ANALYSIS OF SATISFACTION AND USEFULNESS OF LEARNING MANAGEMENT SYSTEM (LMS) USING EUCS AND TTF METHODS
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Keywords

Learning Management
Task Technology Fit
End User Computing System
Online Learning

Abstract

Student satisfaction with using the Learning Management System (LMS) is one factor determining the achievement of bold learning objectives in tertiary institutions. This study aims to test the satisfaction and usefulness of LMS for students in learning to dare to use several variables in End User Computing Satisfaction (EUCS) and Task Technology Fit (TTF). The relationship between variables in EUCS and TTF was tested using the Structural Equation Model (SEM) based on 184 respondent data obtained from students using Moodle LMS at a university in Jakarta. The study's results revealed that the variable task characteristics and technological characteristics significantly affected TTF and EUCS tasks, and TTF positively affected EUCS. The results of the study provide recommendations that the resolution of LMS technology and the ease of use of LMS are the dominant factors influencing student satisfaction in using LMS

https://doi.org/10.30742/melekitjournal.v9i2.324
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References

Ahmed, Z., & Kader, A. (2017). mBanking adoption; Exploratory factor analysis; UTAUT; TTF; Bangladesh. http://www.icommercecentral. com

Ambra, J. D. , Wilson, C. S., & Akter, S. (2013). Application of the task-technology fit model to structure and evaluate Application of the task-technology fit model to structure and evaluate the adoption of e-books by academics. Recommended Citation. https://ro.uow.edu.au/ comm-papers/3189

Chin, W. W. (1998). The Partial Least Squares Approach for Structural Equation Modeling.

Chin, W. W., & Dibbern, J. (2010). An Introduction to a Permutation Based Procedure for Multi-Group PLS Analysis: Results of Tests of Differences on Simulated Data and a Cross-Cultural Analysis of the Sourcing of Information System Services Between Germany and the USA. In Handbook of Partial Least Squares (pp. 171–193). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-32827-8_8

Coates, H., James, R., & Baldwin, G. (2005). A Critical Examination Of The Effects Of Learning Management Systems On University Teaching And Learning. Tertiary Education and Management 2005 11:1, 11(1), 19–36. https://doi.org/10.1007/ S11233-004-3567-9

Cronbach, L. J. (1951). Coefficient Alpha and The Internal Structure of Tests.

Dishaw, M. T., Strong, D. M., & Bandy, D. B. (2002). 2002-Eighth Americas Conference on Information Systems. https://www.researchgate. net/publication/228781418

Doll, W. J., & Torkzadeh, G. (1988). The Measurement of End-User Computing Satisfaction. MIS Quarterly, 12(2), 259. https://doi.org/10.2307/ 248851

Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. In Source: Journal of Marketing Research (Vol. 18, Issue 1).

Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS Quarterly: Management Information Systems, 19(2), 213–233. https://doi.org/10.2307/249689

Ha J.H, S. Y. (2014). An Analysis on the Relation of Elementary Students’ VARK Styles and Scientific Communication Skills. Journal of Korean Elementary Science Education, 33(4), 724–735.

Hair JR. J.F, Anderson R.E, Tatham R.L, & Black W.C. (2009). Multivariate Data Analysis Fifth Edition. Prentice Hall, Inc.

Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20, 277–319. https://doi.org/10.1108/S1474-7979(2009)0000020014

Klarner, P., Sarstedt, M., Hoeck, M., & Ringle, C. M. (2013). Disentangling the Effects of Team Competences, Team Adaptability, and Client Communication on the Performance of Management Consulting Teams. Long Range Planning, 46(3), 258–286. https://doi.org/10.1016/J.LRP.2013.03.001

McGill, T. J., & Klobas, J. E. (2009). A task–technology fit view of learning management system impact. Computers & Education, 52(2), 496–508. https://doi.org/10.1016/J.COMPEDU.2008.10.002

Nasser, R., Cherif, M., & Romanowski, M. (2011). Factors that Impact Student Usage of the Learning Management System in Qatari Schools Nasser. In Cherif and Romanowski (Vol. 12, Issue 6).

Oliveira, T, dkk. Extending the the understanding of mobile banking adoption, When UTAUT meets TTF and ITM. International Journal of Information Management, 34(5), 689–703. https://doi.org/ 10.1016/j.ijinfomgt.2014.06.004

Pallant, J. (2020). A Step-by-Step Guide to Data Analysis Using SPSS for Windows.

RIAD, dkk. (2009). . Turkish Online Journal of Distance Education, 10(4), 27–40.

Sarstedt, M., Hair, J. F., Nitzl, C., Ringle, C. M., & Howard, M. C. (2020). Beyond a tandem analysis of SEM and PROCESS: Use of PLS-SEM for mediation analyses! International Journal of Market Research, 62(3), 288–299. https://doi.org/10.1177/1470785320915686

Srichanyachon, A. N. (2014). EFL LEARNERS’ PERCEPTIONS OF USING LMS (Vol. 13, Issue 4).

Straub, D., & Gefen, D. (2004). Validation Guidelines for IS Positivist Research. Communications of the Association for Information Systems, 13. https://doi.org/10.17705/ 1cais.01324

Yadegaridehkordi E, L. N. A. N. (2016). Task-Technology Fit Assessment of Cloud-Based Collaborative Learning Technologies. International Journal of Information Systems in the Service Sector, 8(3), 58–73.

How to Cite

[1]
Y. Shintya and R. Darmadi, “ANALYSIS OF SATISFACTION AND USEFULNESS OF LEARNING MANAGEMENT SYSTEM (LMS) USING EUCS AND TTF METHODS”, MelekIT, vol. 9, no. 2, pp. 113–122, Dec. 2023.
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