Levering AI to enhance students' conceptual understanding and confidence in mathematics

IF 5.1 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning Pub Date : 2024-09-13 DOI:10.1111/jcal.13065

Allan Mesa Canonigo

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引用次数: 0

Abstract

Motivation

This research investigates the transformative impact of integrating AI into mathematics education, aiming to enhance students' conceptual understanding and self-efficacy. It addresses the crucial need for innovative teaching methods in response to contemporary challenges in education and aims to fill gaps in understanding the potential drawbacks and benefits of AI implementation.

Objectives

The primary goal of this study is to investigate the effects of AI tools, such as GeoGebra and ChatGPT, on students' conceptual understanding and self-efficacy in a mathematics classroom setting, with a focus on collaborative learning, teacher-led discussions, and problem-solving.

Methods

Employing a mixed-methods approach, the research involves pre- and post-implementation surveys, supplemented by qualitative data from interviews, focus groups, and classroom observations. The study emphasises the utilisation of AI in collaborative learning environments and explores the challenges and opportunities associated with its integration.

Results and Conclusions

The study reveals a noteworthy enhancement in students' conceptual understanding and self-efficacy belief when AI tools are incorporated into mathematics education. However, it highlights concerns such as technological challenges, potential teacher replacement fears, biases in AI systems, and difficulties related to pacing and social interaction. To optimise the use of AI, the paper suggests strategies like adaptive learning platforms, real-world simulations, intelligent tutoring systems, and data-driven instruction, positioning AI as a complement rather than a substitute for traditional teaching methods. The study recommends addressing challenges through additional support resources and transparent communication, emphasising the need for a thoughtful integration of AI in education.

查看原文本刊更多论文

利用人工智能增强学生对数学概念的理解和信心

研究动机本研究探讨将人工智能融入数学教育的变革性影响，旨在增强学生对概念的理解和自我效能感。它满足了对创新教学方法的迫切需要，以应对当代教育中的挑战，并旨在填补在理解人工智能实施的潜在缺点和益处方面的空白。本研究的主要目标是调查 GeoGebra 和 ChatGPT 等人工智能工具在数学课堂环境中对学生概念理解和自我效能感的影响，重点关注协作学习、教师引导的讨论和问题解决。研究强调了人工智能在协作学习环境中的应用，并探讨了与整合人工智能相关的挑战和机遇。结果与结论研究显示，当人工智能工具被纳入数学教育时，学生的概念理解和自我效能感信念得到了显著提升。然而，研究也强调了一些令人担忧的问题，如技术挑战、潜在的教师替代恐惧、人工智能系统的偏见以及与节奏和社会互动有关的困难。为了优化人工智能的使用，论文提出了自适应学习平台、真实世界模拟、智能辅导系统和数据驱动教学等策略，将人工智能定位为传统教学方法的补充而非替代。研究建议通过额外的支持资源和透明的沟通来应对挑战，强调有必要将人工智能深思熟虑地融入教育。

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