Facilitating Depth of Explanation: Utilising Reflective Feedback in Collaborative Learning Environments

IF 4.6 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning Pub Date : 2025-02-24 DOI:10.1111/jcal.70010

Suping Yi, Wayan Sintawati, Yibing Zhang

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引用次数: 0

Abstract

Background

Natural language processing (NLP) and machine learning technologies offer significant advantages, such as facilitating the delivery of reflective feedback in collaborative learning environments while minimising technical constraints for educators related to time and location. Recently, scholars' interest in reflective feedback has increased scientifically. However, robust empirical evidence evaluating the impacts of feedback mechanisms and innovative NLP methods on enhancing the quality of explanations in knowledge building (KB) remains limited.

Objectives

This study investigated whether reflective feedback can assist primary school students in internalising and enhancing the depth of their explanations within a KB context.

Method

Employing a design-based research methodology, this study involved 32 sixth-grade students from a primary school in Yangzhou, China, who engaged in a 15-week KB learning initiative.

Results and Conclusions

The findings indicated that (1) students achieved significant progress in developing deep explanations, marked by improvements in logicality, consistency, convergence and structure and (2) students perceived reflective feedback as a critical factor in developing robust and profound explanations and demonstrated positively to the feedback.

Implications

These findings deepened our understanding of explanatory and assessment strategies in KB and highlighted the substantial instructional, technological and practical implications of reflective feedback for educators and learners.

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促进解释的深度：在协作学习环境中利用反思性反馈

自然语言处理（NLP）和机器学习技术提供了显著的优势，例如促进在协作学习环境中提供反思性反馈，同时最大限度地减少与时间和地点相关的教育工作者的技术限制。近年来，学者们对反思性反馈的兴趣在科学上有所增加。然而，评估反馈机制和创新的自然语言处理方法对提高知识构建（KB）解释质量的影响的强有力的经验证据仍然有限。目的本研究探讨反思性反馈是否能帮助小学生内化和提高他们在知识库背景下的解释深度。方法采用基于设计的研究方法，对中国扬州某小学32名六年级学生进行为期15周的知识库学习。结果与结论研究结果表明：(1)学生在深度解释方面取得了显著进步，在逻辑性、一致性、收敛性和结构方面都有所提高；(2)学生认为反思性反馈是构建稳健、深刻的解释的关键因素，并对反馈表现出积极的态度。这些发现加深了我们对知识库的解释和评估策略的理解，并强调了反思性反馈对教育者和学习者的实质性教学、技术和实践意义。

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