Education theory holds that student learning is optimized when teachers tailor instruction to individual needs, often called student-centered teaching. But student-centered education is nearly impossible in the conventional classroom, where teachers juggle large numbers of student-clients, compared with most other human-services occupations. Moreover, students arrive at school with diverse backgrounds, needs, and abilities. Yet schools and teachers are tasked with educating all students, regardless of their level of preparation, motivation, or engagement. At the same time, educators must balance multiple, often competing, goals for these students: Building literacy skills (reading, math, writing, speaking), encouraging academic excellence, developing occupational or vocational skills, ensuring personal social-emotional growth, enhancing social justice and multicultural awareness, and many more. Addressing these goals is a daunting task for any teacher—and the conventional classroom design means this work is done largely on one’s own, in isolation from colleagues. Not surprisingly, teachers often find it difficult to meet students’ needs in the conventional classroom model, leading to teacher dissatisfaction, burnout, and high turnover. And, not surprisingly, this model has long been the target of reform.

Yong Zhao writes in the magazine article “If Schools don’t change, the potential of AI won’t be realized” that we need to reimagine how schools work. He argues that adding AI to traditional classrooms to teach the same subjects and meet the same expectations it would not work. He argues that personalized learning should be about giving students freedom to discover and develop their own strengths and interests. This aligns with what others have written in the other readings in this course that schools should be about giving students agency over their learning. Second, he says project-based learning needs to be redefined. Zhao says that problem-based learning should be about students finding and solving problems with the assistance of AI. “Students need to learn how to find and refine problems worth solving and work through a process of innovation to develop solutions, which can be products of any sort, such as music, dances, tools, movies, paintings, and physical objects”. Third, he says that we must imagine a new curriculum for schools. Zhao admits that what a new curriculum would look like has not been explored but he provides one possibility: a three parts curriculum that teaches (1) the common or public good, including skills and knowledge for living in a nation, (2) what are deem important for all students to learn (e.g, basic literacy, numeracy, digital literacy, financial literacy, and I would add oracy) and (3) a part that is personalized by students. Zhao says for this vision to be realized, pedagogy, assessment and how students are organized in schools needs to be redefined.

I see this as a vision but how this can be done is not clear to me.

Whenever I hear about problem-based learning I also think about the idea of structured inquiry, guided inquiry and open inquiry.

It is obvious to me that Armony & Hassan, (2024) are on the side of The Enthusiasts and the Omni-Assistant, I believe, is a vision for the future. I engaged with this reading in depth for my Speculative Fiction assignment and left it there.

Marzano (2003) reported that research tells us that the human teacher is the single most important factor affecting student achievement. Teachers are pivotal to many aspects of learning such as motivation, role modelling and so on.

We know that teaching is very complex. I learned from my readings and studies and Professional Development (PD) that many of the basic aspects of teaching and learning cannot be captured reliably in data form. This is even more true for capturing the complexity of a classroom and a student’s social circumstances. Research tells us that the human teacher is the single most important factor affecting student achievement. Teachers not only do knowledge transfer and skills building but teachers are also social workers. Yong & Liu, (2024) argued for the same idea, that teachers are pivotal to many aspects of learning such as motivation, role modelling and so on and this is something that AI cannot replace. Human teachers foster emotional intelligence, empathy, and creativity in our students. AI can aid students but cannot replace human interaction. Students learn in relationships with other humans, that is, their human peers and their human teachers.

I have an interest in adaptive learning systems, intelligent tutoring systems (ITS) and personalized learning for a number of years now prior to this course that goes back all the way to 2020. For example, I am familiar with ALEKS https://www.aleks.com/about_aleks before this course and I had engaged with DreamBox Learning and was familiar with Knewton. As a result, Yong & Liu (2024) discussion on AIED and personalized learning really got my attention. Yong & Liu (2024) question as to whether personalized learning powered by AI is a fresh horizon or a castle built on sand is quite pertinent. I recall that in 2020 when I was reading about personalized learning and adaptive learning systems I read about one case of push back by parents against the school board for having students using adaptive learning systems alone for relatively long periods of time without interaction with the teacher.

