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High-School Chemistry Students' Performance and Gender Differences in a Computerized Molecular Modeling Learning Environment

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Abstract

Computerized molecular modeling (CMM) contributes to the development of visualization skills via vivid animation of three dimensional representations. Its power to illustrate and explore phenomena in chemistry teaching stems from the convenience and simplicity of building molecules of any size and color in a number of presentation styles. A new CMM-based learning environment for teaching and learning chemistry in Israeli high schools has been designed and implemented. Three tenth grade experimental classes used this discovery CMM approach, while two other classes, who studied the same topic in the customary approach, served as a control group. We investigated the effects of using molecular modeling on students' spatial ability, understanding of new concepts related to geometric and symbolic representations and students' perception of the model concept. Each variable was examined for gender differences. Students of the experimental group performed better than control group students in all three performance aspects. Experimental group students scored higher than the control group students in the achievement test on structure and bonding. Students' spatial ability improved in both groups, but students from the experimental group scored higher. For the average students in the two groups the improvement in all three spatial ability sub-tests —paper folding, card rotation, and cube comparison—was significantly higher for the experimental group. Experimental group students gained better insight into the model concept than the control group and could explain more phenomena with the aid of a variety of models. Hence, CMM helps in particular to improve the examined cognitive aspects of the average student population. In most of the achievement and spatial ability tests no significant differences between the genders were found, but in some aspects of model perception and verbal argumentation differences still exist. Experimental group females improved their model perception more than the control group females in understanding ways to create models and in the role of models as mental structures and prediction tools. Teachers' and students' feedback on the CMM learning environment was found to be positive, as it helped them understand concepts in molecular geometry and bonding. The results of this study suggest that teaching/learning of topics in chemistry that are related to three dimensional structures can be improved by using a discovery approach in a computerized learning environment.

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REFERENCES

  • Aduldeka, S., Akhter, P., Field, P., Nagle, P., O'sullivan, E., O'Conno, K., and Hathaway, B. J. (1991). The use of desktop molecular modeler software in the teaching of structural chemistry. Journal of Chemical Education, 68: 576–583.

    Google Scholar 

  • Arambula Greenfield, T. (1997). Gender-and grade-level differences in science interest and participation, Science Education 81: 259–275.

    Google Scholar 

  • Baenninger, M., and Newcomb, N. (1989). The role of experience in spatial test performance: A meta analysis. Sex Roles 20: 327–344.

    Google Scholar 

  • Baker, R. S., and Talley, H. L. (1974). Visualization skills as a component of aptitude for chemistry—a construct validation study. Journal of Research in Science Teaching 11(12): 95–97.

    Google Scholar 

  • Barnea, N. (1996). Integrating molecular modeling in teaching chemical bonding and structure and its effect on conceptual change, spatial ability, and model perception. Ph.D. Dissertation, Technion, Haifa, Israel (in Hebrew).

    Google Scholar 

  • Barnea, N., and Dori, Y. J. (1996). Computerized molecular modeling as a tool to improve chemistry teaching. Journal of Chemical Information and Computer Sciences, 36: 629–636.

    Google Scholar 

  • Barnea, N., and Dori, Y. J. (1999). Model Perception among chemistry teachers and students. Paper presented at the 8th European Conference for Research on Learning and Instruction, August, Gotenborg, Sweden.

  • Barnea, N., Dori, Y. J., and Finegold, M. (1995). Model perception among pre-and in-service chemistry teachers, ERIC Document Reproduction Services, ED387 329; SE 056 647, National Institute of Education, Washington, D.C.

    Google Scholar 

  • Ben-Zvi, N., and Gai, R. (1994). Macro-and micro-chemical comprehension of real world phenomena. Journal of Chemical Education 71: 730–732.

    Google Scholar 

  • Bezzi, A. (1991). A Macintosh program for improving three dimensional thinking. Journal of Geological Education, 39: 284–288.

