Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-76fb5796d-5g6vh Total loading time: 0 Render date: 2024-04-25T14:17:44.842Z Has data issue: false hasContentIssue false

26 - Multimedia Learning of Chemistry

Published online by Cambridge University Press:  05 June 2012

By
Robert Kozma  and
Joel Russell
Edited by
Richard Mayer
Robert Kozma
Affiliation:
Center for Technology in Learning, SRI International
Joel Russell
Affiliation:
Oakland University
Richard Mayer
Affiliation:
University of California, Santa Barbara
Get access

Summary

Abstract

This chapter proposes the use of a “situative” theory to complement the cognitive theory of multimedia learning (CTML) of chemistry. The chapter applies situative theory to examine the practices of chemists and to derive implications for the use of various kinds of representations in chemistry education. The two theories have implications for different but complementary educational goals – cognitive theory focusing on the learning of scientific concepts and situative theory focusing on learning science as an investigative process. We go on to present and contrast several examples of multimedia in chemistry that address each goal. We critically review the current state of research on multimedia in chemistry and derive implications for theory development, instructional design and classroom practice, and future research in the area.

What Is the Multimedia Learning of Chemistry?

Multimedia to Support Cognition

Richard Mayer (chapter 3; 2001; 2002, 2003), and others (Schnotz, chapter 4; Sweller, chapter 2) describe an information-processing, cognitive theory of learning. There are three tenets at the base of this theory: dual-channel input, limited-memory capacity, and active processing. Mayer draws on this theory to develop a series of design principles for multimedia presentations that use both auditory–verbal and visual–pictorial channels; address limited cognitive capacity for storing and processing information from these channels; and support students' active selection, organization, and integration of information from both auditory and visual inputs.

Type
Chapter
Information
The Cambridge Handbook of Multimedia Learning , pp. 409 - 428
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

