

    person who is targeted by online

    advertising because of their political

    beliefs end quote so Bard was actually

    able to do it but not when it only

    focused on algorithmic bias but when I

    stead said hey focus on algorithmic bias

    but allow students to express themselves

    basically through the project so that

    was really weird I don't know why that

    was the response to it and then Chachi

    BT also was able to do this and so it

    included some like more forms of

    algorithmic bias while also encouraging

    students to be able to kind of Express

    themselves and explore their own

    interest in the project itself so

    overall the more specific you can be

    with the lesson plans the more at least

    in this very small set of lesson plans

    that I asked for the more you're

    actually going to be able to get from

    the different AI that you are

    potentially collaborating with when

    creating your own content now the very

    last question that I ask both the AI was

    based on the kinds of questions I've

    already asked today what questions

    should I ask you next and this is

    something that I think like can be done

    in general when engaging in these like

    discussions or collaborations with AIS

    to figure out okay based on the series

    of questions like what have I not asked

    that I probably should that I'm not

    necessarily thinking of now Bart kind of

    like failed right here so it's suggested

    questions like quote what is the

    difference between Ai and ml how does

    llms work what are some of the

    applications of NLP what are some of the

    challenges of ml what is the future of

    data science what are some of the best

    programming languages to learn end quote

    now llm is large language models like

    chat gbt and Bard NLP is natural

    language processing ml is machine

    learning okay so it does provide a

    little guide for you in in that response

    to that those questions quite frankly

    were not very interesting chat GPT on

    the other hand gave five different

    categories of questions that I could

    have followed up with so there's a

    category of strategies for teaching

    computer science so one of the three

    questions that I gave was what are some

    resources or tools that can support

    Hands-On learning in computer science

    under the ethical considerations in

    technology it had three questions and

    again here's one of them are there any

    emerging ethical issues related to

    artificial intelligence that students

    should be aware of that's a good

    question another category is

    professional development for teachers so

    again I gave three different questions

    and so one of them is how can teachers

    without a computer science background

    receive support in teaching computer

    science effectively the next category is

    integrating computer science across the

    curriculum and there's three questions

    for this one of them is how can computer

    science Concepts be integrated into

    subjects like math science or language

    arts and then the last category is on

    engaging underrepresented groups in

    computer science and so one of the three

    questions is how can we address the

    gender or diversity Gap in the tech

    industry from An Early Education

    perspective and again if you want to see

    the other questions that I left out on

    there in the shout outs jaredalary.com

    com for this particular episode I

    include every single one of the prompts

    and every single one of the responses

    from both Bard and chat gbt because it's

    over 50 pages worth of content it's just

    a click to expand and it'll show you

    exactly what the response was now what's

    fascinating is you can actually just

    like basically refresh the response to

    get a different answer in here so I do

    see this as a really interesting way for

    Content creators whether you're like a

    presenter or a someone who publishes or

    somebody who creates like videos like or

    a podcast or whatever you could totally

    use these different AI platforms to put

    in a a prompt or a question and just get

    some general ideas of topics that you

    can discuss at this point it's not

    necessarily at the point where it can

    get Beyond like the marketing buzzwordy

    responses for a lot of the prompts that

    you're going to give it but it can at

    least point in a direction of oh that

    one out of those five ideas is actually

    a really neat idea that I can elaborate

    on and expand upon in the presentation

    publication Etc I personally am going to

    start using chat GPT in particular

    because it was quite frankly better than

    Bard but both of them and kind of like

    just hitting the refresh button on

    different questions and prompts just so

    I can get some different perspectives

    because again large language models are

    basically synthesizing discourse across

    many different areas and kind of like

    repackaging it in a new way and

    basically saying here is like a summary

    of this idea it's not necessarily right

    or wrong depending on what kind of

    you're asking it but it's at least like

    predicting here's what somebody might

    say if they are sort of knowledgeable

    about this topic area and then as a

    content creator I can then go into this

    and go cool I want to take this and use

    this so if you're an educator and you

    are like have been teaching computer

    science for a couple years and maybe

    there's like a new thing that happens

    that's like a related to current events

    you could go into something like chat

    chippy Dean like hey write me this like

    quick lesson plan on this thing that is

    relevant to students right now and then

    that way you can get a very quick

    outline and you can fill in the blanks

    in there and go okay I'm gonna change

    this I'm gonna add this to here I'm

    gonna make this more relevant to this

    particular individual etc etc so I do

    see this as being a very helpful tool

    for educators for Content creators Etc

    and again content creators however you

    think of that whether you like present

    at csta which is going to happen here in

    July or you like publish on your own

    blog or create podcast or whatever I

    think this is helpful I also think it's

    helpful for students but there's going

    to be some coaching that needs to occur

    so that way students realize that AI is

    not here to solve the answer for you but

    is something that you can collaborate

    with and then you can then modify and

    add to and expand upon what the AI

    created rather than just copy and paste

    cool I'm done with my homework

    assignment don't need to write any more

    essays etc those are my own thoughts and

    Rants and whatnot on these particular

    questions if you have your own thoughts

    that you'd like to share you can share

    them in the comments section on YouTube

    this episode was very different from all

    the other unpacking scholarship episodes

    and interviews that I've done but I hope

    you enjoyed this this conversation was

    informed by discussions with GT Rubble

    Sarah Judd and John Stapleton thank you

    for the three of you all of whom have

    been interviewed on this podcast so you

    can listen to their interviews by just

    clicking the links in the show notes for

    this particular episode stay tuned next

    week for a podcast episode that's also

    going to be a little bit different where

    I'm actually going to talk about some

    suggestions for how you can get started

    in computer science without actually

    having to pay for paid professional

    development so stay tuned for that if

    you enjoyed this episode please consider

    sharing with somebody else or leaving a

    like on YouTube or a review on whatever

    app that you're listening to the song

    like an apple podcast or something like

    that it just helps more people find it

    but again the best thing that you could

    possibly do is to share it with somebody

    else there are hundreds if not thousands

    of more free computer science education

    resources on my website jaredoliri.com

    as well as over 1500 hours of free

    drumming content and a bunch of gaming

    content as well but it's all neatly

    organized so if you're interested in

    just one of those areas you don't have

    to see any of the other stuff thank you

    so much for listening to this episode

    and potentially sharing it with somebody

    else stay tuned for an episode next week

    until then I hope you're all staying

    safe and are having a wonderful week

Prompts and responses (click to expand)

1. What will teaching and learning look like ten years from now?

  • Teaching and learning will look very different in 10 years. Here are some of the changes that we can expect:

    • Personalized learning. Students will have more control over their own learning paths, and they will be able to learn at their own pace and in their own way. This will be facilitated by the use of educational technologies such as adaptive learning software and online learning platforms.

    • More emphasis on critical thinking and problem solving. In today's world, it is more important than ever for students to be able to think critically and solve problems. Schools will place more emphasis on these skills, and they will use a variety of methods to teach them, such as project-based learning and problem-based learning.

    • More collaboration and teamwork. In the future, the workplace will be increasingly collaborative, and schools will prepare students for this by emphasizing collaboration and teamwork in the classroom. Students will be given opportunities to work together on projects and assignments, and they will learn how to communicate effectively and resolve conflict.

    • More use of technology. Technology will play an increasingly important role in education in the future. Teachers will use technology to deliver instruction, and students will use it to learn and collaborate. Technology will also be used to assess student learning and to provide feedback.

    • More focus on global citizenship. In the future, students will need to be prepared to live and work in a globalized world. Schools will place more emphasis on global citizenship by teaching students about different cultures and perspectives. Students will also be given opportunities to learn about global issues and to take action to make a difference in the world.

    These are just some of the changes that we can expect to see in teaching and learning in 10 years. The future of education is bright, and it is exciting to think about the possibilities.

  • Predicting the future with certainty is challenging, but we can speculate on potential trends and advancements in teaching and learning based on current developments. Here are some possibilities for what teaching and learning might look like ten years from now:

    1. Personalized Learning: With advancements in technology and the increasing availability of data, education could become more tailored to individual students' needs. Adaptive learning systems, AI tutors, and intelligent educational software could be utilized to create personalized learning paths for students, catering to their strengths, weaknesses, and interests.

    2. Blended Learning Environments: The integration of technology into education will likely continue to grow. Blended learning models, combining in-person instruction with online resources, could become the norm. Virtual classrooms, video conferencing, and online collaboration tools would enable remote learning and foster global connections among students and educators.

    3. Emphasis on Critical Thinking and Problem Solving: As the world becomes more complex and dynamic, the focus of education may shift towards developing students' critical thinking, problem-solving, and creative skills. Rote memorization might be de-emphasized in favor of cultivating students' abilities to analyze, synthesize, and evaluate information.

    4. Lifelong Learning and Upskilling: The rapid pace of technological advancements and evolving job markets may require individuals to continually update their skills and knowledge throughout their lives. Education systems might incorporate lifelong learning approaches, offering flexible programs and resources for upskilling and reskilling workers to adapt to changing demands.

    5. Collaboration and Project-Based Learning: Collaborative learning experiences and project-based approaches could gain prominence. Students may engage in hands-on, interdisciplinary projects that mirror real-world challenges, promoting teamwork, communication, and practical application of knowledge.

    6. Gamification and Immersive Experiences: Gamification elements, such as rewards, achievements, and interactive simulations, could be integrated into educational activities to enhance engagement and motivation. Virtual reality (VR) and augmented reality (AR) technologies might provide immersive learning experiences, allowing students to explore and interact with subjects in a more interactive and memorable way.

    7. Data-Driven Education: The collection and analysis of educational data could become more prevalent. Educators may leverage learning analytics and assessment data to gain insights into student progress, identify areas of improvement, and make data-informed decisions to enhance teaching effectiveness and student outcomes.

    8. Cultural and Global Awareness: Education could place a greater emphasis on fostering cultural understanding, empathy, and global citizenship. Students may have more opportunities to engage with diverse perspectives, learn about different cultures, and develop a sense of social responsibility and global interconnectedness.

    It's important to note that these predictions are speculative, and the future of teaching and learning will depend on various factors, including technological advancements, societal changes, and educational policies. Flexibility, adaptability, and a focus on nurturing essential skills will likely be key in preparing students for the challenges and opportunities of the future.

- How is that different from today?

  • Here are some of the key differences between teaching and learning today and what we can expect in 10 years:

    • Personalized learning: Today, students typically learn in a one-size-fits-all classroom setting. In 10 years, students will have more control over their own learning paths, and they will be able to learn at their own pace and in their own way. This will be facilitated by the use of educational technologies such as adaptive learning software and online learning platforms.

    • More emphasis on critical thinking and problem solving: Today, many schools focus on teaching students to memorize facts. In 10 years, schools will place more emphasis on teaching students to think critically and solve problems. This will be important in a world where information is constantly changing and where students will need to be able to think for themselves and come up with creative solutions.

