Introducing Artificial Intelligence Literacy in Schools: A Review of Competence Areas, Pedagogical Approaches, Contexts and Formats

In this episode I unpack Olari, Tenório, and Romeike’s (2023) publication titled “Introducing artificial intelligence literacy in schools: A review of competence areas, pedagogical approaches, contexts and formats,” which is a review of literature exploring how researchers from 31 papers investigated AI-related literacies in schools.

  • Over the last several months Educators

    have been wondering about the potential

    for AI in education whether it be

    teaching AI or using AI within classroom

    context or just for learning outside of

    classroom but some Educators might be

    wondering well what are some of the best

    practices for AI in schools one way you

    can actually explore that is by doing a

    review of literature now having done

    reviews of literature this can take a

    long time hundreds of hours depending on

    the amount of literature you have to

    reveal or you could read somebody else

    who's done that work for you or in this

    case listen to a podcast on that today's

    episode of the csk8 podcast is going to

    talk about a review of literature on how

    schools are introducing AI within School

    context we're going to do that by

    looking at the paper which is titled

    quote introducing artificial

    intelligence literacy in schools colon a

    review of competence areas pedagogical

    approaches context and formats end

    quilts it was written by Victoria allari

    Camila tenorrillo and Ralph romica

    apologies if I'm mispronounce any names

    here's the abstract for this paper quote

    introducing artificial intelligence AI

    literacy to school students is

    challenging as AI education is

    constantly growing Educators can

    struggle to decide which content is

    relevant and how it can be taught

    therefore examining which practices and

    formats have already been evaluated with

    students and are used repeatedly and

    which are challenging or should be

    explored further is necessary to

    facilitate teaching Ai and encourage the

    development of new activities in this

    literature review We address this need

    using a directed and conventional

    content analysis we systematically

    analyzed 31 cases of introducing AI

    literacy in schools in terms of three

    categories a competence areas B

    pedagogical approaches and c contexts

    and formats when analyzing the results

    we identified underrepresented

    competence areas and summarize common

    pedagogical practices in recurrent

    formats and context additionally we

    investigated the approach to using data

    to make abstract AI knowledge accessible

    to novices end quote vital summarizes

    particular publication into a single

    sentence I'd say that this review of

    literature explored how researchers from

    literacies in schools we're going to be

    talking about this particular paper in

    relation to K-12 education but also

    higher education as that's what we do in

    these unpacked King scholarship episodes

    of the CSK8 podcast this is episode 190

    which means we've got a ton more content

    on my website but if you go to

    jaredoleary.com you can find the show

    notes for this episode as well as

    hundreds more and hundreds of more free

    resources lesson plans etc for computer

    science Educators as well as 1500 hours

    of drumming content and a bunch of

    gaming content because I create content

    for a living and by the way if you're

    curious about my professional background

    you can find my CV on my website in case

    you were curious about all the things

    I've done working with evergrade

    kindergarten through doctoral student in

    a variety of contexts now in the

    introduction of the paper the authors

    talk about how AI literacy has been a

    subject of research for many years it's

    actually something we've talked about in

    the podcast since episode 13 which was

    titled AI for all curriculum development

    and gender discourse with Sarah Judd so

    if you haven't listened to that episode

    I highly recommend taking a look at it

    but with AI being such a common Topic in

    education at least in recent months has

    been more popular outside of computer

    science to talk about it the author's

    question will well which content is

    useful for AI education and how might we

    actually teach it or how is it being

    taught or explored in the various

    research Publications on AI literacy in

    schools so in section 2 of the paper

    which is titled artificial intelligence

    literacy and school education the

    authors kind of explore this a bit so

    they summarize some Publications and

    reviews the literature on this topic so

    for example on PDF page two of this

    particular publication the authors talk

    about AI literacy and so they summarize

    this as quote a set of competencies that

    enable individuals to evaluate AI

    Technologies critically communicate and

    collaborate effectively with AI and use

    AI as a tool online at home and in the

    workplace end quote while other authors

    look at AI as a potential way for

    expanding computational thinking to do

    what's called computational thinking 2.0

    at least proposed by some of the authors

    and other authors talk about how AI

    could be introduced to students in terms

    of focusing on perception representation

    and reasoning learning natural

