On Jul 30, 2019, at 8:24 PM, Frank Zeng <xxxxxx@aafie.org> wrote:

Hi Rachel,

 

To answer your question:

 

“At this point, I think that I'm seeking help understanding"  “how it works”, not to improve/customize/design the algorithms."  Can you recommend some resources educators might find helpful?”:

 

There are many online resources available as you know. I’d like to categorize most of them into two: 

1. Those for people/students with right background to learn AI completely, with all details;
2. Those for  people to learn AI concepts, without details.

 

What you need, is something in the middle, with the following characteristic: it is easy for someone without all the background to understand how algorithms (= AI) work. Unfortunately there isn’t anyone who made this type of resources available. With this situation, as I mentioned, the fastest way is to learn from an AI expert who can explain the algorithms in your language. For example, you don’t have the math knowledge to understand SGD, which is a common technique being used in many AI algorithms, an expert can explain it intuitively, with the help of illustrations etc..

 

Frank     

 

From: Smith, Rachel <xxxxxx@newtown.k12.ct.us> 
Sent: Tuesday, July 30, 2019 8:22 AM
To: Frank Zeng <xxxxxx@aafie.org>
Subject: Re: [AI4K12] Simple considerations

 

Hi Frank,

Thanks for breaking down what's needed regarding math. At this point, I think that I'm seeking help understanding"  “how it works”, not to improve/customize/design the algorithms."  Can you recommend some resources educators might find helpful?

Thank you,

Rachel

 

On Tue, Jul 30, 2019 at 3:07 AM Frank Zeng <xxxxxx@aafie.org> wrote:

To put it precisely –

 

1. If you want to understand how the machine recognized cats (understanding “how it works”), or, you even want to improve/customize/design AI algorithms for your specific problems, you need to have math knowledge, primarily Probability, Statistics, Linear Algebra, Calculus; 
2. If you want to just use AI open sources to build models, so that you can solve problems with easy ways (without understanding “how it works”), you only need to understand model structures and terminologies (primarily the so called “hyper-parameters”), plus some practices/experience from AI experts for selecting algorithms and training models. No math is required;
3. If you want to just play models like the “entertainment-type of projects” in many simple AI courses, you only need to understand a few terminologies. No math is required.

 

The number 2 and number 3 don’t require you to have math background, however, “how it works” is going to be always a “secret” for you. 

 

Actually, for number 1, if your goal is only to understand “how it works”, not to improve/customize/design the algorithms, the required math is limited (an AI expert can make you learn the math in a short period of time if you have Algebra knowledge).

Frank

 

From: xxxxxx@lists.aaai.org <xxxxxx@lists.aaai.org> On Behalf Of Jordan Blakeley Hoffman
Sent: Monday, July 29, 2019 3:18 PM
To: Frank Zeng <xxxxxx@aafie.org>; 'April DeGennaro' <xxxxxx@mail.fcboe.org>; 'Ken Kahn' <xxxxxx@gmail.com>
Cc: 'Smith, Rachel' <xxxxxx@newtown.k12.ct.us>; xxxxxx@lists.aaai.org
Subject: Re: [AI4K12] Simple considerations

 

Hi All,

 

Such an interesting conversation. I do worry about the notion that math is a prerequisite to being an “AI expert,” or that mathematical understanding equates a solid understanding of AI.

 

Even though I now hold a degree in mathematics, I struggled a lot with math anxiety and stereotype threat throughout my K12 years and think that if AI had been pitched to me as something “only folks who are good at math” do, I would not have joined the field. And I am afraid that if this is the framing we pass on to educators, or if this is the mindset we bake into national standards, this might also be the framing we pass on to students (educators, I’m curious what your thoughts are on this). 

 

My colleague Randi Williams has talked about using AI as a gateway to getting students excited about mathematics (e.g. Imagine motivating learning about the Pythagorean theorem through the K-NN algorithm), and I much prefer this framing than thinking of mathematical competency as a prerequisite to learning (or teaching) AI topics. 

