Instructor presence in instructional video: Effects on visual attention, recall, and perceived learning

Computers in Human Behavior

Volumn 71, Issue , 2017, Pages 79-89

  Wang, Jiahui ^a   Antonenko, Pavlo D ^a  

^a UNIVERSITY OF FLORIDA   (United States)

Author keywords

Instructional video; Instructor presence; Learning; Mental effort; Perception; Visual attention

Indexed keywords

HUMAN COMPUTER INTERACTION; SENSORY PERCEPTION;

INSTRUCTIONAL VIDEOS; INSTRUCTOR PRESENCE; LEARNING; MENTAL EFFORT; VISUAL ATTENTION;

BEHAVIORAL RESEARCH;

CLINICAL ARTICLE; HUMAN; LEARNING; MATHEMATICS; PERCEPTION; RECALL; SATISFACTION; VIDEORECORDING; VISUAL ATTENTION;

EID: 85012273592     PISSN: 07475632     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.chb.2017.01.049     Document Type: Article

References (56)

1. Alibali, M.W., Nathan, M.J., Embodiment in mathematics teaching and learning: Evidence from learners' and teachers' gestures. Journal of the Learning Sciences 21:2 (2012), 247–286.
2. Allen, I.E., Seaman, J., Poulin, R., Straut, T.T., Online report card: Tracking online education in the United States. Sloam Consortium., 2016.
3. Anderson, G., Beal, C.R., Children's recognition of inconsistencies in science texts: Multiple measures of comprehension monitoring. Applied Cognitive Psychology 9 (1995), 261–272.
4. Antonenko, P.D., Niederhauser, D.S., The influence of leads on cognitive load and learning in a hypertext environment. Computers in Human Behavior 26:2 (2010), 140–150.
5. Antonenko, P., Paas, F., Grabner, R., van Gog, T., Using electroencephalography to measure cognitive load. Educational Psychology Review 22:4 (2010), 425–438.
6. Argyle, M., Bodily communication. 1988, Routledge.
7. Baddeley, A.D., Hitch, G., Working memory. The Psychology of Learning and Motivation 8 (1974), 47–89.
8. Bandura, A., Cervone, D., Differential engagement of self-reactive influences in cognitive motivation. Organizational Behavior and Human Decision Processes 38:1 (1986), 92–113.
9. Baylor, A.L., Kim, Y., Simulating instructional roles through pedagogical agents. International Journal of Artificial Intelligence in Education 15:2 (2005), 95–115.
10. Bhat, S., Chinprutthiwong, P., Perry, M., Seeing the instructor in two video styles: Preferences and patterns. Proceedings of the 8th international conference on educational data mining, 2015, 305–312.
11. Boucheix, J., Lowe, R.K., An eye tracking comparison of external pointing cues and internal continuous cues in learning with complex animations. Learning and Instruction 20:2 (2010), 123–135.
12. Canham, M., Hegarty, M., Effects of knowledge and display design on comprehension of complex graphics. Learning and Instruction 20:2 (2010), 155–166.
13. Chen, C., Wu, C., Effects of different video lecture types on sustained attention, emotion, cognitive load, and learning performance. Computers & Education 80 (2015), 108–121.
14. Clark, R.C., Mayer, R.E., E-learning and the science of instruction: Proven guidelines for consumers and designers of multimedia learning. 2016, John Wiley & Sons.
15. Cowan, N., The magical number 4 in short-term memory: A reconsideration of mental storage capacity. Behavioral and Brain Sciences 24:1 (2001), 87–114.
16. Cui, G., Lockee, B., Meng, C., Building modern online social presence: A review of social presence theory and its instructional design implications for future trends. Education and information technologies 18:4 (2013), 661–685.
17. Fredericksen, E., Pickett, A., Shea, P., Pelz, W., Swan, K., Student satisfaction and perceived learning with online courses - principles and examples from the suny learning network. Journal of Asynchronous Learning Networks 4:2 (2000), 7–41.
18. Garrison, D.R., Online community of inquiry review: Social, cognitive, and teaching presence issues. Journal of Asynchronous Learning Networks 11:1 (2007), 61–72.
19. Gobert, J., Sao Pedro, M., Baker, R., Toto, E., Montalvo, O., Leveraging educational data mining for real time performance assessment of scientific inquiry skills within microworlds. Journal of Educational Data Mining 4:1 (2012), 111–143.
20. van Gog, T., Scheiter, K., Eye tracking as a tool to study and enhance multimedia learning. Learning and Instruction 20:2 (2010), 95–99.
21. van Gog, Tamara, The signaling (or cueing) principle in multimedia learning. The Cambridge handbook of multimedia learning, 2014, 263–278.
22. Gunawardena, C.N., Zittle, F.J., Social presence as a predictor of satisfaction within a computer mediated conferencing environment. American Journal of Distance Education 11:3 (1997), 8–26.
23. Guo, P.J., Kim, J., Rubin, R., How video production affects student engagement: An empirical study of MOOC videos. Proceedings of the first ACM conference on learning at scale conference, 2014, ACM, 41–50.
24. Holsanova, J., Holmberg, N., Holmqvist, K., Reading information graphics: The role of spatial contiguity and dual attentional guidance. Applied Cognitive Psychology 23:9 (2009), 1215–1226.
25. Homer, B.D., Plass, J.L., Blake, L., The effects of video on cognitive load and social presence in multimedia-learning. Computers in Human Behavior 24:3 (2008), 786–797.
26. Jarodzka, H., Scheiter, K., Gerjets, P., Van Gog, T., In the eyes of the beholder: How experts and novices interpret dynamic stimuli. Learning and Instruction 20:2 (2010), 146–154.
