System for Detecting Learner Stuck in Programming Learning

Getting stuck is an inevitable part of learning programming. Long-term stuck decreases the learner’s motivation and learning efficiency. The current approach to supporting learning in lectures involves teachers finding students who are getting stuck, reviewing their source code, and solving the prob...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Vol. 23; no. 12; p. 5739
Main Authors: Oka, Hiroki, Ohnishi, Ayumi, Terada, Tsutomu, Tsukamoto, Masahiko
Format: Journal Article
Language:English
Published: Switzerland MDPI AG 01.06.2023
MDPI
Subjects:
Accuracy
Biometrics
Brain research
Cognitive load
Computational linguistics
Education
Educational materials
Electroencephalography
Emotions
Eye movements
Heart beat
Heart rate
heart rate information
Humans
Language processing
Learning
Learning - physiology
machine learning
Memory
Methods
Motivation
multi-modal
Natural language interfaces
Problem solving
Programmers
programming learning
Questionnaires
Science education
sensing
Software
stuck
Students
Syntax
Teachers
sensing
programming learning
machine learning
multi-modal
heart rate information
stuck
ISSN:1424-8220, 1424-8220
Online Access:Get full text
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Summary:Getting stuck is an inevitable part of learning programming. Long-term stuck decreases the learner’s motivation and learning efficiency. The current approach to supporting learning in lectures involves teachers finding students who are getting stuck, reviewing their source code, and solving the problems. However, it is difficult for teachers to grasp every learner’s stuck situation and to distinguish stuck or deep thinking only by their source code. Teachers should advise learners only when there is no progress and they are psychologically stuck. This paper proposes a method for detecting when learners get stuck during programming by using multi-modal data, considering both their source code and psychological state measured by a heart rate sensor. The evaluation results of the proposed method show that it can detect more stuck situations than the method that uses only a single indicator. Furthermore, we implemented a system that aggregates the stuck situation detected by the proposed method and presents them to a teacher. In evaluations during the actual programming lecture, participants rated the notification timing of application as suitable and commented that the application was useful. The questionnaire survey showed that the application can detect situations where learners cannot find solutions to exercise problems or express them in programming.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s23125739