Ahmed Lachheb , Javier Leung , Victoria Abramenka-Lachheb , Rajagopal Sankaranarayanan
{"title":"高等教育中的人工智能:文献计量学分析、综合和研究批判","authors":"Ahmed Lachheb , Javier Leung , Victoria Abramenka-Lachheb , Rajagopal Sankaranarayanan","doi":"10.1016/j.iheduc.2025.101021","DOIUrl":null,"url":null,"abstract":"<div><div>To better characterize and understand AI in higher education and its role in relation to educational disparities and inclusivity, this paper presents a comprehensive bibliometric assessment of research on AI in higher education. Using quantitative topic modeling and qualitative analysis methods, this study describes: (1) the research landscape of AI in higher education and (2) the common topics of AI in higher education research, including topics related to inclusive education. Based on these descriptions, this study offers a synthesis and critique of research on AI in higher education on the following issues: (a) the use of AI to address educational disparities and foster inclusivity, (b) the ethics of AI-powered large language learning models and translation tools, and (c) AI literacy. The findings of this study call on higher education scholars/researchers to reaffirm higher education research and educational mission, and the standards of rigorous research to lead the knowledge on AI.</div></div>","PeriodicalId":48186,"journal":{"name":"Internet and Higher Education","volume":"67 ","pages":"Article 101021"},"PeriodicalIF":6.8000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"AI in higher education: A bibliometric analysis, synthesis, and a critique of research\",\"authors\":\"Ahmed Lachheb , Javier Leung , Victoria Abramenka-Lachheb , Rajagopal Sankaranarayanan\",\"doi\":\"10.1016/j.iheduc.2025.101021\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>To better characterize and understand AI in higher education and its role in relation to educational disparities and inclusivity, this paper presents a comprehensive bibliometric assessment of research on AI in higher education. Using quantitative topic modeling and qualitative analysis methods, this study describes: (1) the research landscape of AI in higher education and (2) the common topics of AI in higher education research, including topics related to inclusive education. Based on these descriptions, this study offers a synthesis and critique of research on AI in higher education on the following issues: (a) the use of AI to address educational disparities and foster inclusivity, (b) the ethics of AI-powered large language learning models and translation tools, and (c) AI literacy. The findings of this study call on higher education scholars/researchers to reaffirm higher education research and educational mission, and the standards of rigorous research to lead the knowledge on AI.</div></div>\",\"PeriodicalId\":48186,\"journal\":{\"name\":\"Internet and Higher Education\",\"volume\":\"67 \",\"pages\":\"Article 101021\"},\"PeriodicalIF\":6.8000,\"publicationDate\":\"2025-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Internet and Higher Education\",\"FirstCategoryId\":\"95\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1096751625000302\",\"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}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Internet and Higher Education","FirstCategoryId":"95","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1096751625000302","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}
AI in higher education: A bibliometric analysis, synthesis, and a critique of research
To better characterize and understand AI in higher education and its role in relation to educational disparities and inclusivity, this paper presents a comprehensive bibliometric assessment of research on AI in higher education. Using quantitative topic modeling and qualitative analysis methods, this study describes: (1) the research landscape of AI in higher education and (2) the common topics of AI in higher education research, including topics related to inclusive education. Based on these descriptions, this study offers a synthesis and critique of research on AI in higher education on the following issues: (a) the use of AI to address educational disparities and foster inclusivity, (b) the ethics of AI-powered large language learning models and translation tools, and (c) AI literacy. The findings of this study call on higher education scholars/researchers to reaffirm higher education research and educational mission, and the standards of rigorous research to lead the knowledge on AI.
期刊介绍:
The Internet and Higher Education is a quarterly peer-reviewed journal focused on contemporary issues and future trends in online learning, teaching, and administration within post-secondary education. It welcomes contributions from diverse academic disciplines worldwide and provides a platform for theory papers, research studies, critical essays, editorials, reviews, case studies, and social commentary.