GRiSSH::Themes in science and technology education | Vol.6, No.2, 2013 | The effect of representations on difficulty perception and learning of the physical concept of pressure

Information

The effect of representations on difficulty perception and learning of the physical concept of pressure

Part of : Themes in science and technology education ; Vol.6, No.2, 2013, pages 91-108

Issue:

Vol.6, No.2, 2013

Pages:

91-108

Author:

Abstract:

Previous research indicates that when learners divide their attention over different sources of information (representations), learners perceive the information as more difficult and have a harder time increasing their understanding. This can be overcome by integrating representations. In this research, using 85 participants, we hypothesized that integrated representations of physics would be perceived as less difficult. Repeated measures MANOVA showed a significant interaction effect between results on the learning tasks and the perceived difficulty questionnaire. Results are discussed in the context of the performance evaluation effect that can occur in more ecologically valid settings.

Subject:

Educational sciences

Subject (LC):

Εκπαίδευση

Keywords:

multiple representations, integration, difficulty perception, ecological setting, physics education

Notes:

Appendix with questionnaire

References (1):

Ainsworth, S. (1999). The functions of multiple representations. Computers & Education, 33, 131-152.Ainsworth, S. (2006). DeFT: A conceptual framework for considering learning with multiple representations. Learning and Instruction, 16, 183-198.Ainsworth, S. (2008). The educational value of multiple-representations when learning complex scientific concepts. In J. Gilbert, M. Reiner & M. Nakhleh (eds.), Visualisation: Theory and practice in science education (pp. 191-208). Deventer: Kluwer Academic Publishers.Berthold, K., & Renkl, A. (2009). Instructional aids to support a conceptual understanding of multiple representations. Journal of Educational Psychology, 101(1), 70-87.Bloomfield, L. (ed.) (2006). How things work: The physics of everyday life. New York: John Wiley & Sons.Bodemer, D., Ploetzner, R., Feuerlein, I., & Spada, H. (2004). The active integration of information during learning with dynamic and interactive visualizations. Learning and Instruction, 14, 325-341.Bratfisch, O. (1972). Perceptual correlates of mental performance: Perceived difficulty and experienced intellectual activity. Retrieved 20 May 2013, from http://www.eric.ed.gov/ERICWebPortal/detail?accno=ED080557.Brünken, R., Plass, J., & Leutner, D. (2003). Direct measurement of cognitive load in multimedia learning. Educational Psychologist, 38(1), 53-61.Carpreau, M., Depover, A., Herreman, W., Merlin, N., & Vandekerckhove, A. (2007). Physics Today 4.1. [Fysica Vandaag 4.1]. Kapellen: Pelckmans.Chandler, P., & Sweller, J. (1991). Cognitive load theory and the format of instruction. Cognition and Instruction, 8(4), 293-332.Chandler, P., & Sweller, J. (1992). The split-attention effect as a factor in the design of instruction. Britisch Journal of Educational Psychology, 62(2), 233-246.Cheng, M., & Gilbert, J. (2007). Towards a better utilization of diagrams in science educational research. Retrieved 20 May 2013, from http://na-serv.did.gu.se/ESERA2007/pdf/153B.pdf.Chittleborough, G., & Treagust, D. (2008). Correct interpretation of chemical diagrams requires transforming from one level of representation to another. Research in Science Education, 38, 463–482.Cierniak, G., Scheiter, K., & Gerjets, P. (2009). Explaining the split-attention effect: Is the reduction of extraneous cognitive load accompanied by an increase in germane cognitive load?. Computers in Human Behaviour, 25(2), 315-324.Cook, M. (2006). Visual representations in science education: The influence of prior knowledge and cognitive load theory on instructional design principles. Science Education, 90(6), 1073-1091.Cox, R., & Brna, P. (1995). Supporting the use of external representations in problem solving: The need for flexible learning environments. Journal of Artificial Intelligence in Education, 6(2/3), 239-302.de Jong, T. (2010). Cognitive load theory, educational research, and instructional design: Some food for thought. Instructional Science, 38, 105-134.de Jong, T., Ainsworth, S., Dobson, M., van der Hulst, A., Levonen, J., Reimann, P., Sime, J., van Someren, M., Spada, H., & Swaak, J. (1999). Acquiring knowledge in science and mathematics: The use of multiple representations in technology-based learning environments. In W. Van Someren, P. Reimann, H. Boshuizen & T. de Jong (eds.), Learning with multiple representations (pp. 9-40). Oxford: Pergamon.Ginns, P. (2006). Integrating information: A meta-analysis of the spatial contiguity and temporal contiguity effects. Learning and Instruction, 16(6), 511-525.Harskamp, E. G., Mayer R. E., & Suhre, C. (2007). Does the modality principle for multimedia learning apply to science classrooms? Learning and Instruction, 17(5), 