Design Framework of Adaptive Intelligent Tutoring Systems

Abstract

The aim of this study is to examine adaptation elements and Intelligent Tutoring System (ITS) elements used in Adaptive Intelligent Tutoring Systems (AITSs), using meta-synthesis methods to analyze the results of previous research. Toward this end, articles appearing in the Web of Science, Google Scholar, Eric and Science Direct databases in 2000 and later were identified with the keyphrase “adaptive intelligent tutoring system.” Application of exclusion and inclusion procedures to the articles accessed in the search resulted in the selection of 32 articles, which were analyzed using meta-synthesis methods and then evaluated in the light of prespecified themes and elements used in AITSs were determined. According to results, the systems were designed for a wide range of fields such as Information Technologies, Mathematics, Science, Medicine, and Foreign Language Education. In these systems, content adaptation was generally used, based mostly on such criteria as feedback, student level, student learning and cognitive styles, and student performance. And besides 4 basic ITS modules (knowledge, student, teaching and user interface), some different modules such as guide module, strategy module, personal learning module, knowledge base module, communication module, system administrator module and messaging module were used. Finally, some suggestions were given for such studies in the future. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.