Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
12-2023
Abstract
Immediate feedback has been shown to improve student learning. In programming courses, immediate, automated feedback is typically provided in the form of pre-defined test cases run by a submission platform. While these are excellent for highlighting the presence of logical errors, they do not provide novice programmers enough scaffolding to help them identify where an error is or how to fix it. To address this, several tools have been developed that provide richer feedback in the form of program repairs. Studies of such tools, however, tend to focus more on whether correct repairs can be generated, rather than how novices are using them. In this paper, we describe our experience of using CLARA, an automated repair tool, to provide feedback to novices. First, we extended CLARA to support a larger subset of the Python language, before integrating it with the Jupyter Notebooks used for our programming exercises. Second, we devised a preliminary study in which students tackled programming problems with and without support of the tool using the ‘think aloud’ protocol. We found that novices often struggled to understand the proposed repairs, echoing the well-known challenge to understand compiler/interpreter messages. Furthermore, we found that students valued being told where a fix was needed—without necessarily the fix itself—suggesting that ‘less may be more’ from a pedagogical perspective.
Keywords
automated feedback system, program repair, learning programming, higher education, novice learners
Discipline
Educational Assessment, Evaluation, and Research | Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
2023 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE): Auckland, November 28 - December 1: Proceedings
First Page
1
Last Page
6
ISBN
9781665453318
Identifier
10.1109/TALE56641.2023.10398393
Publisher
IEEE
City or Country
Piscataway, NJ
Citation
KURNIAWAN, Oka; POSKITT, Christopher M.; HOQUE, Ismam Al; LEE, Norman Tiong Seng; JÉGOUREL, Cyrille; and SOCKALINGAM, Nachamma.
How helpful do novice programmers find the feedback of an automated repair tool?. (2023). 2023 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE): Auckland, November 28 - December 1: Proceedings. 1-6.
Available at: https://ink.library.smu.edu.sg/sis_research/8638
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/TALE56641.2023.10398393