Skip to main content Accessibility help
×
Hostname: page-component-78c5997874-m6dg7 Total loading time: 0 Render date: 2024-11-09T07:15:04.399Z Has data issue: false hasContentIssue false

13 - Principles of Multimedia Learning Based on Social Cues : Personalization, Voice, and Image Principles

Published online by Cambridge University Press:  05 June 2012

Richard E. Mayer
Affiliation:
University of California, Santa Barbara
Richard Mayer
Affiliation:
University of California, Santa Barbara
Get access

Summary

Abstract

Social cues may prime social responses in learners that lead to deeper cognitive processing during learning and hence better test performance. The personalization principle is that people learn more deeply when the words in a multimedia presentation are in conversational style rather than formal style. This principle was supported in 10 out of 10 experimental tests, yielding a median effect size of 1.3. The voice principle is that people learn more deeply when the words in a multimedia message are spoken in a standard-accented human voice rather than in a machine voice or foreign-accented human voice. This principle was supported in four out of four experimental comparisons, with a median effect size of 0.8. The image principle is that people do not necessarily learn more deeply from a multimedia presentation when the speaker's image is on the screen rather than not on the screen. This principle was based on nine experimental tests with mixed results, yielding a median effect size of 0.2.

What Are the Personalization, Voice, and Image Principles?

Definitions

The goal of this chapter is to examine the research evidence concerning three principles for multimedia design that are based on social cues – personalization, voice, and image principles. The personalization principle is that people learn more deeply when the words in a multimedia presentation are in conversational style rather than formal style.

Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2005

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Atkinson, R. K. (2002). Optimizing learning from examples using animated pedagogical agents. Journal of Educational Psychology, 94, 416–427CrossRefGoogle Scholar
Atkinson, R. K., Mayer, R. E., & Merrill, M. M. (in press). Fostering social agency in multimedia learning: Examining the impact of an animated agent's voice. Contemporary Educational PsychologyGoogle Scholar
Brunken, R., Plass, J., & Leutner, D. (2003). Direct measurement of cognitive load in multimedia learning. Educational Psychologist, 38, 53–62CrossRefGoogle Scholar
Cassell, J., Sullivan, J., Prevost, S., & Churchill, E. (Eds.). (2000). Embodied conversational agents. Cambridge, MA: MIT PressGoogle Scholar
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum AssociatesGoogle Scholar
Cortina, J. M., & Nouri, H. (2000). Effect size for ANOVA designs. Thousand Oaks, CA: SageCrossRefGoogle Scholar
Craig, S. D., Gholson, B., Driscoll, D. M. (2002). Animated pedagogical agent in multimedia educational environments: Effects of agent properties, picture features, and redundancy. Journal of Educational Psychology, 94, 428–434CrossRefGoogle Scholar
Grice, H. P. (1975). Logic and conversation. In Cole, P. & Morgan, J. (Eds.), Syntax and semantics (Vol. 3, pp. 41–58). New York: Academic PressGoogle Scholar
Harp, S. F., & Mayer, R. E. (1998). How seductive details do their damage: A theory of cognitive interest in science learning. Journal of Educational Psychology, 90, 414–434CrossRefGoogle Scholar
Lepper, M. R., Woolverton, M., Mumme, D., & Gurtner, J. (1993). Motivational techniques of expert human tutors: Lessons for the design of computer-based tutors. In Lajoie, S. P. & Derry, S. J. (Eds.), Computers as cognitive tools (pp. 75–105). Hillsdale, NJ: ErlbaumGoogle Scholar
Mayer, R. E. (2001). Multimedia learning. New York: Cambridge University PressCrossRefGoogle Scholar
Mayer, R. E., Dow, G., & Mayer, S. (2003). Multimedia learning in an interactive self-explaining environment: What works in the design of agent-based microworlds?Journal of Educational Psychology, 95, 806–813CrossRefGoogle Scholar
Mayer, R. E., Fennell, S., Farmer, L., & Campbell, J. (2004). A personalization effect in multimedia learning: Students learn better when words are in conversational style rather than formal style. Journal of Educational Psychology, 96, 389–395CrossRefGoogle Scholar
Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38, 43–52CrossRefGoogle Scholar
Mayer, R. E., Sobko, K., & Mautone, P. D. (2003). Social cues in multimedia learning: Role of speaker's voice. Journal of Educational Psychology, 95, 419–425CrossRefGoogle Scholar
Moreno, R., & Mayer, R. E. (2000). Engaging students in active learning: The case for personalized multimedia messages. Journal of Educational Psychology, 92, 724–733CrossRefGoogle Scholar
Moreno, R., & Mayer, R. E. (2004). Personalized messages that promote science learning in virtual environments. Journal of Educational Psychology, 96, 165–173CrossRefGoogle Scholar
Moreno, R., Mayer, R. E., Spires, H. A., & Lester, J. C. (2001). The case for social agency in computer-based teaching: Do students learn more deeply when they interact with animated pedagogical agents?Cognition and Instruction, 19, 177–213CrossRefGoogle Scholar
Paas, F., Renkl, A., & Sweller, J. (2003). Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38, 1–4CrossRefGoogle Scholar
Paas, F., Tuovinen, J. E., Tabbers, H., & Gerven, P. W. M. (2003). Cognitive load measurement as a means to advance cognitive load theory. Educational Psychologist, 38, 63–72CrossRefGoogle Scholar
Reeves, B., and Nass, C. (1996). The media equation. New York: Cambridge University PressGoogle Scholar
Sweller, J. (1999). Instructional design in technical areas. Camberwell, Australia: ACER PressGoogle Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×