    Google Scholar 

  • Bishop, E. J. (1978). Developing students' spatial ability. The Science Teacher 45(8):20–23.

    Google Scholar 

  • Bloom, B. (1956). Taxonomy of Educational Objectives: Handbook-I. Cognitive Domain, David McKay, New York.

    Google Scholar 

  • Campanario, J. M., Bronchalo, E., and Hidalgo, M. A. (1994). An effective approach for teaching intermolecular interactions. Journal of Chemical Education, 71: 761–766.

    Google Scholar 

  • Chapman, O. L. (1994). Teaching creative molecular design. In Seibert, E. D., Estee, C. R. (Eds.), Science. Discoveries on Science Teaching: TheLink, Society of College Science Teachers (NSTA), Cedar City, Utah, pp. 6–13.

    Google Scholar 

  • Choi, B., and Genaro, E. (1987). The effectiveness of using computer simulated experiments on junior high students' understanding of the volume displacement concept. Journal of Research on Computing in Education 24: 539–552.

    Google Scholar 

  • Connor, J. M., and Serbin, L. A. (1980). Mathematics, visualspatial ability, and sex roles (final report). ERIC Document Reproduction Services, ED 205305, National Institute of Education, Washington, D.C.

    Google Scholar 

  • Crabbe, J. C., and Appleyard, J. R. (1994). Desktop Molecular Modeler (version 3.0). Oxford University Press, Oxford.

    Google Scholar 

  • De Posada, J. M. (1997). Conceptions of high school students concerning the internal structure of metals and their electric conduction: structure and evolution. Science Education 81(4): 445–467.

    Google Scholar 

  • Dori, Y. J. (1995). Cooperative studyware development of organic chemistry module by experts, teachers and students. Journal of Science Education and Technology 4: 163–170.

    Google Scholar 

  • Dori, Y. J., and Barnea, N. (1993). A computer aided instruction module on polymers, Journal of Chemical Information and Computer Sciences 33: 325–331.

    Google Scholar 

  • Dori, Y. J., and Barnea, N. (1997). In-service chemistry teachers training: the impact of introducing computer technology on teachers attitudes and classroom implementation. International Journal of Science Education 19(5): 577–592.

    Google Scholar 

  • Dori, Y. J., and Hameiri, M. (1998). The “mole environment” studyware: applying multidimensional analysis to quantitative chemistry problems. International Journal of Science Education 20(3): 317–333.

    Google Scholar 

  • Dori, Y. J., Gabel, D., Bunce, D., Barnea, N., and Hameiri, M. (1996). Using novel technologies to enhance chemistry understanding at the phenomena, molecular and symbolic levels. Proceeding of the Second Jerusalem International Science and Technology Education Conference, Jerusalem, Israel, S2–40a.

  • Ekstrom, R. B. (1973). Cognitive Factors: Some Recent Literature, Educational Testing Service, PR-73-30, Princeton, New Jersey.

    Google Scholar 

  • Ekstrom, R. B., French, J. W., and Harmon, H. H. (1976). Manual For Kit of Factor-Referenced Cognitive Tests, Educational Testing Service, Princeton, New Jersey.

    Google Scholar 

  • Eliot, J. K., and Fralley, S. J. (1976). Sex differences in spatial ability. Young Children 31(6): 487–498.

    Google Scholar 

  • Eliot, J. K., and Hauptman, A. (1981). Different dimensions of spatial ability. Studies in Science Education 8: 45–66.

    Google Scholar 

  • Gabel, D. L. (1998). The complexity of chemistry and implications for teaching. In Fraser, B. J., and Tobin, K. G. (Eds.), International Handbook of Science Education, Kluwer Academic Publishers, London, pp. 233–248.

    Google Scholar 

  • Gabel, D. L., Briner, D., and Haines, D. (1992). Modeling with magnets–A unified approach to chemistry problem solving. The Science Teacher March, 58–63.