    interaction and societal impact as it

    relates to Ai and learning schooling Etc

    there were a number of papers in here

    that really pique my interest so I

    recommend taking a looking at section

    two which is basically the review of

    literature to find some other

    Publications that might interest you

    I'll be doing some unpacking scholarship

    episodes in the future on some of these

    on PDF page 3 the authors mentioned two

    research questions that kind of guide

    this particular review of literature one

    is which competence areas are

    underrepresented in the current AI

    literacy approaches and then the second

    research question is what are the common

    pedagogical practices recurrent formats

    and context in AI education so on the

    third section of this paper this is on

    the method so the authors talk about how

    they used an exploratory leader to

    review using some various qualitative

    content analyzes methods so they use

    snowball approaches and keyword searches

    to try and find some papers that would

    kind of like match some broader criteria

    of artificial intelligence in relation

    to schooling they specifically were

    looking in the Publications within ACM

    ultimately they ended up identifying 31

    studies and these were from 2010 through

    passages within the text like taking a

    condensed paper and turning into outline

    format and kind of using those like big

    headers as codes to kind of summarize

    the main sections in this and then you

    take those codes and you compare it with

    other Publications to see okay well what

    are people actually talking about across

    all these papers how are they similar

    different Etc all right but let's get

    into the results so 4.1 is category 1

    which is on the competence areas all

    right so in this section they talked

    about how to use the Doug stove triangle

    which is quote a framework for

    describing the phenomenon of

    digitization that should be included in

    education this approach involved

    examining each study from three

    perspectives a technological does the

    study Foster technological competencies

    do the students learn how AI Works B

    social cultural does the study promote

    social cultural competencies did

    students learn what the impact of

    technology is and see user oriented does

    the study promote a user-oriented

    perspective did the student learn how to

    use AI end quote it's from page four so

    from the technological perspective so

    this was kind of exploring well what

    were students learning about AI in

    particular so like how did it work how

    would you actually create your own AI or

    engage in deep learning techniques Etc

    the social cultural perspective was kind

    of exploring papers that might have

    looked at okay what are some of the

    biases that are found when using AI then

    the third perspective might include

    something like okay well how is it that

    we're able to use AI with our own

    learning or creating Etc now in their

    findings they found that a very small

    number of Publications actually explored

    all three of those areas simultaneously

    or within the same study most of the

    studies focused on the technological and

    user-oriented perspectives so in other

    words quote most studies concern

    students ability to know how AI systems

    work and how to use them but not what

    their effects are end quote so in other

    words the researchers were mainly

    focusing on the content area of AI or

    how to use AI but not necessarily be

    ethical impacts of AI in whatever

    context is being applied in going back

    to some of the relatively recent

    episodes that we've talked about with

    ethics this presents a potential area

    for educators to explore not only

    artificial intelligence but how it

    connects with ethics if you want to

    learn more about that make sure you

    check out some of the podcast episodes

    that I will link in the show notes at

    o'leary.com so now that we've learned

    that researchers have mainly explored

    the technological and user-oriented

    perspectives when it comes to artificial

    intelligence and education but let's

    talk about well what were the

    pedagogical approaches that were used so

    this is category two so they found that

    many of the research Publications were

    talking about how it's important to use

    data that is relevant to students rather

    than abstract disconnected data that

    doesn't really have any kind of impact

    or relationship to the students who are

    learning it so one of the things that

    was frequently brought up was that

    students could actually go and collect

    their own data and use that to kind of

    feed into the machine learning processes

    for AI this could lead into the that

    third area that wasn't really discussed

    very much in terms of biases so if you

    are an educator who is interested in

    kind of exploring machine learning and

    having students collecting and feeding

    in their own data into AI when two

    different students have two different

    results for their AI on whatever the

    context may be this presents an

    opportunity to kind of discuss well how

    might bias in the data that we provided

    to have an impact on the result so for

    example you might use like a facial

    Wrecking thing and talk about how hey

    this student with a lighter skin

    complexion collected photos from their

