Comparison of Biometric Information During Learning of Visual- and Text-Based Programming Languages

Novice programmers often start with visual-based programming languages, such as Blockly or Scratch, whereas experts tend to use text-based programming languages, such as C, C++, Java, or Python. However, a seamless transition from a visual- to a text-based language is yet to be established. Our stud...

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Vydáno v:2023 8th International STEM Education Conference (iSTEM-Ed) s. 1 - 5
Hlavní autoři: Umezawa, Katsuyuki, Nakazawa, Makoto, Hirasawa, Shigeichi
Médium: Konferenční příspěvek
Jazyk:angličtina
japonština
Vydáno: IEEE 20.09.2023
Témata:
biometric information
Biometrics (access control)
C++ languages
Java
learning analytics
Python
text-based program-ming
Training
visual-based programming
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Abstract Novice programmers often start with visual-based programming languages, such as Blockly or Scratch, whereas experts tend to use text-based programming languages, such as C, C++, Java, or Python. However, a seamless transition from a visual- to a text-based language is yet to be established. Our study proposes an approach for this transition by introducing intermediate content with features that bridge the gap between visual- and text-based languages, as demonstrated in our previous study. We also show that incorporating this intermediate content enhances understanding of the text-based language. In this study, we measure learners' biometric information during their course of learning of both visual- and text-based languages, aiming to identify any differences in the biometric information during the training process.
AbstractList Novice programmers often start with visual-based programming languages, such as Blockly or Scratch, whereas experts tend to use text-based programming languages, such as C, C++, Java, or Python. However, a seamless transition from a visual- to a text-based language is yet to be established. Our study proposes an approach for this transition by introducing intermediate content with features that bridge the gap between visual- and text-based languages, as demonstrated in our previous study. We also show that incorporating this intermediate content enhances understanding of the text-based language. In this study, we measure learners' biometric information during their course of learning of both visual- and text-based languages, aiming to identify any differences in the biometric information during the training process.
Author Nakazawa, Makoto
Umezawa, Katsuyuki
Hirasawa, Shigeichi
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  givenname: Shigeichi
  surname: Hirasawa
  fullname: Hirasawa, Shigeichi
  email: hira@waseda.jp
  organization: Waseda University,Data Science Center,Tokyo,Japan
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SubjectTerms biometric information
Biometrics (access control)
C++ languages
Java
learning analytics
Python
text-based program-ming
Training
visual-based programming
Title Comparison of Biometric Information During Learning of Visual- and Text-Based Programming Languages
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