Investigating the Essential of Meaningful Automated Formative Feedback for Programming Assignments
June 21, 2019 Β· Declared Dead Β· π IEEE Symposium on Visual Languages / Human-Centric Computing Languages and Environments
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Authors
Qiang Hao, Jack P Wilson, Camille Ottaway, Naitra Iriumi, Kai Arakawa, David H Smith
arXiv ID
1906.08937
Category
cs.HC: Human-Computer Interaction
Citations
18
Venue
IEEE Symposium on Visual Languages / Human-Centric Computing Languages and Environments
Last Checked
4 months ago
Abstract
This study investigated the essential of meaningful automated feedback for programming assignments. Three different types of feedback were tested, including (a) What's wrong - what test cases were testing and which failed, (b) Gap - comparisons between expected and actual outputs, and (c) Hint - hints on how to fix problems if test cases failed. 46 students taking a CS2 participated in this study. They were divided into three groups, and the feedback configurations for each group were different: (1) Group One - What's wrong, (2) Group Two - What's wrong + Gap, (3) Group Three - What's wrong + Gap + Hint. This study found that simply knowing what failed did not help students sufficiently, and might stimulate system gaming behavior. Hints were not found to be impactful on student performance or their usage of automated feedback. Based on the findings, this study provides practical guidance on the design of automated feedback.
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