Title: Personalised e-learning system using learner profile ontology and sequential pattern mining-based recommendation

Authors: S. Muruganandam; Narayanasamy Srininvasan

Addresses: Sathyabama University, Chennai, India ' Faculty of Computing, Sathyabama University, Chennai, India

Abstract: The ever-zooming issue of personalisation in the domain of the e-learning or the adaptive e-learning has emerged as a hot subject of intriguing debate among the inquisitive investigators in the last few years. In the learning contents module, all the critical learning materials in the shape of text, video or audio are collected and saved by means of the data management approach so as to effectively orchestrate the entire learning material. In the profile ontology module, the learner profile is saved as the ontology with a clear-cut framework and data. The Markov model is also utilised in this regard. In the instructor module, the online tutoring for each and every learner in accordance with the protocol devised by means of the captioned techniques is carried out. The execution is performed through the JAVA programming and protégé device and the performance is subjected to assessment.

Keywords: e-learning; prefix-span algorithms; graphical user interface; GUI; dataset description; personalised learning; personalisation; learner profile ontology; sequential pattern mining; data mining; recommendation systems; recommender systems; electronic learning; online learning.

DOI: 10.1504/IJBIDM.2017.082704

International Journal of Business Intelligence and Data Mining, 2017 Vol.12 No.1, pp.78 - 93

Received: 17 Aug 2016
Accepted: 10 Oct 2016
Published online: 07 Mar 2017 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article