Skip to main content
SpringerLink
Log in
Book cover

International Conference on Human-Computer Interaction

HCII 2020: Virtual, Augmented and Mixed Reality. Design and Interaction pp 135–151Cite as

Towards a Predictive Framework for AR Receptivity

  • Conference paper
  • First Online:

  • 2416 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12190))

Abstract

Given the sometimes disparate findings and the increasing application of AR in both training and operations, as well as increased affordability and availability, it is important for researchers, user interface and user experience (UI/UX) designers, and AR technology developers to understand the factors that impact the utility of AR. To increase the potential for realizing the full benefit of AR, adequately detailing the interrelated factors that drive outcomes of different AR usage schemes is imperative. A systematic approach to understanding influential factors, parameters, and the nature of the influence on performance provides the foundation for developing AR usage protocols and design principles, which currently are few. Toward this end, this work presents a theoretical model of factors impacting performance with AR systems. The framework of factors, including task, human, and environmental factors, conceptualizes the concept of “AR Receptivity”, which aims to characterize the degree to which the application of AR usage is receptive to the technology design and capabilities. The discussion begins with a brief overview of research efforts laying the foundation for the model’s development and moves to a review of receptivity as a concept of technology suitability. This work provides details on the model and factor components, concluding with implications for application of AR in both the training and operational settings.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Azuma, R.: A survey of augmented reality. Presence Teleoperators Virtual Environ. 6(4), 355–385 (1997)

    Article  Google Scholar 

  2. Lee, K.: Augmented reality in education and training. TechTrends 56(2), 13–21 (2012)

    Article  Google Scholar 

  3. Dunleavy, M., Dede, C., Mitchell, R.: Affordances and limitations of immersive participatory augmented reality simulations for teaching and learning. J. Sci. Educ. Technol. 18(1), 7–22 (2009)

    Article  Google Scholar 

  4. Sääski, J., Salonen, T., Hakkarainen, M., Siltanen, S., Woodward, C., Lempiäinen, J.: Integration of design and assembly using augmented reality. In: Ratchev, S., Koelemeijer, S. (eds.) IPAS 2008. IIFIP, vol. 260, pp. 395–404. Springer, Boston, MA (2008). https://doi.org/10.1007/978-0-387-77405-3_39

    Chapter  Google Scholar 

  5. Hou, L.: Evaluating the use of augmented reality to facilitate assembly. Curtin theses (2013). https://espace.curtin.edu.au/bitstream/handle/20.500.11937/2125/190332_Hou2013.pdf?sequence=2&isAllowed=y

  6. Jung, S., Lee, D., Biocca, F.: Psychological effects on 3 Dimensions projection mapping versus 2 dimensions: exploratory study. In: Proceedings of the International Society for Presence Research 2014, pp. 213–222 (2014)

    Google Scholar 

  7. Lambie, A.J.: Directing attention in an augmented reality environment: an attentional tunneling evaluation. Thesis, Rochester Institute of Technology (2015). https://pdfs.semanticscholar.org/2b60/6c3c0e1e8afe2cdb2456a61909451f6b544e.pdf

  8. Webel, S., Engelke, T., Peveri, M., Olbrich, M., Preusche, C.: Augmented reality training for assembly and maintenance skills. In: BIO Web of Conferences, vol. 1, p. 97 (2011)

    Google Scholar 

  9. Gabbard, J.L., Mehra, D.G., Swan, J.E.: Effects of AR display context switching and focal distance switching on human performance. IEEE Trans. Visual Comput. Graphics 25(6), 2228–2241 (2018)

    Article  Google Scholar 

  10. Schmidt-Daly, T.N., Riley, J.M., Hale, K.S., Yacht, D., Hart, J.: Augmented REality Sandtables (ARESs) Impact on Learning (No. ARL-CR-0803). Design Interactive, Inc. Orlando United States (2016)

    Google Scholar 

  11. Amburn, C.R., Vey, N.L., Boyce, M.W., Mize, J.R.: The augmented reality sandtable (ARES) (No. ARL-SR-0340). Army Research Lab Aberdeen Proving Ground MD, Human Research and Engineering Directorate (2015)