    family who had similar complexions and

    when compared to another student who had

    darker complexions the results of the AI

    kind of was very different in terms of

    making it so that it was easier for the

    lighter complexion to detect lighter

    complexion and harder to detect a darker

    complexion and the opposite might be

    true for the other scenario this could

    open up a discussion on okay well

    depending on what kind of data we

    provide it's going to make it so that

    the AI is good in one area in terms of

    detecting a certain type of complexion

    and bad when detecting a different type

    of complexion and if we want to make it

    so that it's able to equally detect it

    or across a range of complexions perhaps

    we should feed it a variety of different

    photos from different complexions and

    whatnot that's just one example but

    another example might be like a text bot

    or something having students create

    something based off of text that you

    provided if one student were to feed in

    text from like a very technical book

    versus another student who's going to

    feed in text from like a Twitter feed or

    something like that that you might get

    very different results in terms of the

    kind of responses that you'll get from

    that Tech spot and again that presents

    an opportunity to discuss well why is

    that you don't necessarily have to go

    into those projects with the front

    loading of hey I'm going to teach you

    about bias but can instead anticipate

    that bias is likely going to show up in

    some way that is going to be easily seen

    by the students so you can know in

    advance hey at some point down the road

    we're going to have a conversation on AI

    and bias or Ai and ethics Etc so you can

    prepare for that without necessarily

    even having to let students know that

    hey this is going to happen at some

    point if for some reason it does not

    happen then maybe at the end of the unit

    you can talk about okay now let's talk

    about some examples of where this could

    have gone wrong even though we were not

    able to potentially detect some of the

    biases that were happening because

    there's always going to be some kind of

    biases within the technology that we

    create and the algorithms that we write

    or the data that we provide to machine

    learning Etc but we might not be able to

    detect them but again check out some of

    those discussions on ethics to kind of

    get some ideas on how you could

    potentially explore that in your classes

    standpoint the authors found that

    collaboration was a big focus and so was

    active learning so because this was like

    summarizing how to introduce AI into

    school programs a lot of the

    characterizations that could be used to

    describe these Publications were

    exploring like a low four barrier of

    Entry to getting into Ai and education

    making things Hands-On playful and

    Project based so rather than doing

    activities students were actually

    creating or engaging in a longer term

    project for example using some data for

    some machine learning Concepts now in

    these particular research Publications

    that they're looking at they found that

    this wasn't just for a particular age

    group this could be done in lower age

    groups as well as up through high school

    college Etc so you can have younger

    students like elementary students engage

    in artificial intelligence like in data

    collections for things that were like

    relevant to them now in category three

    this was on context and formats I'm

    going to read a couple paragraphs from

    page seven of the PDF quote the findings

    indicate that the activities described

    in the studies were align with the

    students's context though they had an

    artificially created purpose while the

    studies reference context from students

    is every day's life such as games

    friends animals food

    students performed artificially created

    tasks example using particular software

    to train a classification model with a

    data set that is prepared by the

    educator and did not transfer their

    knowledge into other domains students

    applying knowledge to new contexts and

    working on projects they cared about

    were rarely reported the formats used in

    the unanalyze studies range from short

    activities and one day workshops to

    Summer Schools lasting several weeks

    most activities reported were not part

    of the regular computer science

    curriculum and occurred in the context

    of other subjects examples social

    studies or outside regular school

    classes the activities were based on the

    assumption that students had no prior

    knowledge of AI and were conducted by

    researchers though the studies did not

    specify whether School teachers were

    also involved in the education process

    only Heinz at all bergstein at all

    Williams and Brazil casperson at all

    reported involving teachers and

    preparing them to the multipliers and

    test AI materials end quote apologies

    that probably mispronounced all those

    names alright so this is important to to

    think about so the majority of these

    research studies that were explored from

    again 2010 to 2021 were a short term so

    maybe a single day or maybe for a summer

    over the course of a few weeks so we

    didn't really get a look at long-term

    impacts here this was just introducing

