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

EasyChair Preprint 529

Abstract

Recommending learning assets in e-Learning systems represents a key aspect. 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 graph algorithms within the Data Structures course. A preliminary case study presents a comparative analysis between a group a 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 received recommended questions over the other ones.

Keyphrases: Quizzes, Recommender System, SVD, e-learning

@booklet{EasyChair:529,
  author    = {Oana Maria Teodorescu and Paul Stefan Popescu and Marian Cristian Mihaescu},
  title     = {Taking e-Assessment Quizzes - A Case Study with an SVD Based Recommender System},
  doi       = {10.29007/4nwc},
  howpublished = {EasyChair Preprint 529},
  year      = {EasyChair, 2018}}