I agree with the main premises in Yong & Liu (2024) conclusion: that we need to balance the promises and perils of AIED. In their conclusion with an eye to the future, the authors note that the role of teachers should shift to focus more on developing skills such as critical thinking, emotional intelligence, and creativity. I would add social skills, communication skills and oracy to this list. They argue that the role of teachers should evolve to facilitators who guide students in using AI tools effectively. I agree with the authors that teacher’s expertise in the human-centric areas of teaching and learning that AI cannot fully replicate is critical. Yong & Liu (2024) sees teachers as having to leverage AI’s capabilities to support and enhance learning but must preserve the human elements of teaching.

Yong & Liu (2024) make the profound point that AIED holds the promise of personalization and efficiency in education but education is a profoundly human enterprise. Thus we must be cautious to integrate AI into teaching and learning while preserving the human aspects of education.

“In navigating the integration of AI in education, it’s crucial to find a balance between machine efficiency and human creativity. This balance is key to creating an educational environment that is both inclusive and effective, leveraging AI for its strengths while valuing the irreplaceable aspects of human interaction. Achieving this harmony not only is beneficial for current learning environments but will also set a foundational legacy for future generations of learners” (Yong & Liu, 2024, p.61).

Sal Khan is one of the Enthusiasts and in his TED Talk “How A could save (not destroy) education” talked about giving every student an amazing AI personal tutor and giving every teacher an amazing AI Teaching Assistant. He talked their educational chatbot, Khanmigo, and how AI opens up new possibilities for more interactive approaches to teaching and learning.

I listened to Greg Brockman fascinating TED Talk “The inside story of ChatGPT’s astonishing potential” over and over, many, many times because I was so fascinated about what he said. It is easier for me to copy the description of the talk as I cannot do better. “In a talk from the cutting edge of technology, OpenAI cofounder Greg Brockman explores the underlying design principles of ChatGPT and demos some mind-blowing, unreleased plug-ins for the chatbot that sent shockwaves across the world. After the talk, head of TED Chris Anderson joins Brockman to dig into the timeline of ChatGPT’s development and get Brockman’s take on the risks, raised by many in the tech industry and beyond, of releasing such a powerful tool into the world”.

So here we hear it straight from the horse’s mouth, as they say, from the founder of OpenAI himself, that ChatGPT is a purely syntactic process, but out of it we see an emergence, a sort of semantics emerging from a syntactic process. I recall Steven Pemberton explaining that ChatGPT is a stochastic parrot.

As the interviewer explained, generative AI are just prediction machines. But yet they can produce amazing results. It is all about the idea of emergence. And the key idea of emergence is that when you get more of a thing, suddenly different things emerge. For example, ant colonies. We have single ants running around. When you bring enough of them together you get an ant colony that show completely emergent, different behaviour. Another example is cities. A few houses together are just a few houses together. But as you grow the number of houses you get a city. Then things emerge such as suburbs, cultural centers and traffic jams.

Another takeaway for me is the point that there is no real understanding inside of generative AI, it does not have common sense, and we can never know that is is not generating errors. My understanding is that Greg Brockman answer is that there is no easy answer to this question but he thinks we will eventually get there. The example he gave is how do you check if it has done a good summary of a book? You have to read the whole book yourself and no one wants to do that.

References

Armony, Y., & Hazzan, O. (2024). What Is the Omni-Assistant? In Inevitability of AI Technology in Education (pp. 83-98). Springer.

Brockman, G. (2023, April). The inside story of ChatGPT’s astonishing potential [Video]. Ted Conferences. https://www.ted.com/talks/greg_brockman_the_inside_story_of_chatgpt_s_astonishing_potential

Khan, S. (2023, April). How AI could save (not destroy) education[Video]. Ted Conferences. https://www.ted.com/talks/sal_khan_how_ai_could_save_not_destroy_education

Marzano, R. J. (2003). What works in schools : translating research into action. Association for Supervision and Curriculum Development.

SAI Conference (2024, Dec 11). There’s no I in AI. Join Steven Pemberton as he delves into the fascinating world of Artificial Intelligence and uncovers the latest advancements and trends that are shaping the future of humanity. [Video]. YouTube. https://www.youtube.com/watch?v=lS4-QSR1sNk

Yong, K.-T., & Liu, M. (2024). Balancing the Scale. In Academia’s Billion-Dollar Roulette (pp. 56-62). Routledge.

Zhao, Y. (2025). Could the Pandemic Change Education for the Better? Educational Leadership, 82(5), 36.