Is it possible to identify effective teacher feedback through collective intelligence, and incentivise its adoption through different behavioural prompts?
This experiment will aim to find out whether it is possible to uncover the type of feedback from teachers that leads to the greatest improvement in students understanding and performance in maths tests. The experiment will do this by analysing data generated from teachers and pupils on the Eedi online assessment platform, including over 19,000 pieces of teacher feedback. If it is possible to identify the most effective feedback, the second part of the experiment will then test different behavioural prompts. This will generate insight on how to get teachers to adopt the most impactful feedback practices.
There is little evidence on what the most effective feedback is, yet it takes a lot of teachers’ time and is important for student learning. If successful, this experiment would reveal significant differences in the effectiveness of written teacher feedback, with some common principles underlying impactful feedback. Understanding which particular behavioural prompts encourage teachers to change their feedback practice could generate insights in how to increase feedback effectiveness and ultimately enhance student performance.
The research into behavioural prompts will help other designers understand how they might best incentivise the uptake of insights generated through collective intelligence. As a new potential application of collective intelligence in the education field, the outcomes will also continue to build the case for people’s contribution to collective intelligence gathering initiatives and inspire other new use-cases.