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The role of feedback and guidance as intervention methods to foster computational thinking in educational robotics learning activities for primary school
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Chevalier, Morgane; Giang, Christian; El-Hamamsy, Laila; Bonnet, Evgeniia; Papaspyros, Vaios; Pellet, Jean-Philippe; Audrin, Catherine; Romero, Margarida; Baumberger, Bernard; Mondada, Francesco
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In: http://infoscience.epfl.ch/record/291194 (2022)
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Abstract:
Computational thinking (CT) is considered an emerging competence domain linked to 21st-century competences, and educational robotics (ER) is increasingly recognised as a tool to develop CT competences. This is why researchers recommend developing intervention methods adapted to classroom practice and providing explicit guidelines to teachers on integrating ER activities. The present study thus addresses this challenge. Guidance and feedback were considered as critical intervention methods to foster CT competences in ER settings. A between-subjects experiment was conducted with 66 students aged 8 to 9 in the context of a remote collaborative robot programming mission, with four experimental conditions. A two-step strategy was employed to report students' CT competence (their performance and learning process). Firstly, the students' CT learning gains were measured through a pre-post-test design. Secondly, video analysis was used to identify the creative computational problem-solving patterns involved in the experimental condition that had the most favourable impact on the students’ CT scores. Results show that delayed feedback is an effective intervention method for CT development in ER activities. Subject to delayed feedback, students are better at formulating the robot behaviour to be programmed, and, thus, such a strategy reinforces the anticipation process underlying the CT.
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URL: https://infoscience.epfl.ch/record/291194/files/1-s2.0-S0360131522000021.pdf
http://infoscience.epfl.ch/record/291194
https://doi.org/10.1016/j.compedu.2022.104431
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Why, What and How to help each Citizen to Understand Artificial Intelligence?
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In: EISSN: 0933-1875 ; KI - Künstliche Intelligenz ; https://hal.inria.fr/hal-03024034 ; KI - Künstliche Intelligenz, Springer Nature, 2021, pp.1610-1987 (2021)
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Formalizing Problem Solving in Computational Thinking : an Ontology approach
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In: IEEE ICDL 2021 – International Conference on Development and Learning 2021 ; https://hal.inria.fr/hal-03324136 ; IEEE ICDL 2021 – International Conference on Development and Learning 2021, Aug 2021, Beijing, China (2021)
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Interdisciplinarité et usages co-créatifs du numérique en éducation
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In: L’interdisciplinarité à l’école. Succès, résistance, diversité ; https://hal.archives-ouvertes.fr/hal-02422218 ; L’interdisciplinarité à l’école. Succès, résistance, diversité, pp.257-277, 2019, 978-2-88930-288-8 ; https://www.alphil.com/index.php/l-interdisciplinarite-a-l-ecole.html (2019)
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