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Students’ Understanding Is Enhanced Through Molecular Modeling

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Abstract

Integration of molecular modeling into General Chemistry lab encourages students to dually process molecular concepts both verbally and pictorially. When students are tested utilizing questions not previously encountered the dual processing of information can contribute to a transfer to knowledge. General Chemistry students utilized molecular modeling in lab and a comparison of a treatment and nontreatment group during two semesters is presented for a pretest, posttest, and on semester exam questions. The treatment group tested significantly higher than the nontreatment group on both the posttest and semester exam questions related to molecular concepts illustrating that there was a transfer of knowledge.

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References

  • Baddeley, A. D. (1992). Working memory. Science 255: 556–559.

    Google Scholar 

  • Barnea, N. (1997). In Gilbert, J. K. (Ed.), The Use of Computer-Based Analog Models to Improve Visualization and Chemical Understanding, The University of Reading, The New Bulmershe Papers, UK.

    Google Scholar 

  • Barnea, N., and Dori, Y. J. (2000). Computerized molecular modeling: Technology for enhancing model perception among chemistry educators and the new learners. Chemistry Education: Research and Practice in Europe 1: 109–120.

    Google Scholar 

  • Bunce, D. M., and 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: 911–927.

    Google Scholar 

  • Chandler, P., and Sweller, J. (1991). Cognitive load theory and the format of instruction. J. Cognition and Instruction 8: 293–332.

    Google Scholar 

  • Clark, J. M., and Paivio, A. (1991). Dual coding theory and education. Educational Psychological Review 3: 149–210.

    Google Scholar 

  • Dabrowiak, J. C., Hatala, P. J., and McPike, M. (2000). A mole-cular modeling program for teaching structural biochemistry. Journal of Chemical Education 77, 397.

    Google Scholar 

  • Dori, Y. J., and Barak, M. (2001). Virtual and physical molecular modeling: Fostering model perception and spatial understanding. Educational Technology and Society 4: 61–74.

    Google Scholar 

  • Ealy, J. B. (1999). A student evaluation of molecular modeling in first year college chemistry. Journal of Science Education and Technology 8, 309.

    Google Scholar 

  • Ealy, J. B. (2001). Exercises, Assessment, and the Results of Assessment of Spartan, American Chemical Society National Meeting, San Diego, California.

    Google Scholar 

  • Ealy, J. B. (2003). Results of a Second Study of Students’ Utilization of Molecular Modeling in General Chemistry: Comparison with Students Who Did Not Utilize Molecular Modeling, American Chemical Society National Meeting, New York City, New York.

    Google Scholar 

  • Friedel, A. W., and Maloney, D. P. (1992). An exploratory, classroom-based investigation of students’ difficulties with subscripts. Science Education 76: 65–78.

    Google Scholar 

  • Gabel, D. L. (1993). Use of the particulate nature of matter in developing conceptual understanding. Journal of Chemical Education 70: 193–194.

    Google Scholar 

  • Gabel, D. L., and Bunce, D. M. (1994). In Gabel, D. (Ed.), Research on Problem Solving: Chemistry, MacMillan, New York.

    Google Scholar 

  • Gasyna, Z. L., and Rice, S. A. (1999). Computational chemistry in the undergraduate chemistry curriculum: Development of a comprehensive course formula. Journal of Chemical Education 76, 1023.

    Google Scholar 

  • Hanna, N. R. (2002). Educational Technology and Society, http://ifets.ieee.org/periodical/vol_3_2002/hanna.html.

  • Johnstone, A. H. (1991). Why is science difficult to learn? Things are seldom what they seem. Journal of Computer Assisted Learning 7: 75–83.

    Google Scholar 

  • Johnstone, A. H. (2000). Teaching of chemistry - logical or psychological. Chemistry Education: Research and Practice in Europe 1: 9–15.

    Google Scholar 

  • Jones, M. B. (2001). Molecular modeling in the undergraduate chemistry curriculum. Journal of Chemical Education 78, 867.

    Google Scholar 

  • Kozma, R. B. (1999). In Roschelle, C. H. J. (Ed.), Students Collaborating with Computer Models and Physical Experiments, Lawrence Erlbaum Associates, Mahwah, NJ; Stanford University, Palo Alto, CA.

