Successful mobile learning (mLearning) initiatives are surprisingly diverse. Some prescribe standardised devices and applications to a cohort of learners while others adopt a Bring Your Own Device (BYOD) strategy, using a mesh of different devices, apps and content. Some weave tools into existing learning scenarios, while others use mLearning to create new ones. This diversity creates a challenge for those evaluating emerging technologies as tools for learning (how to identify the specific impact that one piece of technology has on the learning process and outcomes), as well as those hoping to transition good mobile content from one learning scenario to another.

Mobile learning frameworks like FRAME highlight this inter-relationship, showing how the learning outcomes emerge from an interaction between the technology, the learner and the context. However, evaluating mLearning experiences can be difficult because of the many variables.

This chapter builds on research funded by the U.S. government in the Mobile Learning Environment (MoLE) project, which explored the different technologies that underpin most mLearning content, trying to answer the question “Which formats and technologies are best for simplifying the process of moving good mobile learning between different platforms?” The project team researched and tested the most relevant guidelines and standards, as well as building many different prototypes, culminating in a 24-nation live trial on tablets, media players and smartphones. The optimal solution was found to be a “mesh” of different technical approaches, bridging some of the gaps between mobile platforms, and improving the portability of the learning apps that run on them.

The standards and technical approach proposed in this chapter form the basis of the open source OMLET framework (Open Mobile Learning Toolkit). OMLET 100 is a core component of several commercial deployments in the U.S. and the UK. Content suppliers are starting to adopt these standards to build new mLearning content. Most significantly, the U.S. government JKO (Joint Knowledge Online) platform has adopted them for all future content that they commission.

Keywords

BYOD · HTML5 · mobile learning · MoLE · OMLET · open apps