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Technology acceptance of augmented reality and wearable technologies ilrn 2017 slides

"Technology Acceptance of Augmented Reality and Wearable Technologies" #TAM at #iLRN2017
by Fridolin Wild, Roland Klemke, Paul Lefrere, Mikhail Fominykh and Timo Kuula
Paper presented at the 3rd Immersive Learning Research Network Conference in Coimbra, Portugal on 28 June 2017
Publication: https://link.springer.com/chapter/10.1007/978-3-319-60633-0_11

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Technology acceptance of augmented reality and wearable technologies ilrn 2017 slides

  1. 1. 29/06/2017 WEARABLE EXPERIENCE FOR KNOWLEDGE-INTENSIVE TRAINING 687669 WEKIT 1 Technology Acceptance of Augmented Reality and Wearable Technologies presented by Mikhail Fominykh, Europlan UK ltd MIKHAIL.FOMINYKH@EUROPLAN-UK.EU
  2. 2. 29/06/2017 WEARABLE EXPERIENCE FOR KNOWLEDGE-INTENSIVE TRAINING 687669 WEKIT 2 Team Fridolin Wild Performance Augmentation Lab, Oxford Brookes University, UK wild@brookes.ac.uk Roland Klemke Open University of the Netherlands Roland.Klemke@ou.nl Paul Lefrere CCA Ltd, UK paul.lefrere@cca-research.co.uk Mikhail Fominykh Europlan Ltd, UK mikhail.fominykh@europlan-uk.eu Timo Kuula VTT, Finland Timo.Kuula@vtt.fi
  3. 3. Motivation: Immersive Learning Immersive Learning is a dynamic area: Societal needs evolve to require new learning goals & methods Enabling technologies include new mixes (eg AR + wearables) R&D into immersive learning finds promising ways to address long-standing needs (eg faster learning, from peers, at lower cost) 29/06/2017 WEARABLE EXPERIENCE FOR KNOWLEDGE-INTENSIVE TRAINING 687669 WEKIT 3
  4. 4. Motivation: Technology Acceptance Models Technology Acceptance Models (TAMs) can predict which aspects of which R&D innovations fit which Stakeholder needs. The technology acceptance aspects of each generation of learning technology require re- evaluation, to assess user satisfaction with new affordances, experiences & possibilities. 29/06/2017 WEARABLE EXPERIENCE FOR KNOWLEDGE-INTENSIVE TRAINING 687669 WEKIT 4
  5. 5. Technology Acceptance Models & Immersive Learning Stakeholder acceptance of new generations of Immersive-Learning technology depends on ‘fit’ between Technology, Needs, Wants: 1. Technology-push: eg immersive learning exploiting advances in entertainment-focused input & output technologies in mobile devices (such as sensors for eye-tracking in augmented reality) 2. Demand-pull: eg learners who judge immersive learning solutions in terms of their use of the latest phone’s new features 3. TAMs: broaden to include possible changes in eg our capacity to re- experience & reflect upon our own experiences; our ability to share actual experiences; our capacity to synthesize partly-false memories that combine fragments of our direct experiences & synthesized third-party experiences; etc 29/06/2017 WEARABLE EXPERIENCE FOR KNOWLEDGE-INTENSIVE TRAINING 687669 WEKIT 5
  6. 6. 29/06/2017 WEARABLE EXPERIENCE FOR KNOWLEDGE-INTENSIVE TRAINING 687669 WEKIT 6 WEKIT Funding: EU Horizon 2020, ICT-20 2015: Technologies for better human learning and teaching Budget: EUR 2.753.143,75 WEKIT Community https://wekit-community.org/ WEKIT project website http://wekit.eu/
  7. 7. Experience and knowledge Learning = = converting experience to knowledge immediate experience (aka ‘practice’) information for a master level (aka ‘theory’) separated 29/06/2017 WEARABLE EXPERIENCE FOR KNOWLEDGE-INTENSIVE TRAINING 687669 WEKIT 8 Mikhail Fominykh, Fridolin Wild, Carl Smith, Victor Alvarez and Mikhail Morozov: "An Overview of Capturing Live Experience with Virtual and Augmented Reality”, DOI: 10.3233/978-1-61499-530-2-298.
