An ontology-driven software product line architecture for developing gamified intelligent tutoring systems

Diego Dermeval, Glauber Leite, João Almeida, Josmário Albuquerque, Ig I. Bittencourt, Sean W.M. Siqueira, Seiji Isotani and Alan Pedro Da Silva

International Journal of Knowledge and Learning, 2017, vol. 12, issue 1, 27-48

Abstract: Intelligent tutoring systems (ITSs) are effective to provide instruction for students in several situations. Many works have been using gamification by adding game elements to learning contexts aiming to engage students and to drive desired learning behaviours. However, the design of gamified ITS should deal with a huge variability. Software product lines (SPLs) promise to offer rapid product development and more affordable development costs to build software from the same family. A key factor to successfully implement a product-line approach is to structure commonalities and variabilities into a product line architecture (PLA). In this paper, we propose a PLA for developing gamified ITSs that uses an ontology-driven feature modelling strategy. We illustrate how our architecture could be applied to instantiate a product on the basic math domain. We also discuss a set of implications of using it as well as how it could support the evolution/changing of gamified ITSs.

Keywords: ITSs; intelligent tutoring systems; gamification; gamified intelligent tutoring systems; SPL; software product line; ontologies. (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=88181 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijklea:v:12:y:2017:i:1:p:27-48

Access Statistics for this article

More articles in International Journal of Knowledge and Learning from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().