CoChat
Sign Up
Cited by 85Online and Blended LearningInnovative Teaching and Learning MethodsEducational Technology and E-Learning

Use of live chat in higher education to support self-regulated help seeking behaviours: a comparison of online and blended learner perspectives

Open access
Broadbent, Jaclyn, Lodge, Jason·2021·International Journal of Educational Technology in Higher Education
DOI 10.1186/s41239-021-00253-2PMC PMC8021438
Open this paper in CoChat — free accountOpen PDF

Abstract

Help-seeking is an essential self-regulatory and metacognitive skill. In the online learning environment, much of the learning is self-directed and there are generally less opportunities to receive help in real time. The uses of email and discussion boards are the most common method of seeking help in these environments. The current study explored students’ perceptions of the use of live chat technology for online academic help-seeking within higher education, with a focus on comparing online and blended learners’ perspectives. Participants were 246 students who were studying psychology online (n = 91) or in blended learning (n = 155) environments. The live chat technology was well received by both groups, especially for its ability to provide instant, real-time, and convenient help. Live chat was particularly well received by online learners, who were more satisfied, felt more cared about by the teaching team, and would be more likely to recommend it to others than blended learners. Further, online learners reported that live chat gave them better access to staff, and felt that this feature was a good approximation for more traditional face-to-face conversations. As an online, synchronous, private help-seeking tool between student and teacher, these findings provide a strong endorsement for the use of live chat in higher education, particularly for online learners.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/s41239-021-00253-2

Cites

5 of 5 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Online learning environments require learners to have more self-regulation of their learning than traditional face-to-face meetings.

    “Online learning environments differ from traditional face-to-face meetings in that learners need more self-regulation of their learning, and they don't have the same opportunities to receive help as they do in face-to-face settings (Broadbent & Lodge, 2021).”

    From A Systematic Review of Studies Exploring Help-Seeking Strategies in Online Learning Environments (2023) · cites this paper as Broadbent & Lodge, 2021

    The Abstract says online learning is largely self-directed and offers fewer opportunities for real-time help. The Introduction also describes reduced opportunities for interaction and help-seeking compared with face-to-face classrooms. These passages support the sentence’s point about access to help, but do not explicitly establish that online learners need more self-regulation than face-to-face learners. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

  • Online learners do not have the same opportunities to receive help as they do in face-to-face settings.

    “Online learning environments differ from traditional face-to-face meetings in that learners need more self-regulation of their learning, and they don't have the same opportunities to receive help as they do in face-to-face settings (Broadbent & Lodge, 2021).”

    From A Systematic Review of Studies Exploring Help-Seeking Strategies in Online Learning Environments (2023) · cites this paper as Broadbent & Lodge, 2021

