Applying AI to study and improve learning and teaching practices: An invitation to a collaboration

  

The Full List of The Publications on The Methodology of Teaching Science

Table of Content /  List of Posts

In Physics there is an object called a prototype (or a standard, or an étalon).

It has enormous importance in physics, in science, and in life in general, because based on a prototype scientists and engineers make simpler, cheaper, and in large quantities copies of the prototype and use them to make consistent and accurate measurements, the result of which does not depend on by whom and where that measurement was made. A prototype ensures uniformity of the measures across human practices and professional fields.

But not in education.

Education has no prototypes.

That makes the field of education virtually immeasurable, hence, non-scientific. Education research is not an actual scientific research establishing strong correlations between well-defined parameters, but an exploration, similar to a geographer exploring a new territory and writing letters with the description of the discoveries he/she made (or a botanist or zoologist describing new species they found).

This state of affairs, however, can be changed, and the company that pioneers the transformation from an exploration to a scientific research will dominate the market of educational practices for years ahead.

I have developed specific instruments that can make this transformation to happen in physics education (and the principles can be applied to other STEM areas, starting from math and chemistry).

Anyone who is interested to learn more about my approach is welcome to contact me (scroll down for the contact information; as well as for the confirmation of my professional abilities).

Two short video presentations:

1. Open Classroom Initiative: invest in the first world-wide open library of lessons

2. Invest in EdTech and disrupt K12 education

There are apps which will solve for you any regular equation from a standard textbook (just take a picture).
There are NO apps or computer programs which can solve problems from a standard elementary physics textbook. Because solving physics problems requires a very specific way of thinking, i.e. specific type of intelligence.
And that shows the difference between math and physics. Physics uses math, which means, physics is math plus ... a lot more called thinking.
P.S. This is one of five strategic projects I am interested in ("Don't place all your eggs in one basket") 
Some of my "interventions" into the field of AI development:
On The Definition of AI
Relax! The real AI is Not Coming Any Soon!
The Dawn of the New AI Era (the 1st piece on AI training)
Who Will Train Our Artificial Puppies (the 2nd piece on AI training)?

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Applying AI to study and improve learning 

and teaching practices: An invitation to a collaboration

 
To Whom It May Concern:

I am one of those people called “bilinguals” who, according to the President ofM.I.T. Prof. Rafael Reif, will be transforming the future of AI.

I am a theoretical physicist by trade, a physics instructor and a writer by my profession, and an expert on human intelligence.

I would like to be a part of the laboratory “AI for education” of any institution which has or will be opening such a laboratory.

I personally would like to be involved into the research and development of AI named “a perfect physics student”, i.e. and AI which can solve any problem from any regular physics textbook.; and AI named “a perfect physics teacher”, i.e. AI which can explain to a regular person how to solve any problem from any regular physics textbook, and guide a student through the problem-solving process better than an average physics teacher does it these days.

I am a very good physics teacher. I have a solid proof of that. For example, this is an excerpt from one of many student evaluations: “I hated physics before taking this course, and now after taking both 105 and 106 with Mr. V, I actually really enjoy it. He is one of the best teachers I've ever had. Thank you” (ten more pages on this link :) ).

Why am I good a teaching physics?
Because I know patterns needed for creating solutions to physics problems; I know patterns needed for learning how to create solutions to physics problems; and I know patterns needed for teaching how to create solutions to physics problems; and I am good at using those patterns in my teaching practice.

I also have a very good knowledge of how AI works (currently), or should work (in general). I have published some pieces on the matter, including one giving an operational definition of AI: the latest piece is available at http://www.cognisity.how/2018/05/AHLI.html; the original definition is presented at http://www.cognisity.how/2017/12/AIdef.html.

In fact, the latter piece had been reviewed in a professional peer reviewed magazine with the following response, quote:

“10-Jan-2018

Dear Dr. Voroshilov:

We enjoyed your letter, but the board declines to publish it because they thought it would be too controversial.

Sincerely,

Editor, Journal of Experimental & Theoretical Artificial Intelligence”.

I think, “too controversial” may be exactly what the lab “AI for Education” should embrace.

Of course, the strategy which will be used for AI in physics education can be used for math education, and for other science subjects.

I also have an experience in educational consulting and teacher professional development and have a clear vision for specific projects merging advances in AI with advancing the practice of education in general.

Recent DARPA pre-solicitation # DARPA-PA-18-02-02, titled “the Artificial Intelligence Research Associate (AIRA) program” “invites submissions of innovative basic research proposals to address two main objectives: 1) explore and develop novel new AI algorithms and approaches for discovery of scientific laws and governing equations for complex physical phenomena”.

