Tracking Students' Cognitive Processes During Program Debugging-An Eye-Movement Approach

This study explores students' cognitive processes while debugging programs by using an eye tracker. Students' eye movements during debugging were recorded by an eye tracker to investigate whether and how high- and low-performance students act differently during debugging. Thirty-eight comp...

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Bibliographic Details
Published in:IEEE transactions on education Vol. 59; no. 3; pp. 175 - 186
Main Authors: Lin, Yu-Tzu, Wu, Cheng-Chih, Hou, Ting-Yun, Lin, Yu-Chih, Yang, Fang-Ying, Chang, Chia-Hu
Format: Journal Article
Language:English
Published: New York IEEE 01.08.2016
Institute of Electrical and Electronics Engineers, Inc
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
C (programming language)
Cognition
Cognition analysis
Cognitive Processes
Computer bugs
Computer Science Education
Computer Software
Debugging
Eye Movements
eye-movement analysis
Eyes
Foreign Countries
Logic
Logical Thinking
Majors (Students)
Manuals
program debugging
Programming
programming instruction
Programming Languages
Programming profession
Protocol Analysis
Sequential analysis
Sequential Learning
Strategy
Students
Tracking
Troubleshooting
Undergraduate Students
Taiwan
ISSN:0018-9359, 1557-9638
Online Access:Get full text
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Summary:This study explores students' cognitive processes while debugging programs by using an eye tracker. Students' eye movements during debugging were recorded by an eye tracker to investigate whether and how high- and low-performance students act differently during debugging. Thirty-eight computer science undergraduates were asked to debug two C programs. The path of students' gaze while following program codes was subjected to sequential analysis to reveal significant sequences of areas examined. These significant gaze path sequences were then compared to those of students with different debugging performances. The results show that, when debugging, high-performance students traced programs in a more logical manner, whereas low-performance students tended to stick to a line-by-line sequence and were unable to quickly derive the program's higher-level logic. Low-performance students also often jumped directly to certain suspected statements to find bugs, without following the program's logic. They also often needed to trace back to prior statements to recall information, and spent more time on manual computation. Based on the research results, adaptive instructional strategies and materials can be developed for students of different performance levels, to improve associated cognitive activities during debugging, which can foster learning during debugging and programming.
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ISSN:0018-9359
1557-9638
DOI:10.1109/TE.2015.2487341