 

Additionally, when we think about equipping students for careers in AI, I think we need to remember that there are AI experts who contribute to the field through their expertise lies in knowing law, design, philosophy, social science, communication, etc. Thus, it feels like to me if we want educators to go “deeper” than their students, it would make sense for any of these areas to be possible avenues to pursue. And then they could go deeper with their students on these subjects as they relate to AI.  

 

Tl;dr – I worry that focusing on mathematics might exclude teachers and students from AI, and might perpetuate the idea that the only folks who bring valuable knowledge to the field are those who have the same, traditional training that those who get a CS degree receive. 

 

Thoughts? 

 

Blakeley

 

From: <xxxxxx@lists.aaai.org> on behalf of Frank Zeng
Reply-To: Frank Zeng
Date: Monday, July 29, 2019 at 5:12 PM
To: 'April DeGennaro', 'Ken Kahn'
Cc: "'Smith, Rachel'", "xxxxxx@lists.aaai.org"
Subject: RE: [AI4K12] Simple considerations

 

Hello Everyone,

 

Thanks for the educators who have just shared their experience! I think they did a very good job in exploring the important task. Continuing with our discussion, there are reasons that educators should be well-equipped with a solid understanding of AI:    

 

Firstly, as Andrew Ng and many other world AI experts said, AI is gong to be as important as “utility”, it’s a new electricity. Going forward, you will see AI being used everywhere. When your students walk out of their schools, they will see that one would not be considered an engineer if he/she does not understand AI, as EVERY product/service will have AI involved. Recently, Google and Amazon have called all engineers to learn AI! I could not emphasize more on the importance of AI. Being an educator, even only from your personal career’s perspective, the more you understand about AI, the brighter your future career will be!

 

Secondly, as many educators have pointed out, some students are very advanced. They would not be satisfied with superficial concepts. If a teacher frequently failed to answer students questions. I don’t think he/she feels comfortable in teaching the students. We always have a diversified student body and it is the educator’s responsibility to meet all students needs. 

 

Thirdly,  I really think high school students should get chance to learn “AI algorithms”. If we don’t teach algorithms, AI projects are essentially “entertainment”, which is only ok for elementary school (or middle school) students with a purpose to just bring interest (and basic concepts) to them. Without understanding algorithms, it is impossible for students to transfer what they have learned to a new problem/project. Entertainment type of AI projects should not be for high school students.   

 

Furthermore, AI is a big subject. Actually AI is such a branch that it is growing extremely fast. Even for AI professionals, we have to spend a lot of time reading new papers, but we are still struggling with keeping the pace with the latest development. Right now, Deep Reinforcement Learning and Unsupervised Learning are becoming the main street and very important AI technologies, but I don’t think many people know what they are. Although we cannot expect educators to understand everything, but at least, educators should understand the “big picture” .   

 

A final note: if you want to learn the current “big picture” for AI or any other stuff in AI, we can schedule a talk using Adobe Connect. Please shoot me an email for your request.  

 

Best regards,

 

Frank

 

 

 

 

From: xxxxxx@lists.aaai.org <xxxxxx@lists.aaai.org> On Behalf Of April DeGennaro
Sent: Monday, July 29, 2019 3:29 AM
To: Ken Kahn <xxxxxx@gmail.com>
Cc: Frank Zeng <xxxxxx@aafie.org>; Smith, Rachel <xxxxxx@newtown.k12.ct.us>; xxxxxx@lists.aaai.org
Subject: Re: [AI4K12] Simple considerations

 

Ken,

I agree with you on a discussion about how much "technical detail" is needed in K-12. I teach gifted kids and while I am not bound to the state standards as our the general education teachers, it is not appropriate to spend all my teaching time on a strict AI curriculum. Your sentence: One can learn from playing with a "cat recognition" system how similar systems could help diagnose x-rays or help farmers eliminate weeds. really describes the "learning goal" of my AI instruction. I feel that my students, in K-5 need to develop an understanding that AI is using data to "make sense" of the world in specific areas whether it is Delta's use of AI to determine load factors or a chatbot helping answer frequently asked questions for business and industry or as in your example, improved medical care or agriculture. I am not sure they need to know much more than "there are algorithms for that." Rather than expecting every teacher to develop an understanding of AI, can't we use technology to connect students who wish for advanced experiences to find them and like most kids these days, YouTube themselves into expertise in AI? It is generally the way we get teachers to "allow" students to code and develop basic CS experience. Reassure them that kids can learn CS without teachers having to "be ahead" of them.