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 36

  1. Amador, P. V., & Amador, J. M. (2017). Academic help seeking: a framework for conceptualizing Facebook use for higher education support. TechTrends, 61 (2), 195–202. 10.1007/s11528-016-0135-3 · DOI
  2. Boling, E. C., Hough, M., Krinsky, H., Saleem, H., & Stevens, M. (2012). Cutting the distance in distance education: Perspectives on what promotes positive, online learning experiences. The Internet and Higher Education, 15 (2), 118–126. 10.1016/j.iheduc.2011.11.006 · DOI
  3. Broadbent, J. (2020). Am I just another number? Using online education innovations to personalise the student experience in online learning. In S. McKenzie, M. Mundy, F. Garivaldis, & K. Dyer (Eds.), Tertiary online teaching and learning: TOTAL perspectives and resources for digital education (pp. 13–25).
  4. Broadbent, J., & Lodge, J. M. (2020). Engaging large first year classes using digital technology: A case study. In S. Morrissey, G.J. Rich, A. Padilla-López, L. Karine de Souza, Taylor, & J. Jaafar (Eds.), Teaching Psychology Around the world (pp. 205–217). Cambridge Scholars Publishing.
  5. Chen, C. S. (2002). Self-regulated learning strategies and achievement in an introduction to information systems course. Information Technology, Learning, and Performance Journal, 20(1), 11–25. https://search.proquest.com/scholarly-journals/self-regulated-learning-strategies-achievement/docview/219841960/se-2?accountid=201395
  6. Cheng, K. H., Liang, J. C., & Tsai, C. C. (2013). University students’ online academic help seeking: The role of self-regulation and information commitments. The Internet and Higher Education, 16, 70–77. 10.1016/j.iheduc.2012.02.002 · DOI · Paper page
  7. Chyr, W. L., Shen, P. D., Chiang, Y. C., Lin, J. B., & Tsai, C. W. (2017). Exploring the effects of online academic help-seeking and flipped learning on improving students’ learning. Journal of Educational Technology & Society, 20(3), 11–23. https://www.jstor.org/stable/26196116
  8. Greenland, S. J., & Moore, C. (2014). Patterns of online student enrolment and attrition in Australian open access online education: a preliminary case study. Open Praxis, 6(1), 45–54. https://www.learntechlib.org/p/130685/.
  9. Hitchcock, L. I., & Young, J. A. (2016). Tweet, tweet!: Using live Twitter chats in social work education. Social Work Education, 35 (4), 457–468. 10.1080/02615479.2015.1136273 · DOI
  10. Kang, L., Wang, X., Tan, C. H., & Zhao, J. L. (2015). Understanding the antecedents and consequences of live chat use in electronic markets. Journal of Organizational Computing and Electronic Commerce, 25 (2), 117–139. 10.1080/10919392.2015.1033935 · DOI
  11. Karabenick, S. A. (2003). Seeking help in large college classes: A person-centered approach. Contemporary Educational Psychology, 28 (1), 37–58. 10.1016/S0361-476X(02)00012-7 · DOI · Paper page
  12. Kay, R. H., & Lauricella, S. (2015). Investigating and comparing communication media used in higher education. Journal of Communication, 2 (1), 1–20. 10.7726/jcthb.2015.1001 · DOI
  13. Kitsantas, A., & Chow, A. (2007). College students’ perceived threat and preference for seeking help in traditional, distributed, and distance learning environments. Computers & Education, 48 (3), 383–395. 10.1016/j.compedu.2005.01.008 · DOI
  14. Klein, A. Z., da Silva Freitas, J. C., Barbosa, J. L. V., & Baldasso, L. (2018). The educational affordances of mobile instant messaging (MIM): Results of Whatsapp® used in higher education. International Journal of Distance Education Technologies (IJDET), 16 (2), 51–64. 10.4018/IJDET.2018040104 · DOI
  15. Koc, S., & Liu, X. (2016). An investigation of graduate students' help-seeking experiences, preferences and attitudes in online learning. Turkish Online Journal of Educational Technology-TOJET, 15(3), 27–38. https://eric.ed.gov/?id=EJ1106358
  16. Lauricella, S., & Kay, R. (2013). Exploring the use of text and instant messaging in higher education classrooms. Research in Learning Technology. 10.3402/rlt.v21i0.19061 · DOI
  17. Li, L., & Pitts, J. P. (2009). Does it really matter? Using virtual office hours to enhance student-faculty interaction. Journal of Information Systems Education, 20(2), 175–185. http://jise.org/Volume20/n2/JISEv20n2p175.pdf
  18. Lodge, J. M. (2010). Communicating with first year students; so many channels but is anyone listening? A practice report. Student Success, 1 (1), 100–105. 10.5204/intjfyhe.v1i1.23 · DOI
  19. Luo, T., Sickel, J., & Cheng, L. (2017). Preservice teachers’ participation and perceptions of Twitter live chats as personal learning networks. TechTrends, 61 (3), 226–235. 10.1007/s11528-016-0137-1 · DOI
  20. Matteson, M. L., Salamon, J., & Brewster, L. (2011). A systematic review of research on live chat service. Reference & User Services Quarterly, 51(2), 172–190. https://www.jstor.org/stable/refuseserq.51.2.172
