WORKING DRAFT authorea.com/31655
Main Data History
Export
Show Index Toggle 1 comments
  •  Quick Edit
  • Glasses, Watches, Fabrics, and Video Self Modelling in Education and Training: A systematic review and comparison of use cases

    Abstract

    Abstract

    We are living in an age of the “Internet of Things”(IoT) and “Internet of Self”(IoS), pervasive and omnipresent electronic media and “quantified self” at the physical and biochemical levels. Real time monitoring of self through glasses, watches, wearable computing devices, including fabrics can be harnessed for education.

    The use of video is now ubiquitous in learning including the use of short sequences demonstrating practice exercises and instructional sequences (eg Khan Academy) allowing anytime anywhere study. We need to be clear we are talking about the opportunity to learn, opportunity becomes learning when the individual engages in a cognitive process, wearing or carrying a device provides the opportunity, cognition the learning. Rapid learning from the future and its associated self model theory (Dowrick 2012) draws on over four decades of self modeling using purposefully constructed videos. These have been used to teach, through observation, individuals skills and procedures that they are not able to achieve at present, but by viewing a possible future depicting the individual successfully engaged in achieving, rapid learning takes place usually within several viewings. These “Feedforward” video clips are typically less than two minutes in length (Dowrick 1976).

    Despite several implementations of the self measurement technologies, it is not clear how self modeling and emergent technologies based on the Internet of Things, wearable computing, and personal monitoring devices compare and contrast with each other to further education. It is clear that the internet of things and the internet of self (personalized learning opportunities) play and will continue to play a huge part in the developing world. The objective of this paper is to provide a comprehensive survey of the literature in the form of a systematic implementations with what is known about the Internet of self through the effectiveness of self modeling. Such a comparison will be helpful in predicting the potential success and may provide new directions for the use of the emerging tools.

    The organization of the paper will be in three parts as follows: a brief background history of the emergence of the Internet of Things, the concept of video self modeling and describe their potential in changing teaching and learning practices in the tertiary sector particularly in professional education a systematic review of the effectiveness of the emergent technologies (IoT, and wearable computing devices) for educational purposes, and finally, we shall provide a synthesis of how the more effective technologies can be compared, contrasted, and combined with the practices of self modeling to foster effective learning.

    We shall select English language intervention studies published in the last 10 years. The review, will critically appraise information identifying possible biases, ascertain the quality of the studies, and rank order the publications. We will estimate summary effect sizes for differing combinations wherever possible. The resulting discussion of the Internet of Things and self will inform pedagogical tools for rapid learning.

    Introduction or Background

    We are living in an age of the “Internet of Things”(IoT) and “Internet of Self”(IoS), pervasive and omnipresent electronic media and “quantified self” at the physical and biochemical levels. Real time monitoring of self through glasses, watches, wearable computing devices, including fabrics can be harnessed for education.

    The use of video is now ubiquitous in learning including the use of short sequences demonstrating practice exercises and instructional sequences (eg Khan Academy) allowing anytime anywhere study. We need to be clear we are talking about the opportunity to learn, opportunity becomes learning when the individual engages in a cognitive process, wearing or carrying a device provides the opportunity, cognition the learning. Rapid learning from the future and its associated self model theory (Dowrick 2012) draws on over four decades of self modeling using purposefully constructed videos. These have been used to teach, through observation, individuals skills and procedures that they are not able to achieve at present, but by viewing a possible future depicting the individual successfully engaged in achieving, rapid learning takes place usually within several viewings. These “Feedforward” video clips are typically less than two minutes in length (Dowrick 1976).

    Despite several implementations of the self measurement technologies, it is not clear how self modeling and emergent technologies based on the Internet of Things, wearable computing, and personal monitoring devices compare and contrast with each other to further education. It is clear that the internet of things and the internet of self (personalized learning opportunities) play and will continue to play a huge part in the developing world. The objective of this paper is to provide a comprehensive survey of the literature in the form of a systematic implementations with what is known about the Internet of self through the effectiveness of self modeling. Such a comparison will be helpful in predicting the potential success and may provide new directions for the use of the emerging tools.

    The organization of the paper will be in three parts as follows: a brief background history of the emergence of the Internet of Things, the concept of video self modeling and describe their potential in changing teaching and learning practices in the tertiary sector particularly in professional education a systematic review of the effectiveness of the emergent technologies (IoT, and wearable computing devices) for educational purposes, and finally, we shall provide a synthesis of how the more effective technologies can be compared, contrasted, and combined with the practices of self modeling to foster effective learning.

    Methods

    Study Questions

    What is the effectiveness of the Internet of Things, and wearable computing for teaching and learning? How does this compare and contrast with the effectiveness of video self modelling?

    Inclusion and Exclusion Criteria for the selection of the studies

    English language Studies were included be included in this review if:

    1. Published within the last 10 years
    2. The studies test the effectiveness of the Internet of Things or Connectted Devices
    3. The studies test effectiveness of using these devices in the classroom settings, or for personal or professional education
    4. The studies employ a valid comparison group
    5. The resaarch question or outcome that the studies examine relate to an educational or learning outcome
    6. If the studies do not match any of the above six criteria, then the study will be excluded from the scope of this review.
    7. A study originally published in another language and made available with a reliable English language translation will be considered for review.
    8. If a study is not included as a primary study or systematic or non-systematic acadeic review, then the study will not be included in the review.
    9. We also did not consider only newspaper reports, or letters to the editor unless these reports had links to studies and in those cases, original studies were included for review

    Search Terms and Search Criteria

    • Initially, the following databases will be searched for identification of studies: Medline (pubmed), EMBASE, ERIC, Google Scholar, and the composite database in the University of Canterbury Library
    • Reference List of the articles included in the studies will be searched for further information
    • Google and Bing Academic Search Engines
    • Hand Searches for additional studies that may not have been published in the scholarly journal article databases
    • Prominent researchers in the filed were contacted to provide inputs for further studies that we could have otherwise missed

    The Search Algorithm

    Add the search algorithm here. Perhaps with a table

    Critical Appraisal and Summary of the studies