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An Integrated Model to Predict Students' Online Learning Behavior in Emerging Economies: A Hybrid SEM-ANN Approach

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Title: An Integrated Model to Predict Students' Online Learning Behavior in Emerging Economies: A Hybrid SEM-ANN Approach
Language: English
Authors: Smriti Mathur, Alok Tewari, Sushant Vishnoi, Vaishali Agarwal
Source: Journal of International Education in Business. p102-126 18(1):102-126.
Availability: Emerald Publishing Limited. Howard House, Wagon Lane, Bingley, West Yorkshire, BD16 1WA, UK. Tel: +44-1274-777700; Fax: +44-1274-785201; e-mail: emerald@emeraldinsight.com; Web site: http://www.emerald.com/insight
Peer Reviewed: Y
Page Count: 25
Publication Date: 2025
Document Type: Journal Articles
DOI: 10.1108/JIEB-01-2024-0004
ISSN: 2046-469X
1836-3261
Abstract: Purpose The online learning environment is a function of dynamic market forces constantly restructuring the e-learning landscape's complete ecosystemcape. This study aims to propose an e-learning framework by integrating the Technology Acceptance Model (TAM) and Theory of Planned Behaviour (TPB) to predict students' Online Learning Readiness and Behaviour. Design/methodology/approach A structured questionnaire was used to collect data from 406 students through a survey. The data were analysed using two-stage structural equation modelling and artificial neural network (ANN). Findings The study's results revealed that perceived ubiquity (PUB) positively influences perceived ease of use, usefulness and attitude. Similarly, perceived mobility significantly influences perceived ease of use and attitude. Furthermore, attitude, subjective norms, perceived behavioural control and perceived usefulness significantly influence readiness to learn online, which further influences students' online learning behaviour. The root-mean-square error (RMSE) values obtained from the ANN analysis indicate the models' predictive solid accuracy. Originality/value The study contributes to the existing literature by proposing an Online Learning Behaviour Model by integrating the TAM and the TPB frameworks in association with two additional constructs, PUB and Perceived Mobility. Secondly, this study proposes a unique triangulation framework of recommendations for learners, educators and policymakers.
Abstractor: As Provided
Entry Date: 2025
Accession Number: TJ1023506
Database: ERIC
FullText Text:
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  Data: An Integrated Model to Predict Students' Online Learning Behavior in Emerging Economies: A Hybrid SEM-ANN Approach
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  Data: Emerald Publishing Limited. Howard House, Wagon Lane, Bingley, West Yorkshire, BD16 1WA, UK. Tel: +44-1274-777700; Fax: +44-1274-785201; e-mail: emerald@emeraldinsight.com; Web site: http://www.emerald.com/insight
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  Data: Purpose The online learning environment is a function of dynamic market forces constantly restructuring the e-learning landscape's complete ecosystemcape. This study aims to propose an e-learning framework by integrating the Technology Acceptance Model (TAM) and Theory of Planned Behaviour (TPB) to predict students' Online Learning Readiness and Behaviour. Design/methodology/approach A structured questionnaire was used to collect data from 406 students through a survey. The data were analysed using two-stage structural equation modelling and artificial neural network (ANN). Findings The study's results revealed that perceived ubiquity (PUB) positively influences perceived ease of use, usefulness and attitude. Similarly, perceived mobility significantly influences perceived ease of use and attitude. Furthermore, attitude, subjective norms, perceived behavioural control and perceived usefulness significantly influence readiness to learn online, which further influences students' online learning behaviour. The root-mean-square error (RMSE) values obtained from the ANN analysis indicate the models' predictive solid accuracy. Originality/value The study contributes to the existing literature by proposing an Online Learning Behaviour Model by integrating the TAM and the TPB frameworks in association with two additional constructs, PUB and Perceived Mobility. Secondly, this study proposes a unique triangulation framework of recommendations for learners, educators and policymakers.
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