 

I hope we can have more of a discussion of this topic. I think it is very important in positioning AI in the classroom!

April

 

On Sun, Jul 28, 2019 at 3:57 AM Ken Kahn <xxxxxx@gmail.com> wrote:

Frank Zeng wrote:

 

... you really need to understand the algorithms in AI. If you are doing a simple AI project with students which is just “cat recognition”, if you don’t understand the algorithm, you will end up with just being able to say “that is what AI can do for you!”.  

 

I would like to see a discussion of how much technical detail and algorithm understanding is possible and appropriate for different grade levels Understanding things like backpropagation and stochastic gradient descent in depth is probably inappropriate with very few exceptions for K-12. A "light" understanding may have some value. Even with no understanding of the algorithms one can learn how providing more and varied training data improves accuracy, what kinds of mistakes a "cat recognition" system makes, etc. One can learn from playing with a "cat recognition" system how similar systems could help diagnose x-rays or help farmers eliminate weeds.

 

Is the idea that school students should know AI algorithms something like the (controversial) idea that students should know how a computer represents and multiplies numbers? I think those few who want to learn about binary representations and floating point circuitry should have support but I don't think it is for the mainstream K-12 students.

 

AI professionals can (and should) help teachers understand AI but we also need to be careful. New Math came about because professional mathematicians knew mathematics but not learning sciences and pedagogy.

 

Best,

 

-ken kahn

 

On Sun, 28 Jul 2019 at 03:12, Frank Zeng <xxxxxx@aafie.org> wrote:

I’m an AI professional, so I can share some of my opinion from another perspective here.

 

I did take a look at the AI courses being offered to educators like ISTE's AI courses. Like many similar courses, their objective is more on “AI popularization”, instead of understanding AI technologically. The important point is that, if you want to feel comfortable to teach AI to students (no matter what grades the students are), you really need to understand the algorithms in AI. If you are doing a simple AI project with students which is just “cat recognition”, if you don’t understand the algorithm, you will end up with just being able to say “that is what AI can do for you!”.  And, figuring out how it works is not something you and your students can brainstorm and find the solutions.  

 

To understand AI algorithms, the educators really need to learn AI technology. Learning how to teach AI in classrooms can only happen if you understand how AI works.  If we talk about offering AI certificates to educators from universities, the certificates must be from the Computer Science Departments of the universities, not from School of Education. Also, it is hard to believe that one without math background can understand AI algorithms, unless he/she learns math prior to learning AI. 

 

It is said that in other countries, like China, the central governments have mandated that all K-12 schools will open AI courses to students. So far, China has produced more than 15 different sets of AI textbooks for K12 schools. Their goal is to open AI courses in most K12 schools before 2021. We are lag behind and need to act quickly. Our educators should learn AI directly from AI professionals so that they can learn quickly and feel comfortable in teaching AI in classrooms (Learning from online videos is not easy for educators without much background).  The best way probably is to ask AI professionals to give educators free lessons.  My team is willing to give K12 educators free AI lessons through live online classes using Adobe Connect. I think a 32 sessions of interactive classes would give K12 educators a very clear picture in terms of how AI works (even without math background). With Adobe Connect, we can have all the related educators from a single county in a state join the AI class by Internet from home or office at the same time. We could cover all K12 schools in a short period of time if we also have other AI professional teams join us for doing this. 

 

Best,

 

Frank Zeng, Director

AAFIE Artificial Intelligence Labs

 

From:xxxxxx@lists.aaai.org <xxxxxx@lists.aaai.org> On Behalf Of Smith, Rachel
Sent: Saturday, July 27, 2019 1:16 PM
To: xxxxxx@lists.aaai.org
Subject: Re: [AI4K12] Simple considerations

 

Hi Brenda,

 

Thanks for sharing your insight. I think your idea about creating a website targeting teens may work really well-- especially if we could offer resources for guidance counselors. The idea of a competition is also neat. Today, there's one in Pittsburgh, I believe. Check out the WAICY website for more info.

 

It was really interesting for me to learn what's going on in TX. At ISTE this year, I had the chance to meet with affiliates from across the country, and I learned that many states are struggling to implement CS. CT recently adopted CSTA standards and a CS requirement. I've been working with our state's Computer Science Council to develop a plan to implement CS instruction-- from teacher preparation/certification to curriculum. It's a lot of work with a lot of moving parts. Just like Texas, we have amazing K12 educators, and we have amazing districts. Yet each district is approaching the new requirements differently. Some offer CS as electives at the high-school level, others integrate it into core subjects from preK-12. There are many approaches, and a one-size-fits all doesn't work. I often look to Rhode Island, which  has done a tremendous job of integrating CS into K12, for inspiration. Right now, there are a few universities offering a CS certification program in CT, and the state is working to create pathways for educators like me, who have a Master's in Literature but are teaching CS. I'm on the board of CECA, our state's ISTE affiliate, and we are always striving to help educators feel more comfortable teaching CS.

 

I don't know how many of us are familiar with the design-thinking process, but I've recently used it to apply for Google's EI program. I'd like to make it easier for teachers to understand AI so that they feel comfortable enough to teach it. ISTE's AI course is a great resource. Yet even after taking it, trying to interpret the college-level AI courses on YouTube, and reading so many articles/studies, I still feel I need to learn more to truly teach it to my middle-school students. I'm trying my very best, though, and know that while I have some introduction lesson plans crafted, it will take me a while to feel truly comfortable with this subject. But here's the thing-- admitting that I don't know the answer to a question and working with the student to find a answer is pretty cool. Not only does it make me more human, it empowers my students. At middle school, I can be goofy, make mistakes, and admit that I don't know and kids will respond to that. 

 

I want to work on a solution that meets K12 teachers at their level. I have so many ideas, but have been afraid to put them into action because I don't have the background knowledge. But the application process to the EI program taught me that I still can contribute in some meaningful way. 

 

Anyway- I've veered from the topic. Thanks for sharing, and I look forward to learning from and connecting with everyone in the future.

 

Best,

Rachel Smith

 

 

 

 

 

On Sat, Jul 27, 2019 at 12:14 PM Brenda Flinn <xxxxxx@gmail.com> wrote:

Hello all,

 

I work in support services at a high school and I get to somewhat observe daily activity. I would like to pass on some simple observations as you consider things.

 

First, Texas tried to add computer science to the curriculum, but recently dropped it. It was a difficult fit which I will offer two reasons in my opinion:

 

(1) how to use a TI calculator instructions are in the math books, computing instructions are absent, and

 

(2) few teachers are prepared to teach computer science.

 

Now, like it or not, Texas heavily influences textbook content for all states. Changing the content is a 20 year political endeavor even digitally. And on top of that, state boards of education must approve books used in the classroom. For example, English teachers can only teach literature from a choice of books on an approved list.

 

So, I would offer that you make a better way for certifying educators to teach computer science. Computer science college graduates are locked out of teaching in public schools because they lack the teacher education requirement hours mandated by states. Encourage universities to offer computer science and educator courses in one degree much like that of music educators.

 

Incentivize AI challenges attached to high school mathematics classes as an extension of basic, current lesson plans. School participation in interscholastic competitions is active and a source of pride (like debate or social studies). You have to work with those judging graded interscholastic competitions to get one going in AI that matches what is on the plate in the classroom.

 

Finally, an easy to navigate, responsive website is needed with the excitement of AI news, clear pathways on how to become an educator of computer science in each state ... all geared toward an age 13 to 18 audience plus their teachers and parents.

 

Okay, I hope you can use these observations as you grow. I can offer you latex development for printing, website creation and maintenance, and content writing.

 

Please let me know if I can be of assistance.

 

Sincerely,

Brenda Flinn

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