research-article

A Systematic Literature Review of Automated Feedback Generation for Programming Exercises

Authors:

Bastiaan HeerenAuthors Info & Claims

ACM Transactions on Computing Education (TOCE), Volume 19, Issue 1

Article No.: 3, Pages 1 - 43

https://doi.org/10.1145/3231711

Published: 28 September 2018 Publication History

Abstract

Formative feedback, aimed at helping students to improve their work, is an important factor in learning. Many tools that offer programming exercises provide automated feedback on student solutions. We have performed a systematic literature review to find out what kind of feedback is provided, which techniques are used to generate the feedback, how adaptable the feedback is, and how these tools are evaluated. We have designed a labelling to classify the tools, and use Narciss’ feedback content categories to classify feedback messages. We report on the results of coding a total of 101 tools. We have found that feedback mostly focuses on identifying mistakes and less on fixing problems and taking a next step. Furthermore, teachers cannot easily adapt tools to their own needs. However, the diversity of feedback types has increased over the past decades and new techniques are being applied to generate feedback that is increasingly helpful for students.

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cover image ACM Transactions on Computing Education

ACM Transactions on Computing Education Volume 19, Issue 1

March 2019

156 pages

EISSN:1946-6226

DOI:10.1145/3282284

Editor:
Chris Hundhausen
Washington State University, USA

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Published: 28 September 2018

Accepted: 01 May 2018

Revised: 01 April 2018

Received: 01 January 2018

Published in TOCE Volume 19, Issue 1

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