    AI into schools or school contexts and

    these weren't necessarily for computer

    science classes or Computer Science

    Education that I imagine is going to

    change I imagine there's going to be a

    lot more discussion a lot more research

    on AI and education in a variety of

    contexts not only in computer science

    context but also in education context

    I.E classes that are not specific to

    computer science this presents some

    interesting things that I'm going to

    bring up in some of the lingering

    questions and thoughts at the end of

    this particular podcast episode however

    I want to now discuss the discussion

    section which starts on page seven at

    the bottom right so here's the first

    main finding quote most studies were

    concerned with developing students's

    ability to know how AI systems work and

    how to operate them but not what their

    effects are end quote that makes sense

    especially considering that the studies

    were not necessarily taking place within

    a context of Computer Science Education

    so again it was like taking place in

    like the social studies class or

    something else the second main finding

    was that quote students were actively

    engaged in the learning process however

    they were frequently reported to learn

    about AI in restrictive context moreover

    they did not apply their knowledge to

    new domains end quote now why is this

    important well transfer is important

    because if you're learning something in

    one context you want to be able to know

    whether or not it actually benefits in

    other areas

    and that right there is my co-host

    Minnie who is my dog now the authors

    talk about how this is similar to the

    idea of a playpen versus like a

    playground in a playpen you are in the

    little small enclosed area it's very

    safe there's only things in there that

    you're supposed to play with and there

    are limited number of things that you

    can do within that smaller space but in

    a playground there might be more things

    and more areas to explore maybe even

    some areas that aren't necessarily

    designed for the thing that you're doing

    like having fun same thing we can kind

    of apply in education talked about this

    in the interview with Gail lovely which

    is from episode 11 is titled exploring

    Cs and CT in pre-k with Gail lovely so

    from an educational standpoint the way

    that this relates to this is that if

    we're in a playpen you might have a very

    nicely crafted educational experience

    within this box but there might be

    limited opportunities for thinking

    creatively Etc within that small space

    in a playground area there might be many

    more opportunities to explore and to be

    creative and run around Etc but it might

    not be as tightly crafted of as an

    educational experience where you lie on

    on that Continuum between like a

    playground and a playpen is kind of

    determined by the goals that you have

    for the students that you're working

    with and you like the context that

    you're in and like even administrator

    pressures stresses Etc but I personally

    generally lean much more towards the

    playground rather than towards the

    playpen so the authors point out that

    hey most of these studies we're focusing

    on the playpen experience but we should

    really explore playgrounds if we were

    trying to focus on creativity the play

    pen may be a good stepping point but not

    necessarily a great destination to end

    at now the third main discussion area is

    quote AI education is still a marginal

    Topic in schools however if the goal is

    to spread AI literacy widely it should

    be integrated into regular school

    lessons more formats should be available

    for advanced students and teachers

    should be more involved end quote and

    the authors point out this is important

    to consider because if we're going to

    have ai education in schools and in

    these research studies we really need to

    involve teachers in them and we also

    need to help train them which I'll talk

    about more in a moment the last thing

    that they mention as a main discussion

    point on page 8 is quote AI education

    appears to be inextricably linked to

    data literacy however a solid

    theoretical Foundation that explores the

    relationship between Ai and data

    literacy is lacking end quote in episode

    data analysis and implications of Cs as

    a skill with and Gunn we talk about data

    analysis a little bit so I highly

    recommend checking out that episode but

    this is a really interesting point that

    data goes hand in hand with a lot of

    stuff that's going on with AI so if you

    want to kind of get a twofer and be able

    to explore AI Concepts and practices but

    also do some data analysis and

    collection Etc you might be able to do

    it by combining the two and that right

    there is kind of like a summary of the

    findings and discussion of this

    particular paper it leads to some

    lingering questions and thoughts that I

    have so one of them is when teaching AI

    what balance do you strive for between

    learning about Ai and using AI as a tool

    for learning or creating in other words

    do you focus more on teaching how AI

    works or more on how you can use various

    AI Tools in your everyday life when do

    you focus on one over the other do you

    strive for a balance between the two or

