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Metacognition01:26

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Metacognition is a conscious process where individuals are aware of their cognitive and executive processes, such as planning before solving a problem or self-monitoring during reading. For instance, a writer may need help with composing a piece. The situation involves a writer who is working on a piece of writing, but while doing so, they realize that something is missing. They notice that their characters lack depth or details. This realization occurs because the writer is reflecting on their...
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Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
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According to Charles Cooley, we base our image on what we think other people see (Cooley 1902). We imagine how we must appear to others, then react to this speculation. We don certain clothes, prepare our hair in a particular manner, wear makeup, use cologne, and the like—all with the notion that our presentation of ourselves is going to affect how others perceive us. We expect a certain reaction, and, if lucky, we get the one we desire and feel good about it. But more than that, Cooley...
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Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties
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Evaluating students' experiences in self-regulated smart learning environment.

Yusufu Gambo1, Muhammad Zeeshan Shakir1

  • 1School of Computing, Engineering and Physical Sciences, University of the West of Scotland, Paisley, PA12BE Scotland UK.

Education and Information Technologies
|July 11, 2022
PubMed
Summary
This summary is machine-generated.

This study evaluated a mobile app for smart learning, finding it supported online learning but needed improved user functions. A subsequent version was better, with students suggesting a web-based option for broader accessibility and engagement.

Keywords:
Mixed-methodMobile appOnline learningSelf-regulated learningSmart learning environment

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Area of Science:

  • Educational Technology
  • Human-Computer Interaction
  • Online Learning

Background:

  • Smart and mobile technologies are transforming education into smart learning environments.
  • Online learners require engaging and active learning experiences.
  • A previously developed self-regulated smart learning mobile app needs evaluation.

Purpose of the Study:

  • To explore final-year undergraduate students' experiences with a smart learning mobile app.
  • To investigate usability, challenges, and factors influencing satisfaction for future implementation.
  • To fill the gap in well-documented studies on student experiences in smart learning environments.

Main Methods:

  • Cyclical mixed-method evaluations involving 85 final-year undergraduate students.
  • Quantitative data collection via surveys on satisfaction factors.
  • Qualitative data collection through focus group discussions on usability and challenges.

Main Results:

  • The mobile app initially supported the online learning process.
  • Students suggested improvements in user functionalities for motivation and engagement.
  • A second evaluation showed continued support, with a recommendation for a web-based version and confirmation of information system quality impact on satisfaction.

Conclusions:

  • Smart learning mobile applications can support online learning experiences.
  • Usability, information system qualities, and moderating factors significantly influence student satisfaction.
  • Future research should consider facilitators' experiences for sustainable smart learning development.