  • Gabel, D. L., and Bunce, D. M. (1994). Research on problem solving: chemistry. In Gabel, D. L. (Ed.), Handbook of Research on Science Teaching and Learning, Macmillan, New York, pp. 301–326.

    Google Scholar 

  • Gabel, D. L., Samuel, K., and Hunn, D. (1987). Understanding the Particulate Nature of Matter. Journal of Chemical Education 64(8): 695–697.

    Google Scholar 

  • Gabel, D. L., and Sherwood, R. (1980). The effect of student manipulation of molecular models on chemistry achievement according to Piagetian level. Journal of Research in Science Teaching 17(1): 75–81

    Google Scholar 

  • Garnet, P. J., Garnet, P. J., and Hackling, M. W. (1995). Students' alternative conceptions in chemistry: A review of research and implications for teaching and learning. Studies in Science Education, 25: 69–95.

    Google Scholar 

  • Garnet, P. J., Tobin, K., and Swingler, D. J. (1985). Reasoning abilities of western Australian secondary school students. European Journal of Science Education 7: 387–397.

    Google Scholar 

  • Gilbert, S. W. (1991). Model building and a definition of science. Journal of Research in Science Teaching 28: 73–79.

    Google Scholar 

  • Gulinska, H., Lewicki, R., and Burewicz, A. (1991). Interactive computer video programs used in the process of chemistry teaching. Journal of Chemical Education 68(6): 490–492.

    Google Scholar 

  • Gunstone, R. F. (1989). The importance of specific science content in the enhancement of metacognition. In Fensham, P. J., Gunstone, R. S., and White, R. T. (Eds.), The Content of Science, Palmer Press, London.

    Google Scholar 

  • Herron, J. D. (1978). Piajet in the classroom. Journal of Chemical Education 55: 165–170.

    Google Scholar 

  • Ingham, A. M., and Gilbert, J. K. (1991). The use of Analogue models by students of chemistry at higher education level. International Journal of Science Education 13(2): 193–202.

    Google Scholar 

  • Jegede, O. J., and Okebukola, P. A. (1992). Differences in sociocultural environment perceptions associated with gender in science classroom. Journal of Research in Science Teaching 29: 637–647.

    Google Scholar 

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

    Google Scholar 

  • Kahle, J. B. (1996). Gender issues in science education. University of Dortmund Summer Symposium, Dortmund, Germany.

    Google Scholar 

  • Kahle, J. B., and Lakes, M. K. (1983). The myth of equality in science classrooms. Journal of Research in Science Teaching 20: 131–140.

    Google Scholar 

  • Kahle, J. B., and Meece, J. L. (1994). Girls and science education. A developmental model. In Gabel, D. (Ed.), Handbook of Research in Science Teaching and Learning (1559–1610). National Science Teachers Association, Washington, D.C.

    Google Scholar 

  • Kahle, J. B., Parker, L. H., Rennie, L. J., and Riley, D. (1993). Gender differences in science education. Building a model. Educational Psychologist 28(4): 379–404.

    Google Scholar 

  • Kiser, L. (1990). Interaction of spatial visualization with computer enhanced and traditional presentations of linear absolute value inequalities. Journal of Computers in Mathematics and Science Teaching 10, 85–96.

    Google Scholar 

  • Koslow, R. E. (1987). Sex-related differences and visual spatial mental imagery as factors affecting symbolic motor skill acquisition. Sex Roles 1: 521–527.

    Google Scholar 

  • Kosslyn, S. M. (1987). Seeing and imagining in the cerebral hemisphere: a computational approach. Psychological Review 94: 148–175.

    Google Scholar 

  • Krajcik, J. S. (1991). Developing students' understanding of chemical concepts. In Glynn, S. M., Yeany, R. H., and Britton, B. K. (Eds.), The Psychology of Learning Science, Lawrence Erlbaum, Hillsdale, New Jersey, pp. 117–147.

