Integrated user-interface acceptance model for e-learning system

As a learning process, e-learning is aimed to achieve learning objectives, through which, the education is expected to become more accessible, cheaper, more fun, and easier to share and to learn. Disintegrated theories discussing separately e-learning interface usability evaluation and user technology acceptance caused gaps in understanding e-learning comprehensively. It creates challenges to incorporate the theories of user learning style, usability, and user benefit to evaluate and develop e-learning. The purpose of this research is to identify user difficulties and user interface requirement, to develop an integrated user interface acceptance model for e-learning based on user learning style, usability and user benefits, to measure the attributes that support the integration of user interface acceptance model and to evaluate the significant, reliability and validity of the model. This research consisted of three phases of experiments. The first phase is identifying user difficulties and user interface requirements. From the study results, it shows that user interface difficulties covering user communication (21%), choice menu (17%), self-assessment (14%), and interactive media (12%) pose the most challenging aspects for the e-learning users. The results also show that the user interface requirements are user expectation (39%), communicativeness (32%) and media elements (29%). The second phase is developing User Interface Acceptance Model by using Structural Equation Model and LISREL v8.80. There are twelve hypotheses for measurement model and three for structural model. Structural Equation Model was used to determine the suitability of model, while its validity and reliability were measured by composite construct reliability and variance extracted measure. Based on t-value, loading factors, and the relative suitability of each attribute, the User Interface Acceptance Model for e-learning can be accepted. Based on the Goodness of Fit statistical value in the first and the second model, the model of e-learning user interface has a highly significant correlation with e-learning acceptance. Strong construction between variables is evidenced by the construct reliability above 0.70 and variance extracted above 0.50. The third phase of the research is developing UIA prototype by using Moodle v9 and MANOVA analysis to compare the difference level of twelve attributes in User Interface Acceptance toward two groups of experiment. Finally, it was found that there are significant effects between User Acceptance and groups which were obtained from knowledge, robustness, safety, communicativeness and expectation. It was also found the significant user acceptance effects to grade which were obtained from motivation, knowledge, know-ability, safety, media element and motivation. It can be concluded that based on the e-learning users’ requirements, this research has developed integrated user interface acceptance model for e-learning. It is expected this model can be used for developing and e-learning evaluation in the future. Hopefully this model could be an alternative to measure and to develop e-learning interface acceptance later.

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