  21. McInnerney J. M., & Roberts T. S. (2004). Online learning: Social interaction and the creation of a sense of community. Educational Technology & Society, 7(3), 73–81. https://www.jstor.org/stable/10.2307/jeductechsoci.7.3.73 · DOI
  22. Mtshali, M. A., Maistry, S. M., & Govender, D. W. (2015). Online chats: A strategy to enhance learning in large classes. South African Journal of Education, 35 (4), 1–9. 10.15700/saje.v35n4a1215 · DOI
  23. Pimmer, C., Brühlmann, F., Odetola, T. D., Dipeolu, O., Gröhbiel, U., & Ajuwon, A. J. (2018). Instant messaging and nursing students’ clinical learning experience. Nurse Education Today, 64, 119–124. 10.1016/j.nedt.2018.01.034 29475195 · DOI
  24. Puzziferro, M. (2008). Online technologies self-efficacy and self-regulated learning as predictors of final grade and satisfaction in college-level online courses. American Journal of Distance Education, 22 (2), 72–89. 10.1080/08923640802039024 · DOI
  25. Raiman, L., Antbring, R., & Mahmood, A. (2017). WhatsApp messenger as a tool to supplement medical education for medical students on clinical attachment. BMC Medical Education, 17 (1), 7–16. 10.1186/s12909-017-0855-x 28061777 PMC5219809 · DOI
  26. Robles, H. R., Guerrero, J., LLinas, H., & Montero, P. (2019). Online teacher–students interactions using WhatsApp in a law course. Journal of Information Technology Education: Research, 18, 231–252. · DOI
  27. Schunk, D. H., & Zimmerman, B. J. (2012). The motivational role of adaptive help seeking in self-regulated learning. In Motivation and self-regulated learning (pp. 327–350). Routledge.
  28. So, S. (2016). Mobile instant messaging support for teaching and learning in higher education. The Internet and Higher Education, 31, 32–42. 10.1016/j.iheduc.2016.06.001 · DOI
  29. Sun, Z., Lin, C. H., Wu, M., Zhou, J., & Luo, L. (2018). A tale of two communication tools: Discussion-forum and mobile instant-messaging apps in collaborative learning. British Journal of Educational Technology, 49 (2), 248–261. 10.1111/bjet.12571. · DOI
  30. Tang, Y., & Hew, K. F. (2017). Is mobile instant messaging (MIM) useful in education? Examining its technological, pedagogical, and social affordances. Educational Research Review, 21, 85–104. 10.1016/j.edurev.2017.05.001 · DOI
  31. Timmis, S. (2012). Constant companions: Instant messaging conversations as sustainable supportive study structures amongst undergraduate peers. Computers & Education, 59 (1), 3–18. 10.1016/j.compedu.2011.09.026 · DOI
  32. Vivian, R. (2011). University students’ informal learning practices using Facebook: Help or hindrance?. In International Conference on ICT in Teaching and Learning (pp. 254–267). Springer, Berlin, Heidelberg.
  33. Zimmerman, B. J. (1986). Becoming a self-regulated learner: Which are the key subprocesses? Contemporary Educational Psychology, 11 (4), 307–313. 10.1016/0361-476X(86)90027-5 · DOI
  34. Zimmerman, B. J. (1990). Self-regulated learning and academic achievement: An overview. Educational Psychologist, 25 (1), 3–17. 10.1207/s15326985ep2501_2. · DOI · Paper page
  35. Zimmerman, B. J. (2015). Self-regulated learning: Theories, measures, and outcomes. International encyclopedia of the social and behavioral sciences. Elsevier. http://www.sciencedirect.com/science/article/pii/B9780080970868260601
  36. Zimmerman, B. J., & Moylan, A. R. (2009). Self-regulation: Where metacognition and motivation intersect. In Handbook of metacognition in education (pp. 311–328). Routledge.

Cited by

Sorted by citations

Authors
Broadbent, J., & Lodge, J.
Affiliations
  • Deakin University (AU)
  • The University of Queensland (AU)
Corresponding author
Broadbent, Jaclyn
ORCID
Venue
International Journal of Educational Technology in Higher Education
Publisher
Springer Science and Business Media LLC
Published
2021-04-06
Volume
18
Issue
1
Pages
17-17
ISSN
2365-9440 (ISSN-L)
DOI
10.1186/s41239-021-00253-2
PMC
PMC8021438
OpenAlex
W3148540411
Cited by
85
References
5
Citations by year
2026: 9 · 2025: 10 · 2024: 20 · 2023: 27 · 2022: 13 · 2021: 6
FWCI
29.01
Type
journal article
Language
en
Open access
Licence
Locations
  • International Journal of Educational Technology in Higher Education (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Figshare (submittedVersion, cc-by)
Topics
  • Social Sciences › Education › Online and Blended Learning
  • Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
  • Physical Sciences › Computer Science › Information Systems › Educational Technology and E-Learning
Keywords
live chat, help-seeking, student self-regulation, online learning, blended learning, student perceptions, synchronous communication, student-teacher interaction, student satisfaction

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review