Skip to main content
SpringerLink
Log in

Towards a Computerized Approach to Identify Attentional States of Online Learners

  • Conference paper
  • First Online:
HCI International 2021 - Late Breaking Papers: Cognition, Inclusion, Learning, and Culture (HCII 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 13096))

Included in the following conference series:

  • 1239 Accesses

Abstract

In this study we investigated how digital leaners’ behavior could be used to identify their attentional state at the time. It was expected to map attentional states with the level of challenge presented and the level of engagement achieved by an activity related to learning. To identify the main attentional considerations and related behavior, we have administered a questionnaire among 43 participants and requested them to self-report on attentional states, the measures of motivation, and the required effort. The questionnaire was adapted from Everyday Life attentional Scale (ELAS), and tested on 6 activities related to learning, directly or indirectly. The average level of focus the participants reported on these activities ranged from 50%–65%. They also declared to feel restless (53.5%) and stressed (41.9%) when motivated to do a task. Interestingly, 67.4% of the participants attributed to social media use when distracted from the learning activity. This study opens several avenues to use behavioral data of digital learners to identify the attentional state shifts of digital learners. Relationships among the cognitive load, the behavioral interactions, and level of attention can be observed. However, the nature and the magnitude of such relationships are yet to be explored.

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

Access this chapter

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 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
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

Institutional subscriptions

Similar content being viewed by others

References

  1. Fuermaier, A.B.M., Groen, Y., Tucha, L., Weisbrod, M., Aschenbrenner, S.F., Tucha, O.: Everyday Life Attention Scale (ELAS): normative data of n = 1,874 dutch participants. Applied Neuropsychology: Adult (2019). https://doi.org/10.1080/23279095.2019.1605994

  2. Adler, R.F., Benbunan-Fich, R.: Juggling on a high wire: multitasking effects on performance. Int. J. Hum.-Comput. Stud. 70, 156–168 (2012). https://doi.org/10.1016/j.ijhcs.2011.10.003

    Article  Google Scholar 

  3. Adler, R.F., Benbunan-Fich, R.: The effects of task difficulty and multitasking on performance. Interact. Comput. 27, 430–439 (2015). https://doi.org/10.1093/iwc/iwu005

    Article  Google Scholar 

  4. Bailey, B.P., Konstan, J.A.: On the need for attention-aware systems: measuring effects of interruption on task performance, error rate, and affective state. Comput. Hum. Behav. 22, 685–708 (2006). https://doi.org/10.1016/j.chb.2005.12.009

    Article  Google Scholar 

  5. Chen, C.-M., Wang, J.Y., Yu, C.M.: Assessing the attention levels of students by using a novel attention aware system based on brainwave signals. Br. J. Educ. Technol. 48(2), 348–369 (2017). https://doi.org/10.1111/bjet.12359

  6. Clark, R.C., Mayer, R.E.: E-Learning and the Science of Instruction, 4th edn. Wiley, Hoboken (2016)

    Google Scholar 

  7. Czerwinski, M., Horvitz, E., Wilhite, S.: A diary study of task switching and interruptions. ACM Press, pp. 175–182 (2016). https://doi.org/10.1145/985692.985715

  8. Davidson, C.N.: Now you see it: how the brain science of attention will transform the way we live, work, and learn. Viking, New York (2011)

    Google Scholar 

  9. Ferri, F., Grifoni, P., Guzzo, T.: Online learning and emergency remote teaching: opportunities and challenges in emergency situations. Societies 10(4), 86 (2020). https://doi.org/10.3390/soc10040086

    Article  Google Scholar 

  10. Foehr, U.G.: Media Multitasking among American Youth: Prevalence, Predictors and Pairings (Unpublished PhD Thesis). Stanford, CA, USA (2003)

    Google Scholar 

  11. Forster, S., Lavie, N.: Harnessing the wandering mind: the role of perceptual load. Cognition 111, 345–355 (2009). https://doi.org/10.1016/j.cognition.2009.02.006

    Article  Google Scholar 

  12. Forster, S.: Distraction and mind-wandering under load. Front. Psychol. 4, 283(2013). https://doi.org/10.3389/fpsyg.2013.00283