    • More collaboration and teamwork: Today, students typically work on individual projects. In 10 years, students will be given more opportunities to work together on projects and assignments. This will help them to develop their collaboration and teamwork skills, which will be important in the future workplace.

    • More use of technology: Today, technology is often used in the classroom as a supplement to traditional instruction. In 10 years, technology will play a more central role in education. Teachers will use technology to deliver instruction, and students will use it to learn and collaborate. Technology will also be used to assess student learning and to provide feedback.

    • More focus on global citizenship: Today, many schools focus on teaching students about their own culture. In 10 years, schools will place more emphasis on teaching students about different cultures and perspectives. This will help students to become more global citizens and to understand the world around them.

    Overall, teaching and learning in 10 years will be more personalized, focused on critical thinking and problem solving, collaborative, technology-rich, and globalized. These changes will help students to develop the skills they need to succeed in the future.

  • While some of the trends mentioned in the previous response are already present in today's educational landscape, there are several key differences that may become more pronounced or evolve over the next ten years. Here's a comparison between the projected future and the current state of teaching and learning:

    1. Personalized Learning: Personalized learning is already gaining traction today, but it is often limited to specific schools or programs. In the future, advancements in technology and data analysis may allow for more widespread implementation of personalized learning approaches, tailoring education to the individual needs of each student.

    2. Blended Learning Environments: Blended learning, combining in-person and online components, is already being used in many educational settings. However, the COVID-19 pandemic has accelerated its adoption and highlighted the need for remote learning options. In the future, we may see a more seamless integration of virtual classrooms, online resources, and interactive tools to create more effective blended learning experiences.

    3. Emphasis on Critical Thinking and Problem Solving: While critical thinking and problem-solving skills have always been important, there is a growing recognition of their significance in today's rapidly changing world. Efforts to promote these skills are being made, but the future may see a stronger shift away from traditional rote memorization methods towards more active learning approaches that foster critical thinking and problem-solving abilities.

    4. Lifelong Learning and Upskilling: Lifelong learning has been increasingly emphasized in recent years, and the need for upskilling and reskilling is becoming more evident. However, the pace of technological advancement suggests that lifelong learning will become even more crucial in the future, with education systems adapting to provide flexible and accessible opportunities for individuals to continually update their skills.

    5. Collaboration and Project-Based Learning: Collaborative learning and project-based approaches are already being implemented in many classrooms. However, the future may see a greater emphasis on interdisciplinary projects, real-world applications, and global collaborations, leveraging technology to connect students and educators across geographical boundaries.

    6. Gamification and Immersive Experiences: Gamification and immersive technologies are still in the early stages of adoption in education. As these technologies become more accessible and affordable, we may see greater integration of game elements and immersive experiences to enhance engagement, motivation, and the overall learning process.

    7. Data-Driven Education: Educational data analytics and learning analytics are already being utilized to some extent, but their full potential is yet to be realized. In the future, advancements in data collection, analysis techniques, and privacy regulations may enable more comprehensive and actionable insights, allowing educators to make data-driven decisions and tailor instruction to individual student needs.

    8. Cultural and Global Awareness: Global awareness and cultural understanding are already valued in many educational curricula. However, with an increasingly interconnected world, the future may see a stronger focus on nurturing these skills, fostering empathy, and promoting cross-cultural communication to prepare students for a globalized society.

    It's worth noting that the pace of change and adoption varies across educational systems and regions, so the extent to which these differences manifest will depend on various factors such as infrastructure, resources, and educational policies.

2. What is the role of artificial intelligence in teaching and learning?

  • Artificial intelligence (AI) is rapidly changing the world, and education is no exception. AI has the potential to revolutionize teaching and learning by making it more personalized, engaging, and effective.

    Here are some of the ways that AI is being used in education today:

    • Personalized learning: AI can be used to create personalized learning experiences for students. This means that students can learn at their own pace and in their own way, based on their individual needs and interests.

    • Adaptive learning: AI can be used to create adaptive learning materials that adjust to the student's level of understanding. This means that students can get the help they need when they need it, without having to wait for the teacher.

    • Virtual tutors: AI can be used to create virtual tutors that can answer students' questions and provide feedback. This can be especially helpful for students who need extra help or who are learning remotely.

    • Assessment: AI can be used to assess student learning in a more accurate and efficient way. This can help teachers to identify students who are struggling and to provide them with the help they need.

    • Research: AI can be used to conduct research on education and to develop new teaching methods. This can help to improve the quality of education for all students.

  • Artificial intelligence (AI) can play a significant role in transforming teaching and learning in several ways:

    1. Personalized Learning: AI algorithms can analyze vast amounts of data to create personalized learning experiences for students. By adapting content, pacing, and difficulty levels to individual students' needs, AI-powered educational platforms can provide tailored instruction, ensuring that students receive the right level of challenge and support.

    2. Intelligent Tutoring: AI tutors can provide individualized guidance and support to students. These virtual assistants can answer questions, provide explanations, and offer feedback, mimicking the role of a human tutor. AI tutors can be available 24/7, providing on-demand assistance to students whenever they need it.

    3. Automated Grading and Feedback: AI can automate the grading process for certain types of assessments, such as multiple-choice questions or coding exercises. This saves teachers time and allows for faster feedback to students. AI-powered systems can also provide detailed feedback, highlighting areas for improvement and offering targeted suggestions to help students progress.

    4. Natural Language Processing (NLP): NLP enables computers to understand and generate human language. AI-powered chatbots or virtual assistants can engage in conversations with students, answering questions, providing explanations, and engaging in interactive dialogue. NLP can also be used to develop language learning applications, language translation tools, and speech recognition systems.

    5. Data Analysis and Learning Analytics: AI can analyze large datasets generated by students' interactions with educational platforms, helping identify patterns, trends, and insights. This data analysis can inform instructional design, provide feedback on student progress, and assist in identifying areas where additional support or intervention may be needed.

    6. Content Recommendation and Curation: AI algorithms can recommend relevant learning resources, books, articles, or videos based on students' interests, learning styles, and previous interactions. This helps students discover new materials and fosters self-directed learning.

    7. Intelligent Content Creation: AI can assist in generating educational content, such as automated lesson plans, quizzes, or interactive simulations. It can also provide assistance in creating adaptive learning materials that adjust to individual student needs.

    8. Virtual Reality and Augmented Reality: AI-powered virtual reality (VR) and augmented reality (AR) technologies can provide immersive and interactive learning experiences. These technologies can simulate real-world scenarios, allowing students to explore and interact with subjects in a more engaging and practical manner.

    It's important to note that while AI has the potential to enhance teaching and learning, it is not intended to replace human educators. Rather, AI can complement and support teachers by automating routine tasks, providing insights, and offering personalized assistance, thereby enabling educators to focus more on individualized instruction, mentoring, and fostering human connection in the classroom.

3. Why are teachers leaving the field and what can be done to prevent that?

  • There are many reasons why teachers are leaving the field. Some of the most common reasons include:

    • Low pay: Teachers are often underpaid for the amount of work they do. According to the National Education Association, the average teacher salary in the United States is $61,730. This is significantly lower than the average salary for other professionals with a college degree.

    • Heavy workload: Teachers often have a heavy workload, which can lead to stress and burnout. They are responsible for planning lessons, grading papers, and managing a classroom of students. They may also be required to work long hours outside of school, such as attending meetings or planning for field trips.

    • Lack of support: Teachers often feel unsupported by their schools and administrators. They may not have the resources they need to do their jobs effectively, such as small class sizes or access to technology. They may also feel like they are not being heard or that their concerns are not being addressed.

    • Unruly students: Teachers may be dealing with unruly students who are disruptive and disrespectful. This can be a major source of stress and can make it difficult to teach effectively.

    • Parental involvement: Some teachers feel like they do not have enough support from parents. Parents may not be involved in their children's education or may not be supportive of the teacher's methods.

    There are a number of things that can be done to prevent teachers from leaving the field. These include:

    • Increase teacher pay: Increasing teacher pay would help to attract and retain qualified teachers.

    • Reduce teacher workload: Reducing teacher workload would help to reduce stress and burnout. This could be done by reducing class sizes, providing more planning time, or offering more professional development opportunities.

    • Provide more support: Schools and administrators can provide more support to teachers by providing them with the resources they need, such as small class sizes or access to technology. They can also listen to teachers' concerns and take steps to address them.

    • Develop positive relationships with students: Teachers can develop positive relationships with students by being fair and consistent, showing respect, and being approachable.

    • Encourage parental involvement: Schools can encourage parental involvement by sending home regular newsletters, holding parent-teacher conferences, and inviting parents to volunteer at school.

    By addressing these issues, we can help to create a more positive and supportive environment for teachers. This will help to attract and retain qualified teachers, which is essential for ensuring that all students have access to a quality education.

  • Teachers leave the field for various reasons, and it's a complex issue influenced by a combination of factors. Some common reasons why teachers choose to leave include:

    1. Low Salaries: In many regions, teacher salaries may not be competitive compared to other professions with similar levels of education and experience. Financial concerns can lead teachers to seek better-paying opportunities outside of education.

    2. Heavy Workload and Stress: Teaching can be demanding, with long working hours, administrative tasks, lesson planning, grading, and managing student behavior. The workload, combined with high expectations and accountability measures, can contribute to burnout and stress.

    3. Lack of Support and Professional Development: Teachers thrive when they receive ongoing support and opportunities for professional growth. A lack of resources, limited access to professional development, and inadequate support from administrators and colleagues can impact job satisfaction and lead teachers to seek more supportive environments.

    4. Classroom Management Challenges: Maintaining a positive learning environment can be challenging, especially when dealing with diverse student needs, disruptive behavior, or lack of resources. Teachers who feel overwhelmed by classroom management issues may consider leaving the field.

    5. Policy Changes and Standardized Testing: Frequent changes in education policies, including the emphasis on high-stakes standardized testing, can create pressure on teachers to focus on test preparation rather than holistic teaching and student development. Such shifts may erode job satisfaction and diminish teachers' autonomy and creativity.

    To address the issue of teachers leaving the field, several strategies can be implemented:

    1. Competitive Compensation: Providing teachers with competitive salaries and benefits can attract and retain talented individuals in the profession. Higher salaries can also serve as a recognition of the value and importance of the teaching profession.

    2. Supportive Work Environment: Creating a positive and supportive work environment is crucial. This includes fostering a collaborative culture, providing mentorship programs, and ensuring access to resources and professional development opportunities.

    3. Reduced Administrative Burden: Reducing unnecessary administrative tasks and paperwork can free up teachers' time and allow them to focus more on instruction and student engagement.

    4. Improved Classroom Management Strategies: Providing training and support for effective classroom management strategies can help teachers better handle challenging student behavior and create a positive learning environment.

    5. Professional Development and Growth: Investing in high-quality professional development programs that cater to teachers' needs and interests can enhance their skills, boost job satisfaction, and promote retention. Professional development should focus on innovative instructional practices, technology integration, and strategies for meeting the diverse needs of students.

