Cognitive-based methods to facilitate learning of software applications via E-learning systems

E-learning systems, which are used for teaching complex software, can facilitate learning if they provide an appropriate teaching approach that decreases learners’ cognitive load in addition to providing practical knowledge. We believe there is lack of cognitively guided educational recommendations...

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Bibliographic Details
Main Authors: Ali Darejeh, Sara Mashayekh, Nadine Marcus
Format: Article
Language:English
Published: Taylor & Francis Group 2022-12-01
Series:Cogent Education
Subjects:
Online Access:https://www.tandfonline.com/doi/10.1080/2331186X.2022.2082085
Description
Summary:E-learning systems, which are used for teaching complex software, can facilitate learning if they provide an appropriate teaching approach that decreases learners’ cognitive load in addition to providing practical knowledge. We believe there is lack of cognitively guided educational recommendations on how to effectively and efficiently design such learning platforms. We thus provide an integrative review paper that overviews relevant literature to cognitive load theory to provide practical solutions and an empirically validated framework to decrease learners’ cognitive load and improve the learning of complex software through E-learning systems. The solutions (which contain practical examples) are proposed based on different concepts of cognitive load theory including using analogies, worked examples and infographics to facilitate schema acquisition; keeping learners’ concentration on the target tools by preventing split-attention and redundancy effects and applying the training wheel method; using interactive videos based on embodied cognition theory and finally considering the modality and transient information effects in designing E-learning systems. These solutions are related to adapting the learning platform to human cognitive structures and can lead to increased learning performance by preventing working memory from being overwhelmed, thus facilitating the formation of schemas and resulting in more efficient and reliable learning with less effort.
ISSN:2331-186X