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Exploring the effect of improved learning performance: A mobile augmented reality learning system.

Wei-Tsong Wang1, Ying-Lien Lin1, Hsin-En Lu1

  • 1Department of Industrial and Information Management, National Cheng Kung University, No.1, University Road, Tainan City, 701 Taiwan, Republic of China.

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Summary

Mobile augmented reality learning systems (MARLS) enhance online science education by improving student engagement and learning effectiveness. Information feedback in MARLS positively impacts learning, but high cognitive load can hinder effectiveness.

Keywords:
Continued intentionExtraneous cognitive loadFlow experienceImproved learning performanceInformation feedbackPerceived learning effectiveness

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Area of Science:

  • Educational Technology
  • Cognitive Science

Background:

  • Students often experience high cognitive load with complex scientific material.
  • The COVID-19 pandemic necessitated online learning, highlighting the need for effective digital tools.
  • Augmented reality (AR) offers potential for clearer explanations of sophisticated concepts.

Purpose of the Study:

  • To investigate the impact of mobile augmented reality learning systems (MARLS) on perceived learning effectiveness.
  • To explore how MARLS can mitigate challenges of reduced face-to-face interaction in online education.
  • To examine the role of information feedback and cognitive load within MARLS.

Main Methods:

  • 204 university students participated in a learning task using MARLS.
  • Data were collected via questionnaires to assess the research model.
  • Theoretical frameworks included information feedback, flow theory, and cognitive load theory.

Main Results:

  • Information feedback positively influenced flow experience, perceived learning effectiveness, and continued intention.
  • Enhanced learning performance correlated positively with continued intention.
  • Extraneous cognitive load negatively moderated the link between information feedback and perceived learning effectiveness.

Conclusions:

  • MARLS can be an effective tool for online science education, particularly in reducing cognitive load.
  • Optimizing information feedback within MARLS is crucial for maximizing learning effectiveness.
  • Further research should explore implications for designing engaging and effective AR learning experiences.