Differential Analysis of Heart Rate, Facial Expressions and Brain Wave During Learning of Visual- and Text-Based Languages

From 2020, programming education has become compulsory in elementary schools. Visual-based programming languages are becoming popular as an introduction to programming. At universities, students learn text-based programming languages such as C and Java. Much research has been conducted on the transi...

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Vydáno v:2024 IEEE World Engineering Education Conference (EDUNINE) s. 1 - 6
Hlavní autoři: Umezawa, Katsuyuki, Koshikawa, Takumi, Nakazawa, Makoto, Hirasawa, Shigeichi
Médium: Konferenční příspěvek
Jazyk:angličtina
japonština
Vydáno: IEEE 10.03.2024
Témata:
Biometrics (access control)
Computer languages
e-Learning
EEG
Engineering education
Facial Expression Analysis
Heart rate
Java
Keyboards
Language Learning
Learning Condition
Task analysis
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Abstract From 2020, programming education has become compulsory in elementary schools. Visual-based programming languages are becoming popular as an introduction to programming. At universities, students learn text-based programming languages such as C and Java. Much research has been conducted on the transition from visual- to text-based programming languages. However, most related studies are limited to questionnaire evaluation after learning. In this study, we focus on evaluation during learning. Specifically, 18 types of biometric information (heart rate, 12 facial expressions, and 5 types of brain waves) of learners are measured during visual- and text-based programming language learning. According to the experimental results, the values of "sadness" and "brain wave representing difficulty" were higher when using a visual-based programming language than when using a text-based programming language. Furthermore, the difference was larger in the group with poor keyboard input skills. This group performed the task while feeling contempt, sadness, negative emotions, and difficulties.
AbstractList From 2020, programming education has become compulsory in elementary schools. Visual-based programming languages are becoming popular as an introduction to programming. At universities, students learn text-based programming languages such as C and Java. Much research has been conducted on the transition from visual- to text-based programming languages. However, most related studies are limited to questionnaire evaluation after learning. In this study, we focus on evaluation during learning. Specifically, 18 types of biometric information (heart rate, 12 facial expressions, and 5 types of brain waves) of learners are measured during visual- and text-based programming language learning. According to the experimental results, the values of "sadness" and "brain wave representing difficulty" were higher when using a visual-based programming language than when using a text-based programming language. Furthermore, the difference was larger in the group with poor keyboard input skills. This group performed the task while feeling contempt, sadness, negative emotions, and difficulties.
Author Nakazawa, Makoto
Umezawa, Katsuyuki
Koshikawa, Takumi
Hirasawa, Shigeichi
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  email: umezawa@info.shonan-it.ac.jp
  organization: Shonan Institute of Technology,Department of Informatics,Kanagawa,Japan
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  givenname: Takumi
  surname: Koshikawa
  fullname: Koshikawa, Takumi
  email: 19A3096@sit.shonan-it.ac.jp
  organization: Shonan Institute of Technology,Department of Information Science,Kanagawa,Japan
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  givenname: Makoto
  surname: Nakazawa
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  email: nakazawa@jc.u-aizu.ac.jp
  organization: Junior College of Aizu,Department of Industrial Information Science,Fukushima,Japan
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  givenname: Shigeichi
  surname: Hirasawa
  fullname: Hirasawa, Shigeichi
  email: hira@waseda.jp
  organization: Data Science Center, Waseda University,Tokyo,Japan
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SubjectTerms Biometrics (access control)
Computer languages
e-Learning
EEG
Engineering education
Facial Expression Analysis
Heart rate
Java
Keyboards
Language Learning
Learning Condition
Task analysis
Title Differential Analysis of Heart Rate, Facial Expressions and Brain Wave During Learning of Visual- and Text-Based Languages
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