Recommendation mechanism based on students' working memory capacity in learning systems

Ting Wen Chang, Moushir M. El-Bishouty, Sabine Graf, Kinshuk

Research output: Chapter in Book/Report/Conference proceedingPublished Conference contributionpeer-review

3 Citations (Scopus)

Abstract

Students' learning performances are susceptible to their cognitive abilities, such as working memory capacity (WMC). WMC is very limited and can be easily overloaded in learning activities that require complex cognitive tasks. This study aims to provide teachers with meaningful recommendations for designing and improving learning contents and learning presentation based on students' WMC. Our previous research successfully detects students' WMC from their learning behaviours in learning systems. This paper proposes the next step of providing meaningful recommendations to the teachers based on different levels of students' WMC. The recommendations are based on the guidelines of cognitive load theory that are intended to assist in presentation of information in order to reduce working memory overload.

Original languageEnglish
Title of host publicationProceedings - 2013 IEEE 13th International Conference on Advanced Learning Technologies, ICALT 2013
Pages333-335
Number of pages3
DOIs
Publication statusPublished - 2013
Event2013 IEEE 13th International Conference on Advanced Learning Technologies, ICALT 2013 - Beijing, China
Duration: 15 Jul. 201318 Jul. 2013

Publication series

NameProceedings - 2013 IEEE 13th International Conference on Advanced Learning Technologies, ICALT 2013

Conference

Conference2013 IEEE 13th International Conference on Advanced Learning Technologies, ICALT 2013
Country/TerritoryChina
CityBeijing
Period15/07/1318/07/13

Keywords

  • cognitive load theory
  • instructional design
  • learning system
  • working memory capacity

Fingerprint

Dive into the research topics of 'Recommendation mechanism based on students' working memory capacity in learning systems'. Together they form a unique fingerprint.

Cite this