  8. 8. Experience and knowledge Learning = = converting experience to knowledge immediate experience (aka ‘practice’) information for a master level (aka ‘theory’) Experiencedlearner 29/06/2017 WEARABLE EXPERIENCE FOR KNOWLEDGE-INTENSIVE TRAINING 687669 WEKIT 9
  9. 9. Methodology What is Wearable Experience? 29/06/2017 WEARABLE EXPERIENCE FOR KNOWLEDGE-INTENSIVE TRAINING 10 The Wearable Experience training methodology aims to provide an innovative learning method that is based on the idea of capturing the experience of an expert and enabling trainees to wear it while re-enacting, thus giving the trainee access to the tacit knowledge of the expert and enabling master-apprentice knowledge sharing. Capture Re-enact Evaluate Bibeg Limbu, Mikhail Fominykh, Roland Klemke, Marcus Specht, and Fridolin Wild: "Supporting Training of Expertise with Wearable Technologies”, Springer, in press.
  10. 10. 29/06/2017 WEARABLE EXPERIENCE FOR KNOWLEDGE-INTENSIVE TRAINING 687669 WEKIT 11 Hardware design
  11. 11. TAMs for benchmarking acceptance of AR/WT solutions AR/WT solutions have widely-varying form factors & user interfaces. These set constraints on AR/WT acceptance, limiting how we construct acceptance scales & then benchmark solutions. Comments on scale-construction & benchmarking in the application areas of WEKIT: 1. AR/WT in Aviation 2. AR/WT in Medicine 3. AR/WT in Space 29/06/2017 WEARABLE EXPERIENCE FOR KNOWLEDGE-INTENSIVE TRAINING 687669 WEKIT 12 Structural Equation Model of the Unified Theory of Acceptance and Use of Technology (Venkatesh et al., 2003)
  12. 12. Methodology 1. Collecting items from existing TAMs (91 items) 2. Testing reliability and measuring internal validity (15 subjects) ◦ Measuring the correlation (Pearson’s r) across the responses with the sum scores of all items ◦ Calculating the item-to-item correlations to identify further those items loading onto the same construct ◦ Measuring Cronbach’s α to estimate interrater reliability, comparing the reliability for the full pool as well as the final subset selection 3. Running the resultant questionnaire with experts (33 subjects) 29/06/2017 WEARABLE EXPERIENCE FOR KNOWLEDGE-INTENSIVE TRAINING 687669 WEKIT 13
  13. 13. Item pool generation and reduction 29/06/2017 WEARABLE EXPERIENCE FOR KNOWLEDGE-INTENSIVE TRAINING 687669 WEKIT 14 0.3 0.4 0.5 0.6 0.7 0.8 Number of items for different Pearson's correlation coefficient thresholds 020406080 69 64 45 36 12 2
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  15. 15. Excluded items ▪ Anxiety (group CANX) does not correlate with the sum scores (probably not relevant for work context) ▪ Questions about management support are too early to ask (lack of exposure) ▪ Questions about integration with legacy systems do not work (need the right users) ▪ Appeal of the workplace to younger people is out of place (respondents may not know this) ▪ Content and content experience could not be answered (maybe end-users do not see this separation between content and system) ▪ Privacy (may be a result of lack of exposure) ▪ Value for money (need the right users) 29/06/2017 WEARABLE EXPERIENCE FOR KNOWLEDGE-INTENSIVE TRAINING 687669 WEKIT 16
