Investigating Trend-setters in E-learning Systems using Polyadic Formal Concept Analysis and Answer Set Programming

Paper: Sanda Dragoş, Diana Haliţă, Diana Troancă, Investigating Trend-setters in E-learning Systems using Polyadic Formal Concept Analysis and Answer Set Programming, Proceedings of the 4th International Workshop on Artificial Intelligence for Knowledge Management (AI4KM 2016), pp. 42-48 New York, USA

Abstract: Web-based educational systems offer unique opportunities to study how students learn and based on the analysis of the users’ behavior, to develop methods to improve the e-learning system. These opportunities are explored, in the current paper, by blending web usage mining techniques with polyadic formal concept analysis and answer set programming. In this research, we consider the problem of investigating browsing behavior by analyzing users’ behavioral patterns on a locally developed e-learning platform, called PULSE. Moreover, we investigate users’ behavior by using similarity measures of various chains of accessed pages in a tetradic and a pentadic setting. Furthermore, we present in this paper an approach for detecting repetitive behavioral patterns in order to determine trend-setters and followers.

Keywords: Web-based educational systems, polyadic formal concept analysis, answer set programming, repetitive behavioral patterns

Acknowledgments: Diana Haliță was supported by a doctoral research made possible by the financial support of the Sectoral Operational Programme for Human Resources Development 2007-2013, co-financed by the European Social Fund, under the project POSDRU/187/1.5/S/155383 – ”Quality, excellence, transnational mobility in doctoral research”. Diana Troanca was supported by a one year research grant from DAAD, the German Academic Exchange Service.