Empowering student self-regulated learning and science education through ChatGPT: A pioneering pilot study

IF 6.7 1区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH British Journal of Educational Technology Pub Date : 2024-03-22 DOI:10.1111/bjet.13454
Davy Tsz Kit Ng, Chee Wei Tan, Jac Ka Lok Leung
{"title":"Empowering student self-regulated learning and science education through ChatGPT: A pioneering pilot study","authors":"Davy Tsz Kit Ng,&nbsp;Chee Wei Tan,&nbsp;Jac Ka Lok Leung","doi":"10.1111/bjet.13454","DOIUrl":null,"url":null,"abstract":"<div>\n \n <section>\n \n <p>In recent years, AI technologies have been developed to promote students' self-regulated learning (SRL) and proactive learning in digital learning environments. This paper discusses a comparative study between generative AI-based (SRLbot) and rule-based AI chatbots (Nemobot) in a 3-week science learning experience with 74 Secondary 4 students in Hong Kong. The experimental group used SRLbot to maintain a regular study habit and facilitate their SRL, while the control group utilized rule-based AI chatbots. Results showed that SRLbot effectively enhanced students' science knowledge, behavioural engagement and motivation. Quantile regression analysis indicated that the number of interactions significantly predicted variations in SRL. Students appreciated the personalized recommendations and flexibility of SRLbot, which adjusted responses based on their specific learning and SRL scenarios. The ChatGPT-enhanced instructional design reduced learning anxiety and promoted learning performance, motivation and sustained learning habits. Students' feedback on learning challenges, psychological support and self-regulation behaviours provided insights into their progress and experience with this technology. SRLbot's adaptability and personalized approach distinguished it from rule-based chatbots. The findings offer valuable evidence for AI developers and educators to consider generative AI settings and chatbot design, facilitating greater success in online science learning.</p>\n </section>\n \n <section>\n \n <div>\n \n <div>\n \n <h3>Practitioner notes</h3>\n <p>What is already known about this topic\n\n </p><ul>\n \n <li>AI technologies have been used to support student self-regulated learning (SRL) across subjects.</li>\n \n <li>SRL has been identified as an important aspect of student learning that can be developed through technological support.</li>\n \n <li>Generative AI technologies like ChatGPT have shown potential for enhancing student learning by providing personalized guidance and feedback.</li>\n </ul>\n <p>What this paper adds\n\n </p><ul>\n \n <li>This paper reports on a case study that specifically examines the effectiveness of ChatGPT in promoting SRL among secondary students.</li>\n \n <li>The study provides evidence that ChatGPT can enhance students' science knowledge, motivation and SRL compared to a rule-based AI chatbot.</li>\n \n <li>The study offers insights into how ChatGPT can be used as a tool to facilitate SRL and promote sustained learning habits.</li>\n </ul>\n <p>Implications for practice and/or policy\n\n </p><ul>\n \n <li>The findings of this study suggest that educators should consider the potential of ChatGPT and other generative AI technologies to support student learning and SRL.</li>\n \n <li>Educators and students should be aware of the limitations of AI technologies and ensure that they are used appropriately to generate desired responses.</li>\n \n <li>It is also important to equip teachers and students with AI competencies to enable them to use AI for learning and teaching.</li>\n </ul>\n </div>\n </div>\n </section>\n </div>","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":"55 4","pages":"1328-1353"},"PeriodicalIF":6.7000,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjet.13454","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"British Journal of Educational Technology","FirstCategoryId":"95","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/bjet.13454","RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
引用次数: 0

Abstract

In recent years, AI technologies have been developed to promote students' self-regulated learning (SRL) and proactive learning in digital learning environments. This paper discusses a comparative study between generative AI-based (SRLbot) and rule-based AI chatbots (Nemobot) in a 3-week science learning experience with 74 Secondary 4 students in Hong Kong. The experimental group used SRLbot to maintain a regular study habit and facilitate their SRL, while the control group utilized rule-based AI chatbots. Results showed that SRLbot effectively enhanced students' science knowledge, behavioural engagement and motivation. Quantile regression analysis indicated that the number of interactions significantly predicted variations in SRL. Students appreciated the personalized recommendations and flexibility of SRLbot, which adjusted responses based on their specific learning and SRL scenarios. The ChatGPT-enhanced instructional design reduced learning anxiety and promoted learning performance, motivation and sustained learning habits. Students' feedback on learning challenges, psychological support and self-regulation behaviours provided insights into their progress and experience with this technology. SRLbot's adaptability and personalized approach distinguished it from rule-based chatbots. The findings offer valuable evidence for AI developers and educators to consider generative AI settings and chatbot design, facilitating greater success in online science learning.