Agapova, O., Jones, L., Ushakov, A., Ratcliffe, A., & Martin, M. (2002). Encouraging independent chemistry learning through multimedia design experiences. Chemical Education International, 3(3), 1–8Google Scholar
Ardac, D., & Akaygun, S. (2004). Effectiveness of multimedia-based instruction that emphasizes molecular representations on students' understanding of chemical change. Journal of Research in Science Teaching, 41(4), 317–337CrossRefGoogle Scholar
Banerjee, A. (1995). Teaching chemical equilibrium and thermodynamics in undergraduate general chemistry classes. Journal of Chemical Education, 72, 879–881CrossRefGoogle Scholar
Barnea, N., & Dori, Y. (1999). High-school chemistry students' performance and gender differences in a computerized molecular modeling learning environment. Journal of Science Education and Technology, 8(4), 257–271CrossRefGoogle Scholar
Bragin, V. (1996). Interactive computer visualization in the introductory chemistry curriculum. Journal of Chemical Education, 73(8), 747–749CrossRefGoogle Scholar
Brown, A., & Campione, J. (1996). Guided discovery in a community of learners. In McGilly, K. (Ed.), Classroom lessons: Integrating cognitive theory and classroom practice (pp. 229–270). Cambridge, MA: MIT PressGoogle Scholar
Brown, J. S., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational Researcher, 18(1), 32–42CrossRefGoogle Scholar
Bunce, D., & Gabel, D. (2002). Differential effects on the achievement of males and females of teaching the particulate nature of chemistry. Journal of Research in Science Teaching, 39(10), 911–927CrossRefGoogle Scholar
Camacho, M., & Good, R. (1989). Problem solving and chemical equilibrium: Successful versus unsuccessful performance. Journal of Research in Science Teaching, 26, 251–272CrossRefGoogle Scholar
Cody, J., & Dawn, W. (2003). Laboratory sequence in computational methods for introductory chemistry. Journal of Chemical Education, 80(7), 793–795CrossRefGoogle Scholar
Dori, Y., & Barak, M. (2001). Virtual and physical molecular modeling: Fostering model perception and spatial understanding. Educational Technology and Society, 4(1), 61–73Google Scholar
Francoeur, E. (2002). Cyrus Levinthal, the Kluge, and the origins of interactive molecular graphics. Endeavour, 26(4), 127–131CrossRefGoogle Scholar
Gabel, D. (1998). The complexity of chemistry and its implications for teaching. In Fraser, B. & Tobin, K. (Eds.), International handbook of science education (pp. 233–248). Dordrecht, The Netherlands: KluwerCrossRefGoogle Scholar
Gabel, D., & Bunce, D. (1994). Research on problem solving: Chemistry. In Gable, D. (Ed.), Handbook of research on science teaching and learning (pp. 301–326). New York: MacMillianGoogle Scholar
Gorodetsky, M., & Gussarsky, E. (1986). Misconceptualization of the chemical equilibrium concept as revealed by different evaluation methods. European Journal of Science Education, 8(4), 427–441CrossRefGoogle Scholar
Greeno, J. (1998). The situativity of knowing, learning, and research. American Psychologist, 53(1), 5–26CrossRefGoogle Scholar
Jones, M. (2001). Molecular modeling in the undergraduate chemistry curriculum. Journal of Chemical Education, 78(7), 867–868CrossRefGoogle Scholar
Kantardjieff, K., Hardinger, S., & Willis, W. (1999). Introducing computers early in the undergraduate chemistry curriculum. Journal of Chemical Education, 76(5), 694–697CrossRefGoogle Scholar
Kozma, R. B. (2000a). Students collaborating with computer models and physical experiments. In Roschelle, J. & Hoadley, C. (Eds.), Proceedings of the Conference on Computer-Supported Collaborative Learning 1999. Mahwah, NJ: Lawrence Erlbaum AssociatesGoogle Scholar
Kozma, R. B. (2000b). The use of multiple representations and the social construction of understanding in chemistry. In Jacobson, M. & Kozma, R. (Eds.), Innovations in science and mathematics education: Advanced designs for technologies of learning (pp. 11–46). Mahwah, NJ: Lawrence Erlbaum AssociatesGoogle Scholar
Kozma, R. B., Chin, E., Russell, J., & Marx, N. (2000). The role of representations and tools in the chemistry laboratory and their implications for chemistry learning. Journal of the Learning Sciences, 9(3), 105–144CrossRefGoogle Scholar
Kozma, R. B., & Russell, J. (1997). Multimedia and understanding: Expert and novice responses to different representations of chemical phenomena. Journal of Research in Science Teaching, 34(9), 949–9683.0.CO;2-U>CrossRefGoogle Scholar
Kozma, R. B., & Russell, J. (in press). Students becoming chemists: Developing representational competence. In Gilbert, J. (Ed.), Visualization in Science Education. Dordrecht, The Netherlands: KluwerCrossRef
Kozma, R. B., Russell, J., Johnston, J., & Dershimer, C. (1990, April). College students' conceptions and misconceptions of chemical equilibrium. Paper presented at the meeting of the American Educational Research Association, Boston, MA
Kozma, R. B., Russell, J., Jones, T., Marx, N., & Davis, J. (1996). The use of multiple, linked representations to facilitate science understanding. In Vosniadou, S., Glaser, R., DeCorte, E., & Mandel, H. (Eds.), International perspective on the psychological foundations of technology-based learning environments (pp. 41–60). Hillsdale, NJ: Lawrence Erlbaum AssociatesGoogle Scholar