  13. Gonázlez, V.M., Mark, G.: Constant, constant, multi-tasking craziness: managing multiple working spheres. ACM Press, pp. 113–120 (2004). https://doi.org/10.1145/985692.985707

  14. Iqbal, S.T., Horvitz, E.: Disruption and recovery of computing tasks: field study, analysis, and directions. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, p. 677. ACM Press, New York City (2007). https://doi.org/10.1145/1240624.1240730

  15. Jo, J., Kim, B., Seo, J.: EyeBookmark: assisting recovery from interruption during reading. In: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, pp. 2963–2966. ACM Press, New York City (2015). https://doi.org/10.1145/2702123.2702340

  16. Kushlev, K., Proulx, J., Dunn, E.W.: Silence your phones : smartphone notifications increase inattention and hyperactivity symptoms. In: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, pp. 1011–1020. ACM Press, New York City (2016). https://doi.org/10.1145/2858036.2858359

  17. Laurie-Rose, C., Frey, M., Ennis, A., Zamary, A.: Measuring perceived mental workload in children. Am. J. Psychol. 127, 107–125 (2014)

    Article  Google Scholar 

  18. Lavie, N., Beck, D.M., Konstantinou, N.: Blinded by the load: attention, awareness and the role of perceptual load. Philos. Trans. R. Soc. B Biol. Sci. 369, 20130205–20130205 (2014). https://doi.org/10.1098/rstb.2013.0205

    Article  Google Scholar 

  19. Lavie, N., Hirst, A., de Fockert, J.W., Viding, E.: Load theory of selective attention and cognitive control. J. Exp. Psychol. Gen. 133(3), 339–354 (2004). https://doi.org/10.1037/0096-3445.133.3.339

    Article  Google Scholar 

  20. Lee, U., et al.: Hooked on smartphones: an exploratory study on smartphone overuse among college students. ACM Press, pp. 2327–2336 (2014). https://doi.org/10.1145/2556288.2557366

  21. LNCS Homepage. http://www.springer.com/lncs. Accessed 4 Oct 2017

  22. Lottridge, D.M., et al.: The effects of chronic multitasking on analytical writing. In: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, pp. 2967–2970. ACM Press, New York City (2015). https://doi.org/10.1145/2702123.2702367

  23. Mark, G., Iqbal, S.T., Czerwinski, M., Johns, P., Sano, A.: Neurotics can’t focus: an in situ study of online multitasking in the workplace. In: Presented at the CHI 2016, pp. 1739–1744. ACM Press, New York City (2016). https://doi.org/10.1145/2858036.2858202

  24. Mark, G., Iqbal, S.T., Czerwinski, M., Johns, P.: Bored mondays and focused afternoons: the rhythm of attention and online activity in the workplace. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 3025–3034. ACM Press, New York City (2014) https://doi.org/10.1145/2556288.2557204

  25. Mark, G., Iqbal, S.T., Czerwinski, M., Johns, P., Sano, A., Lutchyn, Y.: Email duration, batching and self-interruption: patterns of email use on productivity and stress. In: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, pp. 1717–1728. ACM Press, New York City (2016).https://doi.org/10.1145/2858036.2858262

  26. Monk, T.H., Buysse, D.J., Potts, J.M., DeGrazia, J.M., Kupfer, D.J.: Morningness-eveningness and lifestyle regularity. Chronobiol. Int. 21, 435–443 (2004). https://doi.org/10.1081/CBI-120038614

    Article  Google Scholar 

  27. NASA Task Load Index (TLX), n.d

    Google Scholar 

  28. Chen, P.S.D., Lambert, A.D., Guidry, K.R.: Engaging online learners: the impact of Web-based learning technology on college student engagement. Comput. Educ. 54(4), 1222–1232 (2010). ISSN 0360–1315, https://doi.org/10.1016/j.compedu.2009.11.008

  29. Deng, Q., Wu, Z.: Students’ attention assessment in elearning based on machine learning. In: proceedings Earth and Environmental Science, vol. 199 (2018). https://doi.org/10.1088/1755-1315/199/3/032042

  30. Rodgers, S., Maloney, B., Ploderer, B., Brereton, M.: Managing Stress, Sleep and Technologies: An Exploratory Study of Australian University Students. Presented at the ozCHI, Launceton, TAS, Australia (2016)

