Cognitive Factors That Influence Children’s Learning from a Multimedia Science Lesson

Florencia K. ANGGORO, Nancy L. STEIN, Benjamin D. JEE


The present study examined the cognitive factors that influence children’s physical science learning from a multimedia instruction. Using a causally coherent text and visual models, we taught 4th- and 7th- grade children about the observable and molecular properties of the three states of water. We manipulated whether the text was read by a tutor (which supports simultaneous encoding of the verbal and visual information, i.e., temporal contiguity) or whether children read the text on their own (which supports self pacing and interpretation of the information). Children in each condition received either static or dynamic graphics. Results showed that, regardless of the type of graphics, children demonstrated the greatest learning gains when the text was read to them by a tutor. This effect was more pronounced for the younger children. Thus, conditions that promote integration of verbal and visual information may provide the greatest support to children’s learning from a causally coherent multimedia science lesson.


Science Learning, Multimedia Instruction, Causal Coherence, Elementary Education.

Paper Details

Paper Details
Topic EU Education Programs
Pages 93 - 108
Issue IEJEE, Volume 5, Issue 1, Special Issue Learning and Instruction in the Natural Sciences
Date of acceptance 01 October 2012
Read (times) 588
Downloaded (times) 357

Author(s) Details

Florencia K. ANGGORO

College of the Holy Cross , United States

Nancy L. STEIN

National Opinion Research Center and the University of Chicago , United States

Benjamin D. JEE

College of the Holy Cross , United States


Bar, V., & Galili, I. (1994). Stages of children's views about evaporation. International Journal of Science Education, 16(2), 157-174.

Duschl, R. A., Schweingruber, H. A., Shouse, A. W., National Research Council (U.S.). Committee on Science Learning Kindergarten Through Eighth Grade. National Research Council (U.S.). Board on Science Education & National Research Council (U.S.) (2007). Taking science to school: Learning and teaching science in grades K-8. Washington, D.C.: National Academies Press.

Flavell, J. H. ( 2000 ). Development of children’s knowledge about the mental world. International Journal of Behavioral Development, 24, 15–23.

Gobert, J., & Buckley, B. (2000). Special issue editorial: Introduction to model-based teaching and learning. International Journal of Science Education, 22(9), 891-894.

Goldberg, F., & Bendall, S. (1995). Making the invisible visible: A teaching/learning environment that builds on a new view of the physics learner. American Journal of Physics 63(11), 978-991.

Jose, T. J. & Williamson, V. M. (2005). Molecular visualization in science education: An evaluation of the NSF funded workshop. Journal of Chemical Education, 82(6), 937-943.

Klausmeier, H. J. (1992). Concept learning and concept teaching. Educational Psychologist, 27(3), 267. Larkin, J., & Simon, H. (1987). Why a diagram is (sometimes) worth ten thousand words. Cognitive Science, 11, 65-99.

Mandler, J. M. (2008). On the birth and growth of concepts. Philosophical Psychology, 21(2), 207-230.

Mayer, R.E., & Anderson, B. (1991). Animations need narrations: An experimental test of a dualcoding hypothesis. Journal of Educational Psychology, 3, 484-490.

Mayer, R.E., & Chandler, P. (2001). When learning is just a click away: Does simple user interaction foster deeper understanding of multimedia messages? Journal of Educational Psychology, 93, 390-397.

Mayer, R. E., Hegarty, M., Mayer, S., & Campbell, J. (2005). When static media promote active learning: Annotated illustrations versus narrated animations in multimedia instruction. Journal of Experimental Psychology: Applied, 11(4), 256-265.

Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38, 43-52.

McNamara, D. S., Kintsch, E., Songer, N. B., & Kintsch, W. (1996). Are good texts always better?Interactions of text coherence, background knowledge, and levels of understanding in learning from text. Cognition and Instruction, 14(1), 1-43.

Metcalfe, J., & Shimamura, A. P. (1994). Metacognition: knowing about knowing. Cambridge, MA: MIT Press.

