Optimizing Google Classroom User Behaviour: An Integrated Analysis Using TAM and TPB Models

Authors

  • Edy Suryanto Universitas Negeri Semarang, Indonesia
  • Nina Oktarina Universitas Negeri Semarang, Indonesia
  • Tusyanah Tusyanah Universitas Negeri Semarang, Indonesia

DOI:

https://doi.org/10.35445/alishlah.v15i3.2487

Keywords:

Google Classroom, Intergration Models, TAM, TPB

Abstract

Google classroom as one of the learning platforms has been popularly used. This study aims to examine the determinants of user behavior by testing perceived ease of use variables, perceived usefulness, and subjective norm as a predictor of intention and actual control as moderation of intention-to-behavior relationship. The population in this study are 108  students in vocational high school. This study uses survey techniques or saturated samples. Data collection in this study using questionnaires. The analysis method used is a structural equation model (SEM) with SmartPLS 3.0 analysis tool. The study results found that perceived ease of use, perceived usefulness, and subjective norm are predictors of behavioral intentions with a value of R2 0.783 or 78.3%. Behavior intention predicts user behavior with R2 0.647 or 64.7%. Actual control succeeded in moderating the relationship of behavior intention to and use behavior. According to the study's results, students' behavioral intention to use Google Classroom was predicted by the Perceived Ease of Use, Perception of Usefulness, and Subject Norm. Actual behavior control can strengthen student use behavior of students using Google Classroom. The students will have a strong intention to use Google Classroom when they have actual control over themselves.

References

Abdillah, W., & Hartono. (2015). Partial Least Square (PLS). Penerbit Andi.

Ajzen, I. & Fishbein, M. (1980) Understanding Attitudes and Predicting Social Behavior Englewood Cliffs. NJ: Prentice-Hall

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.

Ajzen, I., & Kruglanski, A. W. (2019). Reasoned action in the service of goal pursuit. Psychological Review, 126(5), 774-786. https://doi.org/10.1037/rev0000155

Ajzen, I. (2020). The theory of planned behavior: Frequently asked questions. Human Behavior and Emerging Technologies, 2(4), 314-324. https://doi.org/10.1002/hbe2.195

Al Kurdi, B., Alshurideh, M., & Salloum, S. A. (2020). Investigating a theoretical framework for E-learning technology acceptance. International Journal of Electrical and Computer Engineering (IJECE), 10(6), 6484. https://doi.org/10.11591/ijece.v10i6.pp6484-6496

Alim, N., Linda, W., Gunawan, F., & Saad, M. S. M. (2019). The effectiveness of Google Classroom as an instructional media: A case of state Islamic institute of Kendari, Indonesia. Humanities and Social Sciences Reviews, 7(2). https://doi.org/10.18510/hssr.2019.7227

Al-Maroof, R.S., Salloum, S.A. (2021). An Integrated Model of Continuous Intention to Use of Google Classroom. In: Al-Emran, M., Shaalan, K., Hassanien, A. (eds) Recent Advances in Intelligent Systems and Smart Applications. Studies in Systems, Decision, and Control, vol 295. Springer, Cham. https://doi.org/10.1007/978-3-030-47411-9_18

Al-Maroof, R. A., & Al-Emran, M. (2018). Students acceptance of Google Classroom: An exploratory study using PLS-SEM approach. International Journal of Emerging Technologies in Learning (iJET), 13(06), 112. https://doi.org/10.3991/ijet.v13i06.8275

Al-Rahmi, W. M., Yahaya, N., Aldraiweesh, A. A., Alamri, M. M., Aljarboa, N. A., Alturki, U., & Aljeraiwi, A. A. (2019). Integrating Technology Acceptance Model with Innovation Diffusion Theory: An Empirical Investigation on Students’ Intention to Use E-Learning Systems. IEEE Access, 7. https://doi.org/10.1109/ACCESS.2019.2899368

Assidiqi, M. H., & Sumarni, W. (2020). Pemanfaatan Platform Digital di Masa Pandemi Covid-19. Prosiding Seminar Nasional Pascasarjana.

