Reflection of individual cognitive load theories in digital learning from a pedagogical point of view: An empirical study of the impact of language skills in an e-Learning program for migrants and refugees

Nele Rohde, Nicole Flindt, Christian Rietz, Yoo Kyung Chang, Elke Stracke, Gulzhaina Kassymova, Stanislav Sabaliauskas

Research output: Contribution to journalArticlepeer-review

Abstract

Abstract.Cognitive Load Theory (CLT) and the Cognitive Theory of Multimedia Learning (CTML) deal with the thesis that human working memories can only store and retain a limited number of items and address how to utilize individual capacity in the learning process without provoking cognitive overload. Based on these theoretical insights, traditional ways of non-digitalized learning are usually perceived to be more effective, asthere may be less cognitive overload due to digital multimedia design; however, with the use of modern technology, digital educational offerings such as e-Learning programs can be effective as modified and tailored to the learners’ needs. This article studies how language barriers can negatively impact the success of e-Learning programs for migrants and refugees from the perspective of CLT and a pedagogical point of view. The theoretical framework of CLT and CTML applied to interpret the findings from empirical data collected as part of the EU-funded project “Young Refugees AI Student Empowerment Program – RAISE.” The project aims to capture the participants´ experiences and cognitive skills by shaping pedagogical strategies that
adjust to the learner’s optimal pace and learning needs. The study explores the structural requirements of e-Learning programs for migrants and refugees based on Cognitive Load Theories. The baseline is that e-Learning is complex and demands significant working memory resources. This effect is significantly elevated to
a point where it harms learning when the external demands vastly exceed the corresponding cognitive working memory resources.
Original languageEnglish
Pages (from-to)1-20
Number of pages20
JournalStatistics, accounting and audit
Volume4
Issue number91
DOIs
Publication statusPublished - Nov 2023

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