Instructional Video and GenAI-Supported Chatbot in Digital Game-Based Learning: Influences on Science Learning, Cognitive Load and Game Behaviours

IF 4.6 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning Pub Date : 2025-07-16 DOI:10.1111/jcal.70094

Kun Huang, Ching-Huei Chen

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引用次数: 0

Abstract

Background

Digital game-based learning (DGBL) has shown promise in enhancing learning and motivation, with appropriate scaffolding playing a crucial role in facilitating student inquiries and knowledge acquisition through science games. While scaffolding is generally effective in promoting learning in DGBL, there is variability among different scaffold types, and the impact of scaffolding on cognitive load remains unclear.

Objectives

This study investigates the effects of two scaffolding tools to support secondary students' science learning in a DGBL environment: instructional videos that provide systematic and structured assistance to elucidate underlying science concepts within the game, and a chatbot providing adaptive, contextualised advice and feedback, supported by Generative Artificial Intelligence (GenAI).

Methods

A total of 160 seventh-grade students participated in the study. Using a 2 × 2 experimental design and a sequential analysis of game trace data, we explore the individual and combined effects of instructional videos and the GenAI-supported chatbot on science learning, game performance, cognitive load and game behaviours.

Results

Results indicate that instructional videos had a significant positive effect on science learning outcomes, with the two groups that had access to instructional videos significantly outperforming the other two groups without the videos, F (1, 153) = 55.64, p < 0.001, partial η² = 0.27. Additionally, a significant interaction effect was observed on extraneous cognitive load, with the lowest extraneous load reported by participants who had access to both instructional videos and the chatbot, F (1, 153) = 6.75, p = 0.01, partial η² = 0.04. Sequential analysis of game trace data revealed distinct behaviour patterns among the four treatment groups, with the group that had access to GenAI only displaying the most fragmented game inquiry behaviours.

Conclusions

This study contributes to the limited research on the use of instructional videos and GenAI chatbots to scaffold science learning in DGBL environments. The findings highlight instructional videos as a strong scaffold in DGBL. Furthermore, the combination of instructional videos and the GenAI chatbot can result in less extraneous load than the GenAI chatbot alone, while fostering more cohesive inquiry behaviours. Additionally, we underscore the significance of learners' self-regulated learning skills in fully leveraging GenAI in constructivist learning environments like DGBL.

查看原文本刊更多论文

数字游戏学习中的教学视频和基因支持的聊天机器人：对科学学习、认知负荷和游戏行为的影响

数字游戏学习（DGBL）已显示出增强学习和动机的希望，适当的框架在促进学生通过科学游戏进行探究和获取知识方面发挥着至关重要的作用。虽然支架在促进DGBL学习方面普遍有效，但不同支架类型之间存在差异，并且支架对认知负荷的影响尚不清楚。本研究调查了两种脚手架工具在DGBL环境中支持中学生科学学习的效果：教学视频提供系统和结构化的帮助，以阐明游戏中的潜在科学概念，以及由生成人工智能（GenAI）支持的聊天机器人提供自适应的、情境化的建议和反馈。方法对160名初一学生进行问卷调查。采用2 × 2实验设计和游戏追踪数据的序列分析，我们探讨了教学视频和genai支持的聊天机器人对科学学习、游戏表现、认知负荷和游戏行为的单独和联合影响。结果教学视频对学生的科学学习效果有显著的正向影响，有视频的两组学生的学习效果显著优于没有视频的两组学生，F (1,153) = 55.64, p < 0.001，偏η2 = 0.27。此外，在外部认知负荷上观察到显著的交互作用，同时访问教学视频和聊天机器人的参与者报告的外部负荷最低，F (1,153) = 6.75, p = 0.01，偏η2 = 0.04。游戏追踪数据的顺序分析揭示了四个实验组之间不同的行为模式，能够访问GenAI的那一组只显示了最零散的游戏查询行为。本研究有助于在DGBL环境中使用教学视频和GenAI聊天机器人来支持科学学习的有限研究。研究结果强调，教学视频是DGBL的有力支撑。此外，教学视频和GenAI聊天机器人的结合可以比单独的GenAI聊天机器人产生更少的外来负载，同时培养更有凝聚力的查询行为。此外，我们强调了学习者自我调节学习技能在DGBL等建构主义学习环境中充分利用GenAI的重要性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Computer Assisted Learning EDUCATION & EDUCATIONAL RESEARCH-

CiteScore

9.70

自引率

6.00%

发文量

116

期刊介绍： The Journal of Computer Assisted Learning is an international peer-reviewed journal which covers the whole range of uses of information and communication technology to support learning and knowledge exchange. It aims to provide a medium for communication among researchers as well as a channel linking researchers, practitioners, and policy makers. JCAL is also a rich source of material for master and PhD students in areas such as educational psychology, the learning sciences, instructional technology, instructional design, collaborative learning, intelligent learning systems, learning analytics, open, distance and networked learning, and educational evaluation and assessment. This is the case for formal (e.g., schools), non-formal (e.g., workplace learning) and informal learning (e.g., museums and libraries) situations and environments. Volumes often include one Special Issue which these provides readers with a broad and in-depth perspective on a specific topic. First published in 1985, JCAL continues to have the aim of making the outcomes of contemporary research and experience accessible. During this period there have been major technological advances offering new opportunities and approaches in the use of a wide range of technologies to support learning and knowledge transfer more generally. There is currently much emphasis on the use of network functionality and the challenges its appropriate uses pose to teachers/tutors working with students locally and at a distance. JCAL welcomes: -Empirical reports, single studies or programmatic series of studies on the use of computers and information technologies in learning and assessment -Critical and original meta-reviews of literature on the use of computers for learning -Empirical studies on the design and development of innovative technology-based systems for learning -Conceptual articles on issues relating to the Aims and Scope