Understanding the Effects of Visual Cueing on Social Media Engagement With YouTube Educational Videos

Zixing Shen New Mexico State University ; Songxin Tan South Dakota State University ; Michael J. Pritchard

Abstract

<roman xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><b>Background</b>:</roman> Social media like YouTube have transformative effects on technical communication. Technical communication scholars have attended to the increasing use of social media personally, pedagogically, and professionally. Our stream of research focuses on YouTube videos for educational purposes within the various research avenues. <roman xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><b>Literature review</b>:</roman> YouTube has become a viable platform for learning. YouTube educational videos have been studied from many different perspectives, yet research on engagement with YouTube educational videos is scarce, despite the importance of engagement in both learning and social media. Following extant research on YouTube educational video features, we probe the effects of visual cueing on social media engagement. <roman xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><b>Research question</b>:</roman> How does visual cueing (anchors and intrinsic visual features) affect social media engagement with YouTube educational videos? <roman xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><b>Methodology</b>:</roman> We sampled 196 YouTube educational videos on 28 physics and astronomy topics, and extracted visual cueing from the videos and social media engagement information from YouTube. Multiple linear regression analyses were conducted. <roman xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><b>Results</b>:</roman> Our analyses show that intrinsic visual features (color contrast and visual complexity) are significantly related to social media engagement (involvement, intimacy, and interaction), while anchors (math equations and models) are not. <roman xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><b>Conclusion</b>:</roman> Our study supports the empirical knowledge on social media engagement with YouTube educational videos and expands on the technical communication research for YouTube educational videos. In addition, this research contributes to the literature on engagement by extending its relevance to the social media learning environment. Finally, our study provides content creators with new video design insights that can be used to enhance social media engagement with YouTube educational videos.

Journal
IEEE Transactions on Professional Communication
Published
2022-06-01
DOI
10.1109/tpc.2022.3156225
CompPile
Open Access
Closed
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Cited by in this index (1)

  1. IEEE Transactions on Professional Communication

References (87) · 11 in this index

  1. Technical communication in a social media world
    Intercom
  2. Technical Communication Quarterly
  3. Technical Communication Quarterly
  4. Technical Communication Quarterly
  5. Communication Design Quarterly
Show all 87 →
  1. Technical Communication Quarterly
  2. Communication Design Quarterly
  3. Designing outrage, programming discord: A critical interface analysis of Facebook as a ca…
    Tech. Commun.
  4. Journal of Business and Technical Communication
  5. Technical Communication Quarterly
  6. Technical Communication Quarterly
  7. YouTube beauty tutorials as technical communication
    Tech. Commun.
  8. 10.1108/OIR-09-2016-0274
     ↗
  9. Technical Communication Quarterly
  10. Technical Communication Quarterly
  11. 10.1016/j.compedu.2020.104009
     ↗
  12. 10.1016/j.compedu.2021.104132
     ↗
  13. 10.1016/j.chb.2015.01.067
     ↗
  14. 10.17705/1jais.00543
     ↗
  15. 10.1037/1076-898X.11.4.266
     ↗
  16. Enhancing learning from dynamic and static visualizations by means of cueing
    J. Educ. Multimedia Hypermedia
  17. Computers As Theatre
  18. 10.1145/264701.264706
     ↗
  19. 10.1002/asi.20801
     ↗
  20. 10.1287/isre.2019.0839
     ↗
  21. The development and evaluation of a survey to measure user engagement in e-commerce envir…
    J. Assoc. Inf. Sci. Technol.
  22. 10.1016/j.im.2016.03.004
     ↗
  23. 10.1016/j.chb.2016.09.024
     ↗
  24. 10.1108/JPBM-06-2014-0635
     ↗
  25. 10.1016/j.comcom.2015.08.002
     ↗
  26. 10.2224/sbp.2015.43.4.579
     ↗
  27. 10.1108/OIR-03-2012-0054
     ↗
  28. Marketings New Key Metric: Engagement
  29. 10.1108/17578041311315030
     ↗
  30. 10.1002/cb.383
     ↗
  31. 10.9776/16235
     ↗
  32. 10.1108/TG-09-2014-0041
     ↗
  33. 10.1145/2912160.2912189
     ↗
  34. Recollections and reflections
  35. 10.17705/1thci.00076
     ↗
  36. 10.3102/00346543074001059
     ↗
  37. Measuring learner engagement in computer- equipped college classrooms
    J. Educ. Multimedia Hypermedia
  38. 10.1016/j.jsp.2006.04.002
     ↗
  39. 10.1007/978-1-4614-2018-7_19
     ↗
  40. 10.1207/S1532480XADS0504_04
     ↗
  41. School bonding in children and adolescents: Conceptualization, assessment, and associated…
    Clin. Child Fam. Psychol. Rev.  ↗
  42. 10.5430/ijhe.v8n6p171
     ↗
  43. 10.1111/j.1467-8535.2010.01157.x
     ↗
  44. 10.1111/bjet.12235
     ↗
  45. 10.1145/2556325.2566239
     ↗
  46. 10.1080/0144929X.2018.1549596
     ↗
  47. 10.1108/INTR-10-2019-0416
     ↗
  48. 71 Up-To-Date YouTube Statistics For Your Marketing Strategy in 2021
  49. 10.1016/j.chb.2015.09.010
     ↗
  50. Like it or not. What characterizes Youtubes more popular instructional videos
    Tech. Commun
  51. New modes of help: Best practices for instructional video
    Tech. Commun.
  52. 10.55177/tc786532
     ↗
  53. 10.21432/T2VG77
     ↗
  54. Knowledge, information, biases and signal assemblages
  55. A data-frame theory of sensemaking
  56. 10.1016/S0361-3682(96)00024-4
     ↗
  57. 10.1007/978-3-642-27851-8_227-6
     ↗
  58. 10.1007/978-3-642-02728-4_17
     ↗
  59. 10.2307/25750702
     ↗
  60. 10.1002/asi.23427
     ↗
  61. 10.1080/0144929X.2019.1602167
     ↗
  62. 10.1016/S0959-4752(02)00016-6
     ↗
  63. 10.1017/cbo9780511816819
     ↗
  64. 10.1007/s10648-009-9098-7
     ↗
  65. 10.1016/0042-6989(93)90202-8
     ↗
  66. 10.1207/s15516709cog1202_4
     ↗
  67. 10.1007/s10648-019-09465-5
     ↗
  68. 10.1162/105474698565686
     ↗
  69. 10.1207/S15327043HUP1504_03
     ↗
  70. 10.1016/j.compedu.2020.103939
     ↗
  71. 10.1111/add.12835
     ↗
  72. 10.1177/1354856517736982
     ↗
  73. 10.1080/17524032.2017.1289108
     ↗
  74. 10.1016/0167-2789(92)90242-F
     ↗
  75. 10.1002/j.1538-7305.1948.tb01338.x
     ↗
  76. 10.3389/fpsyg.2017.02368
     ↗
  77. 10.53841/bpspag.2005.1.56.31
     ↗
  78. Multivariate Data Analysis
  79. 10.1016/j.chb.2018.03.036
     ↗
  80. A unified view of learning from animated and static graphics
  81. 10.1080/00461520.2014.965823
     ↗
  82. 10.1037/a0032674
     ↗