I would like to point at the fact that the reasoning process one uses when constructing a solution to a physics problem one has no experience of solving in the past has close similarities to the reasoning process one uses “for discovery of scientific laws and governing equations for complex physical phenomena”.

Creating AI which can solve physics problems is a natural step toward creating AI Research Associate.

Since I am not in the field of AI, I have no chance to get any funding from DARPA.

That is why I started searching for a group of established researches who would be interested in my projects “AI as perfect physics student”, and “AI as perfect physics teacher”.

I am confident with all the stages of the development of AI applications besides coding, but coding is the least important or at least the last part of the whole process (in fact, any good physicists can become a good coder, but the reversed statement is wrong: http://www.cognisity.how/2017/12/cyber.html).

I hope to hear from a relevant person with whom I could discuss the details of my prospective/possible professional involvement/collaboration.

Sincerely,

Dr. Valentin Voroshilov

www.Cognisity.How
www.GoMars.xyz

valbu@bu.edu

617-657-9436

BU, Physics Department

P.S. This is one of five strategic projects I am interested in ("Don't place all your eggs in one basket")

_____________

My Elevator Pitch

Applying AI to study and improve learning and teaching practices: An invitation to a collaboration

(also in Russian and Chinese)

Dear Experts,

I am HEPHI, i.e. a Highly Experienced Practitioner in Human Intelligence, a.k.a. a Teacher (http://www.teachology.xyz/evvv.html). 

I also have been doing a research in education, including best practices for teaching physics and teacher professional development (http://www.teachology.xyz/vv.htm).

I am not in the field of AI, machine learning or cloud computing per se, but I know enough about it.

I am critical to the term "Artificial Intelligence" (although I gave an operational definition of AI, e.g. "On a definition of AI", or "The Dawn of The New AI Era"), but I firmly believe in the power of the deep machine learning, and I have a clear vision of how it can be used to study and improve learning and teaching practices on a large scale.

In particular, I have developed a specific strategy for using advances in AI to developing a new type of content knowledge measuring instruments in physics, mathematics, and chemistry. Based on my knowledge of how mind learns, I also envision a specific strategy which will lead to the development of AI capable of solving physics problems, potentially even win a physics competition.

I am searching for individuals or organizations which would be interested in collaborating on this type of R&D.

I hope we could have a conversation, which could lead to our partnership.

Please, feel free to contact me:

valbu@bu.edu (always works)

617-657-9436 (when at work may not be able to answer immediately).

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Thank you for visiting,
Dr. Valentin Voroshilov
Education Advancement Professionals
GoMars.xyz

To learn more about my professional experience:
"Dr. Voroshilov from A to Z" 
 
"The Backpack Full of Cash": pointing at a problem, not offering a solution

Essentials of Teaching Science

Appendix I: the reasons

On Wednesday, 02/14/2018, I was listening to a live Congressional hearing on AI (https://oversight.house.gov/hearing/game-changers-artificial-intelligence-part/).

Everyone who has a slightest interest in AI should do it, too. I would like to point at only three (of many) interesting moments.

1. Despite one of the first of the stated goals of the hearing (to clarify what AI is), no one of the four panelists offered a clear definition, except saying “AI is what we see in the futuristic movies” (meaning, basically, devices/systems acting like people). I wish I could represent or at least to have a discussion about my definition of AI (which is an artificially manufactured system which can create solutions to problems the system has never solved before: http://gomarsnow.blogspot.com/2017/12/AIdef.html).

2. When asked when AI could exhibit reasoning abilities similar to human, all four panelists offered numbers between 20 and 30 years from now. Which makes a perfect sense to me. If they said "fifty" congressmen could start thinking "well, if it so far ahead, what's the all fuss, we have more pressing matters to finance?". But they just could not say "ten" because they all knew (and all in the field know, and they knew they know) that "ten years from now" is just not realistic, not believable (and lying to the Congress is bad – at least according to movies). 

3. When asked about the areas where AI can bring significant advances, NONE (!) of the participants named education – no one! Clearly “big fish” in AI don’t have education on the list of their priorities (didn’t pop up in their mind), or at least as a potential funding generated field. That is despite the fact that the training procedures they use to “teach” AI, such as “supervised learning” and “reinforcement learning”, are just simplest teaching approaches – way before, say, John Dewey’s Constructivism. The reason behind this fact is very simple – current AI does NOT require any complicated teaching strategy, current AI is not really smarter than a dog (can recognize a face, a voice, a command), well, very fast thinking dog. And since AI will not be requiring such a strategy for at least twenty years, why even bother (even if it will matter rather soon, because those who can see already see "The Dawn of The New AI Era")? 

