Adopsi Blended Learning untuk Mahasiswa Perguruan Tinggi dengan Menggunakan Pendekatan Extended UTAUT

Achmad Munsharif; Edwin Pramana; Lukman Zaman

doi:10.21107/rekayasa.v17i1.25869

Adopsi Blended Learning untuk Mahasiswa Perguruan Tinggi dengan Menggunakan Pendekatan Extended UTAUT

Achmad Munsharif, Edwin Pramana, Lukman Zaman

Abstract

This research aims to determine the factors that influence the understanding of students' intentions in higher education in using blended learning and determine the relationship between factors in the theoretical model. This research was conducted because there is still a lack of research in the world that discusses the application of blended learning in higher education in developing countries such as Indonesia. Blended learning in higher education during the Covid-19 pandemic is still needed today because educational institutions have limited space to accommodate students and to follow technological development trends and utilize them in the world of education. Questionnaires distributed via Google Form were used to collect data. The sample was 541 blended learning users from various universities in Indonesia. All variables from the theoretical model are measured using existing scales. Structural Equation Model (SEM) is used to analyze the theoretical model. SPSS and Amos are used as analysis support software. This research contributes to the theoretical understanding of Blended Learning adoption as well as practices and guidelines for higher education institutions to successfully implement Blended Learning in their institutions. Of the eight initial hypotheses, there are seven hypotheses that are very significant. The three factors with the largest magnitude are effort expectancy, performance expectancy and system functionality. Effort expectancy is the most influential factor in implementing blended learning in higher education institutions.

Keywords

blended learning, adopted technology, structural equation modelling

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References

A. Bandura, “Self-Efficacy: Toward a Unifying Theory of BehavioralChange*,” Pergamon Press Ltd, 1978. Amira Natasha Amiruddin, A. Huzaim (2022) “Challenges and Benefits of Blended Learning on Tertiary Education ESL Classrooms: A Literature Review”, Creative Education, 13, 3715-3730. doi: 10.4236/ce.2022.1311235

Andrina Granic (́2023), “Technology Acceptance and Adoption in Education”, Handbook of Open, Distance and Digital Education, 2023 springer.

Butler-Pascoe, M. E., & Wiburg, K. M. (2003). “Technology and Teaching English Language Learners. Pearson College Division”, Society forInformation Technology & Teacher Education International Conference .

Brown, S. A., and Venkatesh, V. (2005) “Model of adoption of technology in households: A baseline model test and extension incorporating household life cycle”, Management Information Systems Research Center, University of Minnesota Vol. 29, No. 3 (Sep., 2005), pp. 399-426

D. George and P. Mallery(2003), SPSS for windows step by step: A simple guideand reference. 11.0 update. . Boston: Allyn and Bacon. (pp.68-73). Atlantis Press. https://doi.org/10.2991/assehr.k.191217.012

Georgios Zacharis,Kleopatra Nikolopoulou(2022), “Factors predicting University students’ behavioral intention to use eLearning platforms in the post-pandemic normal: an UTAUT2 approach with ‘Learning Value’”, Education and Information Technologies volume 27, pages12065–12082 (2022).

Jameson Goto, Anzanilufuno Munyai (2022), “The Acceptance and Use of Online Learning by Law Students in a South African University: An Application of the UTAUT2 Model”, AJIS Vol. 14 Iss. 1 (2022).

Heather Staker and Michael B. Horn. (2012). “Classifying K-12 Blended Learning”. InnoSight Institute.

Khanh Ngo Nhu Tran (2016) “The Adoption of Blended E-learning Technology in Vietnam using a Revision of the Technology Acceptance Model”, Journal of Information Technology Education: Research Volume 15, 2016

Kim, S. S., Malhotra, N. K., and Narasimhan, S. (2005). “TwoCompeting Perspectives on Automatic Use: A Theoretical and Empirical Comparison,” Information Systems Research (16:4), pp. 418-432.

Lee, H., Cho, H. J., Xu, W., and Fairhurst, A. (2010). “The Influenceof Consumer Traits and Demographics on Intention to Use RetailSelf- Service Checkouts,” Marketing Intelligence & Planning (28:1), pp. 46- 58.

Morris, M. G., Venkatesh, V., and Ackerman, P. L. (2005). “Gender and Age Differences in Employee Decisions about New Technology: An Extension to the Theory of Planned Behavior,” IEEE Transactions on Engineering Management (52:1), pp. 69-84.

Norman Rudhumbu (2022), “Applying the UTAUT2 to predict the acceptance of blended learning by university students”, Asian Association of Open universities Journal ISSN: 2414-6994.

Nurmasitah, S., Faridi, A., Astuti, P., & Nurrohmah, S. (2019). Students’ Perception toward the Implementation of Blended Learning for Teaching ESP in Faculty of Engineering. In 1st Vocational Education International Conference (VEIC 2019)

Pedro Garrido-Gutiérrez et al (2023), “Student Acceptance of E-Learning during the COVID-19 Outbreak at Engineering Universities in Spain”, Educ. Sci. 2023, 13(1), 77; https://doi.org/10.3390/educsci13010077

Rex B. Kline(2016), “Principles and Practice of Structural Equation Modeling”, the guilford press New York ISBN 978-4625-5191-0.

R.Kurniawan, Pramana(2021). “Adopsi Blended Learning pada Pendidikan Non Formal Menggunakan Model Extended Technology Acceptance”. Indonesian Journal of Information Systems (IJIS) Vol. 4, No. 1, August 2021

Seyyed Mohsen Azizi et al.(2022), “Factors affecting the acceptance of blended learning in medical education: application of UTAUT2 model”, BMC Med Educ 20, 367 (2020). https://doi.org/10.1186/s12909-020-02302-2 .

Viswanath Venkatesh & James Y. L. Thong (2012). “CONSUMER acceptance and use of information technology: extending the unified theory of acceptance and use of technology”, Management Information Systems Research Center, University of Minnesota Vol. 36, No. 1 (March 2012).

Vo, H. M., Zhu, C., & Diep, N. A. (2017). The effect of blended learning on student performance at course- level in higher education: A meta-analysis. Studies in Educational Evaluation, 53, 17-28.

Wu, J.-H., Tennyson, R. D., & Hsia, T.-L. (2010).” A study of student satisfaction in a blended e-learning system environment”. Computers & Education, 55(1), 155–164.