Baber, H. (2018). Factors influencing the intentions of Non-Muslims in India to accept Islamic finance as an alternative financial system. Journal of Reviews on Global Economics, 7, 317-323. https://doi.org/10.6000/1929-7092.2018.07.27

Binyamin, S. S., Rutter, M. J., & Smith, S. (2019). Extending the technology acceptance model to understand students’ use of learning management systems in Saudi higher education. International Journal of Emerging Technologies in Learning, 14(3). https://doi.org/10.3991/ijet.v14i03.9732

Buabeng-Andoh, C. (2018). Predicting students’ intention to adopt mobile learning. Journal of Research in Innovative Teaching & Learning, 11(2). https://doi.org/10.1108/jrit-03-2017-0004

Chowdhury, F. (2020). Blended learning: How to flip the classroom at HEIs in Bangladesh? Journal of Research in Innovative Teaching & Learning, 13(2). https://doi.org/10.1108/jrit-12-2018-0030

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly: Management Information Systems, 13(3). https://doi.org/10.2307/249008

Ghozali, I. (2014). Model Persamaan Struktural Konsep dan Aplikasi dengan Program AMOS 22.0 Update Bayesian SEM (Edisi 4). Universitas Diponegoro.

Gunasinghe, A., Hamid, J. A., Khatibi, A., & Azam, S. M. F. (2020). The adequacy of UTAUT-3 in interpreting academician’s adoption to e-Learning in higher education environments. Interactive Technology and Smart Education, 17(1). https://doi.org/10.1108/ITSE-05-2019-0020

Guner, H., & Acarturk, C. (2020). The use and acceptance of ICT by senior citizens: a comparison of technology acceptance model (TAM) for elderly and young adults. Universal Access in the Information Society, 19(2). https://doi.org/10.1007/s10209-018-0642-4

Hanif, A., Jamal, F. Q., & Imran, M. (2018). Extending the technology acceptance model for the use of e-learning systems by digital learners. IEEE Access, 6. https://doi.org/10.1109/ACCESS.2018.2881384

Hudia, Z. H., Iskandar, M. Z. I. N., & Mohd, R. (2019). Determinants that Influence a consumer's intention to adopt Islamic financial products. International Journal of Innovation, Creativity and Change, 7(10), 102-124. https://ijicc.net/images/vol7iss10/71008_Hudi_2019_E_R.pdf

Jordan, M. M., & Duckett, N. D. (2018). Universities confront “tech disruptionâ€: Perceptions of student engagement online using two learning management systems. The Journal of Public and Professional Sociology, 10(1).

Kaur, J., & Bhardwaj, N. (2021). Their control will make or break the sustainable clothing deal study of the moderating impact of actual behavioral control on the purchase intention-behaviour gap for sustainable clothing in India. Australasian Accounting, Business and Finance Journal, 15(5 Special Issue). https://doi.org/10.14453/aabfj.v15i5.6

Kumar, J. A., & Bervell, B. (2019). Google Classroom for mobile learning in higher education: Modelling the initial perceptions of students. Education and Information Technologies, 24(2), 1793-1817. https://doi.org/10.1007/s10639-018-09858-z

Octaberlina, L. R., & Muslimin, A. I. (2020). EFL students' perspective towards online learning barriers and alternatives using Moodle/Google Classroom during the COVID-19 pandemic. International Journal of Higher Education, 9(6), 1. https://doi.org/10.5430/ijhe.v9n6p1

Paul, J., Modi, A., & Patel, J. (2016). Predicting green product consumption using theory of planned behavior and reasoned action. Journal of Retailing and Consumer Services, 29, 123-134. https://doi.org/10.1016/j.jretconser.2015.11.006

