We’ve heard a lot about feedback being important, but so often we’re basing assumptions on qualitative responses from a few enthusiastic learners. What about in a class of 600? Do the numbers stack up? Further, feedback takes many forms – how do we know which approach works best? And how can we teach a large cohort of teaching associates and students to give good feedback?

Testing the evidence

A team of us (Simon Knight, Andy Leigh, Yvonne Davila, Leigh Martin, Dan Krix, and Alexandra Thompson) set about exploring the data from an innovative benchmarking task, run in a large (~500 student) first year undergraduate life sciences subject: Biocomplexity. You can check out the slides below (presented at the Teaching and Learning Forum), or read the paper online:

Knight, S., Leigh, A., Davila, Y.C., Martin, L.J., & Krix, D.W. (forthcoming). Calibrating Assessment Literacy Through Benchmarking Tasks. Assessment & Evaluation in Higher Education.

View the slide show here:

In this subject, students develop both their evolutionary biology knowledge, and their academic and communication skills within that context. To support these students’ understanding of their assessment criteria, they: (1) complete a benchmarking task, in which they use SPARKPlus to assess three exemplars, subsequently receiving feedback on their accuracy and viewing all other feedback given including the instructors; and (2) complete a self-assessment for their own assignment, which follows the same criteria as those assessed in the benchmarking.


Benchmarking is intended to, (1) engage students with the assessment criteria and their application; (2) critically expose students to exemplars of varying quality, and the evaluation of these exemplars; and (3) provide diagnostic information to the students and teaching team regarding the calibration of their evaluative judgement against the assessment criteria.

Data from 2012-15 of this innovation was analysed to investigate the relationship between accuracy of student-assessments and learning outcomes, and to understand the features of quality feedback in these tasks. Analysis indicates that:

  • students who complete the benchmarking task perform better
  • that students who are more accurate self-assessors perform better
  • That students who are more accurate in the benchmarking task are also more accurate in the self-assessment task
  • The students are overwhelmingly positive about the task, and are able to articulate its key intended learning outcomes

Feature image by José Alejandro Cuffia.

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