Automatic detection of frustration of novice programmers from contextual and keystroke logs

Novice programmers exhibit a repertoire of affective states over time when they are learning computer programming. The modeling of frustration is important as it informs on the need for pedagogical intervention of the student who may otherwise lose confidence and interest in the learning. In this pa...

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Main Author: FWA, Hua Leong
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Language:English
Published: Institutional Knowledge at Singapore Management University 2015
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Online Access:https://ink.library.smu.edu.sg/sis_research/6909
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spelling sg-smu-ink.sis_research-79122022-02-07T02:36:02Z Automatic detection of frustration of novice programmers from contextual and keystroke logs FWA, Hua Leong Novice programmers exhibit a repertoire of affective states over time when they are learning computer programming. The modeling of frustration is important as it informs on the need for pedagogical intervention of the student who may otherwise lose confidence and interest in the learning. In this paper, contextual and keystroke features of the students within a Java tutoring system are used to detect frustration of student within a programming exercise session. As compared to psychological sensors used in other studies, the use of contextual and keystroke logs are less obtrusive and the equipment used (keyboard) is ubiquitous in most learning environment. The technique of logistic regression with lasso regularization is utilized for the modeling to prevent over-fitting. The results showed that a model that uses only contextual and keystroke features achieved a prediction accuracy level of 0.67 and a recall measure of 0.833. Thus, we conclude that it is possible to detect frustration of a student from distilling both the contextual and keystroke logs within the tutoring system with an adequate level of accuracy. 2015-07-24T07:00:00Z text https://ink.library.smu.edu.sg/sis_research/6909 info:doi/10.1109/ICCSE.2015.7250273 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University keystrokes frustration novice learning programming Graphics and Human Computer Interfaces Numerical Analysis and Scientific Computing Programming Languages and Compilers
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic keystrokes
frustration
novice
learning
programming
Graphics and Human Computer Interfaces
Numerical Analysis and Scientific Computing
Programming Languages and Compilers
spellingShingle keystrokes
frustration
novice
learning
programming
Graphics and Human Computer Interfaces
Numerical Analysis and Scientific Computing
Programming Languages and Compilers
FWA, Hua Leong
Automatic detection of frustration of novice programmers from contextual and keystroke logs
description Novice programmers exhibit a repertoire of affective states over time when they are learning computer programming. The modeling of frustration is important as it informs on the need for pedagogical intervention of the student who may otherwise lose confidence and interest in the learning. In this paper, contextual and keystroke features of the students within a Java tutoring system are used to detect frustration of student within a programming exercise session. As compared to psychological sensors used in other studies, the use of contextual and keystroke logs are less obtrusive and the equipment used (keyboard) is ubiquitous in most learning environment. The technique of logistic regression with lasso regularization is utilized for the modeling to prevent over-fitting. The results showed that a model that uses only contextual and keystroke features achieved a prediction accuracy level of 0.67 and a recall measure of 0.833. Thus, we conclude that it is possible to detect frustration of a student from distilling both the contextual and keystroke logs within the tutoring system with an adequate level of accuracy.
format text
author FWA, Hua Leong
author_facet FWA, Hua Leong
author_sort FWA, Hua Leong
title Automatic detection of frustration of novice programmers from contextual and keystroke logs
title_short Automatic detection of frustration of novice programmers from contextual and keystroke logs
title_full Automatic detection of frustration of novice programmers from contextual and keystroke logs
title_fullStr Automatic detection of frustration of novice programmers from contextual and keystroke logs
title_full_unstemmed Automatic detection of frustration of novice programmers from contextual and keystroke logs
title_sort automatic detection of frustration of novice programmers from contextual and keystroke logs
publisher Institutional Knowledge at Singapore Management University
publishDate 2015
url https://ink.library.smu.edu.sg/sis_research/6909
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