Zebra - A User Modeling System for Adaptive Learning

Loc Nguyen

The dissertation is published in Standard Scientific Research and Essays (SSRE).

The associated software is available at https://goo.gl/BUBpFg.

Git source.

The research is presented at The 2014 World Engineering Education Forum (WEEF2014), Dubai, UAE, December 2014.

Nowadays modern society requires every citizen always updates and improves her / his knowledge and skills necessary to working and researching. E-learning or distance learning gives everyone a chance to study at anytime and anywhere with full support of computer technology and network. Adaptive learning, a variant of e-learning, aims to satisfy the demand of personalization in learning. The adaptive learning system (ALS) is defined as the computer system that has ability to change its action to provide learning content and pedagogic environment/method for every student in accordance with her/his individual characteristics. Therefore, the ultimate goal of this research is to give the best support to learners in their learning path and this is an enthusiastic contribution to research community. Learners’ information and characteristics such as knowledge, goal, experience, interest, background, etc are the most important to adaptive system. These characteristics are organized in structure so-called learner model (or user model) and the system or computer software that builds up and manipulates learner model is called user modeling system (or learner modeling system). This research proposes a learner model that consists of three essential kinds of information about learners such as knowledge, learning style and learning history. Such three characteristics form a triangle and so this learner model is called Triangular Learner Model (TLM). The ideology of TLM is that user characteristics are various and only some information is really necessary to adaptive learning and an optimal user modeling system should choose essential information relating to user’s study to build up learner model.