Assessing Mobile Learning System Performance in Indonesia: Reports of the Model Development and Its Instrument Testing

TL;DR

This study develops and tests a model for assessing mobile learning system performance in Indonesia, combining IS success, motivation, and culture theories, with initial validation indicating reliable indicators.

Contribution

It adapts and applies the DeLone and McLean IS success model to mobile learning in a developing country context, providing methodological guidance for future research.

Findings

Two indicators were rejected, suggesting areas for model refinement.

The model demonstrates reliability and validity in initial testing.

Methodological explanations aid novice researchers in model development.

Abstract

It is undeniable that people life patterns and technological developments are interrelated within a supply and demand cycle. In the education world, the emergence of the internet and mobile technologies has opened the learning boundaries through the use of mobile learning (m-learning). In Indonesia, the learning service industry has been begun to enliven the outside school education sector for almost five years ago. Even though the learning has been discussed around a decade ago, however, it is still rare studies that discuss the performance of the m-learning system based on the end-user perceptions in particular. Therefore, the study may still indispensable, especially from the perspectives of a developing nation. This paper elucidates the preliminary stage results of the above-mentioned study, including the results of the model development and its instrument testing. The DeLone and Mclean information system (IS) success model was adopted, combined with the individual motivation and organizational culture theories, and then adapted into the processional and causal logic of the success model. Around 50 respondent data were collected online and processed and analyzed based on the outer model assessments of the PLS-SEM method using SmartPLS 3.0 to know the reliability and validity of each indicator. The result shows that two of 31 are rejected indicators. The rejections may be the revision considerations for the next study stages. Although this may be trivial for experts, the clarity of its methodological explanations may guide the novice researchers, how to develop a research model and its instrument testing.