Educational Research Online: E-Learning Sequences Analyzed By Means Of Optimal-Matching
Stefan Iske, Technische Universität Darmstadt, Germany
EdMedia + Innovate Learning, in Vienna, Austria ISBN 978-1-880094-65-5 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC
This article presents the methodology of analyzing processes of e-learning by means of optimal-matching. The overall aim of optimal-matching is the identification of patterns, regularities and structures in navigational sequences (i.e. navigational paths). Thereby navigation as the interaction of a user with a hypertextual online learning environment is focussed. Based on the concept of Levenshtein distance empirical navigational sequences are compared and grouped by similarity using the method of cluster analysis. In methodological perspective the described approach is differentiated from methods of analyzing aggregated properties of navigational processes. From an educational point of view the process of navigation in hypertextual learning environments is described as autodidactics. Results of an empirical study of 1600 sequences including 4600 informational units in an hypertextual online learning environment are presented.
Iske, S. (2008). Educational Research Online: E-Learning Sequences Analyzed By Means Of Optimal-Matching. In J. Luca & E. Weippl (Eds.), Proceedings of ED-MEDIA 2008--World Conference on Educational Multimedia, Hypermedia & Telecommunications (pp. 3780-3789). Vienna, Austria: Association for the Advancement of Computing in Education (AACE).
© 2008 Association for the Advancement of Computing in Education (AACE)