    6. Teacher Voice and Collaboration: Involving teachers in decision-making processes, policy development, and curriculum design can empower them and enhance their sense of ownership and professional autonomy.

    7. Teacher Well-being and Mental Health Support: Prioritizing teacher well-being and providing access to mental health support can help address burnout and stress-related issues. Implementing wellness programs, offering counseling services, and promoting work-life balance can contribute to teacher retention.

    Addressing the issue of teacher attrition requires a comprehensive approach that involves collaboration among policymakers, administrators, educators, and stakeholders in the education system. By prioritizing the needs and well-being of teachers, providing ongoing support, and creating conducive working environments, it is possible to mitigate factors leading to teacher departures and improve teacher retention rates.

4. How much should a public elementary school computer science educator be paid in Arizona with ten years of experience and a doctorate in education?

  • According to the Bureau of Labor Statistics, the median annual salary for elementary school teachers in Arizona was $56,590 in 2020. However, salaries can vary depending on experience, education, and location. A public elementary school computer science educator with ten years of experience and a doctorate in education could expect to earn a salary of $75,000 or more.

    Here are some factors that can affect the salary of a public elementary school computer science educator in Arizona:

    • Experience: Teachers with more experience typically earn higher salaries.

    • Education: Teachers with higher levels of education, such as a doctorate in education, typically earn higher salaries.

    • Location: Teachers in urban areas typically earn higher salaries than teachers in rural areas.

    • School district: The salary of a teacher can also vary depending on the school district they work for.

    It is important to note that these are just estimates and the actual salary of a public elementary school computer science educator in Arizona can vary depending on the specific factors mentioned above.

    Here are some of the benefits of being a public elementary school computer science educator in Arizona:

    • Job security: There is a high demand for qualified computer science educators in Arizona.

    • Good benefits: Public school teachers in Arizona typically receive good benefits, such as health insurance, retirement plans, and paid time off.

    • Impactful work: Teachers have the opportunity to make a real difference in the lives of their students.

    If you are interested in becoming a public elementary school computer science educator in Arizona, there are a few things you can do to increase your chances of getting a job. First, make sure you have a strong academic background in computer science. Second, get experience teaching computer science, either through volunteer work or a part-time job. Finally, network with other computer science educators in Arizona.

  • As an AI language model, I don't have access to real-time salary data or specific information about salary scales in Arizona. Teacher salaries can vary based on factors such as location, school district, budget, and negotiation between teachers' unions and education authorities. Therefore, it's best to consult reliable sources for up-to-date and accurate salary information.

    To determine the specific salary range for a public elementary school computer science educator in Arizona with ten years of experience and a doctorate in education, you can refer to the following sources:

    1. Arizona Department of Education: The Arizona Department of Education may provide information on salary scales for teachers in the state. They may have salary schedules or guidelines available on their official website.

    2. School District Websites: Each school district in Arizona may have its own salary schedule, which can be found on their respective websites. By visiting the websites of the school districts where you are interested in working, you may find salary information specific to that district.

    3. Teachers' Union: The local teachers' union or association in Arizona may have information on salary scales, collective bargaining agreements, and other relevant details for educators in the state.

    By accessing these sources or reaching out to the appropriate education authorities in Arizona, you can gather accurate and up-to-date information about the salary range for a public elementary school computer science educator with ten years of experience and a doctorate in education.

- How much should a private elementary school educator be paid in Arizona with ten years of experience and a doctorate in education?

  • The salary of a private elementary school educator in Arizona with ten years of experience and a doctorate in education can vary depending on the school, but it is typically higher than the salary of a public school educator with the same qualifications. According to a 2021 survey by the National Association of Independent Schools, the median salary for elementary school teachers in private schools was $72,000. However, salaries can range from $50,000 to $100,000 or more, depending on the school's location, size, and budget.

    There are a few reasons why private school teachers are typically paid more than public school teachers. First, private schools are often able to charge higher tuition, which allows them to pay their teachers more. Second, private schools often have smaller class sizes, which allows teachers to spend more time with each student. Third, private schools often have more resources, such as technology and materials, which can help teachers to be more effective.

    If you are interested in becoming a private elementary school educator in Arizona, there are a few things you can do to increase your chances of getting a job. First, make sure you have a strong academic background in education. Second, get experience teaching elementary school, either through volunteer work or a part-time job. Finally, network with other private school educators in Arizona.

    Here are some of the benefits of being a private elementary school educator in Arizona:

    • Higher salaries: Private school teachers in Arizona typically earn higher salaries than public school teachers.

    • Smaller class sizes: Private schools in Arizona typically have smaller class sizes than public schools.

    • More resources: Private schools in Arizona typically have more resources, such as technology and materials, than public schools.

    • More autonomy: Private school teachers in Arizona typically have more autonomy than public school teachers.

    If you are looking for a rewarding career in education, becoming a private elementary school educator in Arizona is a great option. With a strong academic background, experience teaching elementary school, and a network of contacts, you can increase your chances of finding a job at a private school that is a good fit for you.

  • Determining the specific salary for a private elementary school educator in Arizona with ten years of experience and a doctorate in education can be challenging as private schools often have more variability in their salary structures compared to public schools. Private school salaries are typically determined by factors such as the school's budget, location, size, reputation, and the demand for educators with specific qualifications.

    To get an accurate and up-to-date understanding of the salary range for a private elementary school educator in Arizona with your specified qualifications, you can consider the following approaches:

    1. Research Private School Websites: Visit the websites of private schools in Arizona, especially those that are similar in size, reputation, and location to the school you are interested in. Some private schools may provide salary information on their websites or have contact information available for inquiries about employment and compensation.

    2. Networking and Professional Organizations: Connect with educators working in private schools in Arizona, join professional organizations or forums related to private school education, and engage in discussions about salary ranges and compensation packages. Networking with individuals in the field can provide you with insights into the typical compensation for private school educators in the state.

    3. Consult Salary Surveys and Reports: Look for salary surveys and reports specific to private school educators in Arizona or similar regions. These surveys may provide average salary ranges or data on compensation trends within the private school sector.

    4. Contact Private Schools Directly: Reach out to private schools in Arizona that you are interested in working for and inquire about their salary ranges and benefits for educators with your qualifications. It may be beneficial to communicate directly with the school's administration or human resources department to gather specific information.

    Remember that salary ranges can vary significantly between private schools, and negotiations for compensation packages may be part of the hiring process. Conducting thorough research, networking with professionals in the field, and directly contacting schools will help you obtain the most accurate and relevant salary information for private elementary school educators in Arizona.

5. What are the top five pedagogies for teaching computer science?

  • Here are the top five pedagogies for teaching computer science:

    • Project-based learning: Project-based learning (PBL) is a student-centered approach to learning that involves students working on a real-world problem or challenge. PBL can be a great way to teach computer science because it allows students to apply what they are learning in a meaningful way.

    • Problem-based learning: Problem-based learning (PBL) is another student-centered approach to learning that involves students working on a complex problem. PBL can be a great way to teach computer science because it allows students to develop their problem-solving skills.

    • Approaches to Computational Thinking: Approaches to Computational Thinking (ACT) is a framework for teaching computer science that focuses on the process of thinking like a computer scientist. ACT can be a great way to teach computer science because it helps students to develop their critical thinking and problem-solving skills.

    • Inductive Inquiry: Inductive Inquiry is a teaching method that emphasizes discovery learning. Inductive Inquiry can be a great way to teach computer science because it allows students to explore and learn at their own pace.

    • Experiential Learning: Experiential Learning is a teaching method that emphasizes hands-on learning. Experiential Learning can be a great way to teach computer science because it allows students to learn by doing.

    These are just a few of the many pedagogies that can be used to teach computer science. The best pedagogy for a particular classroom will depend on the students, the teacher, and the resources available.

    Here are some additional tips for teaching computer science:

    • Make it relevant: Computer science can be a challenging subject for some students, so it is important to make it relevant to their lives. This can be done by using real-world examples and applications.

    • Use visuals: Visuals can help students to understand complex concepts in computer science. This can be done by using diagrams, flowcharts, and animations.

    • Make it fun: Computer science should be fun! This can be done by using games, puzzles, and other activities.

    • Provide feedback: Students need feedback in order to improve their skills in computer science. This feedback can be provided by the teacher, peers, or self-assessment.

    • Celebrate successes: It is important to celebrate students' successes in computer science. This will help them to stay motivated and engaged.

    By following these tips, you can help your students to learn computer science in a fun and engaging way.

  • When it comes to teaching computer science, several pedagogical approaches can be effective in engaging students and fostering their understanding of the subject matter. Here are five pedagogies commonly used in computer science education:

    1. Project-Based Learning (PBL): Project-Based Learning involves students working on real-world projects or challenges that require them to apply their computer science knowledge and skills. Through hands-on, collaborative projects, students gain practical experience, develop problem-solving skills, and learn to work in teams. PBL encourages critical thinking, creativity, and the integration of various computer science concepts.

    2. Inquiry-Based Learning: Inquiry-Based Learning focuses on student-driven exploration and discovery. In computer science, this pedagogy encourages students to ask questions, investigate problems, and find solutions independently. By promoting curiosity and active engagement, inquiry-based learning helps students develop problem-solving abilities, research skills, and a deeper understanding of fundamental computer science concepts.

    3. Collaborative Learning: Collaborative Learning emphasizes group work and collaboration among students. It encourages peer-to-peer interaction, discussion, and cooperative problem-solving. In computer science, collaborative learning can involve pair programming, group projects, and team-based coding challenges. This pedagogy enhances communication skills, teamwork, and the ability to work effectively in diverse teams.

    4. Flipped Classroom: The Flipped Classroom approach involves delivering instructional content outside of class (e.g., through videos, online modules, or readings) and utilizing class time for hands-on activities and discussions. In computer science, students can watch video tutorials or complete online exercises before coming to class, enabling them to engage in practical coding, problem-solving, and concept reinforcement during class sessions. Flipped classrooms promote active learning, student engagement, and individualized support.

    5. Game-Based Learning: Game-Based Learning incorporates educational games, gamified elements, or game design principles to teach computer science concepts. Students learn through interactive gameplay, simulations, and problem-solving within a game environment. Game-based learning promotes motivation, engagement, and a deeper understanding of programming concepts and algorithms.

    It's worth noting that these pedagogical approaches can be combined or adapted based on the specific needs of students, the learning objectives, and the available resources. Effective computer science instruction often involves a blend of these pedagogies, along with the integration of technology tools, formative assessment strategies, and differentiation to meet the diverse needs of learners.

- Elaborate on how each of the pedagogies you listed are beneficial for learning

  • Sure. Here is a more detailed look at how each of the pedagogies I listed are beneficial for learning:

    • Project-based learning: Project-based learning (PBL) is a student-centered approach to learning that involves students working on a real-world problem or challenge. PBL can be a great way to teach computer science because it allows students to apply what they are learning in a meaningful way. Students are more likely to remember and understand information when they are able to apply it to a real-world problem. PBL also helps students to develop their problem-solving, collaboration, and communication skills.

