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Unlocking Augmented Reality Learning Design Based on Evidence From Empirical Cognitive Load Studies—A Systematic Literature Review

  • Jana Gonnermann-Müller*
  • , Jule M. Krüger
  • *Corresponding author for this work

Research output: Contribution to journalReview articleAcademicpeer-review

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Abstract

Background: Despite the numerous positive effects of augmented reality (AR) on learning, previous research has shown ambiguous results regarding the cognitive demand on the learner arising from, for example, the overlay of virtual elements or novel interaction techniques. At the same time, the number of evidence-based guidelines on designing AR is limited or focuses on global effects, primarily relying on media comparison studies, whose validity is criticised. Objective: To guide the meaningful design of learning and training settings, this paper systematically reviews empirical research on AR design and synthesises the findings to develop evidence-based recommendations for designing AR systems considering cognitive load. Methods: We conducted a systematic literature review, initially screening 810 distinct papers and ultimately analysing findings from 27 publications, which report on 29 distinct experimental studies. This selection was based on rigorously defined inclusion and exclusion criteria, adhering to the PRISMA guidelines. Results and Conclusion: The central value of this paper is the aggregation of existing evidence from empirical studies, resulting in 15 recommendations for AR design based on six design dimensions: Spatiality-related, Interaction-related, Contextuality-related, Content-related, Guidance-related and Display Selection. Additionally, with three points for future research, this systematic literature review, first, stresses the need for more empirical evidence and value-added studies. Second, learner characteristics that might influence cognitive load in AR-based learning should be examined. Third, it advocates for the inclusion of measurements beyond the NASA-TLX, and including more physiological measurements (e.g., eye-tracking, EEG) to enhance the applicability of the results for learning and training situations.

Original languageEnglish
Article numbere13095
JournalJournal of computer assisted learning
Volume41
Issue number1
DOIs
Publication statusPublished - Feb 2025
Externally publishedYes

Keywords

  • augmented reality
  • cognitive load
  • design guidelines
  • design principles
  • instructional design
  • workload

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