Feedback and Engagement on an Introductory Programming Module

TL;DR

This study investigates how combining automated and human feedback in an introductory programming course affects student engagement and achievement, highlighting the importance of tailored feedback strategies for different student groups.

Contribution

It provides empirical evidence that a blended feedback approach enhances engagement and emphasizes the need for differentiated feedback based on student types.

Findings

Blended feedback improves student engagement.

Different feedback needs exist among student groups.

Automated and human feedback are complementary.

Abstract

We ran a study on engagement and achievement for a first year undergraduate programming module which used an online learning environment containing tasks which generate automated feedback. Students could also access human feedback from traditional labs. We gathered quantitative data on engagement and achievement which allowed us to split the cohort into 6 groups. We then ran interviews with students after the end of the module to produce qualitative data on perceptions of what feedback is, how useful it is, the uses made of it, and how it bears on engagement. A general finding was that human and automated feedback are different but complementary. However there are different feedback needs by group. Our findings imply: (1) that a blended human-automated feedback approach improves engagement; and (2) that this approach needs to be differentiated according to type of student. We give implications for the design of feedback for programming modules.