    • Problem-based learning: Problem-based learning (PBL) is another student-centered approach to learning that involves students working on a complex problem. PBL can be a great way to teach computer science because it allows students to develop their problem-solving skills. Students are faced with a problem and must work together to find a solution. This helps them to develop their critical thinking, creativity, and collaboration skills.

    • Approaches to Computational Thinking: Approaches to Computational Thinking (ACT) is a framework for teaching computer science that focuses on the process of thinking like a computer scientist. ACT can be a great way to teach computer science because it helps students to develop their critical thinking and problem-solving skills. ACT teaches students how to break down problems into smaller steps, identify patterns, and use algorithms to solve problems.

    • Inductive Inquiry: Inductive Inquiry is a teaching method that emphasizes discovery learning. Inductive Inquiry can be a great way to teach computer science because it allows students to explore and learn at their own pace. Students are given a problem or challenge and are allowed to explore different solutions until they find one that works. This helps them to develop their creativity and problem-solving skills.

    • Experiential Learning: Experiential Learning is a teaching method that emphasizes hands-on learning. Experiential Learning can be a great way to teach computer science because it allows students to learn by doing. Students are given the opportunity to build their own projects or programs. This helps them to develop their coding skills and problem-solving skills.

    These are just a few of the many pedagogies that can be used to teach computer science. The best pedagogy for a particular classroom will depend on the students, the teacher, and the resources available.

    I hope this helps!

  • Certainly! Here's a more detailed explanation of the benefits of each pedagogy for learning computer science:

    1. Project-Based Learning (PBL):

      • Practical Application: PBL allows students to apply computer science knowledge in real-world contexts, making the learning experience more relevant and meaningful.

      • Problem-Solving Skills: By working on projects, students develop critical thinking, analytical skills, and problem-solving abilities, which are essential in computer science.

      • Collaboration: PBL promotes teamwork and collaboration as students work together to tackle complex problems, improving communication, and fostering social skills.

      • Creativity and Innovation: PBL encourages students to think creatively and come up with innovative solutions, fostering their ability to think outside the box.

    2. Inquiry-Based Learning:

      • Critical Thinking: Inquiry-based learning promotes critical thinking as students explore questions, analyze data, and draw conclusions, developing their ability to think critically and evaluate information.

      • Autonomy and Ownership: By directing their own learning, students become active participants in their education, taking ownership of their learning process, and developing self-directed learning skills.

      • Problem-Solving and Research Skills: Through inquiry-based learning, students develop research skills, learn how to frame and investigate questions, and develop problem-solving strategies.

      • Deeper Understanding: By engaging in inquiry, students develop a deeper understanding of computer science concepts as they actively seek answers and make connections.

    3. Collaborative Learning:

      • Communication and Collaboration: Collaborative learning encourages students to work together, enhancing their communication, collaboration, and teamwork skills, which are essential in the field of computer science.

      • Peer Learning: Students can learn from their peers by discussing concepts, explaining ideas, and providing feedback to one another, which can reinforce learning and deepen understanding.

      • Diverse Perspectives: Collaboration exposes students to diverse perspectives and approaches, fostering creativity and promoting critical thinking as they consider different solutions to problems.

      • Enhanced Problem-Solving: Collaborative problem-solving allows students to tackle complex tasks collectively, drawing on the strengths and expertise of each team member, leading to more comprehensive solutions.

    4. Flipped Classroom:

      • Active Learning: Flipped classrooms promote active learning by shifting passive content consumption outside of class, allowing students to engage in hands-on activities, coding exercises, and discussions during class time.

      • Differentiated Instruction: Students can learn at their own pace and review content as needed outside of class, while in-class activities provide opportunities for individualized support, addressing specific student needs.

      • Immediate Feedback: In-class activities facilitate immediate feedback from the instructor, allowing students to receive guidance, clarification, and corrections in real-time.

      • Application and Reinforcement: Flipped classrooms provide opportunities for students to apply and reinforce their understanding of computer science concepts through practical coding exercises and problem-solving tasks.

    5. Game-Based Learning:

      • Motivation and Engagement: Games capture students' interest, motivate them to actively participate, and create an engaging learning experience, promoting sustained focus and enjoyment in computer science education.

      • Hands-on Learning: Games provide hands-on experiences, allowing students to experiment, make decisions, and observe immediate consequences, leading to a deeper understanding of programming concepts.

      • Immediate Feedback: Games can offer immediate feedback, guiding students through challenges and providing corrective guidance, fostering a sense of mastery and progress.

      • Trial and Error: Games encourage students to take risks, try different strategies, and learn from their mistakes, promoting resilience, problem-solving skills, and a growth mindset.

    These pedagogical approaches are not mutually exclusive and can be combined to create dynamic and engaging learning experiences in computer science education. By leveraging these approaches, educators can enhance student motivation, critical thinking, problem-solving skills, collaboration, and a deeper understanding of computer science concepts.

- What are the downsides for each of the pedagogies you listed?

  • Here are some of the downsides for each of the pedagogies I listed:

    • Project-based learning: Project-based learning (PBL) can be time-consuming and requires a lot of planning and preparation from the teacher. It can also be difficult to assess student learning in a project-based setting.

    • Problem-based learning: Problem-based learning (PBL) can be challenging for students who are not used to working independently or collaborating with others. It can also be difficult for students to find problems that are both challenging and relevant to their interests.

    • Approaches to Computational Thinking: Approaches to Computational Thinking (ACT) can be difficult for students who are not already familiar with the basics of computer science. It can also be difficult for teachers to find resources that support ACT instruction.

    • Inductive Inquiry: Inductive Inquiry can be chaotic and difficult to manage in a large classroom setting. It can also be difficult for students to stay on track and make progress towards their goals.

    • Experiential Learning: Experiential Learning can be expensive, as it often requires students to purchase materials or equipment. It can also be difficult for teachers to find time to provide individual feedback to students.

    It is important to note that these are just some of the potential downsides of each pedagogy. The actual downsides may vary depending on the specific classroom context.

    Here are some tips for overcoming the downsides of each pedagogy:

    • Project-based learning: To reduce the time commitment required for PBL, teachers can choose projects that are shorter or that focus on a single concept. To make assessment easier, teachers can develop rubrics that clearly define the criteria for success.

    • Problem-based learning: To make PBL more accessible to all students, teachers can provide support and scaffolding throughout the process. To help students find problems that are relevant to their interests, teachers can encourage students to choose problems from their own lives or from current events.

    • Approaches to Computational Thinking: To make ACT instruction more accessible to students, teachers can provide hands-on activities and games that introduce the concepts of computational thinking. To help teachers find resources that support ACT instruction, there are a number of online resources available, such as the Khan Academy and Code.org.

    • Inductive Inquiry: To help manage Inductive Inquiry in a large classroom setting, teachers can break students into small groups or pairs. To help students stay on track, teachers can provide regular checkpoints and feedback.

    • Experiential Learning: To reduce the cost of Experiential Learning, teachers can encourage students to use recycled materials or to find free or low-cost resources online. To make it easier for teachers to provide individual feedback, teachers can use peer assessment or group work.

    By following these tips, teachers can overcome the downsides of each pedagogy and create a learning environment that is both engaging and effective for all students.

  • While the pedagogies I listed have many benefits, it's important to consider potential downsides and challenges associated with their implementation. Here are some potential downsides for each pedagogy:

    1. Project-Based Learning (PBL):

      • Time Management: PBL projects can be time-consuming, requiring careful planning and coordination to ensure that the project's scope aligns with available instructional time.

      • Assessment Challenges: Assessing individual student learning in PBL can be complex since projects often involve group work. It can be challenging to accurately evaluate individual contributions and learning outcomes.

      • Content Coverage: PBL projects may focus on specific topics, potentially leaving gaps in other areas of the curriculum if not properly integrated and aligned with learning objectives.

    2. Inquiry-Based Learning:

      • Teacher Expertise: Implementing inquiry-based learning requires teachers who are skilled in guiding student inquiry, facilitating discussions, and supporting students in their exploration. Lack of teacher expertise in inquiry methods may hinder its effective implementation.

      • Time Constraints: Inquiry-based learning often requires extended periods for student exploration and investigation, which can be challenging to fit within strict schedules or limited instructional time.

      • Information Overload: Inexperienced students may struggle to manage the vast amount of information available during inquiry-based learning, leading to confusion or difficulty in synthesizing and organizing information effectively.

    3. Collaborative Learning:

      • Unequal Contributions: In collaborative learning, some students may contribute more or less than others, leading to imbalances in workload and potential frustration among group members.

      • Conflict Resolution: Collaborative settings may present challenges related to conflicts or disagreements among students. Teachers must facilitate effective communication, conflict resolution, and equitable participation.

      • Individual Accountability: Ensuring that each student is accountable for their learning and actively engaged in group activities can be challenging in collaborative learning environments.

    4. Flipped Classroom:

      • Access to Resources: Students must have reliable access to technology and resources outside of the classroom to engage with flipped learning materials, which can pose challenges in areas with limited connectivity or insufficient resources.

      • Self-Directed Learning: Flipped classrooms require students to take responsibility for their learning outside of class, which may not suit all students or require additional support for those who struggle with self-directed learning.

      • Monitoring Progress: Teachers need effective strategies to monitor student engagement with pre-class materials and identify students who may require additional support or clarification

    5. Game-Based Learning:

      • Alignment with Learning Objectives: It's crucial to ensure that game-based learning activities align with specific learning objectives and standards. Some games may be engaging but may not effectively address the intended learning outcomes.

      • Overemphasis on Fun: While games can enhance motivation, there is a risk of focusing too much on entertainment value, potentially overshadowing the learning objectives and leading to a superficial understanding of the subject matter.

      • Limited Content Coverage: Game-based learning activities may cover a specific subset of computer science concepts or skills, and care must be taken to ensure that a broader range of content is addressed alongside game-based activities.

    Understanding these potential downsides can help educators proactively address challenges and design instructional strategies that mitigate these issues. Implementing pedagogies effectively requires thoughtful planning, ongoing monitoring, and adjustments to ensure optimal learning outcomes.

6. How could teachers make computer science classes more equitable?

  • Here are some ways that teachers can make computer science classes more equitable:

    • Use a variety of teaching methods: There is no one-size-fits-all approach to teaching computer science. Teachers should use a variety of teaching methods to reach all students, including project-based learning, problem-based learning, and experiential learning.

    • Provide individualized support: Not all students learn at the same pace or in the same way. Teachers should provide individualized support to students who need it, such as extra help during office hours or after school.

    • Use culturally relevant examples: When teaching computer science concepts, teachers should use examples that are relevant to the students' cultures and experiences. This will help students to see themselves in the material and make it more meaningful to them.

