About the Project

Mobile Learning enables contextualised learning anywhere and at any time that would be impossible to achieve with desk-bound computing.

Although mobile technologies have evolved and become more capable of supporting immersive learning experiences, there are still a number of barriers that influence the adoption of mobile learning initiatives in education, at an institutional and at a user level.

Despite the increasing flexibility and mobility of learners, higher education institutions are cautious about investing extensively in mobile technologies because of the rate of emergence of new models and the speed with which devices become obsolete. Full scale evaluations of mobile learning are currently lacking and there is an absence of research on the role, drivers and impact of mobility on learning.

The aim of this project is to develop a Mobile Learning Evaluation Framework (MLEF) that will assist higher education institutions, educators, researchers and practitioners to evaluate the impact and sustainability of mobile learning initiatives within a range of environments.

The MLEF will facilitate and support higher education institutions in the assessment, development and embedding of mobile learning policies and/or practices to enhance the learning experiences of students and support long-term planning for improved learner and institutional outcomes. The framework will be independent of specific technologies and therefore will remain relevant despite the emergence of new devices.

The outcome of the project will be a web-based toolkit that will provide educators with resources such as standardised assessment instruments as well as checklists, guidelines and step-by-step tutorials for the evaluation of m-learning initiatives within various contexts.

 

Development of an Evaluation Framework for Mobile Learning from Uni. of Southern Queensland on Vimeo.

  

This Digital Futures (CRN) Project is a three year collaborative project between the University of Southern Queensland (USQ), The Australian National University (ANU) and The University of South Australia (UniSA). This project is supported through the Australian Government’s Collaborative Research Networks (CRN) program.