Learning accuracy and our judgements
Learning accuracy and our judgements

Learning accuracy and our judgements

As I have recently referenced, once through the voluminous research on Retrieval Practice and Successive Relearning, you find yourself skirting the boundaries of Cognitive Psychology and “Making Retrospective Confidence Judgments Improves Learners’ Ability to Decide What Not to Study,” Robey, Dougherty, & Buttaccio, (2017) is a key paper to read if you have an interest in either Retrieval Practice or Successive Relearning. As we move towards revision season – “What not to study” grows in importance.

Judgements of Learning

Predictions about future retrieval success, known as Judgements of Learning (JOLs), are often viewed as important for effective control over learning. There are essentially, two types of metacognitive judgements and both prospective and retrospective judgements correlate with actual performance accuracy (Chua et al., 2009) with confidence offering a “significant effect of the confidence judgement on final test performance.”

I regularly encounter JoLs references, however much less is known about how Retrospective Confidence Judgements (RCJs), evaluations of past retrieval success. I am interested in RCJs as at RememberMore, we took the decision to employ RCJs withing the adaptive Successive Relearning protocol. To trust their retrospective judgements and their honesty – showing learners both parts of the retrieval prompt pair – before seeking their RCJs.

What did we learn from Robey, Dougherty, & Buttaccio, (2017)? First – the abstract made it clear.

“…participants who made RCJs prior to their restudy decisions were more accurate at identifying items in need of being restudied, relative to participants who made JOLs. The results indicate that having participants assess their confidence in past retrieval success can nudge them toward better utilizing of valid information when deciding which items are in need of further study.”

Robey et al., (2017)

Second, in reading the paper (if I understand it correctly), I learnt that we are both wrestling with fundamentally the same question –

“What makes for the most efficient Successive Relearning protocol?”

Albeit our small team have been progressing our thinking with the input of educator and learner feedback and without the constraints of experimental design – under very different conditions.

Third – I reached the limitations of my statistical knowledge and have added “policy-capturing” methodology to a growing item list of research terms to learn more about.

Fourth, we learnt that an RCJ protocols lead to an interesting behavioural response from learners, in that it encouraged learners to think for longer about whether to restudy an item, yet fewer items were assigned for restudy.

Future thinking points

The paper also prompted thinking on the benefits and drawbacks of “retrieval fluency,” and how these may be used or mitigated. Should narrow Category or Tag selections be restricted? Should “retrieval fluency,” be inhibited?

Does the probability of accuracy at final recall function in response to the latency of prejudgment recall. In other words, do more slowly recalled items have a lower (or higher) probability of being recalled later?

Most importantly, as ever, can we use this information to improve learner outcomes whilst at the same time reducing teacher workload?

Added August 2021

“Successive relearning is a powerful learning tool that is easy to implement in real classrooms and that it confers multiple learning benefits,” Higham et al., (2021).

Robey, A. M., Dougherty, M. R., & Buttaccio, D. R. (2017). Making Retrospective Confidence Judgments Improves Learners’ Ability to Decide What Not to Study. Psychological Science, 28(11), 1683–1693.

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