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

EasyChair Preprint no. 529

11 pagesDate: September 26, 2018


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: e-learning, Quizzes, Recommender System, SVD

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  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},
  howpublished = {EasyChair Preprint no. 529},
  doi = {10.29007/4nwc},
  year = {EasyChair, 2018}}
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