    Google Scholar 

  12. Juan, C., Beatrice, F., Cano, J.: An augmented reality system for learning the interior of the human body. In: 2008 Eighth IEEE International Conference on Advanced Learning Technologies, pp. 186–188. IEEE (2008)

    Google Scholar 

  13. Cheng, K.H., Tsai, C.C.: Affordances of augmented reality in science learning: suggestions for future research. J. Sci. Educ. Technol. 22(4), 449–462 (2013)

    Article  Google Scholar 

  14. Schmidt-Daly, T.N., Riley, J.M., Amburn, C.R., Hale, K.S., David Yacht, P.: Video game play and effect on spatial knowledge tasks using an augmented sand table. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 60, no. 1, pp. 1429–1433. SAGE Publications, Los Angeles (2016)

    Google Scholar 

  15. Khademi, M., Hondori, H.M., Dodakian, L., Cramer, S., Lopes, C.V.: Comparing “pick and place” task in spatial augmented reality versus non-immersive virtual reality for rehabilitation setting. In: 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 4613–4616. IEEE (2013)

    Google Scholar 

  16. Mousavi Hondori, H., Khademi, M., Dodakian, L., Cramer, S., Lopes, C.: A spatial augmented reality rehab system for post-stroke hand rehabilitation. Stud. Health Technol. Inform. 184, 279–285 (2013)

    Google Scholar 

  17. Condino, S., Carbone, M., Piazza, R., Ferrari, M., Ferrari, V.: Perceptual limits of optical see-through visors for augmented reality guidance of manual tasks. IEEE Trans. Biomed. Eng. 67, 411–419 (2020)

    Article  Google Scholar 

  18. Werrlich, S., Eichstetter, E., Nitsche, K., Notni, G.: An overview of evaluations using augmented reality for assembly training tasks. Int. J. Comput. Inf. Eng. 11(10), 1068–1074 (2017)

    Google Scholar 

  19. Kennedy, R.S., Stanney, K., Dunlap, W.P.: Duration and exposure to virtual environments: Sickness curves during and across sessions. Presence Teleoperators Virtual Environ. 9, 463–472 (2000)

    Article  Google Scholar 

  20. Zhang, J., Liu, T.C., Sung, Y.T., Chang, K.E.: Using augmented reality to promote homogeneity in learning achievement. In: 2015 IEEE International Symposium on Mixed and Augmented Reality-Media, Art, Social Science, Humanities and Design, pp. 1–5. IEEE (2015)

    Google Scholar 

  21. Chen, C., Wang, C.-H.: Employing augmented-reality-embedded instruction to disperse the imparities of individual differences in earth science learning. J. Sci. Educ. Technol. 24, 835–847 (2015). https://doi.org/10.1007/s10956-015-9567-3

    Article  Google Scholar 

  22. Stanney, K.M., Fidopiastis, C., Foster, L.: Virtual reality is sexist: but it does not have to be. Front. Robot. AI 7, 4. https://doi.org/10.3389/frobt.2020.00004011

  23. Servotte, J.C., et al.: Virtual reality experience: immersion, sense of presence, and cybersickness. Clin. Simul. Nurs. 38, 35–43 (2020)

    Article  Google Scholar 

  24. Riley, J.M., Kaber, D.B., Draper, J.V.: Situation Awareness and attention allocation measures for quantifying telepresence experiences in teleoperation. Hum. Factors Ergon. Manuf. 14(1), 51–67 (2004)

    Article  Google Scholar 

  25. Witmer, B.G., Bailey, J.H., Knerr, B.W., Parsons, K.C.: Virtual spaces and real world places: transfer of route knowledge. Int. J. Hum. Comput. Stud. 45(4), 413–428 (1996)

    Article  Google Scholar 

  26. Witmer, B.G., Singer, M.J.: Measuring presence in virtual environments: a presence questionnaire. Presence 7(3), 225–240 (1998)

