Accelerometer Input as an Alternative to Direct Manipulation Input for the Assessment of Individual User Learning Styles
Abstract: Access to Individual learner styles is fast becoming an essential component in the development of learner models for eLearning environments. There is an increasing need to establish learning models to facilitate the provision of adaptive content to specific learner needs, especially for the incorporation of adaptive media. Adaptive media is becoming increasingly important as we move toward ubiquitous learning environments. Recent advances in modern interactive input devices and mobile technologies are paving the way for new methods of user data collection for adaptive learner model development. This paper outlines a proposed eLearning system to provide learner style feedback. The aim of the system is to allow for the evaluation of accelerometer input as an alternative to direct manipulation input to infer individual user styles within elearning environments.