A Stumble Detection Method for Programming with Multi-modal Information

Oka, Hiroki; Ohnishi, Ayumi; Terada, Tsutomu; Tsukamoto, Masahiko

doi:10.1007/978-3-031-20436-4_16

Cited by 1 publication

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“…The detection method of getting stuck presented in this paper is the same as that proposed in our previous conference paper [ 16 ]. The result data of the experiment in Section 3 are also the same.…”

Section: Introductionmentioning

confidence: 99%

System for Detecting Learner Stuck in Programming Learning

Oka

Ohnishi

Terada

et al. 2023

Sensors

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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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Section: Introductionmentioning

confidence: 99%