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Cited by 139

The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.

Rethinking (Dis)engagement in human-computer interaction

O'Brien, Heather L., Roll, Ido, Kampen, Andrea, Davoudi, Nilou·2022·Computers in Human Behavior
DOI 10.1016/j.chb.2021.107109
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Crossref · 10.1016/j.chb.2021.107109

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15 of 15 references verified0 citation errors · 0 not checkable

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Citations

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Research works printed but not linked: 37

  1. Arapakis, 2014, User engagement in online news: Under the scope of sentiment, interest, affect, and gaze, J. Assoc. Inf. Sci. Tech., 65, 1988, 10.1002/asi.23096 · DOI
  2. Bachhel, 2014, Effective use of pause procedure to enhance student engagement and learning, Journal of Clinical and Diagnostic Research (JCDR), 8, XM01
  3. Baker, 2010, Better to be frustrated than bored: The incidence, persistence, and impact of learners' cognitive-affective states during interactions with three different computer-based learning environments, International Journal of Human-Computer Studies, 68, 223, 10.1016/j.ijhcs.2009.12.003 · DOI · Paper page
  4. Balwant, 2018, The meaning of student engagement and disengagement in the classroom context: Lessons from organisational behaviour, Journal of Further and Higher Education, 42, 389, 10.1080/0309877X.2017.1281887 · DOI
  5. Cheyne, 2009, Anatomy of an error: A bidirectional state model of task engagement/disengagement and 75 attention-related errors, Cognition, 111, 98, 10.1016/j.cognition.2008.12.009 · DOI
  6. Chipchase, 2017, Conceptualising and measuring student sisengagement in higher education: A synthesis of the literature, International Journal of Higher Education, 6, 31, 10.5430/ijhe.v6n2p31 · DOI
  7. Crilley, 2019, What to do about social media? Politics, populism and journalism, Journalism, 20, 173, 10.1177/1464884918807344 · DOI
  8. Hallnäs, 2015, On the philosophy of slow technology, Acta Univ. Sapientiae Soc., 5, 29
  9. Hallnäs, 2001, Slow technology–designing for reflection, Personal and Ubiquitous Computing, 5, 201, 10.1007/PL00000019 · DOI
  10. Hone, 2016, Exploring the factors affecting MOOC retention: A survey study, Comput. Educ., 98, 157, 10.1016/j.compedu.2016.03.016 · DOI
  11. Hwang, 2020, Interactive music for multisensory e‐commerce: The moderating role of online consumer involvement in experiential value, cognitive value, and purchase intention, Psychology and Marketing, 37, 1031, 10.1002/mar.21338 · DOI
  12. Jennett, 2008, Measuring and defining the experience of immersion in games, International Journal of Human-Computer Studies, 66, 641, 10.1016/j.ijhcs.2008.04.004 · DOI · Paper page
  13. Klie, 2015, The keys to countering cart abandonment, Custom. Relat. Manage., 19, 9
  14. Lalmas, 2014, Measuring user engagement. Synthesis lectures on information concepts, Retrieval & Services, 6, 1
  15. Merkt, 2022, Pushing the button: Why do learners pause online videos?, Computers & Education, 176, 10.1016/j.compedu.2021.104355 · DOI
  16. Moore, 2017, Social media mourning: Using grounded theory to explore how people grieve on social networking sites, Omega, 79, 231, 10.1177/0030222817709691 · DOI
  17. Morton, 2019, Experiences of a web-based quality of life self-monitoring tool for individuals with bipolar disorder: A qualitative exploration, JMIR Ment. Health, 6
  18. Norman, 2003, Affect and machine design: Lessons for the development of autonomous machines, IBM Systems Journal, 42, 38, 10.1147/sj.421.0038 · DOI
  19. O'Brien, 2017, Antecedents and learning outcomes of online news engagement, J. Assoc. Inf. Sci. Tech., 68, 2809, 10.1002/asi.23854 · DOI
  20. O'Brien, 2020, An empirical study of interest, task complexity and search behaviour on user engagement, Information Processing & Management, 57, 102226, 10.1016/j.ipm.2020.102226 · DOI
  21. O'Brien, 2018, A practical approach to measuring user engagement with the refined user engagement scale (UES) and new UES short form, International Journal of Human-Computer Studies, 112, 28, 10.1016/j.ijhcs.2018.01.004 · DOI · Paper page
  22. O'Brien, 2013, Mixed-methods approach to measuring user experience in online news interactions, J. Assoc. Inf. Sci. Tech., 64, 1543, 10.1002/asi.22871 · DOI
  23. Oh, 2015, How does interactivity persuade? An experimental test of interactivity on cognitive absorption, elaboration, and attitudes, J. Commun., 65, 213, 10.1111/jcom.12147 · DOI
  24. Paul, 2011, Optimizing play: How theorycraft changes gameplay and design, Game Studies, 11, 100
  25. Perez, 2017, Identifying productive inquiry in virtual labs using sequence mining, Vol. 10331
  26. Poirier, 2014, Informational balance: Slow principles in the theory and practice of information behaviour, Journal of Documentation, 70, 687, 10.1108/JD-08-2013-0111 · DOI
  27. Reeve, 2013, How students create motivationally supportive learning environments for themselves: The concept of agentic engagement, Journal of Educational Psychology, 105, 579, 10.1037/a0032690 · DOI · Paper page
  28. Roll, 2011, Improving students' help-seeking skills using metacognitive feedback in an intelligent tutoring system, Learning and Instruction, 21, 267, 10.1016/j.learninstruc.2010.07.004 · DOI
  29. Roll, 2015, Understanding, evaluating, and supporting self-regulated learning using learning analytics, J. Learn. Anal., 2, 7, 10.18608/jla.2015.21.2 · DOI
  30. Sacasas, 2018, The tech backlash we really need, New Atlantis, 55, 35
  31. Seo, 2021, Active learning with online video: The impact of learning context on engagement, Comput. Educ., 165, 104132, 10.1016/j.compedu.2021.104132 · DOI
  32. Shahbaznezhad, 2021, The role of social media content format and platform in users' engagement behavior, Journal of Interactive Marketing, 53, 47, 10.1016/j.intmar.2020.05.001 · DOI
  33. Srnicek, 2017, The challenges of platform capitalism: Understanding the logic of a new business model, Juncture, 23, 254, 10.1111/newe.12023 · DOI
  34. Tufekci, 2018, YouTube, the great radicalizer, The NY Times, 10
  35. Uchidiuno, 2018, How do English language learners interact with different content types in MOOC videos?, International Journal of Artificial Intelligence in Education, 28, 508, 10.1007/s40593-017-0156-x · DOI
  36. Webster, 2006, Enhancing the design of web navigation systems: The influence of user disorientation on engagement and performance, MIS Quarterly, 30, 661, 10.2307/25148744 · DOI
  37. Webster, 1997, Audience engagement in multimedia presentations, SIGMIS Database, 28, 63, 10.1145/264701.264706 · DOI

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Metadata

Authors
O'Brien, H. L., Roll, I., Kampen, A., & Davoudi, N.
ORCID
Venue
Computers in Human Behavior
Publisher
Elsevier BV
Published
2022-03
Volume
128
Pages
107109
ISSN
0747-5632
DOI
10.1016/j.chb.2021.107109
Cited by
139
References
15
Language
en
Licence
Funders
  • Gordon and Betty Moore Foundation
  • Social Sciences and Humanities Research Council of Canada (F15-04687)
  • Israel Science Foundation
  • University of British Columbia

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