    Google Scholar 

  • Lazarowitz, R., and Naim, R. (1986). Teachers' workshop: The use of three dimensional models in teaching “The Cell” to ninth grade biology students. National Science Teachers Association (NSTA). National Convention, San Francisco, March.

  • Lazarowitz, R., Hertz-Lazarowitz, R., and Baird, J. H. (1994). Learning science in a cooperative setting: academic achievement and affective outcomes. Journal of Research in Science Teaching 31: 1121–1131.

    Google Scholar 

  • Linn, M., and Hyde, J. S. (1989). Gender, mathematics and science. Educational Researcher 18(8): 17–27.

    Google Scholar 

  • Linn, M. (1998). The Impact of Technology on Science Instruction: Historical Trends and Current Opportunities. In Fraser, B. J., and Tobin, K. G. (Eds.), International Handbook of Science Education, Kluwer Academic Publishers, 265–294.

    Google Scholar 

  • Lohman, D. F. (1986). The effect of speed accuracy trade-off on sex differences in mental rotation. Perception and Psychophysics 39: 427–436.

    Google Scholar 

  • Lord, T. R. (1985). Enhancing the visuo-spatial aptitude of students. Journal of Research in Science Teaching 22(5): 395–405.

    Google Scholar 

  • Lord, T. R. (1987). A look at spatial abilities in undergraduate women science majors. Journal of Research in Science Teaching 24(8): 757–767.

    Google Scholar 

  • MacCoby, E. E., and Jacklin, C. N. (1974). The Psychology of Sex Differences. Stanford University Press, Stanford.

    Google Scholar 

  • Mayers, J. F., Jahoda, G., and Nelson, I. (1988). Patterns of visualspatial performances and spatial ability: dissociation of ethnic and sex differences. British Journal of Psychology 79: 105–119.

    Google Scholar 

  • McFie, J. (1973). Intellectual imbalance: a perceptual hypothesis. British Journal of Social Clinical Psychology 12: 433–434.

    Google Scholar 

  • McGee, G. M. (1979). Human spatial abilities: Psychometric studies and environmental, genetic, hormonal, and neurological influences. Psychological Bulletin 86(5): 889–913.

    Google Scholar 

  • Moore, J. W. (1995). Journal of Chemical Education: Software. Journal of Chemical Education 72(1): 25–26.

    Google Scholar 

  • Millar, R. (1989). Constructive criticisms. International Journal of Science Education 11: 578–596.

    Google Scholar 

  • Mintz, R. (1987). Teaching the Ecological System Through Computerized Simulation. Doctoral Dissertation, Tel Aviv University, Tel Aviv, Israel (In Hebrew).

    Google Scholar 

  • Newcomb, N. (1982). Sex related differences in spatial ability: problems and gaps in current approaches. In Potegal, M. (Ed.), Spatial Abilities. Development and Physiological Foundations. Academic Press.

  • Parland, G. J., and Seeber, F. (1984). Spatial ability and achievement in introductory physics. Journal of Research in Science Teaching 21(5): 507–516.

    Google Scholar 

  • Richmond, G. P. (1980). A limited sex difference in spatial tests scores with a preadolescent sample. Child Development 51(2): 601–602.

    Google Scholar 

  • Rodriguez, W. E. (1990). A dual approach to engineering design visualization. Engineering Design Graphics Journal 54(3): 36–43.

    Google Scholar 

  • Schmidt, H. J. (1997). Students' misconceptions—looking for a pattern. Science Education 81(2): 123–135.

    Google Scholar 

  • Seddon, G. M., and Moore, R. G. (1986). An unexpected effect in the use of models for teaching the visualization of rotation in molecular structures. European Journal of Science Education 8: 79–86.

    Google Scholar 

  • Seddon, G. M., and Shubber, K. E. (1985). The effects of color in teaching the visualization of rotations in diagrams of three dimensional structures. British Educational Research Journal 11: 227–239.