Krajcik, J., Blumenfeld, P., Marx, R., Bass, K., Fredricks, J., & Soloway, E. (1998). Inquiry in project-based science classrooms: Initial attempts by middle school students. Journal of the Learning Sciences, 7(3 & 4), 313–351CrossRefGoogle Scholar
Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. Cambridge, UK: Cambridge University PressCrossRefGoogle Scholar
Martin, N. (1998). Integration of computational chemistry into the chemistry curriculum. Journal of Chemical Education, 75(2), 241CrossRefGoogle Scholar
Mayer, R. (2001). Multimedia learning. Cambridge, UK: Cambridge University PressCrossRefGoogle Scholar
Mayer, R. (2002). Cognitive theory and the design of multimedia instruction: An example of the two-way street between cognition and instruction. New Directions in Teaching and Learning, 89, 55–71CrossRefGoogle Scholar
Mayer, R. (2003). The promise of multimedia learning: Using the same instructional design methods across different media. Learning and Instruction, 13(2), 125–140CrossRefGoogle Scholar
Montgomery, C. (2001). Integrating molecular modeling into the inorganic chemistry laboratory. Journal of Chemical Education, 78(6), 840–844CrossRefGoogle Scholar
Nakhleh, M. (1992). Why some students don't learn chemistry. Journal of Chemical Education, 69(3), 191–196CrossRefGoogle Scholar
National Research Council (996). National science education standards. Washington, DC: National Academy Press
Noh, T., & Scharmann, L. (1997). Instructional influence of a molecular-level pictorial presentation of matter on students' conceptions and problem-solving ability. Journal of Research in Science Teaching, 34(2), 199–2173.0.CO;2-O>CrossRefGoogle Scholar
Roth, W.-M. (1998). Teaching and learning as everyday activity. In Fraser, B. & Tobin, K. (Eds.), International Handbook of science education (pp. 169–181). Dordrecht, The Netherlands: KluwerCrossRefGoogle Scholar
Roth, W.-M. (2001). Situating cognition. The Journal of the Learning Sciences, 10, 27–61CrossRefGoogle Scholar
Roth, W.-M., & McGinn, M. (1998). Inscriptions: Toward a theory of representing as social practice. Review of Educational Research, 68(1), 35–59CrossRefGoogle Scholar
Russell, J. (2004). Enhancing chemical understanding and visualization skills with SMV:Chem – synchronized multiple visualizations of chemistry. Manuscript submitted for publication
Russell, J., & Kozma, R. (1994). 4M:Chem – Multimedia and Mental Models in Chemistry. Journal of Chemical Education, 71 (669–670)CrossRefGoogle Scholar
Russell, J., Kozma, R., Becker, D., & Susskind, T. (2000). SMV:Chem – Synchronized Multiple Visualizations in Chemistry [Computer software]. New York: John WileyGoogle Scholar
Russell, J., Kozma, R., Jones, T., Wykoff, J., Marx, N., & Davis, J. (1997). Use of simultaneous-synchronized macroscopic, microscopic, and symbolic representations to enhance the teaching and learning of chemical concepts. Journal of Chemical Education, 74(3), 330–334CrossRefGoogle Scholar
Sanger, M., & Badger, S. (2001). Using computer-based visualization strategies to improve students' understanding of molecular polarity and miscibility. Journal of Chemical Education, 78(10), 1412–1416CrossRefGoogle Scholar
Sanger, M., & Greenbowe, T. (2000). Addressing student misconceptions concerning electron flow in aqueous solutions with instruction including computer animiations and conceptual change strategies. International Journal of Science Education, 22(5), 521–537CrossRefGoogle Scholar
Sanger, M., Phelps, A., & Fienhold, J. (2000). Using a computer animation to improve students' conceptual understanding of a con-crushing demonstration. Journal of Chemical Education, 77(11), 1517–1520CrossRefGoogle Scholar
Scardamalia, M., & Bereiter, C. (1994). Computer support for knowledge-building communities. Journal of the Learning Sciences, 3(3), 265–283CrossRefGoogle Scholar
Schank, P., & Kozma, R. (2002). Learning chemistry through the use of a representation-based knowledge-building environment. Journal of Computers in Mathematics and Science Teaching, 21(3), 253–279Google Scholar
Stieff, M., & Wilensky, U. (2003). Connected Chemistry: Incoporating interactive simulations into the chemistry curriculum. Journal of Science Education and Technology, 12(3), 285–302CrossRefGoogle Scholar
Thomas, P., & Schwenz, R. (1998). College physical chemistry students' conceptions of equilibrium and fundamental thermodynamics. Journal of Research in Science Teaching, 35(10), 1151–11603.0.CO;2-K>CrossRefGoogle Scholar
Williamson, V., & Abraham, M. (1995). The effects of computer animation on the particulate mental models of college chemistry students. Journal of Research in Science Teaching, 32(5), 521–534CrossRefGoogle Scholar
Xie, Q., & Tinker, R. (in press). Molecular dynamics simulations of chemical reactions for use in education. Journal of Chemical EducationGoogle Scholar
Yang, E.-M., Andre, T., & Greenbowe, T. (2003). Spatialability and the impact of visualization/animation on learning electrochemistry. International Journal of Science Education, 25(3), 329–349CrossRefGoogle Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org 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
×