Exploring undergraduates’ computational thinking and human-computer interaction patterns in generative progressive prompt-assisted programming learning
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| Publicado en: | International Journal of Educational Technology in Higher Education vol. 22, no. 1 (Dec 2025), p. 51 |
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Springer Nature B.V.
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| Acceso en línea: | Citation/Abstract Full Text Full Text - PDF |
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| 100 | 1 | |a Gong, Xin |u Capital Normal University, College of Education, Beijing, China (GRID:grid.253663.7) (ISNI:0000 0004 0368 505X) | |
| 245 | 1 | |a Exploring undergraduates’ computational thinking and human-computer interaction patterns in generative progressive prompt-assisted programming learning | |
| 260 | |b Springer Nature B.V. |c Dec 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Programming education is burgeoning, but it encounters hurdles in implementing thinking-based intelligence instruction. The emergence of generative artificial intelligence, through the utilization of prompt engineering, not only provides meticulous feedback but also significantly elevates the quality and efficiency of human-computer interaction (HCI), thereby nurturing computational thinking (CT). This study aimed to reveal the developmental characteristics of CT and the “black box” of the HCI process through learning analytics methods (i.e., microgenetic analysis, lag sequential analysis, cluster analysis, paired t-tests). 44 college students participated in progressive prompt-assisted programming learning. The results indicated that generative progressive prompts significantly improved students’ CT and its sub-dimensions (i.e., creativity, problem-solving, algorithmic thinking, critical thinking, and cooperativity). Moreover, algorithmic thinking was identified as the core skill in CT development. Additionally, regarding students’ HCI patterns, students with low-level CT focused on more superficial interaction patterns, such as guided and exploratory behaviors, while students with high-level CT concentrated on more in-depth interaction patterns, including debating and summarizing behaviors. Based on our findings, educators in programming should incorporate generative prompts and tailor strategies to accommodate diverse HCI patterns among students with varying CT levels. | |
| 653 | |a Problem solving | ||
| 653 | |a Debugging | ||
| 653 | |a Generative artificial intelligence | ||
| 653 | |a Prompt engineering | ||
| 653 | |a Cognitive ability | ||
| 653 | |a Human-computer interaction | ||
| 653 | |a Feedback | ||
| 653 | |a Cognition & reasoning | ||
| 653 | |a Students | ||
| 653 | |a Colleges & universities | ||
| 653 | |a Cluster analysis | ||
| 653 | |a Learning | ||
| 653 | |a Human-computer interface | ||
| 653 | |a Sequential analysis | ||
| 653 | |a College students | ||
| 653 | |a Programming | ||
| 653 | |a Algorithms | ||
| 653 | |a Critical thinking | ||
| 653 | |a Large language models | ||
| 653 | |a Education | ||
| 653 | |a Human technology relationship | ||
| 653 | |a Classroom communication | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Interpersonal communication | ||
| 653 | |a Teachers | ||
| 653 | |a Teaching | ||
| 653 | |a Undergraduate students | ||
| 653 | |a Tests | ||
| 653 | |a Educational programs | ||
| 653 | |a Learning Analytics | ||
| 653 | |a Educational Benefits | ||
| 653 | |a Guidance | ||
| 653 | |a Educational Resources | ||
| 653 | |a Influence of Technology | ||
| 653 | |a Acceleration (Education) | ||
| 653 | |a Computers | ||
| 653 | |a Educational Technology | ||
| 653 | |a Behavior Patterns | ||
| 653 | |a Cooperative Learning | ||
| 653 | |a Educational Change | ||
| 653 | |a Creative Activities | ||
| 653 | |a Feedback (Response) | ||
| 653 | |a Creativity | ||
| 653 | |a Language Processing | ||
| 653 | |a Engineering Education | ||
| 653 | |a Educational Environment | ||
| 653 | |a Learner Engagement | ||
| 653 | |a Constructivism (Learning) | ||
| 653 | |a Educational Needs | ||
| 653 | |a Cognitive Development | ||
| 700 | 1 | |a Xu, Weiqi |u Zhejiang University, College of Education, Hang-zhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X) | |
| 700 | 1 | |a Qiao, Ailing |u Capital Normal University, College of Education, Beijing, China (GRID:grid.253663.7) (ISNI:0000 0004 0368 505X) | |
| 773 | 0 | |t International Journal of Educational Technology in Higher Education |g vol. 22, no. 1 (Dec 2025), p. 51 | |
| 786 | 0 | |d ProQuest |t Political Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3245318634/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3245318634/fulltext/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3245318634/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |