Setting the Scene
Our most recent H2 Learning podcast interviewed Dan Bowen and Ray Fleming, who host the AI in Education podcast, down in Australia. In the show notes for the podcast they wrote the following:
“The big takeaway: AI shouldn’t just be about efficiency. It should be about shifting the teacher’s role from a source of information to a mentor and guide. By automating the bureaucracy and “red tape” that leads to burnout, we have a chance to make teaching a healthier, more creative, and more fun profession. It’s time to move from “delivering knowledge” to “creating valuable humans.”
We hear this argument quite a lot and while it certainly has the potential to help teachers plan and to create more engaging and differentiated learning experiences, it is also being touted to help in addressing the growing administrative burdens (i.e. paperwork) that teachers are required to complete.
The OECD categorises teacher time as follows:
Much of the current research focuses on the use of AI to save teachers’ time, and in particular to support teaching related tasks, such as “as lesson preparation, sourcing curriculum materials, correcting assignments and tests, collaborating with or mentoring peers, and engaging in professional learning activities”. While in addition they can also be used to support “less directly related to teaching, for example communicating with parents, engaging in school management and extra-curricular activities, counselling students or engaging in administrative duties”. Such tasks are labelled “non-teaching-related tasks” by the OECD, and there is growing evidence that such work is increasing. Some are suggesting that AI can help here, but surely there is a bigger question relating to the relevance of such work and if teachers should be spending an increasing amount of time on such matters. However, that is a discussion for another day.
Emerging Research
Some emerging research from the OECD suggests that AI, and in this case GenAI, can in fact go well beyond support efficiency in schools, and can in fact support effective teaching, learning and assessment practices.
The report notes that “one of the most striking uses for GenAI is tutoring” and that it “can hold flexible, personalised conversations, adapting explanations and language to individual learners’ needs”. The evidence here is emerging but this is some of the emerging prototypes show promise in this regard.
The report speaks about the promise of GenAI to “drastically change the way teachers work” and in so doing boost their productivity and the quality of teaching. It suggests that teachers and AI working together in an iterative way holds great promise for “improved instructional quality while preserving professional judgement”. This seems to preserve the best of both worlds and ensures that teachers’ professional judgement is retained. The report goes on to say that most GenAI tools currently are for general use (i.e. ChatGPT, Copilot, Claude, Gemini etc.) and that most of these tools do not align with school curricula. However, this situation is changing with the creation of chatbots that can help teachers and others with a “wide range of instructional tasks while allowing human oversight”.
Finally, the report highlights a myriad of ways in which GenAI can reshape administrative tasks, “making tasks like admissions, career guidance and curriculum analytics faster and more accurate”. While this sounds very promising, there is clearly a need for caution here, so that machines are not making suggestions and decisions on such issues unchecked. The final line of the Executive Summary captures the potential here very nicely, “when designed with strong pedagogy and human-centred approach, GenAI can do far more than help students complete tasks”. It goes on to say that it “has the potential to deepen student learning, improve teaching practice and streamline institutional management and research”.
Final Word for Now
On reading this report I am reminded of a phrase Clare McAvinia, an Academic Developer in TCD used in relation to Moodle and online platforms some years ago, when she referred to the literature in that field as one of hope and or disappointment. Currently there is a lot of hope and only in time will we know if it is well founded. The OECD research is very thorough, and it captures a wide range of ways that GenAI technologies can be used effectively in educational settings. This is good news and we now need to support teachers, across all levels of education, to explore how these tools can help and to document and share their experiences in relation to where they are successful and where they are not successful. We need this balanced approach to better understanding how teachers can design and manage their classrooms, particularly if and when they use these tools. Such practices goes well beyond efficiency.