Cognitive factors that influence children’s learning from a multimedia science lesson
Keywords:
Science Learning, Multimedia Instruction, Causal Coherence, Elementary EducationAbstract
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.
Downloads
Download data is not yet available.
References
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.
zMcNamara, 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.
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.
zMcNamara, 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.
Downloads
Published
2017-07-25
How to Cite
Anggoro, F. K., Stein, N. L., & Jee, B. D. (2017). Cognitive factors that influence children’s learning from a multimedia science lesson. International Electronic Journal of Elementary Education, 5(1), 93–108. Retrieved from https://iejee.com/index.php/IEJEE/article/view/12
Issue
Section
Articles
