Application of databases to knowledge representation and automation of e-learning processes

Abstract

Building intelligent computer programs supporting learning requires selection of an appropriate representation for knowledge and storing it in a database. Similarly, intelligent information retrieval and knowledge presentation systems require use of databases. The paper has twofold aims. The first aim is verify to what degree simple, low-cost methods related to introducing into a database of the whole e-textbook partitioned into fragments can help in building electronic tutors supporting student learning. The second aim is to identify basic data model components enabling extraction of knowledge contained in e-textbooks such as knowledge items, topics and fragments of e-textbook. Division of e-textbook into fragments is to enable automatic generation of:

  1. Questions and multiple-choice assessments verifying whether students have mastered the course material.
  2. Materials supporting repetition, refreshing and retention of student knowledge including presentations and summaries of concepts involved such as tables, diagrams, indexes and glossaries.
  3. Different versions of e-textbooks.

The paper starts with investigation of data models applied in such systems as Wikimedia, Semantic Web and Aura. Next, database representation of the content of one of the e-textbooks used at the Polish-Japanese Academy of Information Technology is investigated and its application to the automation of e-learning processes is considered. A prototype application embodying some features of e-tutor is presented.

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