Stefan E. Huber, Kristian Kiili, Steve Nebel, Richard M. Ryan, Michael Sailer, Manuel Ninaus
{"title":"通过游戏式学习发挥大型语言模型在教育中的潜力","authors":"Stefan E. Huber, Kristian Kiili, Steve Nebel, Richard M. Ryan, Michael Sailer, Manuel Ninaus","doi":"10.1007/s10648-024-09868-z","DOIUrl":null,"url":null,"abstract":"<p>This perspective piece explores the transformative potential and associated challenges of large language models (LLMs) in education and how those challenges might be addressed utilizing playful and game-based learning. While providing many opportunities, the stochastic elements incorporated in how present LLMs process text, requires domain expertise for a critical evaluation and responsible use of the generated output. Yet, due to their low opportunity cost, LLMs in education may pose some risk of over-reliance, potentially and unintendedly limiting the development of such expertise. Education is thus faced with the challenge of preserving reliable expertise development while not losing out on emergent opportunities. To address this challenge, we first propose a playful approach focusing on skill practice and human judgment. Drawing from game-based learning research, we then go beyond this playful account by reflecting on the potential of well-designed games to foster a willingness to practice, and thus nurturing domain-specific expertise. We finally give some perspective on how a new pedagogy of learning with AI might utilize LLMs for learning by generating games and gamifying learning materials, leveraging the full potential of human-AI interaction in education.</p>","PeriodicalId":48344,"journal":{"name":"Educational Psychology Review","volume":null,"pages":null},"PeriodicalIF":10.1000,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Leveraging the Potential of Large Language Models in Education Through Playful and Game-Based Learning\",\"authors\":\"Stefan E. Huber, Kristian Kiili, Steve Nebel, Richard M. Ryan, Michael Sailer, Manuel Ninaus\",\"doi\":\"10.1007/s10648-024-09868-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This perspective piece explores the transformative potential and associated challenges of large language models (LLMs) in education and how those challenges might be addressed utilizing playful and game-based learning. While providing many opportunities, the stochastic elements incorporated in how present LLMs process text, requires domain expertise for a critical evaluation and responsible use of the generated output. Yet, due to their low opportunity cost, LLMs in education may pose some risk of over-reliance, potentially and unintendedly limiting the development of such expertise. Education is thus faced with the challenge of preserving reliable expertise development while not losing out on emergent opportunities. To address this challenge, we first propose a playful approach focusing on skill practice and human judgment. Drawing from game-based learning research, we then go beyond this playful account by reflecting on the potential of well-designed games to foster a willingness to practice, and thus nurturing domain-specific expertise. We finally give some perspective on how a new pedagogy of learning with AI might utilize LLMs for learning by generating games and gamifying learning materials, leveraging the full potential of human-AI interaction in education.</p>\",\"PeriodicalId\":48344,\"journal\":{\"name\":\"Educational Psychology Review\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":10.1000,\"publicationDate\":\"2024-02-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Educational Psychology Review\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.1007/s10648-024-09868-z\",\"RegionNum\":1,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PSYCHOLOGY, EDUCATIONAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Educational Psychology Review","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1007/s10648-024-09868-z","RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, EDUCATIONAL","Score":null,"Total":0}
Leveraging the Potential of Large Language Models in Education Through Playful and Game-Based Learning
This perspective piece explores the transformative potential and associated challenges of large language models (LLMs) in education and how those challenges might be addressed utilizing playful and game-based learning. While providing many opportunities, the stochastic elements incorporated in how present LLMs process text, requires domain expertise for a critical evaluation and responsible use of the generated output. Yet, due to their low opportunity cost, LLMs in education may pose some risk of over-reliance, potentially and unintendedly limiting the development of such expertise. Education is thus faced with the challenge of preserving reliable expertise development while not losing out on emergent opportunities. To address this challenge, we first propose a playful approach focusing on skill practice and human judgment. Drawing from game-based learning research, we then go beyond this playful account by reflecting on the potential of well-designed games to foster a willingness to practice, and thus nurturing domain-specific expertise. We finally give some perspective on how a new pedagogy of learning with AI might utilize LLMs for learning by generating games and gamifying learning materials, leveraging the full potential of human-AI interaction in education.
期刊介绍:
Educational Psychology Review aims to disseminate knowledge and promote dialogue within the field of educational psychology. It serves as a platform for the publication of various types of articles, including peer-reviewed integrative reviews, special thematic issues, reflections on previous research or new research directions, interviews, and research-based advice for practitioners. The journal caters to a diverse readership, ranging from generalists in educational psychology to experts in specific areas of the discipline. The content offers a comprehensive coverage of topics and provides in-depth information to meet the needs of both specialized researchers and practitioners.