  16. 16. Item grouping Analysis of the 36 included items and their item groups provides the following: Several items correlate highly within their group and a choice can be made for the phrasing with more clarity or for the aesthetically more pleasing formulation 29/06/2017 WEARABLE EXPERIENCE FOR KNOWLEDGE-INTENSIVE TRAINING 687669 WEKIT 17
  17. 17. Final questionnaire 29/06/2017 WEARABLE EXPERIENCE FOR KNOWLEDGE-INTENSIVE TRAINING 687669 WEKIT 18 CODE STATEMENT ATU4 I look forward to those aspects of my job that require me to use AR & WT. CSE4 I could complete a job, if I had used similar technologies before this one to do the same job. EE2 My interaction with AR & WT is clear and understandable. FC1 I have the resources necessary to use AR & WT. HM2b I like working with AR & WT. HT2 I am addicted to using AR & WT. IMG1 People in my organization who use AR & WT have more prestige than those who do not. IMG4 I use AR & WT solutions, because I want to be a forerunner in technology exploitation. IOP1 Interoperability is important for AR & WT. IOP2 I am worried about vendor lock in with AR & WT. IOP3 Integration costs of AR & WT with other software systems in use are high. IS6 I would find it useful if my friends knew where I am and what I am doing. LRN1 Learning curve for AR & WT is too high compared with the value they would offer. PE10 With AR & WT, I immediately know when a task is finished. PE4 Using AR & WT increases my productivity. PE8 AR & WT increase precision of tasks. SI1 People who are important to me think that I should use AR & WT. BI2 I will always try to use AR & WT in my daily life. UF1 Please choose your usage frequency of AR/WT Freq.
  18. 18. Current level of Technology Acceptance 29/06/2017 WEARABLE EXPERIENCE FOR KNOWLEDGE-INTENSIVE TRAINING 687669 WEKIT 19 Technology Acceptance and Use Strongly Disagree Disagree Somewhat Disagree Neither agree or disagree Somewhat agree Agree Strongly Agree ATU4 BI2 CSE4EE2 FC1HM2bHT2 IMG1IMG4IOP1IOP2IOP3 IS6 LRN1PE10 PE4 PE8 SI1 Inverse item
  19. 19. Conclusions (1) A metric scale to assess technology acceptance with constructs and items beyond existing models: Interoperability Learnability Privacy 29/06/2017 WEARABLE EXPERIENCE FOR KNOWLEDGE-INTENSIVE TRAINING 687669 WEKIT 20
  20. 20. Conclusions (2) Action required: Equip workers with devices Match high expectations Issues: Device management Legacy integration Lack of social influence Lack of concern about privacy 29/06/2017 WEARABLE EXPERIENCE FOR KNOWLEDGE-INTENSIVE TRAINING 687669 WEKIT 21
  21. 21. 29/06/2017 WEARABLE EXPERIENCE FOR KNOWLEDGE-INTENSIVE TRAINING 687669 WEKIT 22
  22. 22. 29/06/2017 WEARABLE EXPERIENCE FOR KNOWLEDGE-INTENSIVE TRAINING 687669 WEKIT 23
  23. 23. 29/06/2017 WEARABLE EXPERIENCE FOR KNOWLEDGE-INTENSIVE TRAINING 687669 WEKIT 24
  24. 24. Disclaimer This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 687669. http://wekit.eu/ Q & A Presented by Mikhail Fominykh mikhail.fominykh@europlan-uk.eu 29/06/2017 WEARABLE EXPERIENCE FOR KNOWLEDGE-INTENSIVE TRAINING 687669 WEKIT 25

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  • RalfMastwijk

    Jul. 8, 2017
  • ClementBaptiste

    May. 3, 2019

"Technology Acceptance of Augmented Reality and Wearable Technologies" #TAM at #iLRN2017 by Fridolin Wild, Roland Klemke, Paul Lefrere, Mikhail Fominykh and Timo Kuula Paper presented at the 3rd Immersive Learning Research Network Conference in Coimbra, Portugal on 28 June 2017 Publication: https://link.springer.com/chapter/10.1007/978-3-319-60633-0_11

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