Pratama, A. (2021). Modification of the technology acceptance model in the use of Google Classroom in the COVID-19 era: A case studies in junior high schools. Cypriot Journal of Educational Sciences, 16(5), 2598-2608. https://doi.org/10.18844/cjes.v16i5.6336

Purwanto, P., Abdullah, I., Ghofur, A., Abdullah, S., & Elizabeth, M. Z. (2022). Adoption of Islamic microfinance in Indonesia an empirical investigation: An extension of the theory of planned behaviour. Cogent Business & Management, 9(1). https://doi.org/10.1080/23311975.2022.2087466

Rafique, H., Almagrabi, A. O., Shamim, A., Anwar, F., & Bashir, A. K. (2020). Investigating the Acceptance of Mobile Library Applications with an Extended Technology Acceptance Model (TAM). Computers and Education, 145. https://doi.org/10.1016/j.compedu.2019.103732

Rohmawati, A., Rahmawati, E., & Hidayani, S. (2022). Google Classroom for Learning Reading Comprehension: A Students’ Perception. ELITE Proceeding, 1(1), 19-24.

Salloum, S. A., & Shaalan, K. (2019). Factors Affecting Students’ Acceptance of E-Learning System in Higher Education Using UTAUT and Structural Equation Modeling Approaches. Advances in Intelligent Systems and Computing, 845. https://doi.org/10.1007/978-3-319-99010-1_43

Sitar-Taut, D. A., & Mican, D. (2021). Mobile learning acceptance and use in higher education during social distancing circumstances: an expansion and customization of UTAUT2. Online Information Review, 45(5). https://doi.org/10.1108/OIR-01-2021-0017

Susanto, E., Sasongko, R. N., Kristiawan, M., Nipriansyah, N., & Purdiyanto, P. (2021). Constraints of online learning using Google classroom during COVID-19. Education Quarterly Reviews, 4(2). https://doi.org/10.31014/aior.1993.04.02.201

Su, C. (2019). The effect of users’ behavioral intention on gamification augmented reality in stem (Gar-stem) education. Journal of Baltic Science Education, 18(3), 450-465. https://doi.org/10.33225/jbse/19.18.450

To, A. T., & Trinh, T. H. M. (2021). Understanding behavioral intention to use mobile wallets in vietnam: Extending the tam model with trust and enjoyment. Cogent Business and Management, 8(1). https://doi.org/10.1080/23311975.2021.1891661

Troise, C., O’Driscoll, A., Tani, M., & Prisco, A. (2021). Online food delivery services and behavioural intention – a test of an integrated TAM and TPB framework. British Food Journal, 123(2). https://doi.org/10.1108/BFJ-05-2020-0418

Wahyudin, A. (2015). Metodologi Penelitian: Penelitian Bisnis dan Pendidikan. UNNES PRESS.

Yeop, M. A., Yaakob, M. F. M., Wong, K. T., Don, Y., & Zain, F. M. (2019). Implementation of ICT policy (blended learning approach): Investigating factors of behavioural intention and use behaviour. International Journal of Instruction, 12(1). https://doi.org/10.29333/iji.2019.12149a

Akdim, K., Casaló, L. V., & Flavián, C. (2022). The role of utilitarian and hedonic aspects in the continuance intention to use social mobile apps. Journal of Retailing and Consumer Services, 66, 102888. https://doi.org/10.1016/j.jretconser.2021.102888

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Published

2023-09-19

How to Cite

Suryanto, E., Oktarina, N., & Tusyanah, T. (2023). Optimizing Google Classroom User Behaviour: An Integrated Analysis Using TAM and TPB Models. AL-ISHLAH: Jurnal Pendidikan, 15(3), 3441–3450. https://doi.org/10.35445/alishlah.v15i3.2487

Issue

Vol. 15 No. 3 (2023): AL-ISHLAH: JURNAL PENDIDIKAN

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