学习者生成人工智能关系的度量

IF 4.1 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Sung-Hee Jin
{"title":"学习者生成人工智能关系的度量","authors":"Sung-Hee Jin","doi":"10.1016/j.caeo.2025.100258","DOIUrl":null,"url":null,"abstract":"<div><div>As Artificial Intelligence (AI) becomes increasingly integrated into educational environments, understanding the relationship between learners and AI systems is crucial for optimizing learning outcomes. This study introduces and validates the Learner-Generative AI Relationship Scale, a novel instrument designed to measure the multifaceted nature of learner-AI relationship in educational settings. The scale was developed through a rigorous process involving literature review, expert reviews, and cognitive pre-testing. An exploratory factor analysis with 95 undergraduate students confirmed a three-factor structure: Affective Intimacy, Cognitive Competence, and Social Flow, each comprising three sub-factors. The scale demonstrated good internal consistency and construct validity. To establish concurrent and predictive validity, 75 participants completed an argumentative essay writing task using ChatGPT. Concurrent validity was established through significant correlations with measures of attitude toward AI and AI self-efficacy. Predictive validity was confirmed through regression analyses, which showed that the learner-generative AI relationship significantly predicted learning engagement, perceived cognitive effects, and perceived motivational effects in a ChatGPT-assisted argumentative writing task. This study addresses a critical gap in the literature by providing a comprehensive tool for measuring learner-AI relationships beyond mere interactions and attitudes. The learner-generative AI relationship scale offers researchers and educators a valuable instrument for understanding and improving AI-driven educational systems, potentially informing the design of more effective AI-enhanced learning experiences.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"8 ","pages":"Article 100258"},"PeriodicalIF":4.1000,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Measures of learner-generative ai relationships\",\"authors\":\"Sung-Hee Jin\",\"doi\":\"10.1016/j.caeo.2025.100258\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>As Artificial Intelligence (AI) becomes increasingly integrated into educational environments, understanding the relationship between learners and AI systems is crucial for optimizing learning outcomes. This study introduces and validates the Learner-Generative AI Relationship Scale, a novel instrument designed to measure the multifaceted nature of learner-AI relationship in educational settings. The scale was developed through a rigorous process involving literature review, expert reviews, and cognitive pre-testing. An exploratory factor analysis with 95 undergraduate students confirmed a three-factor structure: Affective Intimacy, Cognitive Competence, and Social Flow, each comprising three sub-factors. The scale demonstrated good internal consistency and construct validity. To establish concurrent and predictive validity, 75 participants completed an argumentative essay writing task using ChatGPT. Concurrent validity was established through significant correlations with measures of attitude toward AI and AI self-efficacy. Predictive validity was confirmed through regression analyses, which showed that the learner-generative AI relationship significantly predicted learning engagement, perceived cognitive effects, and perceived motivational effects in a ChatGPT-assisted argumentative writing task. This study addresses a critical gap in the literature by providing a comprehensive tool for measuring learner-AI relationships beyond mere interactions and attitudes. The learner-generative AI relationship scale offers researchers and educators a valuable instrument for understanding and improving AI-driven educational systems, potentially informing the design of more effective AI-enhanced learning experiences.</div></div>\",\"PeriodicalId\":100322,\"journal\":{\"name\":\"Computers and Education Open\",\"volume\":\"8 \",\"pages\":\"Article 100258\"},\"PeriodicalIF\":4.1000,\"publicationDate\":\"2025-05-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers and Education Open\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666557325000175\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers and Education Open","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666557325000175","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

摘要

随着人工智能(AI)越来越多地融入教育环境,理解学习者和人工智能系统之间的关系对于优化学习成果至关重要。本研究介绍并验证了学习者-生成式人工智能关系量表,这是一种旨在衡量教育环境中学习者-人工智能关系的多面性的新工具。该量表的制定经过了严格的过程,包括文献综述、专家评审和认知预测试。通过对95名大学生的探索性因子分析,确定了情感亲密、认知能力和社会流动三个因子结构,每个因子由三个子因子组成。量表具有良好的内部一致性和结构效度。为了建立并发效度和预测效度,75名参与者使用ChatGPT完成了议论文写作任务。并发效度通过与人工智能态度和人工智能自我效能的测量显着相关来建立。通过回归分析证实了预测效度,这表明学习者生成的AI关系显著预测了chatgpt辅助议论文写作任务中的学习投入、感知认知效果和感知动机效果。本研究通过提供一个全面的工具来衡量学习者与人工智能之间的关系,而不仅仅是互动和态度,从而解决了文献中的一个关键空白。学习者生成人工智能关系量表为研究人员和教育工作者提供了一个有价值的工具,用于理解和改进人工智能驱动的教育系统,可能为设计更有效的人工智能增强学习体验提供信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Measures of learner-generative ai relationships
As Artificial Intelligence (AI) becomes increasingly integrated into educational environments, understanding the relationship between learners and AI systems is crucial for optimizing learning outcomes. This study introduces and validates the Learner-Generative AI Relationship Scale, a novel instrument designed to measure the multifaceted nature of learner-AI relationship in educational settings. The scale was developed through a rigorous process involving literature review, expert reviews, and cognitive pre-testing. An exploratory factor analysis with 95 undergraduate students confirmed a three-factor structure: Affective Intimacy, Cognitive Competence, and Social Flow, each comprising three sub-factors. The scale demonstrated good internal consistency and construct validity. To establish concurrent and predictive validity, 75 participants completed an argumentative essay writing task using ChatGPT. Concurrent validity was established through significant correlations with measures of attitude toward AI and AI self-efficacy. Predictive validity was confirmed through regression analyses, which showed that the learner-generative AI relationship significantly predicted learning engagement, perceived cognitive effects, and perceived motivational effects in a ChatGPT-assisted argumentative writing task. This study addresses a critical gap in the literature by providing a comprehensive tool for measuring learner-AI relationships beyond mere interactions and attitudes. The learner-generative AI relationship scale offers researchers and educators a valuable instrument for understanding and improving AI-driven educational systems, potentially informing the design of more effective AI-enhanced learning experiences.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信