Extending UTAUT model to examine the usages of ChatGPT among Indian students in higher education: a structural equation modelling approach

被引:0
|
作者
Jasrai, Lokesh [1 ]
机构
[1] Lovely Profess Univ, Mittal Sch Business, Phagwara, India
来源
TQM JOURNAL | 2025年
关键词
Higher education; Students; Best practice; Cost-analysis; Education and training; Innovation; ACCEPTANCE; TECHNOLOGY;
D O I
10.1108/TQM-12-2024-0498
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
PurposeThis study used extended Unified Theory of Acceptance and Use of Technology (UTAUT) model to examine the effect of personal expectancy (PE), efforts expectancy (EE), social influence (SI), facilitating conditions (FC), hedonic motivation (HM), price value (PV) and habit (H) on behavioural intention (BI) to use Chat Generative Pre-Trained Transformer (ChatGPT) in higher education for an Indian context. The study also examined moderating effects of students' self-innovativeness (SIN) and integrity (INT) on the relationship between BI and use behaviour (UB) for ChatGPT.Design/methodology/approachA sample of 311 students has been selected from Northern states of India by applying stratified proportionate random sampling method and four disciplines - engineering, business administration, science and fine arts were used as different strata in the sample selection process. Partial least squares structural equation modelling (PLS-SEM) approach has been used in data analysis to assess proposed theoretical model.FindingsThe study found PE, FC, PV and H significantly account for students' BI and actual use of ChatGPT, whereas EE, SI and HM showed a negligible impact on BI. The BI was also found non-significant in predicting the usage behaviour for ChatGPT. The moderation effects of SIN and INT of students were also found non-significant on the relationship between BI and UB.Research limitations/implicationsA limited sample size of study and its focus on Northern states of India constrain the generalizability of findings to the other parts of world.Originality/valueThe study helps to understand the nuances associated with advanced artificial intelligence (AI)-driven tool such as ChatGPT in higher education for the application of best-practices. Therefore, this study aims to bridge this gap by examining determinants of ChatGPT usage with extended version of UTAUT model in Indian context by using additional constructs such as SIN and INT.
引用
收藏
页数:19
相关论文
共 43 条
  • [21] The mediating effects of coping on the stress and health relationships among nursing students: a structural equation modelling approach
    Klainin-Yobas, Piyanee
    Keawkerd, Ornuma
    Pumpuang, Walailak
    Thunyadee, Chanya
    Thanoi, Wareerat
    He, Hong-Gu
    JOURNAL OF ADVANCED NURSING, 2014, 70 (06) : 1287 - 1298
  • [22] Association between digital literacy, internet addiction, and cyberloafing among higher education students: A structural equation modeling
    Arslantas, Tugba Kamali
    Yaylaci, Muhammed Emre
    Ozkaya, Mehmet
    E-LEARNING AND DIGITAL MEDIA, 2024, 21 (04) : 310 - 328
  • [23] Prediction model for abnormal eating behaviour among hospital nurses: A structural equation modelling approach
    Kim, Oksoo
    Jung, Heeja
    INTERNATIONAL JOURNAL OF NURSING PRACTICE, 2021, 27 (05)
  • [24] The Structural Equation Model of actual use of Cloud Learning for Higher Education students in the 21th century
    Amornkitpinyo, Thanyatorn
    Yoosomboon, Sathaporn
    Sopapradit, Sunti
    Amornkitpinyo, Pimprapa
    JOURNAL OF E-LEARNING AND KNOWLEDGE SOCIETY, 2021, 17 (01): : 72 - 80
  • [25] Validation of Internal structure of Self-Directed Learning Readiness Scale among Indian Medical Students using factor analysis and the Structural equation Modelling Approach
    Archana Prabu Kumar
    Abirami Omprakash
    Prabu Kumar Chokkalingam Mani
    Narasimman Swaminathan
    K. Maheshkumar
    K. N. Maruthy
    B. W. C. Sathiyasekaran
    P. V. Vijayaraghavan
    R Padmavathi
    BMC Medical Education, 21
  • [26] Validation of Internal structure of Self-Directed Learning Readiness Scale among Indian Medical Students using factor analysis and the Structural equation Modelling Approach
    Kumar, Archana Prabu
    Omprakash, Abirami
    Mani, Prabu Kumar Chokkalingam
    Swaminathan, Narasimman
    Maheshkumar, K.
    Maruthy, K. N.
    Sathiyasekaran, B. W. C.
    Vijayaraghavan, P. V.
    Padmavathi, R.
    BMC MEDICAL EDUCATION, 2021, 21 (01)
  • [27] Examining the predicting effect of mindfulness on psychological well-being among undergraduate students: A structural equation modelling approach
    Klainin-Yobas, Piyanee
    Ramirez, Debbie
    Fernandez, Zenaida
    Sarmiento, Jenneth
    Thanoi, Wareerat
    Ignacio, Jeanette
    Lau, Ying
    PERSONALITY AND INDIVIDUAL DIFFERENCES, 2016, 91 : 63 - 68
  • [28] Acceptance and Use of Cloud-Based Virtual Platforms by Higher Education Vocational School Students: Application of the UTAUT Model with a PLS-SEM Approach
    Sayginer, Can
    INNOEDUCA-INTERNATIONAL JOURNAL OF TECHNOLOGY AND EDUCATIONAL INNOVATION, 2023, 9 (02): : 24 - 38
  • [29] How AI Literacy Affects Students' Educational Attainment in Online Learning: Testing a Structural Equation Model in Higher Education Context
    Xiao, Jingyu
    Alibakhshi, Goudarz
    Zamanpour, Alireza
    Zarei, Mohammad Amin
    Sherafat, Shapour
    Behzadpoor, Seyyed-Fouad
    INTERNATIONAL REVIEW OF RESEARCH IN OPEN AND DISTRIBUTED LEARNING, 2024, 25 (03): : 179 - 198
  • [30] Analysis of Physical Activity on Mental Hyperactivity, Sleep Quality, and Bodily Pain in Higher Education Students-A Structural Equation Model
    Fernandez-Garcia, Ruben
    Melguizo-Ibanez, Eduardo
    Hernandez-Padilla, Jose Manuel
    Alonso-Vargas, Jose Manuel
    HEALTHCARE, 2024, 12 (18)