    Google Scholar 

  31. Sharma, K., Jermann, P., Dillenbourg, P.: With-me-ness: A gaze-measure for students’ attention in MOOCs. In: ICLS (2014)

    Google Scholar 

  32. Tubbs-Cooley, H.L., Mara, C.A., Carle, A.C., Gurses, A.P.: The NASA Task Load Index as a measure of overall workload among neonatal, paediatric and adult intensive care nurses. Care Nurs, Intensive Crit (2018). https://doi.org/10.1016/j.iccn.2018.01.004

  33. Wang, R., et al.: StudentLife: assessing mental health, academic performance and behavioral trends of college students using smartphones. In: Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, pp. 3–14. ACM Press, New York City (2014). https://doi.org/10.1145/2632048.2632054

  34. Xiao, X., Wang, J.: Undertanding and detecting divided attention in mobile MOOC learning. ACM Press, pp. 2411–2415 (2017). https://doi.org/10.1145/3025453.3025552

  35. Groen, Y., Fuermaier, A.B.M., Tucha, L., Weisbrod, M., Aschenbrenne, S., Tucha, O.: A situation-specific approach to measure attention in adults with ADHD: the everyday life attention scale (ELAS). Appl. Neuropsychol. Adult 26(5), 411–440 (2019). https://doi.org/10.1080/23279095.2018.1437730

    Article  Google Scholar 

Download references

Acknowledgements

We would like to acknowledge the participants of this questionnaire-based survey who contributed voluntarily. We thank the administration of Faculty of Information Technology, University of Moratuwa, Sri Lanka for granting us permissions to administer the questionnaire, and the academics who got involved in questionnaire validation. I would also acknowledge the Senate Research Committee (SRC) of University of Moratuwa, Sri Lanka for the financial assistance (Grant number: SRC/ST/2021/20) for this project.

Author information

Authors and Affiliations

  1. Faculty of Inforamtion Technology, University of Moratuwa, Katubedda, Moratuwa, Sri Lanka

    Indika Karunaratne

  2. University of Colombo School of Computing, Colombo, Sri Lanka

    Ajantha S. Atukorale

Authors
  1. Indika Karunaratne
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ajantha S. Atukorale
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Indika Karunaratne .

Editor information

Editors and Affiliations

  1. University of Crete and Foundation for Research and Technology – Hellas (FORTH), Heraklion, Crete, Greece

    Constantine Stephanidis

  2. Coventry University, Coventry, UK

    Don Harris

  3. Safety and Accident Investigation Centre, Cranfield University, Cranfield, UK

    Wen-Chin Li

  4. Soar Technology Inc., Orlando, FL, USA

    Dylan D. Schmorrow

  5. Design Interactive, Inc., Orlando, FL, USA

    Cali M. Fidopiastis

  6. Foundation for Research and Technology – Hellas (FORTH), Heraklion, Crete, Greece

    Margherita Antona

  7. Tsinghua University, Beijing, China

    Qin Gao

  8. Chongqing University, Chongqing, China

    Jia Zhou

  9. Department of Multimedia and Graphic Arts, Cyprus University of Technology, Limassol, Cyprus

    Panayiotis Zaphiris

  10. Department of Multimedia and Graphic Arts, Cyprus University of Technology, Limassol, Cyprus

    Andri Ioannou

  11. Soar Technology Inc., Orlando, FL, USA

    Robert A. Sottilare

  12. MMS, Fraunhofer FKIE, Wachtberg, Nordrhein-Westfalen, Germany

    Jessica Schwarz

  13. Industrial Design, Eindhoven University of Technology, Eindhoven, Noord-Brabant, The Netherlands

    Matthias Rauterberg

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Karunaratne, I., Atukorale, A.S. (2021). Towards a Computerized Approach to Identify Attentional States of Online Learners. In: Stephanidis, C., et al. HCI International 2021 - Late Breaking Papers: Cognition, Inclusion, Learning, and Culture. HCII 2021. Lecture Notes in Computer Science(), vol 13096. Springer, Cham. https://doi.org/10.1007/978-3-030-90328-2_28

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-90328-2_28

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-90327-5

  • Online ISBN: 978-3-030-90328-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation