A comparison of fuzzy DNP and SEM in analyzing novel mobile learning technology acceptances by learners

Research output: Contribution to conferencePaper

1 Citation (Scopus)

Abstract

Mobile learning, the learning method which learners can leverage mobile devices to learn everywhere, has become the one of the most potential learning approach as novel mobile devices emerges. However, how the novel mobile learning technology can be accepted by learners was seldom addressed. Meanwhile, due to the unavailability of large number (more than 100) experts for evaluating novel mobile learning devices, the traditional statistical methods, e.g. the structural equation model (SEM), are not appropriate for evaluating the factors influencing the acceptance of novel techniques, a feasible research framework will be very helpful for achieving the evaluation purposes. In this work, the author proposes a novel technology acceptance modeling (TAM) evaluation framework with the fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) based Network Process (DNP) to resolve the above mentioned real world problem. The SEM based analytic results based on learners will be introduced for demonstrating the effectiveness of the Fuzzy DNP. An empirical study based on the analysis of factors influencing Taiwanese mobile learners' acceptances of some specific mobile learning software being installed in iPhone will be introduced for demonstrating the feasibility and effectiveness of the proposed method. Based on the analytic results, the Fuzzy DNP based framework can be used for real world technology acceptance analysis of novel mobile learning techniques. Meanwhile, the derived factors which can influence the mobile learning technology acceptances can serve as the basis for educators and marketers for designing and improving the next generation learning devices.

Original languageEnglish
Pages119-124
Number of pages6
DOIs
Publication statusPublished - 2012 Dec 1
Event2012 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2012 - Taichung, Taiwan
Duration: 2012 Nov 162012 Nov 18

Other

Other2012 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2012
CountryTaiwan
CityTaichung
Period12/11/1612/11/18

Fingerprint

Technology Acceptance
Mobile Learning
Structural Equation Model
Mobile Devices
Evaluation
Fuzzy Decision Making
Leverage
Statistical method
Empirical Study
Resolve
Model-based
Software
Modeling
Learning
Framework

Keywords

  • Fuzzy DEMATEL (Decision Making Trial and Evaluation Laboratory)
  • SEM (Structural Equation Model)
  • consumer behavior
  • mobile learning
  • technology acceptance model (TAM)

ASJC Scopus subject areas

  • Logic

Cite this

Huang, C-Y. (2012). A comparison of fuzzy DNP and SEM in analyzing novel mobile learning technology acceptances by learners. 119-124. Paper presented at 2012 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2012, Taichung, Taiwan. https://doi.org/10.1109/iFUZZY.2012.6409686

A comparison of fuzzy DNP and SEM in analyzing novel mobile learning technology acceptances by learners. / Huang, Chi-Yo.

2012. 119-124 Paper presented at 2012 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2012, Taichung, Taiwan.

Research output: Contribution to conferencePaper

Huang, C-Y 2012, 'A comparison of fuzzy DNP and SEM in analyzing novel mobile learning technology acceptances by learners', Paper presented at 2012 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2012, Taichung, Taiwan, 12/11/16 - 12/11/18 pp. 119-124. https://doi.org/10.1109/iFUZZY.2012.6409686
Huang C-Y. A comparison of fuzzy DNP and SEM in analyzing novel mobile learning technology acceptances by learners. 2012. Paper presented at 2012 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2012, Taichung, Taiwan. https://doi.org/10.1109/iFUZZY.2012.6409686
Huang, Chi-Yo. / A comparison of fuzzy DNP and SEM in analyzing novel mobile learning technology acceptances by learners. Paper presented at 2012 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2012, Taichung, Taiwan.6 p.
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