生成人工智能支持的协作问题解决中的群体交互模式:学生与GAI聊天机器人之间交互的网络分析

IF 8.1 1区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH
Shihui Feng
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引用次数: 0

摘要

协作解决问题(CPS)是一项重要的技能,使学生能够通过小组互动共同构建知识和解决复杂问题。虽然群体互动在CPS中的重要性已得到充分认识,但尚不清楚具有高级认知支持的生成式人工智能(GAI)的出现如何改变CPS中的群体动态。本研究通过研究人工智能支持的CPS中的群体互动来弥补这一差距,重点关注表征学生社会动态的结构模式和互动内容。六组三到五名学生使用带有GPT-4.0聊天机器人的在线消息工具进行CPS活动。使用网络分析对群体互动进行建模,并将互动内容编码为社会情感、认知、元认知和协调维度。采用网络分类度量和二项检验学生与GAI聊天机器人之间的互动,我们确定了一种以GAI为中心的互动模式,在这种模式中,学生在协作解决问题的过程中与聊天机器人的互动明显多于同龄人。学生与聊天机器人的互动主要包括认知互动,也包括元认知和社会情感互动。本研究引入了新的网络方法来分析小组互动,并为GAI工具的社会影响提供了新的经验证据和理论见解,强调需要进一步研究影响协作学习中学生与GAI工具之间互动动态的因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Group interaction patterns in generative AI-supported collaborative problem solving: Network analysis of the interactions among students and a GAI chatbot

Group interaction patterns in generative AI-supported collaborative problem solving: Network analysis of the interactions among students and a GAI chatbot

Group interaction patterns in generative AI-supported collaborative problem solving: Network analysis of the interactions among students and a GAI chatbot

Group interaction patterns in generative AI-supported collaborative problem solving: Network analysis of the interactions among students and a GAI chatbot

Group interaction patterns in generative AI-supported collaborative problem solving: Network analysis of the interactions among students and a GAI chatbot

Collaborative problem solving (CPS) is an important skill enabling students to co-construct knowledge and tackle complex problems through group interactions. While the importance of group interactions in CPS is well recognized, it is unclear how the emergence of generative artificial intelligence (GAI), with advanced cognitive support, may alter group dynamics in CPS. This study bridges this gap by examining group interactions in GAI-supported CPS, focusing on the structural patterns and interaction content characterizing students' social dynamics. Six groups of three to five students used an online messaging tool with a GPT-4.0 enabled chatbot for a CPS activity. Group interactions were modelled using network analysis and interaction content was coded into socio-emotional, cognitive, metacognitive, and coordinative dimensions. Employing a network assortativity measure and a binomial test to the interactions among students and the GAI chatbot, we identified a GAI-centred interaction pattern in which students tended to interact significantly more with the chatbot than their peers in the collaborative problem-solving process. Students' interactions with the chatbot involved primarily cognitive interactions but also metacognitive and socio-emotional interactions. This study introduces novel network methods to analyse small group interactions and contributes new empirical evidence and theoretical insights into the social influence of GAI tools, emphasizing the need for further investigations on the factors influencing interaction dynamics among students and GAI tools in collaborative learning.

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来源期刊
British Journal of Educational Technology
British Journal of Educational Technology EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
15.60
自引率
4.50%
发文量
111
期刊介绍: BJET is a primary source for academics and professionals in the fields of digital educational and training technology throughout the world. The Journal is published by Wiley on behalf of The British Educational Research Association (BERA). It publishes theoretical perspectives, methodological developments and high quality empirical research that demonstrate whether and how applications of instructional/educational technology systems, networks, tools and resources lead to improvements in formal and non-formal education at all levels, from early years through to higher, technical and vocational education, professional development and corporate training.
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