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Structural Equation Modeling for Mobile Learning Acceptance by University Students: An Empirical Study

Author

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  • Quadri Noorulhasan Naveed

    (Department of Computer Science, College of Computer Science, King Khalid University, Abha 62529, Saudi Arabia)

  • Mohammad Mahtab Alam

    (Department of Basic Medical Science, College of Applied Medical Science, King Khalid University, Abha 62529, Saudi Arabia)

  • Nasser Tairan

    (Department of Computer Science, College of Computer Science, King Khalid University, Abha 62529, Saudi Arabia)

Abstract

Advanced mobile devices and global internet services have enhanced the usage of smartphones in the education sector and their potential for fulfilling teaching and learning objectives. The current study is an attempt to assess the factors affecting mobile learning acceptance by Saudi university students. A theoretical model of mobile learning acceptance was developed based on the technology acceptance model (TAM) and the unified theory of acceptance and use of technology (UTAUT) model. Theoretically, five independent constructs were identified as most contributory towards the use of mobile learning and tested empirically. Data were collected through an online survey and analyzed using SmartPLS. The results of the study indicate that four constructs were significantly associated with mobile learning acceptance: perceived usefulness (β = 0.085, t = 2.201, and p = 0.028), perceived ease of use (β = 0.031, t = 1.688, and p = 0.013), attitude (β = 0.100, t = 3.771, and p = 0.037), and facilitating conditions (β = 0.765, t = 4.319, and p = 0.001). On the other hand, social influence was insignificant (β = −0.061, t = 0.136, and p = 0.256) for mobile learning acceptance. The contribution of social influence towards the use of mobile learning was negative and insignificant; hence, it was neglected. Thus, finally, four constructs (perceived usefulness, perceived ease of use, attitude, and facilitating conditions) were considered as important determinants of mobile learning acceptance by university students.

Suggested Citation

  • Quadri Noorulhasan Naveed & Mohammad Mahtab Alam & Nasser Tairan, 2020. "Structural Equation Modeling for Mobile Learning Acceptance by University Students: An Empirical Study," Sustainability, MDPI, vol. 12(20), pages 1-17, October.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:20:p:8618-:d:430645
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    References listed on IDEAS

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    1. Jonathan Abramson & Maurice Dawson & Jeffery Stevens, 2015. "An Examination of the Prior Use of E-Learning Within an Extended Technology Acceptance Model and the Factors That Influence the Behavioral Intention of Users to Use M-Learning," SAGE Open, , vol. 5(4), pages 21582440156, December.
    2. Naim Ahmad & Noorulhasan Naveed Quadri & Mohamed Rafik N. Qureshi & Mohammad Mahtab Alam, 2018. "Relationship Modeling of Critical Success Factors for Enhancing Sustainability and Performance in E-Learning," Sustainability, MDPI, vol. 10(12), pages 1-16, December.
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    Cited by:

    1. Adam Malešević & Dušan Barać & Dragan Soleša & Ema Aleksić & Marijana Despotović-Zrakić, 2021. "Adopting xRM in Higher Education: E-Services Outside the Classroom," Sustainability, MDPI, vol. 13(14), pages 1-20, July.
    2. Quadri Noorulhasan Naveed & Adel Ibrahim Qahmash & Mohamed Rafik N. Qureshi & Naim Ahmad & Mohammed Aref Abdul Rasheed & Md Akhtaruzzaman, 2023. "Analyzing Critical Success Factors for Sustainable Cloud-Based Mobile Learning (CBML) in Crisp and Fuzzy Environment," Sustainability, MDPI, vol. 15(2), pages 1-19, January.
    3. Uthman Alturki & Ahmed Aldraiweesh, 2021. "Application of Learning Management System (LMS) during the COVID-19 Pandemic: A Sustainable Acceptance Model of the Expansion Technology Approach," Sustainability, MDPI, vol. 13(19), pages 1-16, October.
    4. Peijie Jiang & Tommy Tanu Wijaya & Mailizar Mailizar & Zulfah Zulfah & Astuti Astuti, 2022. "How Micro-Lectures Improve Learning Satisfaction and Achievement: A Combination of ECM and Extension of TAM Models," Mathematics, MDPI, vol. 10(19), pages 1-19, September.
    5. Tommy Tanu Wijaya & Yiming Cao & Robert Weinhandl & Eri Yusron & Zsolt Lavicza, 2022. "Applying the UTAUT Model to Understand Factors Affecting Micro-Lecture Usage by Mathematics Teachers in China," Mathematics, MDPI, vol. 10(7), pages 1-20, March.
    6. Mohammad Mahtab Alam & Naim Ahmad & Quadri Noorulhasan Naveed & Ayyub Patel & Mohammed Abohashrh & Mohammed Abdul Khaleel, 2021. "E-Learning Services to Achieve Sustainable Learning and Academic Performance: An Empirical Study," Sustainability, MDPI, vol. 13(5), pages 1-20, March.
    7. Quadri Noorulhasan Naveed & Heena Choudhary & Naim Ahmad & Jarallah Alqahtani & Adel Ibrahim Qahmash, 2023. "Mobile Learning in Higher Education: A Systematic Literature Review," Sustainability, MDPI, vol. 15(18), pages 1-22, September.
    8. Md. Zahid Alam & Syed Moudud-Ul-Huq & Md. Nazmus Sadekin & Mohamad Ghozali Hassan & Mohammad Morshedur Rahman, 2021. "Influence of Social Distancing Behavior and Cross-Cultural Motivation on Consumers’ Attitude to Using M-Payment Services," Sustainability, MDPI, vol. 13(19), pages 1-20, September.
    9. Mohammed Abdullatif Almulla & Waleed Mugahed Al-Rahmi, 2023. "Integrated Social Cognitive Theory with Learning Input Factors: The Effects of Problem-Solving Skills and Critical Thinking Skills on Learning Performance Sustainability," Sustainability, MDPI, vol. 15(5), pages 1-26, February.
    10. Ibrahim Youssef Alyoussef, 2021. "E-Learning Acceptance: The Role of Task–Technology Fit as Sustainability in Higher Education," Sustainability, MDPI, vol. 13(11), pages 1-15, June.

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