465-477.Kohl, P., Rosengrant, D., & Finkelstein, N. (2007). Strongly and weakly directed approaches to teaching multiple representation use in physics. Physical Review Special Topics - Physics Education Research, 3(1), 010108.Kolloffel, B., Eysink, T., de Jong, T., & Wilhelm, P. (2009). The effects of representational format on learning combinatorics from an interactive computer simulation. Instructional Science, 37(6), 503-517.Kozma, R. B. (2003). The material features of multiple representations and their cognitive and social affordances for science understanding. Learning and Instruction, 13(2), 205-226.Larkin, J., & Simon, H. (1987). Why a diagram is (sometimes) worth ten thousand words. Cognitive Science, 11(1), 65-99.Marcus, N., Cooper, M., & Sweller, J. (1996). Understanding instructions. Journal of Educational Psychology, 88(1), 49-63.Mayer, R. E., & Gallini, J. K. (1990). When is an illustration worth ten thousand words?. Journal of Educational Psychology, 82(4), 715-726.Merrill, M. D. (1994). Instructional design theory. New Jersey: Educational Technology Publications.Nunnally, Y. J. (1978). Psychometric theory. New York: McGraw Hill.Paas, F., Tuovinen, J., Tabbers, H., & Van Gerven, P. (2003). Cognitive load measurement as a means to advance cognitive load theory. Educational Psychologist, 38(1), 63-71.Pintrich, P. R., & Schunk, D. H. (2002). Motivation in education: Theory, research, and applications. Upper Saddle River, NJ: Merrill (2nd ed.).Robinson, P. (2001). Task complexity, task difficulty, and task production: Exploring interactions in a componential framework. Applied Linguistics, 22(1), 27-57.Rosengrant, D., Van Heuvelen, A., & Etkina, E. (2009). Do students use and understand free-body diagrams? Physical Review Special Topics - Physics Education Research, 5, 010108.Scanlon, E. (1998). How beginning students use graphs of motion. In W. Van Someren, P. Reimann, H. Boshuizen, & T. de Jong (eds.), Learning with multiple representations (pp. 67-86). Oxford: Pergamon.Schnotz, W. (2002). Towards an integrated view of learning from text and visual displays. Educational Psychology Review, 14(1), 101-120.Schnotz, W., Baadte, C., Müller, A., & Rash, R. (2010). Creative thinking and problem solving with depictive and descriptive representations. In L. Verschaffel, E. De Corte, T. de Jong & J. Elen (eds.), Use of representations in reasoning and problem solving (pp. 11-35). London: Routledge.Schnotz, W., & Bannert, M. (2003). Construction and interference in learning from multiple representation. Learning and Instruction, 13(2), 141-156.Schnotz, W., & Kürschner, C. (2007). A reconsideration of cognitive load theory. Educational Psychology Review, 19(4), 469-508.Schunk, D. H. (1985). Self-efficacy and classroom learning. Psychology in the Schools, 22(2), 208-223.Schunk, D. H. (2008). Learning theories: an educational perspective. Upper Saddle River, NJ: Prentice Hall (5th ed.).Stenning, K., & Oberlander, J. (1995). A cognitive theory of graphical and linguistic reasoning: Logic and implementation. Cognitive Science, 19(1), 97-140.Stylianidou, F. (2002). Analysis of science textbook pictures about energy and pupils’ readings of them. International Journal of Science Education, 24(3), 257-283.Sweller, J. (1994). Cognitive load theory, learning difficulty, and instructional design. Learning and Instruction, 4(4), 295-312.Sweller, J. (2008). Human cognitive architecture. In J. M. Spector, M. D. Merrill, J. J. G. Van Merrienboer & M. P. Driscoll (eds.), Handbook of research on educational communications and technology (pp. 369-381). New York, NY: Lawrence Erlbaum Associates (3rd ed.).Sweller, J., Chandler, P., Tierney, P., & Cooper, M. (1990). Cognitive load as a factor in the structuring of technical material. Journal of Experimental Psychology, 119(2), 176-192.van der Meij, J. (2007). Support for learning with multiple representations: Designing simulation-based learning environments. Unpublished doctoral dissertation, Universiteit Twente, Enschede.van der Meij, J., & de Jong, T. (2003). Learning with multiple representations. Paper presented at the EARLI Conference, 26 August, Padua, Italy. Retrieved 20 May 2013, from http://www.it.iitb.ac.in/~s1000brains/rswork/dokuwiki/media/learning_with_multiple_representations.pdf.van der Meij, J., & de Jong, T. (2006). Supporting students’ learning with multiple representations in a dynamic simulation-based learning environment. Learning and Instruction, 16(3), 199-212.Vosniadou, S. (2010). Instructional considerations in the use of external representations: The distinction between perceptually based depictions and pictures that represent conceptual models. In L. Verschaffel, E. De Corte, T. de Jong & J. Elen (eds.), Use of representations in reasoning and problem solving (pp. 36-54). London: Routledge.Yeung, A. (1999). Cognitive load and learner expertise: Split-attention and redundancy effects in reading comprehension tasks with vocabulary definitions. The Journal of Experimental Education, 67(3), 197-217.