A Digital Game-Based Model for Assessing Computational Thinking Skills

Yi, Xitian; Liu, Fanhua; Zhan, Zehui

doi:10.1109/cste55932.2022.00048

Cited by 4 publications

References 14 publications

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Effect of jigsaw‐integrated task‐driven learning on students' motivation, computational thinking, collaborative skills, and programming performance in a high‐school programming course

Zhan,

Li,

2024

Comp Applic In Engineering

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Computer programming has emerged as an important field in K‐12 science, technology, engineering, and maths (STEM) education in the AI era. However, contemporary programming education is hindered by fragmented course content, high complexity, and difficulties in maintaining engagement, impeding smooth progress. More effective collaborative learning strategies need to be explored. This study constructed jigsaw‐integrated task‐driven learning (jigsaw‐TDL) in a high school Python programming course under a STEM curriculum and verified its teaching effectiveness on students’ learning motivation, computational thinking, collaborative skills, and programming performance both quantitatively and qualitatively. Nighty‐nine high school students were randomly assigned to a jigsaw‐TDL group and a general collaborative task‐driven learning group (collaborative‐TDL). During the experiment, a Python programming course was introduced over 7 weeks. Questionnaires, programming tasks, and semistructured interviews were comprehensively applied to examine students’ learning outcomes. Finally, the jigsaw‐TDL group showed significantly better performance than the collaborative‐TDL group in learning motivation, computational thinking, and collaborative skills. However, it only led to better programming performance in the less complex tasks. The majority of students held a positive attitude toward the jigsaw‐TDL model, acknowledging its benefits in group collaboration, programming knowledge acquisition, and application. This research provides empirical evidence and potential guidance for task organization and collaborative learning support in programming courses and STEM education.

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Effect of jigsaw‐integrated task‐driven learning on students' motivation, computational thinking, collaborative skills, and programming performance in a high‐school programming course

Zhan,

Li,

2024

Comp Applic In Engineering

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Exploring the relationship between learning emotion and cognitive behaviors in a digital game

Chen,

Zhan,

Chen

et al. 2024

Future in Educational Research

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Previous studies have primarily explored the learning effects of digital games on students from a macro perspective, mainly ignoring the fine‐grained dimensions of learners' emotions and cognition during gameplay. To enrich the study of learners' emotions and cognitions in the context of digital games, this paper conducts an empirical study using the self‐developed board game “Connect Four Chess” as a research vehicle. We semi‐automatically identify learners' emotional and cognitive behaviors within this game‐based educational context and explore the relationship between the two. The study demonstrates that high‐level learners maintained a high level of insightful emotion throughout the game, excelled at constructing strategic formations to control more significant chessboard areas, and preferred to reserve powerful pieces until the end to secure a winning advantage. Conversely, low‐level learners exhibit a predominant level of neutral emotion, especially during unrelated behaviors, and struggle to maintain a strategic overview, focusing instead on smaller, immediate gains, which hamper the application of deeper strategies.

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Constructing Behavioral Representation of Computational Thinking based on Event Graph: A new approach for learning analytics

Shen

Zhan

et al. 2022

Proceedings of the 6th International Conference on Education and Multimedia Technology

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A Digital Game-Based Model for Assessing Computational Thinking Skills

Cited by 4 publications

References 14 publications

Effect of jigsaw‐integrated task‐driven learning on students' motivation, computational thinking, collaborative skills, and programming performance in a high‐school programming course

Effect of jigsaw‐integrated task‐driven learning on students' motivation, computational thinking, collaborative skills, and programming performance in a high‐school programming course

Exploring the relationship between learning emotion and cognitive behaviors in a digital game

Constructing Behavioral Representation of Computational Thinking based on Event Graph: A new approach for learning analytics

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