This is one of the reasons that all my attempts to reach out to AI professionals failed (so far, and the evidence of that - you reading this post). And this was one of the reasons for me to start - by publishing this post - an open search for collaborators interested into merging advance in AI with education. I consider this as an experiment. In science any outcome is valuable.
Appendix II:

From the NASA's "Brief History of Rockets"
https://www.grc.nasa.gov/www/k-12/TRC/Rockets/history_of_rockets.html

“In 1898, a Russian schoolteacher, Konstantin Tsiolkovsky (1857-1935), proposed the idea of space exploration by rocket. In a report he published in 1903, Tsiolkovsky suggested the use of liquid propellants for rockets in order to achieve greater range. Tsiolkovsky stated that the speed and range of a rocket were limited only by the exhaust velocity of escaping gases. For his ideas, careful research, and great vision, Tsiolkovsky has been called the father of modern astronautics.”

What teachers can do! 
Also, keep in mind, if it wasn't for Steve Wozniak, the world would never knew Steve Jobs.

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Dear Visitor, please, feel free to use the buttons below to share your feelings (ANY!) about this post to your Twitter of Facebook followers.
 
Appendix III 

What you see below is the work of the Google Translate (I have not touched a character, even if I could for Russian translation). The World is large. Many countries may be looking for a breakthrough in AI by merging it with education. My son lives in Somerville, MA and works for a large Chinese corporation. Why can't I?

_____________________________ 

应用人工智能研究和改进学习和教学实践：邀请合作

親愛的專家，

我是HEPHI，即人類智力高度經驗的實踐者，也就是一名教師（http://www.teachology.xyz/evvv.html）。

我也一直在進行教育研究，包括物理教學和教師專業發展的最佳實踐（http://www.teachology.xyz/vv.htm）。

我本人不在AI，機器學習或云計算領域，但我對此足夠了解。

我對“人工智能”一詞至關重要（儘管我給出了AI的可操作定義，例如“關於AI的定義”或“新AI時代的黎明”），但我堅信深入的機器學習，我對如何用它來大規模研究和改進學習和教學實踐有清晰的認識。

特別是，我制定了一項具體的策略，利用AI的進步來開發一種新的物理，數學和化學內容知識測量儀器。基於我關於思維學習的知識，我還設想了一個具體的策略，這將導致人工智能的發展能夠解決物理問題，甚至可能贏得物理競賽。

我正在尋找對此類研發合作感興趣的個人或組織。

我希望我們能夠進行對話，這可能會導致我們的合作關係。

請隨時與我聯繫：

valbu@bu.edu（始終有效）

617-657-9436（工作時可能無法立即回答）。

_____________________________ 

Применение ИИ для изучения и совершенствования методов обучения и преподавания: приглашение к сотрудничеству

Уважаемые эксперты,

Я HEPHI, т. Е. Высоко опытный практик в области интеллекта человека, a.k.a. Teacher (http://www.teachology.xyz/evvv.html).

Я также занимаюсь исследованиями в области образования, включая лучшие практики обучения физике и профессиональному развитию учителей (http://www.teachology.xyz/vv.htm).

Я не в области ИИ, машинного обучения или облачных вычислений сам по себе, но я знаю достаточно об этом.

Я критически отношусь к термину «Искусственный интеллект» (хотя я дал оперативное определение ИИ, например «Об определении ИИ» или «Рассвет новой эры АИ»), но я твердо верю в силу глубокое машинное обучение, и у меня есть четкое представление о том, как его можно использовать для изучения и совершенствования методов обучения и преподавания в больших масштабах.

В частности, я разработал конкретную стратегию использования достижений в области ИИ для разработки нового типа средств измерения знаний в области физики, математики и химии. Основываясь на моих знаниях о том, как ум учится, я также предвижу конкретную стратегию, которая приведет к развитию ИИ, способного решать физические проблемы, потенциально даже выиграть физический конкурс.

Я ищу людей или организаций, которые были бы заинтересованы в сотрудничестве в этом типе исследований и разработок.

Надеюсь, мы сможем поговорить, что может привести к нашему партнерству.

Пожалуйста, не стесняйтесь обращаться ко мне:

valbu@bu.edu (всегда работает)

617-657-9436 (когда на работе невозможно ответить сразу).