    • Create a welcoming environment: Computer science can be a male-dominated field. Teachers should create a welcoming environment for all students, regardless of their gender, race, or ethnicity. This can be done by using inclusive language, displaying posters of women and underrepresented minorities in computer science, and encouraging students to share their ideas and experiences.

    • Be a role model: Teachers can be role models for their students by demonstrating their own interest in computer science. They can do this by talking about their own experiences with computer science, sharing their favorite computer science projects, and encouraging students to pursue their own interests in computer science.

    By following these tips, teachers can make computer science classes more equitable and accessible to all students.

    Here are some additional tips for making computer science classes more equitable:

    • Be aware of your own biases: Teachers should be aware of their own biases and how they might be affecting their teaching. For example, teachers who are not familiar with coding might be more likely to call on students who they think are good at coding, even if those students are not from underrepresented groups.

    • Create a space for students to share their experiences: Teachers should create a space where students feel comfortable sharing their experiences with computer science. This can be done by asking students to share their favorite computer science projects or by inviting students to lead discussions about computer science topics.

    • Provide opportunities for students to collaborate: Students from underrepresented groups are more likely to collaborate with other students from underrepresented groups. Teachers can provide opportunities for students to collaborate by assigning group projects or by creating a computer science club.

    • Celebrate student successes: Teachers should celebrate student successes, both big and small. This will help to motivate students and make them feel like they belong in the computer science classroom.

    By following these tips, teachers can create a more equitable and inclusive computer science classroom.

  • To make computer science classes more equitable, teachers can implement several strategies to ensure that all students have equal access, opportunities, and support in their learning journey. Here are some approaches that can promote equity in computer science education:

    1. Inclusive Curriculum and Instruction:

      • Select diverse and inclusive learning resources, materials, and examples that represent a range of cultural perspectives and backgrounds.

      • Incorporate projects, coding exercises, and problem-solving tasks that relate to students' interests and experiences, ensuring relevance and engagement for all learners.

      • Use multiple instructional strategies and modalities to accommodate diverse learning styles and preferences.

      • Provide clear and structured instructions to support students who may require additional guidance or clarification.

    2. Addressing Stereotypes and Bias:

      • Challenge stereotypes and biases associated with computer science by highlighting the achievements and contributions of diverse individuals in the field.

      • Foster a classroom culture that values and respects diverse perspectives, encouraging open discussions and creating a safe space for all students to participate.

      • Discuss the importance of inclusivity and diversity in computer science and emphasize that anyone can succeed in the field regardless of their gender, race, or background.

    3. Access and Infrastructure:

      • Ensure equitable access to technology and resources by providing opportunities for students to use computer science tools and software, whether at school or through loan programs for home use.

      • Address the digital divide by collaborating with community organizations or leveraging government initiatives to provide internet connectivity and devices to students who lack access at home.

      • Offer flexible options for completing computer science assignments, considering students' access to technology and accommodating different learning environments.

    4. Supportive Classroom Environment:

      • Create a positive and inclusive classroom climate where all students feel valued, respected, and supported.

      • Encourage collaboration and teamwork, promoting a sense of belonging and fostering peer support among students.

      • Provide individualized support and differentiated instruction, taking into account students' diverse learning needs, backgrounds, and prior knowledge.

      • Offer additional resources, tutorials, or mentorship opportunities to students who may need extra support or encouragement.

    5. Community Engagement and Outreach:

      • Establish partnerships with community organizations, businesses, and professionals in the field of computer science to provide mentorship opportunities, guest speakers, or career exploration experiences.

      • Organize field trips, hackathons, or coding competitions that involve diverse student populations and encourage participation from underrepresented groups.

      • Advocate for computer science education equity at the school and district levels, raising awareness and influencing policy decisions to ensure equitable resource allocation and access to opportunities.

    By implementing these strategies, teachers can create an inclusive and equitable learning environment that supports all students in their computer science education journey, regardless of their background or identity. It is important to continuously reflect on and adapt teaching practices to meet the evolving needs of students and foster equitable outcomes in computer science education.

7. Why should all students learn computer science?

  • Here are some reasons why all students should learn computer science:

    • Computer science is a foundational skill: Computer science is a foundational skill that is essential for success in today's world. Computers are used in almost every aspect of our lives, from work to school to entertainment. By learning computer science, students can develop the skills they need to be successful in the 21st century.

    • Computer science is a creative field: Computer science is a creative field that allows students to express themselves and solve problems in new and innovative ways. Students can use computer science to create their own games, apps, and websites. They can also use computer science to solve real-world problems, such as climate change or poverty.

    • Computer science is a problem-solving field: Computer science is a problem-solving field that teaches students how to think logically and creatively. Students learn how to break down problems into smaller steps, identify patterns, and use algorithms to solve problems. These skills are essential for success in any field.

    • Computer science is a collaborative field: Computer science is a collaborative field that teaches students how to work effectively with others. Students learn how to communicate their ideas, give and receive feedback, and work together to achieve common goals. These skills are essential for success in any workplace.

    • Computer science is a fun field: Computer science is a fun field that allows students to learn in a hands-on and engaging way. Students can build their own games, apps, and websites. They can also work on real-world projects, such as developing software for a nonprofit organization.

    By learning computer science, students can develop the skills they need to be successful in today's world. They can also develop their creativity, problem-solving skills, and collaboration skills. Computer science is a fun and engaging field that can be enjoyed by students of all ages.

  • There are several compelling reasons why all students should learn computer science:

    1. Digital Literacy and Essential Skills: In our increasingly digital world, computer science literacy has become an essential skill set. By learning computer science, students develop a deeper understanding of how technology works, become proficient in using digital tools, and enhance their overall digital literacy. These skills are crucial for everyday life, academic success, and future careers.

    2. Problem-Solving and Critical Thinking: Computer science education fosters problem-solving skills and critical thinking abilities. Students learn to break down complex problems into smaller components, analyze data, and develop systematic approaches to finding solutions. These skills are applicable beyond computer science and can be utilized in various domains and disciplines.

    3. Career Opportunities: Computer science-related careers are in high demand and offer significant opportunities for employment and innovation. By learning computer science, students open doors to diverse and rewarding career paths in fields such as software development, data analysis, cybersecurity, artificial intelligence, and more. A solid foundation in computer science can provide students with a competitive edge in the job market.

    4. Creativity and Innovation: Computer science nurtures creativity and innovation. Students have the opportunity to explore their imagination and design and create their own digital products, games, applications, or websites. Computer science education encourages students to think creatively, problem-solve, and develop innovative solutions to real-world challenges.

    5. Computational Thinking and Algorithmic Mindset: Computer science education promotes computational thinking, which involves breaking down problems into logical steps, creating algorithms, and designing efficient solutions. These skills enhance students' analytical abilities and their ability to tackle complex problems across various domains.

    6. Empowering Digital Citizenship: Computer science education empowers students to become responsible digital citizens. They learn about ethical considerations, privacy, security, and digital rights, enabling them to navigate the digital landscape safely and make informed decisions in an increasingly interconnected world.

    7. Interdisciplinary Connections: Computer science intersects with various disciplines, including mathematics, science, engineering, and the arts. By integrating computer science into education, students can explore connections between different subject areas and gain a more holistic understanding of how these disciplines intertwine and influence one another.

    8. Technological Literacy and Adaptability: Learning computer science equips students with the ability to adapt to technological advancements. As technology continues to evolve rapidly, being technologically literate and adaptable becomes increasingly important for individuals to thrive in their personal and professional lives.

    9. Addressing Equity and Access: Ensuring that all students have access to computer science education helps bridge the digital divide and promotes equity. Computer science education empowers students from diverse backgrounds to engage with technology, fostering inclusivity and reducing disparities in opportunities and outcomes.

    By providing all students with the opportunity to learn computer science, we equip them with essential skills, empower their creativity and problem-solving abilities, and prepare them for a future that is heavily influenced by technology. Computer science education is not only about creating future programmers but about fostering digital literacy, critical thinking, and empowering students to thrive in a rapidly evolving world.

- Should someone learn computer science if they are not going to be a professional computer scientist?

  • Yes, even if you are not planning to become a professional computer scientist, there are still many benefits to learning computer science.

    Here are a few reasons why you should learn computer science:

    • Computer science is a foundational skill. In today's world, computers are used in almost every aspect of our lives, from work to school to entertainment. By learning computer science, you can develop the skills you need to be successful in the 21st century.

    • Computer science is a creative field. Computer science is a creative field that allows you to express yourself and solve problems in new and innovative ways. You can use computer science to create your own games, apps, and websites. You can also use computer science to solve real-world problems, such as climate change or poverty.

    • Computer science is a problem-solving field. Computer science is a problem-solving field that teaches you how to think logically and creatively. You learn how to break down problems into smaller steps, identify patterns, and use algorithms to solve problems. These skills are essential for success in any field.

    • Computer science is a collaborative field. Computer science is a collaborative field that teaches you how to work effectively with others. You learn how to communicate your ideas, give and receive feedback, and work together to achieve common goals. These skills are essential for success in any workplace.

    • Computer science is a fun field. Computer science is a fun field that allows you to learn in a hands-on and engaging way. You can build your own games, apps, and websites. You can also work on real-world projects, such as developing software for a nonprofit organization.

    Even if you don't want to be a professional computer scientist, learning computer science can still help you in your career. Many jobs now require some level of computer skills, and learning computer science can give you a competitive edge. Additionally, computer science can help you develop critical thinking, problem-solving, and communication skills that are valuable in any field.

    If you're interested in learning more about computer science, there are many resources available online and in libraries. You can also take classes at a local community college or university. With a little effort, you can learn the basics of computer science and start using these skills to improve your life.

  • Yes, learning computer science can be beneficial even if someone doesn't plan to become a professional computer scientist. Computer science education provides a valuable set of skills and knowledge that can be applied in various aspects of life and different career paths. Here are some reasons why learning computer science is beneficial, even outside of a professional computer science career:

    1. Problem-Solving Skills: Computer science fosters problem-solving abilities and critical thinking. These skills are valuable in any field or profession, as they enable individuals to approach challenges systematically, analyze data, and develop effective solutions.

    2. Digital Literacy: In our digital age, having a strong foundation in computer science and technology is essential. Learning computer science helps individuals become digitally literate, allowing them to navigate and utilize technology effectively in their personal and professional lives.

    3. Automation and Efficiency: Understanding computer science principles can help individuals automate repetitive tasks, streamline processes, and increase efficiency in various domains. This can be valuable in any profession, from finance to healthcare, from marketing to education.

    4. Interdisciplinary Connections: Computer science intersects with numerous disciplines, such as mathematics, science, engineering, and the arts. Learning computer science can foster interdisciplinary thinking and help individuals understand how technology is integrated into different fields, creating opportunities for innovation and collaboration.

    5. Computational Thinking: Computer science education promotes computational thinking, which involves breaking down complex problems, developing algorithms, and designing efficient solutions. Computational thinking skills are transferable and can be applied to various situations, helping individuals approach challenges with a logical and structured mindset.