    Google Scholar 

  • Shoaff-Grubbs, M. M. (1992). The effect of the graphing calculator on female students' spatial visualization skills and levels of understanding in elementary graphing and algebra concepts. Paper based on doctoral dissertation, College of New Rochelle, New Rochelle, New York.

    Google Scholar 

  • Smith, I. M. (1964). Spatial ability: its educational and social significance. University of London Press, London.

    Google Scholar 

  • Stavy, R. (1995). Conceptual development of basic ideas in chemistry. In Glynn, S., and Duit, R. (Eds.), Learning Science in the Schools: Research Reforming Practice, Lawrence Erlbaum, Mahwah, New Jersey, pp. 131–154.

    Google Scholar 

  • Steffen, L. K., Gill, M., Gundersen, K., and Nelson, J. E. (1996) Creating simple, low-cost animations for organic chemistry instruction. The Chemical Educator 1(5). http://journals.springer.ny.com/chedr

  • Talley, H. L. (1973). The use of three dimensional visualization as a moderator in the higher cognitive learning of concepts in college level chemistry. Journal of Research in Science Teaching 10(3): 263–269.

    Google Scholar 

  • Teles, E. J. (1990). Numerical and graphical presentation of functions in pre-calculus. Doctoral dissertation, University of Maryland College Park, 1989. Dissertation Abstracts International 51: 777A.

    Google Scholar 

  • Tobin, K. G., and Garnet, P. (1987). Gender related differences in science activities. Science Education 71: 91–103.

    Google Scholar 

  • Tobin, K. L. (1998). Issues and trends in the teaching of science. In Fraser, B. J., and Tobin, K. G. (Eds.), International Handbook of Science Education, Kluwer Academic Publishers, London, pp. 129–151.

    Google Scholar 

  • Tobin, K., Kahle, J. B., and Fraser, B. J. (1990). Windows into science classrooms: Problems Associated with Higher-Level Cognitive Learning, Palmer Press, New York.

    Google Scholar 

  • Tracy, D. M. (1987). Toys, spatial ability and science and mathematics achievement: are they related? Sex Roles 17: 115–138.

    Google Scholar 

  • Tuckey, H. P., Selvaratnam,M., and Bradley, J. D. (1991). Identification and rectification of student difficulties concerning three dimensional structures, rotation and reflection. Journal of Chemical Education 68: 460–464.

    Google Scholar 

  • Tuckey, H. P., and Selvaratnam,M. (1993). Studies involving three-dimensional visualization skills in chemistry: a review. Studies in Science Education 21: 99–121.

    Google Scholar 

  • Vazquez, J. L. (1991). The effect of the calculator on student achievement in graphing linear functions. Doctoral dissertation, University of Florida, 1990. Dissertation Abstracts International 50: 350BA.

    Google Scholar 

  • Waber, S. C. (1976). Sex differences in cognition: A function of maturation rate. Science 192: 572–574.

    Google Scholar 

  • Wiley, S. E. (1990). Computer graphics and the development of visual perceptions in engineering graphics curricula. Engineering Design Graphics Journal 54(3): 39–43.

    Google Scholar 

  • Williamson, V. M., and Abraham, M. R. (1995). The effects of computer animation on particulate mental models of college chemistry students. Journal of Research in Science Teaching 32(5): 521–534.

    Google Scholar 

  • Witkin, H. A. (1969). Social influences in the development of cognitive style. In Gaskin, D. (Ed.), Handbook of Socialization Theory and Research, Rand McNally, New York.

    Google Scholar 

  • Yalcinalp, S., Geban, O., and Ozkam, I. (1995). Effectiveness of using computer-assisted supplementary instruction for teaching the mole concept. Journal of Research in Science Teaching 32(10): 1083–1095.

    Google Scholar 

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Barnea, N., Dori, Y.J. High-School Chemistry Students' Performance and Gender Differences in a Computerized Molecular Modeling Learning Environment. Journal of Science Education and Technology 8, 257–271 (1999). https://doi.org/10.1023/A:1009436509753

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