Taking e-Assessment Quizzes - A Case Study with an SVD Based Recommender System

Abstract

Recommending learning assets in e-Learning systems represents a key feature. Among many available assets there are quizzes that validate and also evaluate learner’s knowledge level. This paper presents a recommender system based on SVD algorithm that is able to properly recommend quizzes such that learner’s knowledge level is evaluated and displayed in real time by means of a custom designed concept map for graphs algorithms within the Data Structures course. A preliminary case study presents a comparative analysis between a group of learners that received random quizzes and a group of learners that received recommended questions. The visual analytics and interpretation of two representative cases show a clear advantage of the students who received recommended questions over the other ones.