“Can (A)I do this task?” The role of AI as a socializer of students' self-beliefs of their abilities

IF 3.8 1区心理学 Q1 PSYCHOLOGY, EDUCATIONAL

Learning and Individual Differences Pub Date : 2025-06-21 DOI:10.1016/j.lindif.2025.102731

Thorben Jansen , Jennifer Meyer , Johanna Fleckenstein , Allan Wigfield , Jens Möller

{"title":"“Can (A)I do this task?” The role of AI as a socializer of students' self-beliefs of their abilities","authors":"Thorben Jansen , Jennifer Meyer , Johanna Fleckenstein , Allan Wigfield , Jens Möller","doi":"10.1016/j.lindif.2025.102731","DOIUrl":null,"url":null,"abstract":"<div><div>Students' beliefs about their own academic abilities – their answers to the question “Can I do this task?” - are crucial to their success. Learning within AI-supported environments, alongside AI agents, influences students' beliefs about their abilities. Studies show enhancing and diminishing influences that remain unexplained by motivation theory, limiting theories' explanatory effect in AI-supported learning environments, and leaving educational technology research without a solid theoretical foundation. The following article specifies the situated expectancy-value theory (SEVT) for students' self-belief formation in the context of an AI-driven society. The expanded theory conceptualizes AI as becoming an artificial socializer, capturing the role of AI as an instrumental tool and social agents making up students' individual environments. Bridging AI and motivational research provides a framework for systematically investigating students' self-beliefs in AI-supported contexts and how educational technology can support positive self-beliefs, considering students' contexts and individual differences.</div></div>","PeriodicalId":48336,"journal":{"name":"Learning and Individual Differences","volume":"122 ","pages":"Article 102731"},"PeriodicalIF":3.8000,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Learning and Individual Differences","FirstCategoryId":"102","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1041608025001074","RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, EDUCATIONAL","Score":null,"Total":0}

引用次数: 0

Abstract

Students' beliefs about their own academic abilities – their answers to the question “Can I do this task?” - are crucial to their success. Learning within AI-supported environments, alongside AI agents, influences students' beliefs about their abilities. Studies show enhancing and diminishing influences that remain unexplained by motivation theory, limiting theories' explanatory effect in AI-supported learning environments, and leaving educational technology research without a solid theoretical foundation. The following article specifies the situated expectancy-value theory (SEVT) for students' self-belief formation in the context of an AI-driven society. The expanded theory conceptualizes AI as becoming an artificial socializer, capturing the role of AI as an instrumental tool and social agents making up students' individual environments. Bridging AI and motivational research provides a framework for systematically investigating students' self-beliefs in AI-supported contexts and how educational technology can support positive self-beliefs, considering students' contexts and individual differences.

查看原文本刊更多论文

“(A)我能完成这个任务吗？”人工智能作为学生对自己能力的自我信念的社会化者的作用

学生对自己学术能力的信念——他们对“我能完成这项任务吗？”——对他们的成功至关重要。在人工智能支持的环境中学习，以及人工智能代理，会影响学生对自己能力的看法。研究表明，动机理论无法解释的影响会增强或减弱，限制了理论在人工智能支持的学习环境中的解释效果，使教育技术研究缺乏坚实的理论基础。下面的文章详细说明了在人工智能驱动的社会背景下，学生自我信念形成的情境期望值理论（SEVT）。扩展后的理论将人工智能定义为人工社交器，捕捉了人工智能作为工具性工具和构成学生个人环境的社会代理人的角色。连接人工智能和动机研究提供了一个框架，可以系统地调查学生在人工智能支持下的自我信念，以及考虑到学生的环境和个体差异，教育技术如何支持积极的自我信念。

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分钟内获得全文求助全文

来源期刊

Learning and Individual Differences PSYCHOLOGY, EDUCATIONAL-

CiteScore

6.60

自引率

2.80%

发文量

期刊介绍： Learning and Individual Differences is a research journal devoted to publishing articles of individual differences as they relate to learning within an educational context. The Journal focuses on original empirical studies of high theoretical and methodological rigor that that make a substantial scientific contribution. Learning and Individual Differences publishes original research. Manuscripts should be no longer than 7500 words of primary text (not including tables, figures, references).