To use or not to use ChatGPT in higher education? A study of students’ acceptance and use of technology

Interactive Learning Environments, Год журнала: 2023, Номер 32(9), С. 5142 - 5155

Опубликована: Май 8, 2023

ChatGPT is an AI tool that assisted in writing, learning, solving assessments and could do so a conversational way. The purpose of the study was to develop model examined predictors adoption use among higher education students. proposed based on previous theory technology adoption. Seven were selected build predicted behavioral intention behavior ChatGPT. partial-least squares method structural equation modeling used for data analysis. found be reliable valid, results self-reported 534 students from Polish state university. Nine out ten hypotheses confirmed by results. Habit best predictor intention, followed performance expectancy hedonic motivation. dominant determinant personal innovativeness. research highlighted need further examination how tools adopted learning teaching.

Язык: Английский

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Determinants of Intention to Use ChatGPT for Educational Purposes: Findings from PLS-SEM and fsQCA

International Journal of Human-Computer Interaction, Год журнала: 2023, Номер 40(17), С. 4501 - 4520

Опубликована: Июнь 29, 2023

ChatGPT can revolutionize education by enhancing student engagement and making learning more personalized. Drawing on UTAUT2, this study investigated determinants of intention to use for educational purposes. Data were gathered from 406 Malaysian students analyzed using a hybrid approach including "partial least squares" (PLS) "fuzzy-set qualitative comparative analysis" (fsQCA). PLS showed that performance expectancy, effort hedonic motivation, value significantly influence the ChatGPT. Furthermore, we found personal innovativeness information accuracy negatively moderate associations between its determinants. While demonstrated social influence, facilitating conditions, habit do not affect use, fsQCA revealed all factors might suggested eight combinations may lead high use. The results hold various implications developers, instructors, universities provide insights accelerating adoption.

Язык: Английский

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Students’ Acceptance of ChatGPT in Higher Education: An Extended Unified Theory of Acceptance and Use of Technology

Innovative Higher Education, Год журнала: 2023, Номер 49(2), С. 223 - 245

Опубликована: Ноя. 30, 2023

Abstract AI-powered chat technology is an emerging topic worldwide, particularly in areas such as education, research, writing, publishing, and authorship. This study aims to explore the factors driving students' acceptance of ChatGPT higher education. The employs unified theory use (UTAUT2) theoretical model, with extension Personal innovativeness, verify Behavioral intention Use behavior by students. uses data from a sample 503 Polish state university PLS-SEM method utilized test model. Results indicate that Habit has most significant impact (0.339) on intention, followed Performance expectancy (0.260), Hedonic motivation (0.187). effect (0.424) behavior, (0.255) Facilitating conditions (0.188). model explains 72.8% 54.7% variance. While limited size selection, it expected be starting point for more research ChatGPT-like given this recently introduced technology.

Язык: Английский

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Modeling students’ perceptions of artificial intelligence assisted language learning

Computer Assisted Language Learning, Год журнала: 2023, Номер unknown, С. 1 - 22

Опубликована: Авг. 16, 2023

AbstractTo address the emerging trend of language learning with Artificial Intelligence (AI), this study explored junior and senior high school students' behavioral intentions to use AI in second (L2) learning, roles related technological, social, motivational factors. An eight-factor survey was constructed using a 5-point Likert scale. A total 524 valid responses were collected, including 280 from students 244 students. The reliability validity scale satisfactory. technological social factors include effort expectancy, performance influence, facilitating conditions AI-assisted (AILL), which hypothesized predict intention AILL reference Unified Theory Acceptance Use Technology (UTAUT) model. derived L2 Motivational Self System theory (i.e. experience AI, cultural interest instrumentality-promotion AI) be intermediate variables between based on extended UTAUT (UTAUT2). Therefore, combined according UTAUT2 construct proposed model study, named AILL-Motivation-UTAUT results structural equation models showed that interest, could for both students; expectancy influence only students, while not either group. predictive power (80% 74% students) research is higher than or equal (74%). In addition, found perceived by would motivation AILL. verified may inform future studies integration English as foreign learning.Keywords: intelligenceLanguage learningUTAUTMotivationMiddle Ethics approvals statementEthics approval required China.Disclosure statementNo potential conflict reported authors.Data availability statementThe datasets generated and/or analyzed during current are available corresponding author reasonable request.Additional informationFundingThis work supported Beijing Social Science Foundation (22JYA005).Notes contributorsXin AnXin PhD student School Educational Technology, Normal University. Her interests area assessment intelligent computer assisted learning.Ching Sing ChaiChing Chai professor at Chinese University Hong Kong. His areas Technological Pedagogical Content Knowledge (TPACK), teachers' beliefs, design thinking ICT.Yushun LiYushun Li director MOOCs Development Center, educational informalization, intelligence education (AIED), online learning.Ying ZhouYing Zhou an associate Education.Bingyu YangBingyu Yang master science education.

