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Learning Performance of Different Genders’ Computational Thinking

Author

Listed:
  • Ting-Chia Hsu

    (Department of Technology Application and Human Resource Development, National Taiwan Normal University, Taipei City 10610, Taiwan)

  • Ching Chang

    (Department of Technology Application and Human Resource Development, National Taiwan Normal University, Taipei City 10610, Taiwan)

  • Lung-Hsiang Wong

    (National Institute of Education, Nanyang Technological University, Singapore 637616, Singapore)

  • Guat Poh Aw

    (National Institute of Education, Nanyang Technological University, Singapore 637616, Singapore)

Abstract

While the role of computational thinking (CT) has been widely reported in technology applications and further integrated into interdisciplinary learning, the integration of pedagogy-supported interdisciplinary activities for the empowerment of girls’ learning must not solely emphasise CT problem-solving skills. Rather, it must scaffold them with interactive learning that supports their characteristics while catering to gender equality. In this study, a gender-balanced interdisciplinary activity, integrating CT with Mandarin learning (ML), was designed for an elementary school in the Mandarin as a Second Language learning context using Social Robots (SRs). It sought to verify the results of the proposed method along with focused activities and interaction in an SR-integrated activity on the CT abilities and target-language learning of young learners. A total of 46 Grade 5 students, 26 boys and 20 girls, participated in the experiment. The study used a quasi-experimental method by examining the result of pre- and post-tests on language acquisition, programming self-efficacy, the educational robot attitude, and learning perceptions in the activity. The results indicated that there were no gender differences in terms of ML, self-efficacy in programming, or attitudes toward using SRs in the SR-integrated interdisciplinary activities. However, the boys and girls had different perceptions of learning. Suggestions for conducting SR-integrated interdisciplinary learning are given, along with pedagogical implications for the further promotion of women in technology.

Suggested Citation

  • Ting-Chia Hsu & Ching Chang & Lung-Hsiang Wong & Guat Poh Aw, 2022. "Learning Performance of Different Genders’ Computational Thinking," Sustainability, MDPI, vol. 14(24), pages 1-16, December.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:24:p:16514-:d:998659
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    References listed on IDEAS

    as
    1. Vladimiras Dolgopolovas & Valentina Dagiene, 2021. "On the Future of Computational Thinking Education: Moving beyond the Digital Agenda, a Discourse Analysis Perspective," Sustainability, MDPI, vol. 13(24), pages 1-21, December.
    2. Ting-Chia Hsu & Hal Abelson & Natalie Lao & Shih-Chu Chen, 2021. "Is It Possible for Young Students to Learn the AI-STEAM Application with Experiential Learning?," Sustainability, MDPI, vol. 13(19), pages 1-15, October.
    3. Rustam Shadiev & Mengke Yang, 2020. "Review of Studies on Technology-Enhanced Language Learning and Teaching," Sustainability, MDPI, vol. 12(2), pages 1-22, January.
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    Cited by:

    1. Ronald Paucar-Curasma & Liszeth Paola Cerna-Ruiz & Claudia Acra-Despradel & Klinge Orlando Villalba-Condori & Luis Alberto Massa-Palacios & Andrés Olivera-Chura & Isabel Esteban-Robladillo, 2023. "Development of Computational Thinking through STEM Activities for the Promotion of Gender Equality," Sustainability, MDPI, vol. 15(16), pages 1-19, August.

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