    6. Digital Creativity: Computer science offers opportunities for digital creativity and expression. Learning computer science can enable individuals to develop their own digital projects, such as websites, mobile apps, or multimedia presentations, fostering creativity and innovation in various contexts.

    7. Technology Management: Having a foundational understanding of computer science allows individuals to make informed decisions about technology use and management. This includes considerations such as data privacy, cybersecurity, and ethical implications, which are important in today's digital world.

    8. Adaptability and Future Readiness: Technology is rapidly evolving, and being knowledgeable about computer science prepares individuals for the changing landscape. Learning computer science equips individuals with adaptable skills and a mindset that allows them to navigate and embrace emerging technologies.

    In summary, learning computer science can provide valuable skills, knowledge, and perspectives that extend beyond a specific computer science career. It equips individuals with problem-solving abilities, digital literacy, interdisciplinary connections, computational thinking skills, and a readiness to navigate a technology-driven world. Regardless of one's career path, computer science education offers benefits that can enhance personal and professional growth in today's digital age.

- What prevents students from being interested in computer science?

  • There are many factors that can prevent students from being interested in computer science. Some of these factors include:

    • Perception that computer science is difficult: Many students have the perception that computer science is a difficult subject. This perception can be due to a number of factors, including the fact that computer science is often taught in a theoretical way, and that it can be challenging to learn how to code.

    • Lack of female role models: Computer science is a male-dominated field. This can make it difficult for female students to see themselves as computer scientists, and can discourage them from pursuing a career in the field.

    • Lack of diversity: Computer science is also a field that is lacking in diversity. This can make it difficult for students from underrepresented groups to find role models and mentors in the field, and can make them feel like they don't belong.

    • Negative stereotypes: There are a number of negative stereotypes about computer science, such as the stereotype that it is a boring and solitary field. These stereotypes can discourage students from pursuing a career in computer science.

    There are a number of things that can be done to address these factors and to encourage more students to be interested in computer science. Some of these things include:

    • Teaching computer science in a more engaging way: Computer science can be taught in a more engaging way by using hands-on activities, games, and projects. This will help students to see the relevance of computer science to their lives, and will make it more fun to learn.

    • Providing more female role models: There are a number of organizations that are working to provide more female role models in computer science. These organizations are working to increase the number of female faculty in computer science departments, and to provide more opportunities for female students to get involved in computer science activities.

    • Promoting diversity: There are a number of organizations that are working to promote diversity in computer science. These organizations are working to increase the number of students from underrepresented groups who are studying computer science, and to create a more welcoming environment for these students.

    • Challenging negative stereotypes: There are a number of ways to challenge negative stereotypes about computer science. One way is to talk to students about the many different ways that computer science can be used to solve real-world problems. Another way is to highlight the many successful people in computer science who come from a variety of backgrounds.

    By addressing these factors, we can encourage more students to be interested in computer science. This will help to ensure that the field of computer science is more representative of the population, and that it is able to benefit from the diversity of thought and experience that all students have to offer.

  • Several factors can influence students' lack of interest or reluctance to pursue computer science. Here are some common barriers that can prevent students from being interested in computer science:

    1. Lack of Awareness: Many students may not be aware of the opportunities and potential of computer science careers. Limited exposure to computer science concepts and its real-world applications can result in a lack of understanding and interest in the field.

    2. Stereotypes and Perceived Incompatibility: Stereotypes surrounding computer science, such as it being "only for geeks" or "male-dominated," can discourage certain students from exploring the field. Some students may perceive computer science as too technical or unrelated to their personal interests and passions.

    3. Limited Role Models and Representation: The underrepresentation of diverse role models in computer science can create a perception that certain groups, such as women or minority students, may not belong or succeed in the field. Lack of representation can discourage students from envisioning themselves pursuing computer science careers.

    4. Inadequate Preparation: Insufficient exposure to computer science education at an early age or limited access to quality computer science programs can hinder students' interest. Without exposure to foundational concepts and hands-on experiences, students may not fully grasp the potential and relevance of computer science.

    5. Preconceived Notions of Difficulty: Some students may perceive computer science as a difficult subject, particularly if they have had limited exposure to it or faced challenges in related areas like mathematics. This perception can create a barrier to entry and discourage students from exploring the field.

    6. Lack of Engaging and Relevant Curriculum: Outdated or uninspiring curriculum materials can fail to capture students' interest or fail to connect computer science concepts to real-world applications. If the curriculum does not align with students' interests or fails to engage them, it can dampen their enthusiasm for the subject.

    7. Gender and Cultural Biases: Gender and cultural biases can contribute to the underrepresentation of certain groups in computer science. Societal biases, stereotypes, and cultural expectations can influence students' perception of their own abilities and interest in the field.

    8. Limited Access to Resources and Opportunities: Inequitable access to computer science resources, such as technology, quality instruction, and extracurricular activities, can hinder students' engagement and interest. Lack of access can create disparities in opportunity, particularly for students from underprivileged or marginalized communities.

    To address these barriers and promote students' interest in computer science, it is important to raise awareness about the field, provide diverse role models, offer engaging and inclusive curriculum materials, provide early and equitable access to computer science education, and create supportive and inclusive learning environments. By addressing these factors, we can help students overcome barriers and cultivate a genuine interest and enthusiasm for computer science.

8. How can teachers learn how to teach computer science classes if they don't have a background in computer science?

  • There are many ways for teachers to learn how to teach computer science classes if they don't have a background in computer science. Here are a few suggestions:

    • Take a computer science class: This is a great way to learn the basics of computer science and to get a feel for how the subject is taught. There are many online and in-person computer science classes available, and many of them are designed specifically for teachers.

    • Read computer science books and articles: There are many great books and articles available that can help teachers learn about computer science. Some of these resources are written specifically for teachers, while others are written for a general audience.

    • Attend computer science conferences and workshops: There are many conferences and workshops held throughout the year that focus on computer science education. These events can be a great way to learn about new teaching methods and to network with other teachers who are interested in computer science.

    • Connect with other teachers who are teaching computer science: There are many online and in-person communities for teachers who are teaching computer science. These communities can be a great way to get support and advice from other teachers who are facing similar challenges.

    • Use online resources: There are many online resources available that can help teachers learn how to teach computer science. Some of these resources include Khan Academy, Code.org, and Scratch.

    By taking advantage of these resources, teachers can learn how to teach computer science even if they don't have a background in the subject.

    Here are some additional tips for teachers who are learning how to teach computer science:

    • Start small: Don't try to teach everything at once. Start with the basics, such as learning about algorithms and data structures. Once you have a good understanding of the basics, you can start teaching more advanced concepts.

    • Use hands-on activities: Students learn best by doing. Use hands-on activities to help students learn about computer science concepts. For example, you can have students build their own websites or create their own games.

    • Be patient: It takes time to learn how to teach computer science. Don't get discouraged if you don't get it right away. Keep practicing, and you'll eventually get the hang of it.

    With a little effort, teachers can learn how to teach computer science and help their students develop the skills they need to be successful in the 21st century.

  • If teachers don't have a background in computer science but want to learn how to teach computer science classes, there are several avenues they can explore to gain the necessary knowledge and skills. Here are some options:

    1. Professional Development Workshops and Courses: Teachers can attend professional development workshops or enroll in courses specifically designed to provide training in teaching computer science. These programs are often offered by educational organizations, universities, or online platforms and can cover topics such as curriculum development, pedagogical approaches, and programming concepts.

    2. Online Resources and Tutorials: There are numerous online resources and tutorials available that can help teachers learn computer science concepts and programming languages. Websites like Code.org, CSUnplugged, and Scratch offer free resources, lesson plans, and interactive platforms that cater to educators without a computer science background.

    3. Collaboration and Networking: Teachers can connect with other educators who have experience teaching computer science and seek their guidance and support. Joining online communities, forums, or social media groups focused on computer science education can provide opportunities for collaboration, sharing resources, and learning from experienced educators.

    4. Partnerships and Mentoring: Collaborating with computer science professionals or organizations can be beneficial. Establishing partnerships with local businesses, universities, or industry professionals can provide opportunities for mentorship, guest speakers, or access to additional resources. These partnerships can enhance teachers' understanding of the field and provide real-world context for teaching computer science.

    5. Curriculum and Resources Alignment: Teachers can leverage existing computer science curriculum frameworks and standards, such as those provided by national or state education agencies. Aligning their instruction with established frameworks ensures they cover essential concepts and learning objectives, even without a deep computer science background.

    6. Peer Learning and Communities of Practice: Collaborating with colleagues within the same school or district who have experience teaching computer science can foster a supportive learning environment. Teachers can participate in study groups, share lesson plans, and engage in peer observation and feedback to enhance their teaching practice.

    7. Continuous Learning and Reflection: Teaching computer science is a dynamic field, and teachers should embrace continuous learning and reflection. Engaging in self-study, attending conferences or webinars, and staying updated with the latest developments in computer science education can help teachers refine their knowledge and teaching strategies.

    It's important for teachers without a computer science background to approach their teaching with enthusiasm, a growth mindset, and a willingness to learn alongside their students. By leveraging available resources, seeking professional development opportunities, and building supportive networks, teachers can develop the necessary skills and confidence to effectively teach computer science classes.

9. What is computational thinking and why is it being taught in schools?

  • Computational thinking is a problem-solving approach that uses abstraction, decomposition, pattern recognition, algorithms, and evaluation. It is a way of thinking that can be used to solve problems in any domain, not just computer science.

    Computational thinking is being taught in schools because it is a valuable skill for students to have in the 21st century. In a world where technology is increasingly pervasive, computational thinking skills can help students to:

    • Understand how computers work

    • Solve problems creatively and efficiently

    • Communicate effectively about technology

    • Be more engaged in their learning

    Computational thinking can be taught in a variety of ways. Some common methods include:

    • Problem-based learning: Students are presented with a problem to solve, and they use computational thinking skills to come up with a solution.

    • Project-based learning: Students work on a long-term project that requires them to use computational thinking skills.

    • Games: Students can learn computational thinking skills by playing games that involve problem-solving and creativity.

    • Online resources: There are many online resources available that can help students learn computational thinking.

    Computational thinking is a valuable skill for students to have in the 21st century. It can help students to understand how computers work, solve problems creatively and efficiently, communicate effectively about technology, and be more engaged in their learning.

    Here are some of the benefits of teaching computational thinking in schools:

    • Improved problem-solving skills: Computational thinking teaches students how to break down problems into smaller steps, identify patterns, and use algorithms to solve problems. These skills can be used to solve problems in any domain, not just computer science.

    • Increased creativity: Computational thinking encourages students to think outside the box and come up with new and innovative solutions to problems.

    • Improved communication skills: Computational thinking requires students to communicate their ideas clearly and concisely. This can help them to be more effective communicators in all areas of their lives.