Язык: Английский

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Investigating AI-based academic support acceptance and its impact on students’ performance in Malaysian and Pakistani higher education institutions

Education and Information Technologies, Год журнала: 2024, Номер 29(14), С. 18695 - 18744

Опубликована: Март 14, 2024

Язык: Английский

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The Unified Theory of Acceptance and Use of Technology (UTAUT) in Higher Education: A Systematic Review

SAGE Open, Год журнала: 2024, Номер 14(1)

Опубликована: Янв. 1, 2024

This systematic review evaluates the application of Unified Theory Acceptance and Use Technology (UTAUT) model in higher education, analyzing 162 SSCI/SCI-E articles from 2008 to 2022. It reveals a predominant focus on student participants Asia North America. Mobile learning tools are most studied technologies. Surveys continue be top data gathering method, while structural equation modeling is preferred for analysis. The Model combined with UTAUT. UTAUT testing shows performance expectancy has strongest sway behavioral intention. Additionally, underscores nuanced variances impact factors between education general contexts. study calls future applications must promote inclusive research spanning diverse groups, mixed methodologies theoretical perspectives. comprehensive approach imperative fully understand technology adoption patterns enable context-specific integration strategies.

Язык: Английский

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Acceptance and use of ChatGPT in the academic community

Education and Information Technologies, Год журнала: 2024, Номер unknown

Опубликована: Май 18, 2024

Abstract Since OpenAI released ChatGPT, the discussion on its usage in education has been conducted by students and teachers of every level. Also, many studies have performed tool’s possibilities threats related to usage, such as incomplete or inaccurate information obtained even plagiarism. Many universities worldwide introduced specific regulations ChatGPT academic work. Furthermore, research using their attitudes towards it appeared. However, a gap exists higher teachers’ acceptance AI solutions. The goal this was explore level academics Poland, well point out factors influencing intention use tool. study motivation an ongoing mainly focusing disadvantages solutions used scientific work willingness fill showing toward AI. data collected online inviting from Polish public complete prepared survey. survey Unified Theory Acceptance Use Technology 2 (UTAUT2) model extended with Personal Innovativeness. It revealed researchers antecedents technology paper contributes theory structuring regarding application for teaching research, provides practical recommendations adoption academics.

Язык: Английский

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Could AI Ethical Anxiety, Perceived Ethical Risks and Ethical Awareness About AI Influence University Students’ Use of Generative AI Products? An Ethical Perspective

International Journal of Human-Computer Interaction, Год журнала: 2024, Номер unknown, С. 1 - 23

Опубликована: Март 8, 2024

The study aims to explore the factors that influence university students' behavioral intention (BI) and use behavior (UB) of generative AI products from an ethical perspective. Referring decision-making theory, research model extends UTAUT2 with three influencing factors: awareness (EA), perceived risks (PER), anxiety (AIEA). A sample 226 students was analysed using Partial Least Squares Structural Equation Modelling technique (PLS-SEM). results further validate effectiveness UTAUT2. Furthermore, performance expectancy, hedonistic motivation, price value, social all positively BI products, except for effort expectancy. Facilitating conditions habit show no significant impact on BI, but they can determine UB. extended perspective play roles as well. AIEA PER are not key determinants BI. However, directly inhibit From mediation analysis, although do have a direct UB, it inhibits UB indirectly through AIEA. Ethical Nevertheless, also increase PER. These findings help better accept ethically products.

Язык: Английский

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Understanding University Students’ Acceptance of ChatGPT: Insights from the UTAUT2 Model

Applied Artificial Intelligence, Год журнала: 2024, Номер 38(1)

Опубликована: Июнь 21, 2024

The current study explores the determinants of ChatGPT adoption and utilization among a sample Norwegian university students. theoretical perspective is anchored in Unified Theory Acceptance Use Technology (UTAUT2) based on previously tested model. proposed model integrates six constructs to explain Behavioral intentions actual usage patterns higher education context. analyzed responses from 104 students attending Universities West Central Norway using partial-least squares approach structural equation modeling. data showed that performance expectancy emerged as construct with biggest impact intention, followed by Habit. This contributes research factors influencing students' engagement generative AI technologies. Furthermore, it more comprehensive understanding how tools like can be integrated effectively educational contexts both learning instructors teaching.

Язык: Английский

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Face-To-Face, Online and Hybrid Education: University Students’ Opinions and Preferences

Journal of Digital Educational Technology, Год журнала: 2022, Номер 2(2), С. ep2206 - ep2206

Опубликована: Авг. 19, 2022

Although there is a growing number of studies with regard to the forced transition online education during COVID-19 pandemic, fewer students’ perceptions on different modes or comparison among these. The purpose this study was investigate university opinions and preferences regarding face-to-face, hybrid education, soon after their return traditional face-to-face classes. participants were 24 Greek students data collected via semi-structured interviews. Perceived benefits include immediacy teachers, socialization, interactions, as well active participation, while major perceived disadvantage demanding timetable. time space flexibility, followed by familiarity digital technology, negative technical problems loss practical Positive about are often linked combining education. Students’ for future highlight both Implications practices-policies, recommendations adoption hybrid-blended discussed.

Язык: Английский

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