Learning Analytic and Evaluation in Malleable Learning Environments

Abstract

Education has evolved from the traditional classroom of blackboard and chalk to multimedia software teaching, online teaching, hybrid education and so on. Learning objects and scenario are growing in scale and functionality. Because of this increase in complexity, the likelihood of subtle errors is much greater. One-way to achieving this proposed goal is by pre-evaluation of these environments. Many companies and departments have their own evaluation criteria and requirements, but the relative and subjective are too much, so they can not meet the general evaluation. For this reason, we propose a framework able to analyse the learning scenario functionalities and aspects and gives an early evaluation of the designed scenario. The evaluation framework is based on contextual elements: Times, Actors, network, user location and correlation between activities. Then we propose to evaluate learning scenario through formal methods which are mathematically based languages, techniques and tools for specifying and verifying. Use the formal methods does not a priori guarantee correctness and successful. However, they can greatly increase our understanding of the learner’s behaviour with the existing scenario by revealing inconsistencies, ambiguities and incompleteness that might otherwise go undetected.