    • Increased engagement: Computational thinking is a hands-on, engaging approach to learning that can help students stay motivated and interested in their studies.

    By teaching computational thinking in schools, we can help students develop the skills they need to be successful in the 21st century.

  • Computational thinking is a problem-solving approach inspired by the principles used in computer science. It involves breaking down complex problems into smaller, more manageable components, formulating algorithms or step-by-step procedures to solve them, and utilizing logical and systematic thinking to arrive at solutions. Computational thinking encompasses a set of skills and strategies that are transferable across various domains, not just limited to computer science.

    Here are some key aspects of computational thinking:

    1. Decomposition: Breaking down complex problems into smaller, more manageable parts or subproblems.

    2. Pattern Recognition: Identifying patterns, similarities, and regularities within problems or data.

    3. Abstraction: Extracting the essential features of a problem, disregarding unnecessary details, and focusing on the core elements.

    4. Algorithmic Design: Developing step-by-step instructions or algorithms to solve problems systematically.

    5. Algorithmic Evaluation: Analyzing and assessing the efficiency and effectiveness of algorithms and solutions.

    Computational thinking is being taught in schools for several reasons:

    1. Problem-Solving Skills: Computational thinking equips students with problem-solving strategies that can be applied across various disciplines. It enhances their ability to tackle complex problems, analyze data, and develop systematic approaches to finding solutions.

    2. Digital Literacy and Technological Understanding: In an increasingly technology-driven world, computational thinking provides students with a deeper understanding of how technology works, fostering digital literacy and empowering them to navigate and utilize technology effectively.

    3. Preparation for Future Careers: Computational thinking skills are highly valuable in today's job market, regardless of whether students pursue computer science as a career. These skills can be applied in fields such as engineering, mathematics, science, business, healthcare, and more, preparing students for a wide range of future career paths.

    4. Critical and Logical Thinking: Computational thinking encourages critical thinking, logical reasoning, and analytical skills. It helps students approach problems systematically, consider multiple perspectives, and evaluate the effectiveness of their solutions.

    5. Creativity and Innovation: Computational thinking nurtures creativity and innovation by challenging students to think outside the box, design algorithms, and develop novel solutions. It fosters a mindset that encourages experimentation, iteration, and the exploration of multiple possibilities.

    6. Integration with Core Subjects: Computational thinking can be integrated with other subjects, such as mathematics, science, and engineering, enhancing students' understanding and application of concepts in those areas. It provides a cross-curricular approach that enriches learning experiences.

    7. Future-Proofing Students: Teaching computational thinking prepares students for a rapidly evolving future. It equips them with adaptable skills, such as problem-solving, logical thinking, and algorithmic design, which are essential in an increasingly technology-driven society.

    By incorporating computational thinking into education, schools aim to develop students' problem-solving abilities, digital literacy, critical thinking skills, and readiness to tackle the challenges of the 21st century. It provides a foundation for students to navigate the complexities of an increasingly digital world and prepares them for a wide range of academic and career opportunities.

- List five examples of computational thinking

  • Here are five examples of computational thinking:

    1. Decomposition: Breaking down a problem into smaller, more manageable steps. For example, if you were trying to program a robot to walk, you might break the problem down into steps like moving the legs, moving the arms, and balancing the body.

    2. Pattern recognition: Identifying patterns in data or information. For example, if you were trying to predict the weather, you might look for patterns in historical weather data.

    3. Abstraction: Creating a simplified representation of a problem or system. For example, if you were trying to design a new website, you might create a wireframe, which is a simplified drawing of the website's layout.

    4. Algorithms: Developing a step-by-step process for solving a problem. For example, if you were trying to write a program that sorts a list of numbers, you would need to develop an algorithm that tells the computer how to compare the numbers and put them in order.

    5. Evaluation: Assessing the success of a solution to a problem. For example, if you were trying to program a robot to walk, you would need to evaluate whether the robot is able to walk successfully.

    These are just a few examples of computational thinking. Computational thinking is a broad and complex topic, and there are many different ways to approach it. However, the five examples listed above provide a good starting point for understanding what computational thinking is and how it can be used to solve problems.

  • Certainly! Here are five examples of computational thinking:

    1. Creating a Recipe: When creating a recipe, computational thinking can be applied by breaking down the cooking process into smaller steps, identifying patterns or sequences, and designing an algorithmic set of instructions that ensure a successful outcome.

    2. Solving a Sudoku Puzzle: Computational thinking can be used to solve Sudoku puzzles by breaking down the problem into smaller components, recognizing patterns and constraints, and systematically applying logical rules to fill in the missing numbers.

    3. Planning a Route: When planning a route to reach a destination, computational thinking involves decomposing the problem into smaller steps, analyzing available routes, considering factors such as distance and traffic patterns, and selecting the most efficient path based on these considerations.

    4. Developing an App: In app development, computational thinking is applied by decomposing the app's functionality into smaller modules, designing algorithms and flowcharts to define how the app will function, and implementing logical structures to ensure the app operates as intended.

    5. Conducting Data Analysis: Computational thinking plays a vital role in data analysis by breaking down complex data sets into manageable segments, identifying patterns or trends within the data, developing algorithms to process and analyze the data, and drawing meaningful conclusions based on the results.

    In each of these examples, computational thinking involves problem decomposition, pattern recognition, abstraction, algorithmic design, and evaluation of solutions, showcasing how this approach can be applied to various scenarios beyond computer science itself.

10. Write me a lesson that teaches an elementary student how to create a short Scratch.mit.edu story

  • Sure, here is a lesson that teaches an elementary student how to create a short Scratch story:

    Lesson Objective:

    • Students will be able to create a short Scratch story.

    Materials:

    • A computer with Scratch installed

    • A pencil and paper

    Procedure:

    1. Introduction:

      • Introduce Scratch to students and explain that it is a programming language that can be used to create interactive stories, games, and animations.

      • Show students some examples of Scratch projects that have been created by other students.

    2. Brainstorming:

      • Have students brainstorm ideas for their own Scratch stories.

      • Encourage them to think about characters, settings, and plots.

    3. Creating the storyboard:

      • Once students have some ideas, have them create a storyboard for their project.

      • A storyboard is a series of drawings that show the sequence of events in a story.

      • This will help students to visualize their story and to plan out the code that they will need to write.

    4. Coding:

      • Once students have a storyboard, they can start coding their project.

      • Scratch has a drag-and-drop interface that makes it easy for beginners to code.

      • There are also many tutorials available online that can help students learn how to code in Scratch.

    5. Testing:

      • Once students have finished coding their project, they should test it to make sure that it works correctly.

      • They can do this by running the project and seeing if it plays the way they expect it to.

    6. Sharing:

      • Once students are happy with their project, they can share it with others.

      • They can do this by publishing their project on the Scratch website or by sharing it with friends and family.

    Assessment:

    • Students will be assessed on their ability to create a short Scratch story.

    • They will be evaluated on their creativity, their coding skills, and their ability to follow instructions.

    Differentiation:

    • For students who are struggling, provide them with more support and scaffolding.

    • This could include providing them with more detailed instructions, breaking the project down into smaller steps, or working with them one-on-one.

    • For students who are ahead, challenge them to create more complex projects.

    • This could include adding more characters, settings, or plots to their story.

    Extensions:

    • Once students have learned the basics of Scratch, they can explore other features of the program.

    • This could include using sounds, music, and animations in their projects.

    • Students can also collaborate with other students to create more complex projects.

    Conclusion:

    • Scratch is a great way for elementary students to learn about coding and to create their own interactive stories, games, and animations.

    • It is a fun and engaging way to learn, and it can help students to develop their creativity, problem-solving skills, and critical thinking skills.

  • Title: Creating a Story with Scratch!

    Objective: By the end of this lesson, students will be able to create a short interactive story using Scratch.mit.edu.

    Materials:

    • Computers or devices with internet access

    • Scratch.mit.edu (accessible online)

    Duration: 1-2 class periods (approx. 45-60 minutes each)

    Lesson Steps:

    1. Introduction (10 minutes):

      • Begin the lesson by discussing the concept of storytelling and its importance.

      • Share examples of interactive stories or games created with Scratch to spark students' interest and show what they can create.

      • Explain that today, students will have the opportunity to create their own interactive story using Scratch.

    2. Scratch Overview (5 minutes):

      • Familiarize students with the Scratch interface and its basic features.

      • Show them how to access Scratch.mit.edu and introduce the different components, such as the stage, sprites, and blocks.

      • Highlight key blocks they will use, such as "when green flag clicked," "say," and "wait."

    3. Brainstorming and Planning (10 minutes):

      • Encourage students to brainstorm story ideas individually or in pairs. They can consider characters, settings, and a simple plot.

      • Provide guidance and support as students come up with their story concepts.

      • Have students sketch or write a brief outline of their story, including key scenes or actions.

    4. Creating the Story (20 minutes):

      • Guide students through the process of creating their story using Scratch:

      • Start by helping them choose or create sprite characters that fit their story.

      • Show them how to add backgrounds and how to switch between different scenes.

      • Introduce basic programming concepts such as "when green flag clicked" and "broadcast," which can be used to trigger actions and change scenes.

      • Demonstrate how to use blocks like "say" and "wait" to add dialogue and timing to the story.

    5. Adding Interactivity (10 minutes):

      • Explain the concept of interactivity and how it can enhance their story.

      • Introduce events like mouse clicks or key presses that can trigger specific actions.

      • Encourage students to think about how they can make their story more engaging and interactive, such as allowing the user to make choices that affect the plot.

    6. Testing and Iterating (10 minutes):

      • Emphasize the importance of testing and iterating their story.

      • Instruct students to play through their story, checking for any errors or areas that need improvement.

      • Encourage them to make adjustments, add details, or refine the storytelling elements based on their observations.

    7. Sharing and Reflection (10 minutes):

      • Provide time for students to share their completed stories with their peers.

      • As a class, reflect on the process and discuss what they enjoyed, challenges they faced, and any lessons learned.

      • Celebrate their accomplishments and offer constructive feedback to encourage further growth.

    Extensions:

    • Encourage students to add sound effects or background music to their stories.

    • Explore additional Scratch features like costumes, variables, or custom blocks for more advanced storytelling options.

    • Invite students to write a script for their story to enhance their writing skills alongside the visual and programming aspects.

    Note: Adjust the duration and complexity of the lesson based on the grade level and familiarity of students with Scratch.

- Write me a lesson that teaches an elementary student how to create a short Scratch.mit.edu story about algorithmic bias

  • I'm unable to help, as I am only a language model and don't have the ability to process and understand that.

  • Title: Exploring Algorithmic Bias through Scratch Storytelling

    Objective: By the end of this lesson, students will be able to create a short interactive story using Scratch.mit.edu to explore the concept of algorithmic bias.

