Making sense of arguments about AI in the future of education

Forward-Woman-Artificial-Intelligence-Robot-507811_400x283I’m attempting to develop some kind of framework to make sense of the emerging wealth of ideas about artificial intelligence (AI) and it’s potential impact on teaching and learning. This is a first very tentative step in trying to give shape to scaffold our thinking about how AI might change our roles as teachers, our relationships with students, what and how we teach and perhaps what we should be hoping for in an AI rich future.

While I’m still scratching the surface, it seems to me that the arguments about AI in education I’ve explored so far can be categorised against three types (partly inspired by Simon Sinek’s “Why-How-What” Golden Circle)…

(Why) – Learning because of AI

That students will need different knowledge and cognitive skills to survive and thrive in the face of the economic, social, political and cultural disruption that AI will trigger. Non-intelligent digital technology has already taken over many mundane and repetitive tasks of life and work and AI threatens to take over middle-order thinking and procedural processes as well. This includes the “robots are coming for your jobs” arguments. In such a world human value-add is expected to be concentrated in areas such as higher order thinking, collaboration, creativity and judgement.

(How) – Learning through AI

That AI systems and agents will offer new opportunities and challenges for the way teaching and learning occurs. Educational software and eLearning environments powered by AI are expected to provide for personalisation, targeted instruction and timely feedback for learners, enabling transformation of learning processes, experiences, spaces and systems. This includes the “your role as a teacher will be transformed” arguments.

(What) – Learning about AI

That students will need skills and knowledge to allow them to deal with AI in their future lives. They will need to know how to code, to design, to configure, to direct – not just interact with and react to – AI systems and agents, to ensure they are empowered to lead satisfying and successful lives in an AI-rich future. This includes the “we need to teach students to be creators of technology, not just consumers” arguments.

There are also some economic and political arguments/discussions that contribute to the broader context within which education change can be visioned. These include equity and wealth distribution, environmental impacts/considerations, cultural change and the future of work, industry and remuneration.

What do you think? All comments are welcome. My next ambition is to map this Why-How-What organiser against another educational frame (e.g. Bloom’s Taxonomy, PBL Essential Design Elements, TPACK, SAMR etc) to see if the intersections can offer richer ideas and a model to support decision making.

(Also published on the Learning Place 11 April 2017)


Brunskill, Emma (2017) Playtime’s Over: Getting computers to beat humans at games is impressive. But now the real work begins; MIT Technology Review,, last viewed 11 April 2017

Dickson, Ben (2017) How Artificial Intelligence Enhances Education; The Next Web,, last viewed 11 April 2017.

Dickson, Ben (2016) Robots are taking all of our jobs. What’s next? Tech Talks,, last viewed 11 April 2017.

Drabkin, Ron (2017) Machine Learning: The “Next Big Thing” in Education, Getting Smart, last viewed 11 April 2017.

Luckin, Rose and Griffith, Mark (2016) Intelligence Unleashed: An argument for AI in Education; Pearson,, last viewed 11 April 2017.

Online Universities (2012) 10 Ways Artificial Intelligence Can Reinvent Education; Blog,, last viewed 11 April 2017.

Vander Ark, K and Vander Ark T (2017) Rise of AI Demands Project Based Learning; Getting Smart,, last viewed 11 April 2017.

Wood, Alex (2016) Artificial intelligence is the next giant leap in education; Raconteur,, last viewed 11 April 2017.

Yao, Mariya (2017) Why We Need To Democratize Artificial Intelligence Education; Forbes,, last viewed 11 April 2017.

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How AI will disrupt the classroom? Perhaps not enough.

Blog_Insights_AI_TeacherWhen the CEO of an Artifical Intelligence (AI) technology company – like Entefy’s Alston Ghafourifar – pens a piece proclaiming the coming disruption of the classroom by this latest technological phenomenon, it is tempting to recall all the other disruptors that were meant to upend and revolutionise learning. Radio, video, email, the web, social media, interactive whiteboards…

This article on VentureBeat (originally on Entefy’s own blog) hits some useful notes – for example, the importance of the teacher-student relationship and lifelong learning attribtues – but there isn’t much critical discussion of how AI might actually take hold in the schooling landscape. It would have been interesting to consider how education politics might drive initial investment in AI products (e.g. to boost test scores through automation and personalisation of delivery) or the possible equal-and-opposite reaction of disillusionment and vested interests seeking to maintain traditional models of schooling.

Ghafourifar suggests that the best use of AI is to act as a support for teachers, freeing them up from the tedious business of their job (like assessment and record keeping) – it reads like an Entefy reassurance that the machines aren’t to be feared after all and that rather than disruption, what we’ll see is noticeable improvements to existing schooling but around the edges. In the original post there is an intersting table comparing the things teachers and AI are respecively good for. It pays lip service to individualisation and “extending learning beyond the classroom”.


One potential I’d love to see explored is giving students greater agency over their learning and connecting them to real and authentic learning experiences and communities. For example, instead of assessment continuing to be controlled by teachers (even if outsourced to AI platforms) , I wonder how AI might help us transform even codified curriculum (e.g. Australian Curriculum) into something that students and teachers can draw on to make real choices about what and how they will learn. This could provide the basis for promoting lifelong learning skills while avoiding the crowded curriculum. Does every student really need to know about isotopes?

Or could teachers and students use AI to monitor learning progress against curriculum goals using evidence from real world demonstrations of learning in the context of genuinely connected and authentic learning experiences? Perhaps the complexity of aligning the individual learning journeys with codified curriculum goals, need no longer be a barrier to making learning connected for every student.

Changes in Singapore–learning through life, not just exams

Connected learning, according to Wikipedia, is “..a type of learning that integrates personal interest, peer relationships, and achievement in academic, civic, or career-relevant areas…” This definition brings to mind the recent changes announced by the Singapore Ministry of Education (MOE) aimed at promoting learning that is connected to students interests, abilities and aspirations, moving away from the comparitive and competitive model that many argue has pushed the country consistently to the top of the international education rankings for a number of years.

The changes have been driven as much by industry as any other group in Singaporean society, as they realise the need to equip school graduates with the “…the creativity and people skills needed to thrive in a volatile, uncertain future”.