This study explores how educators could use the Information Systems Success (ISS) model to successfully evaluate, select and use mobile educational applications. It aims to illustrate how each dimension of the ISS model could be evaluated to meaningfully contribute to mathematics learning. The increase in mobile device usage has created various opportunities for the development of learning material which can be accessed through these devices. Mobile learning is learning on the move. Mobile learning creates opportunities for learners not to be bound to a fixed location. Learners are able to work at their own pace and they are given access opportunities. The core problem statement of this study is that mathematics educators experience challenges to evaluate, select and use applications that will support meaningful learning in their subject field and the study comments on existing applications with the aim to improve their design. Qualitative data was collected from three mathematics subject specialists, six teachers who specialise in various subject fields, one technology and technical expert and six further education and training (FET) mathematics classes. The information gathered from the participants enabled the researcher to determine how educators evaluate and select mathematical applications and how each dimension of the ISS model could meaningfully contribute to education environments.
The analysis of the data has indicated that teachers do not use a specific methodology to evaluate and select mathematics applications. If they encounter applications they regard as useable they will evaluate the content of the application according to their curricula outcomes. The research contends that each dimension of the ISS model could be evaluated and contributes to the evaluation and selection of mobile education applications (MEAs). This provides credibility to the use of the ISS model as an evaluation tool. The conceptual framework of this study which is based on the ISS model can be regarded as a framework teachers could use to evaluate and select MEAs.