Cognitive Echo: Enhancing think-aloud protocols with LLM-based simulated students

IF 8.1 1区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH
Longwei Zheng, Anna He, Changyong Qi, Haomin Zhang, Xiaoqing Gu
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引用次数: 0

Abstract

In the field of education, the think-aloud protocol is commonly used to encourage learners to articulate their thoughts during the learning process, providing observers with valuable insights into learners' cognitive processes beyond the final learning outcomes. However, the implementation of think-aloud protocols faces challenges such as task interference and limitations in completeness and authenticity of verbal reports. This study proposes a method called Cognitive Echo, which leverages large language models (LLMs) trained with simulated student experiences to enhance the completeness and authenticity of think-aloud verbalizations. LLMs have been demonstrated to simulate human-like behaviour more effectively by memorizing experiences. In this work, we introduce specific learner roles and train the LLMs to act as distinct learners. Our method involves integrating transaction data from learners' interactions with a tutoring system and the tutor's content to create interactive experiences between learners and teachers, thereby training the model to become simulated students with learning experiences. To investigate the effectiveness of this approach, we designed a test playground based on the retrospective think-aloud protocol and examined how LLM-trained simulated students improve cognitive process transparency and generalization of learning strategies. The study found that Cognitive Echo not only reveals what simulated students genuinely think about their learning experiences but also enables them to transfer their different cognitive strategies to new tasks. By training simulated students on real learning behaviour data to ensure their cognitive processes reflect authentic learner experiences, this approach will extend think-aloud protocols to more practice-oriented applications.

Practitioner notes

What is already known about this topic

  • Think-aloud protocols are widely used in educational settings to explore students' cognitive processes by asking them to verbalize their thoughts while solving problems, but they are prone to issues like task interference and incomplete data reporting.
  • Existed applications of simulating student cognition in educational research are rigid and less adaptive to individual learner characteristics.
  • Artificial intelligences, especially large language models, have shown promise in educational contexts, particularly for simulating human-like behaviours.

What this paper adds

  • This paper introduces the concept of Cognitive Echo, a method that integrates LLM-powered simulated students into think-aloud protocols, which addresses the limitations of traditional verbalization-based methods by leveraging retrospective data.
  • The study shows that LLMs, when fine-tuned with authentic learner experiences, can replicate distinct human-like cognitive processes, enabling a more complete and authentic simulation of how students think and solve problems.
  • It demonstrates how the use of LLMs to simulate students' cognitive processes can enhance the transparency and completeness of think-aloud protocols by allowing researchers to capture cognitive strategies and behaviours that would otherwise go unspoken.

Implications for practice and/or policy

  • Teacher training programmes can benefit from integrating LLM-based simulated students, which enable preservice teachers to practice responding to a wide range of cognitive processes and challenges without the constraints of real-time think-aloud tasks.
  • The Cognitive Echo method, by offering a more authentic and less intrusive way of capturing student cognition, can be applied in teacher training scenarios where simulation of real-world classroom dynamics is crucial for developing pedagogical skills.
  • The use of Cognitive Echo could help in the creation of digital twins of educational scenarios, facilitating research into complex educational issues (eg, bullying and learning disabilities) through simulations that model real-world interactions.

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Abstract Image

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认知回声:增强以法学硕士为基础的模拟学生的有声思考协议
在教育领域,有声思维通常用于鼓励学习者在学习过程中表达自己的想法,为观察者提供了对学习者认知过程的宝贵见解,而不仅仅是最终的学习结果。然而,有声思考协议的实现面临着任务干扰和口头报告完整性和真实性的限制等挑战。本研究提出了一种称为认知回声的方法,该方法利用模拟学生经历训练的大型语言模型(llm)来增强有声思维语言的完整性和真实性。法学硕士已经被证明可以通过记忆经验更有效地模拟类似人类的行为。在这项工作中,我们引入了特定的学习者角色,并训练法学硕士作为不同的学习者。我们的方法包括整合学习者与辅导系统互动的交易数据和导师的内容,在学习者和教师之间创造互动体验,从而训练模型成为具有学习体验的模拟学生。为了研究这种方法的有效性,我们设计了一个基于回溯性有声思考协议的测试场地,并研究了法学硕士训练的模拟学生如何提高认知过程的透明度和学习策略的泛化。研究发现,认知回声不仅揭示了模拟学生对自己学习经历的真实想法,还使他们能够将不同的认知策略转移到新的任务中。通过训练模拟学生真实的学习行为数据,以确保他们的认知过程反映真实的学习者体验,这种方法将把有声思维协议扩展到更多面向实践的应用中。关于这个话题我们已经知道的是,有声思考协议被广泛应用于教育环境中,通过要求学生在解决问题时用语言表达他们的想法来探索学生的认知过程,但他们容易出现任务干扰和数据报告不完整等问题。现有的模拟学生认知在教育研究中的应用比较死板,对学习者个体特征的适应性较差。人工智能,特别是大型语言模型,已经在教育环境中显示出前景,特别是在模拟类人行为方面。本文介绍了认知回声的概念,这是一种将法学硕士支持的模拟学生集成到有声思考协议中的方法,它通过利用回顾性数据解决了传统基于语言的方法的局限性。研究表明,法学硕士课程,当与真实的学习者体验进行微调时,可以复制独特的人类认知过程,使学生如何思考和解决问题的模拟更加完整和真实。它展示了如何使用法学硕士来模拟学生的认知过程,通过允许研究人员捕捉认知策略和行为,从而提高“有声思考”协议的透明度和完整性,否则这些策略和行为将无法说出口。教师培训项目可以从整合基于法学硕士的模拟学生中受益,这使职前教师能够在没有实时思考任务限制的情况下练习应对广泛的认知过程和挑战。认知回声法提供了一种更真实、更少干扰的方式来捕捉学生的认知,可以应用于教师培训场景,在这些场景中,模拟真实世界的课堂动态对培养教学技能至关重要。使用认知回声可以帮助创建教育场景的数字双胞胎,通过模拟现实世界的互动,促进对复杂教育问题(例如,欺凌和学习障碍)的研究。
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
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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