TIG Recipient AY2017/2018

David Smith, Assistant Professor of Mathematics, Science Division



This TIG project sought to address some of the shortcomings of traditional peer feedback models by implementing an online and in-class peer feedback model in “Proof”. “Proof” is an MCS module pitched to second year students that serves as a gateway to higher level modules in mathematics, computer science and statistics. In this module, the potential drawbacks of peer assessment are magnified, as the likelihood of a student providing valuable feedback is low, especially towards the beginning of the module.

With support from the TIG, I implemented the following peer feedback model for the Proof module in semester 1 of academic year 2016-2017. In advance of the class, students submit their work as a LaTeX document through a Virtual Learning Environment (VLE). The
instructor pseudononymises the submissions, and distributes the submitted work as PDFs to feedback groups (randomised groups of 3-4 students). Feedback groups must arrive at a consensus on each piece of feedback before recording it, as dialogue equalizes the quality of peer feedback generated and also greatly raises the quality. The peer feedback exercise is run in class time in order to encourage students to view the exercise as a valuable learning activity. The instructor’s manages time and ensures that the feedback groups are operating collaboratively.

After the class, the instructor scans the peer feedback, matches pseudonyms to the students’ submitted work, and distributes the feedback via the VLE. Students are then required to assimilate the feedback they received by submitting a paragraph of reflection through the VLE. This is designed to enforce some engagement with the peer feedback, closing the learning cycle.




Student evaluations reveal generally enthusiastic responses to the learning activities. Students found the exercise valuable. The proposed model for collaborative peer feedback was successful in avoiding many of the most significant drawbacks of peer feedback. Increased automation will further improve the faculty experience, without affecting the student experience. Findings from this effort were presented at the International Conference on Educational Technologies in December 2017 in Sydney, Australia, with support from the TIG. A write up of this approach was published in the “Proceedings of the 2017 IADIS International Conference Educational Technologies.”