Development of Personalized and Context-aware Model in Learning Log System

Abstract

In this paper, we describe a personalization and context-awareness model based on learning log system. It is able to notify the learners of the location-based knowledge surrounding him in accordance with both their needs and context, detect learners' learning styles using their context history and recommend learning objects for them regarding their learning styles. What's more, by monitoring learners' reaction on the recommendation message, the model can improve its prediction. We also conduct a preliminary experiment to observe what kind of benefits it can bring to learners. The results reveal most of the learners benefit from the context-based notification and learning-style based recommendation.