Toward recommending learning tasks in a learner-centered approach

Hazra Imran, Mohammad Belghis-Zadeh, Ting Wen Chang, Kinshuk, Sabine Graf

Research output: Contribution to journalJournal Articlepeer-review

3 Citations (Scopus)


Learner-centered education becomes more and more popular. One way of offering learner-centered education is to have assignments where learners can select from a pool of learning tasks with different difficulty levels (e.g., many easy tasks, few challenging tasks, etc.). However, a problem that learners can face in such assignments is to select the tasks that are most appropriate for them. In this paper, we introduce a rule-based recommender system that supports learners in selecting learning tasks. Such recommendations aim at helping learners to select the tasks from which they can benefit most in terms of maximizing their learning.

Original languageEnglish
Pages (from-to)337-344
Number of pages8
JournalLecture Notes in Educational Technology
Issue number9783662441879
Publication statusPublished - 2015


  • Learning management system
  • Personalization
  • Recommender system


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