A Meta Analysis of Factors Affecting Perceived Usefulness and Perceived Ease of Use in The Adoption of E-Learning Systems
Author(s) -
Rahmi Baki,
Burak Birgören,
Adnan Aktepe
Publication year - 2018
Publication title -
turkish online journal of distance education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.374
H-Index - 22
eISSN - 1309-4564
pISSN - 1302-6488
DOI - 10.17718/tojde.471649
Subject(s) - technology acceptance model , usability , external variable , computer science , psychology , structural equation modeling , knowledge management , variables , applied psychology , human–computer interaction , machine learning , programming language
The full potential of e-learning, a trend that is of growing importance lately, will not be reaped unless the users fully utilize the system, triggering extensive research to be conducted in order to provide valuable insight on a myriad of variables influencing user acceptance in e-learning systems. The main purpose of the study is to determine the factors that affect the intention of users to use e-learning and to get results which can guide system developers and researchers. In accordance with this purpose, 203 studies investigating the e-learning acceptance of the users through the Technology Acceptance Model (TAM) were found in the literature. In those studies, variables which are suggested to determine Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) and results of related hypotheses are analyzed. Finally, a model is proposed. In this model, the most widely accepted hypotheses, affecting PU and PEOU according to the literature are included in the original TAM. As a result; it determines Self Efficacy-PEOU, Subjective Norm-PU, Self Efficacy-PU, Interaction-PU, Enjoyment-PEOU, Anxiety-PEOU, Enjoyment-PU, Compatibility-PU, Subjective Norm-PEOU and Interaction-PEOU as variables that have statistical significance in users’ PU and PEOU, respectively. Moreover, the study examines the relationship between the User Satisfaction and original TAM variables, and proposes the Acceptance and Satisfaction Model for E-Learning (ASME) as a model to best explain the dependent variables described above.
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