Formative criterion-based assessment for Moodle quizzes using intelligent computing

Abstract

This paper describes the use of the granular linguistic model of a phenomenon (GLMP) to model the assessment of integer arithmetic learning and implement the automated generation of a formative criterion-based assessment report in natural language, as well as a numerical grade. The report is generated based exclusively on the objective scores automatically generated by Moodle quizzes. GLMP is based on fuzzy logic and the computational theory of perceptions, and uses inference systems based on linguistic rules.