    do you mainly just focus on I'm only

    going to focus on AI as a tool or I'm

    only going to focus on how it actually

    works it reminds me a lot of like the

    discussions on do we focus on Theory or

    practical application within a classroom

    given that I have like a drum set behind

    me do we focus on music theory or do we

    focus on composing do we focus on how we

    might describe music could we focus on

    how to actually write to our own music

    there's not necessarily a right or wrong

    answer to this but it's something that

    you really should consider if you're

    going to explore AI in education when

    you think of AI literacy are you

    focusing on AI as a tool or are you

    actually going to encourage kids to

    learn how it works or both I'm joined

    Again by my doggo mini another lingering

    thought that I have is AI and education

    is an underexplored area of potential

    professional development for educators

    having previously designed professional

    development and curriculum that's used

    by hundreds of thousands of students

    around the world this is something I've

    spent a lot of time thinking about over

    the last several years whether we're

    using AI as a tool or learning the

    concepts and practices related to Ai and

    how it works I imagine that this is

    something that individual educators are

    going to want to know whether it's

    computer science Educators or Educators

    at large I also Imagine That individual

    consultants and PD providers will be

    able to develop content to help teachers

    to not only teach how to use Ai and what

    it is but they can also use it in their

    own work as an educator so for example

    using AI to draft emails to parents or

    to document student Behavior or progress

    or to generate ideas for lessons Etc so

    if you are a consultant like some of the

    guests that I've had on the show or you

    are a professional development or

    curriculum provider these are some areas

    that you could potentially explore if

    you're already exploring these areas and

    you'd like to come on to talk about this

    in an upcoming episode as an interview

    feel free to let me know there's a

    contact me button on my website

    jaredelary.com now this review of

    literature is not necessarily an

    exhaustive review of literature but it

    is interesting to explore how are people

    exploring AI or at least how have they

    done it from 2010 to 2021 I'm really

    curious how this is going to change over

    the next decade like how are teachers

    going to be using AI in their class what

    about students how we can use it for

    teaching how we're going to use it for

    learning or for creating what kind of

    research is going to come out of this

    I'm very skeptical of adding yet another

    thing that General classroom teachers

    are going to be required to teach in

    their classroom but I also think AI is

    going to be one of those things that

    people are going to use whether they

    want to or not just like technology was

    but next week I'm going to do a little

    bit of a different episode related to AI

    so stay tuned for that a little teaser

    for you and then we're going to explore

    some other areas related to professional

    development so stay tuned for that if

    you are using AI in your classroom or

    you are teaching AI in your classroom

    let me know how you're doing that you

    can reply in the comments on YouTube or

    on social media if you enjoyed this

    episode please consider sharing it with

    somebody else it just helps more people

    find the free podcast episodes and

    resources on my website jaredalary.com

    or if you know a drummer or a gamer

    who'd be interested in the drumming and

    gaming content you can share that as

    well it's all neatly organized stay

    tuned next week for another episode

    until then I hope y'all staying safe and

    are having a wonderful week


Abstract

“Introducing artificial intelligence (AI) literacy to school students is challenging. As AI education is constantly growing, educators can struggle to decide which content is relevant and how it can be taught. Therefore, examining which practices and formats have already been evaluated with students and are used repeatedly and which are challenging or should be explored further is necessary to facilitate teaching AI and encourage the development of new activities. In this literature review, we address this need. Using a directed and conventional content analysis, we systematically analyzed 31 cases of introducing AI literacy in schools in terms of three categories: (a) competence areas, (b) pedagogical approaches, and (c) contexts and formats. When analyzing the results, we identified underrepresented competence areas and summarized common pedagogical practices and recurrent formats and contexts. Additionally, we investigated the approach to using data to make abstract AI knowledge accessible to novices.”


Author Keywords

Artificial intelligence literacy, AI education, data literacy


My One Sentence Summary

This review of literature explored how researchers from 31 papers investigated AI-related literacies in schools.


Some Of My Lingering Questions/Thoughts

  • When teaching AI, what balance do you strive for between learning about AI and using AI as a tool for learning/creating?

  • AI in education is an under explored area of potential professional development for educators


Resources/Links Relevant to This Episode



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