    Article  Google Scholar 

  27. Azuma, R.T.: The challenge of making augmented reality work outdoors. In: Mixed Reality: Merging Real and Virtual Worlds, pp. 379–390 (1999)

    Google Scholar 

  28. Jeffrey, P., Seaton, R.A.F.: A conceptual model of ‘receptivity’ applied to the design and deployment of water policy mechanisms. Environ. Sci. 1(3), 277–300 (2004)

    Article  Google Scholar 

  29. Weng, F., Rong-Jou, Y., Hann-Jang, H., Hui-Mei, S.: A TAM-based study of attitude towards use intention of multimedia among school teachers. Appl. Syst. Innov. 1, 36 (2018). https://doi.org/10.3390/asi1030036

    Article  Google Scholar 

  30. Davis, F.D.: Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Q. 13, 319–340 (1989). https://doi.org/10.2307/249008

    Article  Google Scholar 

  31. Patten, C., et al.: Survey of potential receptivity to robotic-assisted exercise coaching in a diverse sample of smokers and nonsmokers. PLoS ONE 13(5), e0197090 (2018)

    Article  Google Scholar 

  32. Jabeen, F., Khan, M., Ahmad, S.Z.: Understanding the technology receptivity in higher education: evidence from the UAE. Int. J. Technol. Hum. Interact. (IJTHI) 14(3), 39–52 (2018)

    Article  Google Scholar 

  33. Fidopiastis, C.: User-centered virtual environment assessment and design for cognitive rehabilitation applications. Electronic Theses and Dissertations, University of Central Florida (2006). https://stars.library.ucf.edu/etd/911/

  34. Lu, H.P., Chiou, M.J.: The impact of individual differences on e-learning system satisfaction: a contingency approach. Br. J. Edu. Technol. 41(2), 307–323 (2010)

    Article  Google Scholar 

  35. Stanney, K.: Realizing the full potential of virtual reality: human factors issues that could stand in the way. In: Proceedings Virtual Reality Annual International Symposium 1995, pp. 28–34. IEEE (1995)

    Google Scholar 

  36. Broll, W., Lindt, I., Herbst, I., Ohlenburg, J., Braun, A.K., Wetzel, R.: Toward next-gen mobile AR games. IEEE Comput. Graphics Appl. 28(4), 40–48 (2008)

    Article  Google Scholar 

  37. Klopfer, E., Yoon, S.: Developing games and simulations for today and tomorrow’s tech savvy youth. TechTrends 49(3), 33–41 (2004)

    Article  Google Scholar 

  38. Wu, H.K., Lee, S.W.Y., Chang, H.Y., Liang, J.C.: Current status, opportunities and challenges of augmented reality in education. Comput. Educ. 62, 41–49 (2013)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Design Interactive Inc., Orlando, Fl, 32817, USA

    Jennifer M. Riley, Jesse D. Flint, Cali M. Fidopiastis & Kay M. Stanney

  2. U.S. Department of Veterans Affairs, Washington, DC, USA

    Darren P. Wilson

Authors
  1. Jennifer M. Riley
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jesse D. Flint
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Darren P. Wilson
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Cali M. Fidopiastis
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Kay M. Stanney
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jesse D. Flint .

Editor information

Editors and Affiliations

  1. U.S. Army Research Laboratory, Aberdeen Proving Ground, MD, USA

    Jessie Y. C. Chen

  2. U.S. Army Combat Capabilities Development Command, Orlando, FL, USA

    Gino Fragomeni

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Riley, J.M., Flint, J.D., Wilson, D.P., Fidopiastis, C.M., Stanney, K.M. (2020). Towards a Predictive Framework for AR Receptivity. In: Chen, J.Y.C., Fragomeni, G. (eds) Virtual, Augmented and Mixed Reality. Design and Interaction. HCII 2020. Lecture Notes in Computer Science(), vol 12190. Springer, Cham. https://doi.org/10.1007/978-3-030-49695-1_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-49695-1_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-49694-4

  • Online ISBN: 978-3-030-49695-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation