Well-meaning administrators and educators often draw on ‘elite’ universities’ data and experiences for inspiration and adoption. For many, especially those at the coal face, this can be frustrating. When we hear the words “[Insert Elite University] just published a study on x educational approach, and we need to adopt this here”, some may feel an urgency to scream: “But, we aren’t [insert elite university]” or “Just because [elite university] is doing it, doesn’t make it right for us.” – but instead we nod as the frustration simmers.

Where is the origin of this external focus on ‘best practice’, ‘transferability’ and ‘generalisability’ when it comes to teaching and learning?  Is it ‘best practice’ to look to others for evidence around teaching and learning, and if so, to what extent?

The answers to such questions could be informed by exploring the context of teaching and learning and related expertise.

Education is complex, and complex systems aren’t represented by the mean

Complexity theory is well-represented in the literature to explain learning systems.  Underpinning educational systems is the non-linearity defining complexity theory.  As much as we want it to be this simple, teaching doesn’t come down to a teacher who speaks knowledge which is absorbed by a student who then goes on to produce evidence of this learning on an exam. Teaching and learning is filled with uncertainty, complexities, and ambiguities. Education can be represented by entities that come together to form brand new arrangements, typical of complex systems. Those entering the classroom, when education is working well, aren’t the same when they leave. 

Teaching and learning are filled with uncertainty, complexities, and ambiguities.

On any given day, the teacher is influenced by the events of their own day, their own knowledge and their own experiences. These factors then impact on what is taught and how it is delivered. Similar factors are influencing learners’ experiences. Each of us carry with us our unique life story which, within the educational environment, comes together with others’ and their life stories creating a new shared experiential story which continues to develop as the learning progresses. On any given day, in any given classroom, the likelihood that external teaching approaches can be effectively replicated wholesale is next to nil.

Because of these complexities, education research is highly challenging and one-size-fits-all (e.g. “Harvard/Cambridge/Stanford [elite university]-fits-all”) approaches to education are unlikely to be effective.

Whose expertise defines ‘best practice’?

The first challenge related to defining transferability, generalisability and best practice is: defining and identifying whose expertise matters. Are those on the outside or the inside of the learning context best placed to be privileged as experts? Are you the expert on your local context? What about the students, the teachers, the administrators? Who is the expert?

Associate Professor of Educational Psychology, Jason Lodge, who serves as the Deputy Associate Dean (Academic) at the University of Queensland, illustrated the importance of the “expert” view – whether intended or not – with his recent ‘test’ of artificial intelligence. He asked the generative AI system ChatGPT to assist with developing a lesson plan for a postgraduate teacher education course. The AI, in this case, can represent someone devoid of personal experience with the local educational context. It turned out there were quite a few limitations with the ChatGPT-produced lesson plan. In his post on LinkedIn, he wrote: 

“Are we [the author] still smarter than a large language model? When it comes to understanding how we teach, who our students are, and how we can best help them achieve the outcomes, then it seems that we most certainly are.”

When reflecting on why ChatGPT’s lesson plan was insufficient, Lodge described the AI output as being too “formulaic”, and lacking the agility and adaptation needed for success in the unique context in which execution of the lesson plan took place. ChatGPT, despite being able to draw on a broad and diverse (albeit proprietary) dataset, was unable to produce the nuanced, considered, and flexible curriculum that comes from the “creativity and authenticity” of the expert in the room. From Lodge’s post, we can see that this expertise can be drawn from the locals.

In conclusion, Lodge writes “this … raises the question of whether the relational and personal nature of teaching can be codified sufficiently to allow for an effective prompt to be written so that the resulting plan is more suitable.”  Lodge’s words can be applied to any attempt at (or demand for) educational transferability and generalisability: Can someone else’s experience (even when amalgamated from many people’s experiences) be applied to the unique circumstances present in our local learning environments?

What does this mean for evidence-based educational practice?

This blog post isn’t meant to discount the theories and conceptual models which serve as important starting points for developing and evaluating our individual teaching. The purpose of this post is to reflect on who we are defining as experts, in which situations, and to what extent we can and should value experiences from those external to our local, complex educational system in supporting our own.