    Google Scholar 

  • Kruse, R. (2004). Molecular Visualization in Chemistry Education: The GK-12 Program at Danville High School, http://www.inquiry.uiuc.edu.

  • Lowery, M. S., and Plesniak, L. A. (2003). Some like it cold: A computer-based laboratory introduction to sequence and tertiary structure comparison of cold-adapted lactate dehydrogenases using bioinformatics tools. Journal of Chemical Education 80, 1300.

    Google Scholar 

  • Mayer, R. E. (2001). Multi-media Learning, Cambridge University Press, Cambridge, UK.

    Google Scholar 

  • Mayer, R. E. (1999). The Promise of Educational Psychology, Prentice-Hall/Merrill, Upper Saddle River, NJ.

    Google Scholar 

  • Martin, N. H. (1998). Integration of computational chemistry into the chemistry curriculum. Journal of Chemical Education 75, 2, 241–243.

    Google Scholar 

  • Paivio, M. (1986). Mental Representations: A Dual Coding Approach, Oxford University Press, Oxford, England.

    Google Scholar 

  • Patrick, M. H., and Herman, T. (2003). Integrating Physical Models and Computer Visualization to Teach Molecular Literacy, Paper Presented at the American Chemical Society National Meeting, New York City, New York.

  • Patrick, M. H. (2001). Understanding the Bio-Molecular World: Flow of Genetic Information at The Molecular Level, June, www.rpc.msoe.edu/sepa/Introduction.pdf.

  • Peterson, R. R., and Cox, J. R. (2001). Integrating computational chemistry into a project-oriented biochemistry laboratory experience: A new twist on the lysozyme experiment. Journal of Chemical Education 78, 1551.

    Google Scholar 

  • Reeves, J. H., Ward, C. R., and Martin, N. H. (2003). Pocket PCs and Wireless Networks in Science and Mathematics Education, Paper Presented at the American Chemical Society National Meeting, New York City, New York.

  • Schmidt, H. (1988). Paper Presented at the National Association of Research in Science Teaching, Lake of the Ozarks, MO (ERIC Document Reproduction Service.No. ED 291 577).

  • Schmidt, H. (1997). Students’ misconceptions - Looking for a pattern. Science Education 81: 123–135.

    Google Scholar 

  • Shusterman, G. P., and Shusterman, A. J. (1997). Teaching chemistry with electron density models. Journal of Chemical Education 74, 771.

    Google Scholar 

  • Treagust, F., Chittleborough, G., and Mamiala, T. L. (2002). Students’ understanding of the role of scientific models in learning science. International Journal of Science Education. (in preparation) Paper presented at the National Association of Research in Science Teaching, New Orleans, April 7–10.

  • Trunfio, P., Berenfeld, B., Kreikemeier, P., Moran, J., and Moodley, S. (2003). Molecular Modeling and Visualization Tools in Science Education, Symposium Presented at the Annual NARST Meeting, Philadelphia, PA. http://polymer.bu.edu/narst2003.

  • Wavefunction, Inc. Irvine, CA.

  • Wittrock, M. C. (1989). Generative processes of comprehension. Educational Psychologist 24: 345–376.

    Google Scholar 

  • Whitten, K. W., Davis, R. E., and Peck, M. L. (2000). General Chemistry (6th ed.), Saunders College Publishing, Fort Worth, TX.

    Google Scholar 

  • Wolfson, A. J., Hall, M. L., and Branham, T. R. (1996). An integrated biochemistry laboratory, including molecular modeling. Journal of Chemical Education 73, 1026.

    Google Scholar 

  • Wu, H.-K., Krajcik, J. S., Soloway, E. (2001). Promoting understanding of chemical representations: Students’ use of a visualization tool in the classroom. Journal of Research in Science Teaching 38, 821–842.

    Google Scholar 

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Correspondence to Julie B. Ealy.

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Ealy, J.B. Students’ Understanding Is Enhanced Through Molecular Modeling. J Sci Educ Technol 13, 461–471 (2004). https://doi.org/10.1007/s10956-004-1467-x

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