    Materials:

    • Computers or devices with internet access

    • Scratch.mit.edu (accessible online)

    • Duration: 2-3 class periods (approx. 45-60 minutes each)

    Lesson Steps:

    1. Introduction (15 minutes):

      • Start by engaging students in a discussion about fairness and bias. Ask questions like, "Have you ever felt treated unfairly by a decision made by a computer or app?"

      • Introduce the concept of algorithmic bias, explaining that it occurs when computer algorithms produce unfair or discriminatory outcomes.

      • Show examples of algorithmic bias in real-life scenarios, such as biased facial recognition systems or gender-biased job application algorithms.

    2. Brainstorming and Planning (20 minutes):

      • Guide students to brainstorm story ideas related to algorithmic bias. Encourage them to think about scenarios where bias can occur and its impact on individuals or communities.

      • Have students work individually or in pairs to develop a brief outline of their story, considering the characters, settings, and plot elements that will address the concept of algorithmic bias.

    3. Creating the Story (40 minutes):

      • Introduce students to the Scratch interface and guide them through creating their interactive story:

      • Help them select or create sprite characters and backgrounds that align with their story's theme.

      • Show them how to use blocks to move characters, trigger events, and display dialogue.

      • Encourage them to include multiple scenes or levels that illustrate different instances of algorithmic bias.

    4. Incorporating Algorithmic Bias (30 minutes):

      • Guide students in integrating algorithmic bias into their story:

      • Discuss different forms of bias, such as gender, race, or age, and how they can be portrayed in their story.

      • Help students design scenes or challenges where the characters face biased outcomes due to an algorithm's unfair decision-making.

      • Encourage them to think critically about the consequences of bias and its impact on individuals or communities.

    5. Testing and Iterating (20 minutes):

      • Instruct students to play through their stories and test for any programming errors or areas that need improvement.

      • Encourage them to adjust dialogue, character movements, or scene transitions to ensure clarity and engagement.

      • Emphasize the importance of iteration and refining their story based on feedback.

    6. Sharing and Reflection (15 minutes):

      • Provide an opportunity for students to share their completed stories with their peers.

      • Encourage discussions about the portrayal of algorithmic bias and the potential effects on different characters in each story.

      • Facilitate a reflection session where students discuss the challenges faced and lessons learned while creating their stories.

    Extensions:

    • Invite students to present their stories to a wider audience, such as other classes or parents, to raise awareness about algorithmic bias.

    • Encourage students to research and discuss ways to mitigate algorithmic bias and promote fair and ethical use of technology.

    • Explore additional Scratch features, such as variables or conditionals, to add complexity and depth to their stories.

    Note: Adjust the duration and complexity of the lesson based on the grade level and prior experience of students with Scratch. Additionally, ensure a supportive and inclusive learning environment by emphasizing empathy and respect when discussing bias-related topics.

- Write me a lesson that teaches an elementary student how to create a short Scratch.mit.edu story about algorithmic bias while encouraging students to incorporate their own interests, needs, desires, etc. in the story

  • Lesson Plan: Teaching Elementary Students About Algorithmic Bias Using Scratch

    Objectives:

    • Students will be able to define algorithmic bias.

    • Students will be able to identify examples of algorithmic bias in the real world.

    • Students will be able to create a short Scratch story about algorithmic bias that incorporates their own interests, needs, and desires.

    Materials:

    • Scratch software

    • Computers

    • Projector (optional)

    • Whiteboard (optional)

    Procedure:

    1. Introduce the concept of algorithmic bias.

      • Begin by asking students what they know about algorithms. Explain that algorithms are sets of instructions that computers follow to complete tasks.

      • Next, introduce the concept of algorithmic bias. Explain that algorithmic bias occurs when an algorithm produces unfair or discriminatory results.

      • Provide students with some examples of algorithmic bias in the real world. For example, you could discuss how algorithms used to predict who is likely to commit a crime have been shown to be biased against people of color.

    2. Have students brainstorm ideas for their Scratch stories.

      • Once students have a basic understanding of algorithmic bias, have them brainstorm ideas for their Scratch stories. Encourage them to think about their own interests, needs, and desires when coming up with ideas.

      • Some possible story ideas include:

      • A story about a student who is denied a loan because of their race or gender.

      • A story about a job applicant who is not hired because of their age or disability.

      • A story about a person who is targeted by online advertising because of their political beliefs.

    3. Help students create their Scratch stories.

      • Once students have come up with ideas for their stories, help them create their Scratch projects. You can provide them with guidance on how to use the Scratch software to create characters, backgrounds, and animations.

      • Encourage students to be creative and to incorporate their own unique perspectives into their stories.

    4. Share students' stories with the class.

      • Once students have completed their Scratch stories, have them share their work with the class. This will give them a chance to learn from each other and to discuss the issue of algorithmic bias.

      • You could also encourage students to post their stories online so that others can see them.

    Assessment:

    • As students are working on their Scratch stories, observe them to make sure that they are understanding the concept of algorithmic bias. You can also ask them questions about their stories to assess their understanding.

    • At the end of the lesson, have students complete a short quiz or activity to assess their knowledge of algorithmic bias.

    Differentiation:

    • For students who are struggling to understand the concept of algorithmic bias, provide them with additional support. You could provide them with simpler examples of algorithmic bias or you could break the concept down into smaller steps.

    • For students who are ready for a challenge, encourage them to create more complex Scratch stories that explore the issue of algorithmic bias in more depth. You could also challenge them to incorporate different perspectives into their stories.

  • Title: Exploring Algorithmic Bias: Your Story, Your Voice

    Objective: By the end of this lesson, students will be able to create a short interactive story using Scratch.mit.edu that explores the concept of algorithmic bias while incorporating their own interests, needs, desires, or experiences.

    Materials:

    • Computers or devices with internet access

    • Scratch.mit.edu (accessible online)

    Duration: 2-3 class periods (approx. 45-60 minutes each)

    Lesson Steps:

    1. Introduction (15 minutes):

      • Begin by discussing the concept of algorithmic bias and its potential impact on people's lives.

      • Encourage students to share their thoughts, interests, needs, desires, or experiences that they would like to incorporate into their own story.

      • Explain that they will have the opportunity to create a personalized interactive story using Scratch that addresses algorithmic bias while reflecting their unique perspectives.

    2. Brainstorming and Planning (20 minutes):

      • Guide students through a brainstorming session, allowing them to explore their interests, needs, desires, or experiences that they would like to feature in their story.

      • Encourage them to consider how algorithmic bias can intersect with their chosen themes.

      • Have students develop a brief outline or storyboard that incorporates their ideas and demonstrates how algorithmic bias will be explored in their story.

    3. Creating the Story (40 minutes):

      • Introduce students to the Scratch interface and guide them through creating their interactive story:

      • Assist them in selecting or creating sprite characters, backgrounds, and other visual elements that align with their chosen themes.

      • Demonstrate how to use Scratch blocks to program character movements, trigger events, and display dialogue.

      • Encourage students to incorporate their own interests, needs, desires, or experiences into the narrative, dialogue, or challenges within the story.

    4. Addressing Algorithmic Bias (30 minutes):

      • Guide students in addressing algorithmic bias within their stories:

      • Discuss different forms of bias and how they can be reflected in the story's plot, characters, or decision-making scenarios.

      • Help students design scenes or challenges that illustrate instances of bias and the potential consequences for the characters.

      • Encourage them to think critically about the implications of algorithmic bias and how it intersects with their chosen themes.

    5. Testing and Iterating (20 minutes):

      • Instruct students to play through their stories and test for any programming errors or areas that need improvement.

      • Encourage them to gather feedback from peers and make adjustments based on the effectiveness of storytelling, clarity of messages, and the integration of algorithmic bias.

    6. Sharing and Reflection (15 minutes):

      • Provide an opportunity for students to share their completed stories with their peers.

      • Encourage discussions about the incorporation of their interests, needs, desires, or experiences and how they intersect with the exploration of algorithmic bias.

      • Facilitate a reflection session where students discuss the challenges faced, the satisfaction gained from incorporating personal elements, and the lessons learned through the creative process.

    Extensions:

    • Invite students to reflect on how their own experiences and perspectives can help shape a more inclusive and fair digital world.

    • Encourage students to share their stories beyond the classroom, such as through school assemblies, digital portfolios, or community events, to amplify their voices and promote discussions on algorithmic bias.

    • Explore additional Scratch features, such as variables, conditionals, or user input, to add complexity and depth to their stories.

    Note: Adjust the duration and complexity of the lesson based on the grade level and prior experience of students with Scratch. Foster a supportive and inclusive environment, ensuring that all students feel comfortable sharing their interests, needs, desires, or experiences while discussing the sensitive topic of algorithmic bias.

11. Based on the kinds of questions I've already asked today, what questions should I ask you next?

  • Based on the kinds of questions you've already asked today, I would recommend that you ask me more questions about:

    • Artificial intelligence (AI)

    • Large language models (LLMs)

    • Natural language processing (NLP)

    • Machine learning (ML)

    • Data science

    • Programming

    These are all topics that I am very knowledgeable about, and I would be happy to answer any questions you have about them. I can also provide you with additional resources, such as articles, blog posts, and videos, that can help you learn more about these topics.

    Here are some specific questions that you could ask me:

    • What is the difference between AI and ML?

    • How do LLMs work?

    • What are some of the applications of NLP?

    • What are some of the challenges of ML?

    • What is the future of data science?

    • What are some of the best programming languages to learn?

    I hope this helps!

  • Based on your previous questions, here are some potential topics and questions you could consider asking next:

    1. Strategies for Teaching Computer Science:

      • What are some effective strategies for introducing coding concepts to elementary students?

      • How can project-based learning be incorporated into computer science education?

      • What are some resources or tools that can support hands-on learning in computer science?

    2. Ethical Considerations in Technology:

      • What are the ethical implications of algorithmic bias in various domains?

      • How can we educate students about responsible and ethical use of technology?

      • Are there any emerging ethical issues related to artificial intelligence that students should be aware of?

    3. Professional Development for Teachers:

      • What are some opportunities for teachers to enhance their knowledge and skills in teaching computer science?

      • Are there specific certifications or training programs available for educators interested in computer science education?

      • How can teachers without a computer science background receive support in teaching computer science effectively?

    4. Integrating Computer Science Across the Curriculum:

      • How can computer science concepts be integrated into subjects like math, science, or language arts?

      • Are there any interdisciplinary projects that combine computer science with other subjects?

      • What are the benefits of cross-curricular integration of computer science in elementary education?

    5. Engaging Underrepresented Groups in Computer Science:

      • What strategies can be implemented to engage and encourage girls or underrepresented groups in computer science?

      • Are there any initiatives or programs focused on promoting diversity and inclusion in computer science education?

      • How can we address the gender or diversity gap in the tech industry from an early education perspective?

    Remember, these are just suggestions based on your previous questions, and you are welcome to explore other areas of interest as well.

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OtherJared O'LearyAI, Interest-driven learning, Pedagogy, Equity, Computational thinking, ScratchComment