27. Johnson, M.H., Dziurawiec, S., Ellis, H., Morton, J., Newborns' preferential tracking of face-like stimuli and its subsequent decline. Cognition 40:1 (1991), 1–19.
28. Johnson, A.M., Ozogul, G., Moreno, R., Reisslein, M., Pedagogical agent signaling of multiple visual engineering representations: The case of the young female agent. Journal of Engineering Education 102:2 (2013), 319–337.
29. Just, M.A., Carpenter, P.A., A theory of reading: From eye fixations to comprehension. Psychological Review 87:4 (1980), 329–354.
30. Kalyuga, S., Chandler, P., Sweller, J., Managing split-attention and redundancy in multimedia instruction. Applied Cognitive Psychology 13:4 (2011), 351–371.
31. Karpicke, J.D., Blunt, J.R., Retrieval practice produces more learning than elaborative studying with concept mapping. Science 331:6018 (2011), 772–775.
32. Kim, Y., Baylor, A.L., Research-based design of pedagogical agent roles: A review, progress, and recommendations. International Journal of Artificial Intelligence in Education 26:1 (2016), 160–169.
33. Kim, Y.H., Kim, D.J., Wachter, K., A study of mobile user engagement (MoEN): Engagement motivations, perceived value, satisfaction, and continued engagement intention. Decision Support Systems 56:1 (2013), 361–370.
34. Kizilcec, R.F., Papadopoulos, K., Sritanyaratana, L., Showing face in video instruction: Effects on information retention, visual attention, and affect. Proceedings of the 32nd annual ACM conference on human factors in computing systems, 2014, ACM, 2095–2102.
35. de Koning, B.B., Tabbers, H.K., Rikers, R.M.J.P., Paas, F., Attention guidance in learning from a complex animation: Seeing is understanding?. Learning and Instruction 20:2 (2010), 111–122.
36. Krämer, N.C., Bente, G., Personalizing e-learning. The social effects of pedagogical agents. Educational Psychology Review 22:1 (2010), 71–87.
37. Louwerse, M.M., Graesser, A.C., McNamara, D.S., Lu, S., Embodied conversational agents as conversational partners. Applied Cognitive Psychology 23:9 (2008), 1244–1255.
38. Markman, E., Realizing that you don't understand: A preliminary investigation. Child Development 48 (1977), 986–992.
39. Mayer, R.E., Unique contributions of eye-tracking research to the study of learning with graphics. Learning and Instruction 20:2 (2010), 167–171.
40. Mayer, R.E., Principles based on social cues in multimedia learning: Personalization, voice, image, and embodiment principles. The Cambridge handbook of multimedia learning, 2014, 345–368.
41. Mayer, R.E., DaPra, C.S., An embodiment effect in computer-based learning with animated pedagogical agents. Journal of Experimental Psychology: Applied 18:3 (2012), 239–252.
42. Mayer, R.E., Dow, G.T., Mayer, S., Multimedia learning in an interactive self-explaining environment: What works in the design of agent-based microworlds?. Journal of Educational Psychology 95:4 (2003), 806–812.
43. Paas, F., Training strategies for attaining transfer of problem-solving skill in statistics: A cognitive-load approach. Journal of Educational Psychology 84:4 (1992), 429–434.
44. Paas, F., Renkl, A., Sweller, J., Cognitive load theory and instructional design: Recent developments. Educational Psychologist 38:1 (2003), 1–4.
45. Paas, F., Tuovinen, J., Tabbers, H., Van Gerven, P.W., Cognitive load measurement as a means to advance cognitive load theory. Educational Psychologist 38:1 (2003), 63–71.
46. Paas, F., van Merriënboer, J.J.G., Instructional control of cognitive load in the training of complex cognitive tasks. Educational Psychology Review 6 (1994), 51–71.
47. Paivio, A., Dual coding theory: Retrospect and current status. Canadian Journal of Psychology 45:3 (1991), 255–287.
48. Picciano, A.G., Seaman, J., Shea, P., Swan, K., Examining the extent and nature of online learning in American K-12 education: The research initiatives of the Alfred P. Sloan foundation. Internet and Higher Education 15:2 (2012), 127–135.
49. Plass, J.L., Heidig, S., Hayward, E.O., Homer, B.D., Um, E., Emotional design in multimedia learning: Effects of shape and color on affect and learning. Learning and Instruction 29 (2014), 128–140.
50. Plass, J.L., Moreno, R., Brünken, R., Cognitive load theory. 2010, Cambridge University Press.
51. Richardson, J.C., Swan, K., Examining social presence in online courses in relation to students' perceived learning and satisfaction. Journal of Asynchronous Learning Networks 7:1 (2003), 68–88.
52. Schmidt-Weigand, F., Kohnert, A., Glowalla, U., A closer look at split visual attention in system- and self-paced instruction in multimedia learning. Learning and Instruction 20:2 (2010), 100–110.
53. Sowa, L., Thorsen, D., An assessment of student learning, perceptions, and social capital development in undergraduate, lower-division STEM courses employing a flipped classroom pedagogy. Proceedings of 122nd ASEE conference & exposition, 2015, American Society for Engineering Education.
54. Stevens, R.H., Thadani, V., Quantifying student's scientific problem solving efficiency and effectiveness. Technology, Instruction, Cognition, and Learning 5 (2007), 325–337.
55. Sweller, J., Merrienboer, J. J. G. v., Paas, F.G.W.C., Cognitive architecture and instructional design. Educational Psychology Review 10 (1998), 251–296.
56. Yee, N., Bailenson, J.N., Rickertsen, K., A meta-analysis of the impact of the inclusion and realism of human-like faces on user experiences in interfaces. Proceedings of the SIGCHI conference on human factors in computing systems, 2007, ACM, 1–10.