On modeling the quality of concept mapping toward more intelligent online learning feedback: a fuzzy logic-based approach

Abstract

A new model, namely fuzzy inference system (FIS) concept mapping (FISCMAP), is proposed here that explores the fuzzy logic constructs within a computer-based concept mapping (CM) environment. FISCMAP involves modeling techniques as a vehicle to improve the intelligence of an online learning feedback environment that could promote personalization and adaptation to the student’s online educational needs, thus, fighting info-exclusion. From this perspective, the CMapTools is used as the online environment that captures the students’ actions and choices during the CM construction. Eight CMapTools measurements are considered to form inputs to a five-level FIS, equipped with 115 expert’s fuzzy rules. The CMapTools data were drawn from a blended (b)-learning course offered by a Greek Higher Education Institution, involving 20 Master’s students. Experimental results have shown that the proposed FISCMAP scheme, when used for the evaluation of users’ Quality of Concept Map (QoCM) via constructive CM variables (metrics), can provide intelligent descriptors regarding the students’ online CM. Furthermore, the FISCMAP’s dynamic analysis of QoCM and identification of the students’ transitional step behavior, during the development of the CM, provide further insight in the CM building strategies they adopt, forming constructive feedback. The latter reinforces the students’ ability to reflect on and analyze material in order to form reasoned judgments, clearly contributing to their critical thinking and deeper learning.