Electronic Learning Modules in Mobile Devices: A Technology Acceptance Model Approach Using PLS-SEM

Cris Norman P. Olipas¹ , Arsenio P. Gardoce² , Jr. ³

Section:Research Paper, Product Type: Journal-Paper
Vol.8 , Issue.9 , pp.37-44, Sep-2022

Online published on Sep 30, 2022

Copyright © Cris Norman P. Olipas, Arsenio P. Gardoce, Jr. . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

View this paper at   Google Scholar | DPI Digital Library

XML View     PDF Download

How to Cite this Paper

Abstract :
Adopting new information technology (IT) solutions has been one of the most effective means to improve the quality of instruction delivered to students. With the spread of the coronavirus 2019 pandemic, many learning institutions have shifted from the conventional mode of learning, where instructions are usually delivered inside the classroom, into a more flexible mode. Thus, integrating new IT solutions plays a big part in these changes. This study aimed to identify relationships among the variables contained in the Technology Acceptance Model (TAM) to use electronic learning modules on an application installed on mobile devices using partial least square–structural equation modelling (PLS-SEM). Sixty-five-point-nine percent of males and thirty-four-point-one percent of females participated in this study, which made up the eighty-two total number of respondents. Analysis shows that this number of respondents was sufficient for this study. Using WarpPLS 7.0, analysis was performed. Results revealed that there were significant positive relationships between perceived ease of use and perceived usefulness; perceived ease of use and attitude toward using; attitude toward using and intention to use; and perceived usefulness and intention to use. However, the analysis revealed that there was no significant relationship between perceived usefulness and the attitude toward using it. A revised TAM model was presented based on parameter estimates.

Key-Words / Index Term :
Electronic Learning PLS-SEM, Modules, Technology Acceptance Model

References :
[1] C.N.P. Olipas, “Students’ evaluation of the instructional learning modules for Application Development and Emerging Technologies Course,” Puissant, Vol. 4, pp. 1074-1089, 2023.
[2] L.E. Caballero, M.A.M. Ferrer, R.A. Tiria, "The Role of Gamification in the Academic Performance of Junior High School Students in Language Subject," International Journal of Scientific Research in Multidisciplinary Studies, Vol.8, Issue.3, pp.1-4, 2022.
[3] C.N.P. Olipas, R.F. Leona, “The extent of engagement to social networking sites, the impact of mobile games, and the students’ learning experiences: An assessment,” International Journal of Scientific & Technology Research, Vol. 9, Issue.5, pp. 112-119
[4] F.D. Davis, “Perceived usefulness, perceived ease of use, and user acceptance of information technology,” MIS Quarterly, Vol. 13, Issue.3. pp. 319-340, 1989.
[5] C.S, Criollo, S. Lujan-Mora, A. Jaramillo-Alcazar, “Advantages and disadvantages of m-learning in current education.” In Proceedings of the IEEE World Engineering Education Conference (EDUNINE), Buenos Aires, Argentina, pp. 11-14, 2018.
[6] M. Sharples, “Mobile learning: research, practice, and challenges”. Distance Education in China. Vol. 3, Issue.5, pp. 5-11, 2013.
[7] K. Swan, M. Van’t Hooft, A. Kratcoski, D. Unger, “Teaching and learning with mobile computing devices: Closing the gap. mobile technology.” In H.van der Merwe & T. Brown, Mobile Technology: The future of Learning in your hands. mLearn 2005 Book of Abstracts. 4th World Conference on mLearning, Cape Town. pp. 157-161, 2005.
[8] C. O`Malley, G. Vavoula, J. Glew, M. Sharples, P. Lefrere, “MOBIlearn: D4.1 guidelines for learning/teaching/tutoring in a mobile environment”, 2005.
[9] A. Kukulska-Hulme, J. Traxler, “Mobile learning: A handbook for educators and trainers”. Psychology-Press, London, pp. 7-8, 2005.
[10] C.N.P. Olipas, “The Gen Z’s learning experience and its relationship to social media use”, International Journal of Advanced Research and Innovative Ideas in Education. Vol. 8, Issue.1, pp. 1291-1299, 2022
[11] S.C. Chen, L. Shing-Han, L. Chien-Yi, “Recent related research in technology acceptance model: A literature review,” Australian journal of business management and research, Vol. 1, Issue.9, pp. 124, 2011.
[12] A. Granic, N. Marangunic, “Technology acceptance model in educational context: A systematic literature review.” British Journal of Educational Technology. Vol. 50, Issue.5, pp. 2572-2593, 2019.
[13] N.A.N. Roslan, A.F.M. Ayub, N. Ghazali, “Predictor of Instant Messaging Use among Students for Academic Purpose,”, International Journal of Interactive Mobile Technologies, Vol. 14, Issue. 15, pp. 195, 2020
[14] J.H. Kim, M. Kim, M. Park, J. Yoo, “How interactivity and vividness influence consumer virtual reality shopping experience: the mediating role of telepresence,” Journal of Research in Interactive Marketing, Vol. 15, Issue. 3, pp. 502-525, 2021
[15] M. Al-Emran, V. Mezhuyev, A. Kamaludin, “Technology acceptance model in m-learning context: A systematic review,” Computers & Education, Vol. 125. pp. 1-41, 2018.
[16] A. Imtiaz, N. Maarop, “A review of technology acceptance studies in the field of education,” Jurnal Teknologi (Sciences & Engineering), Vol. 69, Issue.2. pp. 27-32, 2014,
[17] N. Kock, P. Hadaya, “Minimum sample size estimation in PLS?SEM: The inverse square root and gamma?exponential methods.” Information Systems Journal, Vol. 28 no. 1, pp 227-261, 2018
[18] N. Kock, “WarpPLS user manual: Version 7.0”. ScriptWarp Systems, Laredo, TX, 2020
[19] C.N.P. Olipas, R.A.G. Cochanco, “The information technology students’ cognitive determinants and its relationship to academic performance,” International Journal of Advanced Engineering Research and Science, Vol.8, Issue.3, pp. 381-389.
[20] M. Tavakol, R. Dennick, “Making sense of Cronbach’s alpha.” International Journal of Medical Education, Vol 2, pp. 53-55, 2011
[21] N. Kock, “Common method bias in PLS-SEM: A full collinearity assessment approach.” International Journal of e-Collaboration, Vol 11, Issue.4, pp. 1-10, 2015.
[22] J.F. Hair, W.C. Black, B.J. Babin, R.E. Anderson, “Multivariate data analysis”. Prentice Hall. Upper Saddle River, NJ, 2009.
[23] N. Kock, G. Lynn, “Lateral collinearity and misleading results in variance-based SEM: An illustration and recommendations”. Journal of the Association for Information Systems, Vol. 13, Issue. 7, pp. 546 – 580, 2012.
[24] C. Fornell, D.F. Larcker, “Evaluating structural equation models with unobserved variables and measurement error”, Journal of Marketing Research, Vol. 18, Issue 1, pp. 39-50, 1981.
[25] J.F. Hair, M. Sarstedt, L. Hopkins, V, Kuppelwieser, “Partial least squares structural equation modeling (PLS-SEM) An emerging tool in business research.” European Business Review, Vol. 26, Issue.2, pp. 106-121. 2014.
[26] J.F. Hair, G.T.M. Hult, C. Ringle, M. Sarstedt, “A primer on partial least squares structural equation modeling (PLS-SEM)”. Sage Publications. 2016
[27] N. Kock, “Using WarpPLS in e-collaboration studies: Descriptive statistics, settings, and key analysis results.” International Journal of e-Collaboration (IJeC), Vol. 7, Issue. 2, pp. 1-18. 2011.
[28] M. Tenenhaus, V.E. Vinzi, Y.M. Chatelin, C. Lauro, “PLS path modeling”. Computational Statistics & Data Analysis, Vol 48, Issue.1, pp. 159-205, 2005.
[29] M. Wetzels, G. Odekerken-Schröder, C. Van Oppen, “Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration.” MIS quarterly, Vol. 33, Issue. 1, pp. 177-195, 2009.
[30] N.M. Suki, N.M. Suki, “Exploring the relationship between perceived usefulness, perceived ease of use, perceived enjoyment, attitude and subscriber’s intention towards using 3G mobile services,” Journal of Information Technology Management, Vol. 22, Issue.1, pp. 1-7, 2011
[31] Q. Ma, L. Liu, “The Technology Acceptance Model”, End User Computing, pp. 1088-1100, 2008.
[32] X. Hong, M. Zhang, Q. Liu, “Preschool Teachers’ Technology Acceptance During COVID-19: An Adapted Technology Acceptance,” Frontiers in Psychology, Vol. 12, pp. 1-11, 2021
[33] N. Kock, “WarpPLS user manual: Version 7.0”. ScriptWarp Systems, Laredo, TX, 2020
[34] Okto Adiya Suryawirawan, “The effect of college students’ technology acceptance on e-commerce adoption”, BISMA (Bisnis dan Manajemen), Vol. 12, Issue.1, pp. 42-62, 2021
[35] N. Larasati, C.A. Wulandadari, “Implementation of Unit Dose Dispensing Using Management Information System in Pharmacy Installation of Panti Rapih Hospital,” Jurnal Manajemen Dan Pelayanan Farmasi (Journal of Management and Pharmacy Practice), Vol. 8, Issue.4, pp. 153, 2019