{"title":"Google or ChatGPT: Who is the better helper for university students","authors":"Mengmeng Zhang, Xiantong Yang","doi":"10.1007/s10639-024-13002-5","DOIUrl":null,"url":null,"abstract":"<p>Using information technology tools for academic help-seeking among college students has become a popular trend. In the evolutionary process between Generative Artificial Intelligence (GenAI) and traditional search engines, when students face academic challenges, do they tend to prefer ChatGPT, or are they more inclined to utilize Google? And what are the key factors influencing learners’ preference to use ChatGPT for academic help-seeking? These relevant questions merit attention. The study employed a mixed-method research design to investigate university students’ online academic help-seeking preferences. The results indicated that students tend to prefer using ChatGPT to seek academic assistance, reflecting the potential popularity of GenAI in the educational field. Additionally, in comparing seven machine learning algorithms, the Random Forest and LightGBM algorithms exhibited superior performance. These two algorithms were employed to evaluate the predictive capability of 18 potential factors. It was found that ChatGPT fluency, ChatGPT distortions, and age were the core factors influencing how university students seek academic help. Overall, this study underscores that educators should prioritize the cultivation of students’ critical thinking skills, while technical personnel should enhance the fluency and reliability of ChatGPT and Google searches, and explore the integration of chat and search functions to achieve optimal balance.</p>","PeriodicalId":51494,"journal":{"name":"Education and Information Technologies","volume":"58 1","pages":""},"PeriodicalIF":4.8000,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Education and Information Technologies","FirstCategoryId":"95","ListUrlMain":"https://doi.org/10.1007/s10639-024-13002-5","RegionNum":2,"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
Using information technology tools for academic help-seeking among college students has become a popular trend. In the evolutionary process between Generative Artificial Intelligence (GenAI) and traditional search engines, when students face academic challenges, do they tend to prefer ChatGPT, or are they more inclined to utilize Google? And what are the key factors influencing learners’ preference to use ChatGPT for academic help-seeking? These relevant questions merit attention. The study employed a mixed-method research design to investigate university students’ online academic help-seeking preferences. The results indicated that students tend to prefer using ChatGPT to seek academic assistance, reflecting the potential popularity of GenAI in the educational field. Additionally, in comparing seven machine learning algorithms, the Random Forest and LightGBM algorithms exhibited superior performance. These two algorithms were employed to evaluate the predictive capability of 18 potential factors. It was found that ChatGPT fluency, ChatGPT distortions, and age were the core factors influencing how university students seek academic help. Overall, this study underscores that educators should prioritize the cultivation of students’ critical thinking skills, while technical personnel should enhance the fluency and reliability of ChatGPT and Google searches, and explore the integration of chat and search functions to achieve optimal balance.
期刊介绍：
The Journal of Education and Information Technologies (EAIT) is a platform for the range of debates and issues in the field of Computing Education as well as the many uses of information and communication technology (ICT) across many educational subjects and sectors. It probes the use of computing to improve education and learning in a variety of settings, platforms and environments.
The journal aims to provide perspectives at all levels, from the micro level of specific pedagogical approaches in Computing Education and applications or instances of use in classrooms, to macro concerns of national policies and major projects; from pre-school classes to adults in tertiary institutions; from teachers and administrators to researchers and designers; from institutions to online and lifelong learning. The journal is embedded in the research and practice of professionals within the contemporary global context and its breadth and scope encourage debate on fundamental issues at all levels and from different research paradigms and learning theories. The journal does not proselytize on behalf of the technologies (whether they be mobile, desktop, interactive, virtual, games-based or learning management systems) but rather provokes debate on all the complex relationships within and between computing and education, whether they are in informal or formal settings. It probes state of the art technologies in Computing Education and it also considers the design and evaluation of digital educational artefacts. The journal aims to maintain and expand its international standing by careful selection on merit of the papers submitted, thus providing a credible ongoing forum for debate and scholarly discourse. Special Issues are occasionally published to cover particular issues in depth. EAIT invites readers to submit papers that draw inferences, probe theory and create new knowledge that informs practice, policy and scholarship. Readers are also invited to comment and reflect upon the argument and opinions published. EAIT is the official journal of the Technical Committee on Education of the International Federation for Information Processing (IFIP) in partnership with UNESCO.
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