Practitioner notes

What is already known about this topic

  • AI technologies have been used to support student self-regulated learning (SRL) across subjects.
  • SRL has been identified as an important aspect of student learning that can be developed through technological support.
  • Generative AI technologies like ChatGPT have shown potential for enhancing student learning by providing personalized guidance and feedback.

What this paper adds

  • This paper reports on a case study that specifically examines the effectiveness of ChatGPT in promoting SRL among secondary students.
  • The study provides evidence that ChatGPT can enhance students' science knowledge, motivation and SRL compared to a rule-based AI chatbot.
  • The study offers insights into how ChatGPT can be used as a tool to facilitate SRL and promote sustained learning habits.

Implications for practice and/or policy

  • The findings of this study suggest that educators should consider the potential of ChatGPT and other generative AI technologies to support student learning and SRL.
  • Educators and students should be aware of the limitations of AI technologies and ensure that they are used appropriately to generate desired responses.
  • It is also important to equip teachers and students with AI competencies to enable them to use AI for learning and teaching.

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
通过 ChatGPT 增强学生自我调节学习和科学教育的能力:一项开创性的试点研究
近年来,人工智能技术不断发展,以促进学生在数字化学习环境中的自我调节学习(SRL)和主动学习。本文以香港 74 名中四學生為對象,在為期三星期的科學學習體驗中,比較研究了基於生成式人工智能的聊天機器人(SRLbot)和基於規則的人工智能聊天機器人(Nemobot)。实验组使用 SRLbot 保持规律的学习习惯并促进他们的自学能力,而对照组则使用基于规则的人工智能聊天机器人。结果表明,SRLbot 有效提高了学生的科学知识、行为参与度和学习动机。量子回归分析表明,互动次数能显著预测自学能力的变化。学生们对 SRLbot 的个性化建议和灵活性表示赞赏,SRLbot 可根据他们的具体学习和 SRL 情景调整回复。ChatGPT 增强型教学设计降低了学习焦虑,提高了学习成绩,激发了学习动机,培养了持久的学习习惯。学生们对学习挑战、心理支持和自我调节行为的反馈,让我们了解了他们在使用这项技术过程中的进步和体验。SRLbot 的适应性和个性化方法使其有别于基于规则的聊天机器人。研究结果为人工智能开发人员和教育工作者提供了宝贵的证据,帮助他们考虑人工智能的生成设置和聊天机器人的设计,促进在线科学学习取得更大的成功。通过提供个性化指导和反馈,像 ChatGPT 这样的生成型人工智能技术已显示出提高学生学习效果的潜力。本文的补充内容本文报告了一项案例研究,专门探讨了 ChatGPT 在促进中学生自律学习方面的有效性。本研究提供的证据表明,与基于规则的人工智能聊天机器人相比,ChatGPT 可以增强学生的科学知识、学习动机和自学能力。本研究为如何将 ChatGPT 用作促进自学能力和培养持续学习习惯的工具提供了见解。对实践和/或政策的启示本研究的结果表明,教育工作者应该考虑 ChatGPT 和其他生成式人工智能技术在支持学生学习和自学能力方面的潜力。教育者和学生应该意识到人工智能技术的局限性,并确保适当使用这些技术来生成所需的反应。同样重要的是,要让教师和学生具备人工智能能力,使他们能够使用人工智能进行学习和教学。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
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.
期刊最新文献
Issue Information A multimodal approach to support teacher, researcher and AI collaboration in STEM+C learning environments Exploring Twitter as a social learning space for education scholars: An analysis of value‐added contributions to the #TPACK network Youths' relationship with culture: Tracing sixth graders' learning through designing culturally centred multimedia projects Seeking to support preservice teachers' responsive teaching: Leveraging artificial intelligence‐supported virtual simulation
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1