National Research Council (U.S.) (1996). National science education standards: Observe, interact, change, learn. Washington, DC: National Academy Press.

Project 2061 (American Association for the Advancement of Science) (1993). Benchmarks for science literacy. New York: Oxford University Press.

Romance, N. R., & Vitale, M. R. (2001). Implementing an in-depth expanded science model in elementary schools: Multi-year findings, research issues, and policy implications. International Journal of Science Education, 23, 373-404.

Romance, N. R., & Vitale, M. R. (2010). Effects of an integrated instructional model for accelerating student achievement in science and reading comprehension in grades 1-2. Presented at the Annual Meeting of the American Educational Research Association, Denver, CO.

Schneider, W. (2008). The development of metacognitive knowledge in children and adolescents: Major trends and implications for education. Mind, Brain, and Education, 2, 114–121.

Shwartz, Y., Weizman, A., Fortus, D., Krajcik, J., & Reiser, B. (2008). Middle school science curriculum: Coherence as a design principle. Paper presented at the National Association of Research in Science Teaching.

Slotta, J. D., & Chi, M. T. H. (2006). The impact of ontology training on conceptual change: Helping students understand the challenging topics in science. Cognition and Instruction, 24, 261-289.

Stein, N. L., Hernandez, M. W., & Anggoro, F. K. (2010). A theory of coherence and complex learning in the physical sciences: What works (and what doesn't). In N. L. Stein & S. W. Raudenbush (Eds.), Developmental science goes to school. New York: Taylor and Francis, Inc.

Stein, N. L., Hernandez, M. W., Anggoro, F. K., & Hedberg, E. (under review). A developmental study of physical science learning: Modeling invisible processes and starting early.

Stein, N. L., & Levine, L. J. (1989). The causal organization of emotional knowledge: A developmental study. Cognition & Emotion, 3(4), 343-378.

Stein, N. L., & Miller, C. A. (1993). A theory of argumentative understanding: Relationships among position preference, judgments of goodness, memory, and reasoning. Argumentation, 7, 183-204.

Stein, N. L., & Trabasso, T. (1982). What's in a story: An approach to comprehension and instruction. In R. Glaser (Ed.), Advances in Instructional Psychology, 2, 212-267. Hillsdale, NJ: Lawrence Erlbaum Associates.

Thagard, P. (2000). Coherence in thought and action. Cambridge: The MIT Press.

Trabasso, T., & Bouchard, E. (2002). Teaching readers how to comprehend text strategically. In Block, C.C. & M. Pressley (Eds.), Comprehension instruction: Research-based best practices (pp. 176-200). New York: The Guilford Press.

Trabasso, T., Secco, T., & van den Broek, P. W. (1984). Causal cohesion and story coherence. In H. Mandl, N. L. Stein & T. Trabasso (Eds.), Learning and comprehension of text (pp. 83-111). Hillsdale, NJ: Lawrence Erlbaum Associates.

Trabasso, T., & Stein, N. L. (1997). Narrating, representing, and remembering event sequences. In P. W. van den Broek, P. J. Bauer & T. Bourg (Eds.), Developmental spans in event comprehension and representation: Bridging fictional and actual events (pp. 237-270). Hillsdale, NJ: Lawrence Erlbaum Associates.

Tversky, B., Heiser, J., Lozano, S., MacKenzie, R., & Morrison, J. (2008). Enriching animations. In R. Lowe & W. Schnotz (Eds.), Learning with animation. Cambridge: Cambridge University Press.

Vosniadou, S. & Brewer, W. F. (1992). Mental models of the earth: A study of conceptual change in childhood. Cognitive Psychology, 24, 535-585.

Winston, P. (1986). Learning by augmenting rules and accumulating censors. In R. S. Michalski, Carbonell, J. G., & Mitchell, T. M. (Ed.), Machine learning: An artificial intelligence approach. New York: Morgan Kaufmann.