Representational technologies and learner problem-solving strategies in chemistry

Authors

  • Brett McCollum Mount Royal University
  • Ana Sepulveda Mount Royal University
  • Yuritzel Moreno Mount Royal University

DOI:

https://doi.org/10.20343/teachlearninqu.4.2.10

Keywords:

Chemistry, Language Development, Phenomenography, Problem Solving, Technology

Abstract

Learning within the sciences is often considered through a quantitative lens, but acquiring proficiency with the symbolic representations in chemistry is arguably more akin to language learning. Representational competencies are central to successful communication of chemical information including molecular composition, structure, and properties. This article reports on a qualitative study of learner experiences when introduced to new symbolic representations and representational technologies. Participants’ descriptions of these resource interactions were collected through semi-structured interviews and surveys, and were analyzed using phenomenography to identify the variety in student experiences. Results illustrate the impact that representational technologies can have on learner development of problem-solving techniques.

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Author Biographies

Brett McCollum, Mount Royal University

Brett McCollum is an Associate Professor at Mount Royal University in the Department of Chemistry and Physics.

Ana Sepulveda, Mount Royal University

Ana Sepulveda is an undergraduate researcher at Mount Royal University in the Faculty of Science and Technology.

Yuritzel Moreno, Mount Royal University

Yuritzel Moreno was an undergraduate researcher at Mount Royal University in the Faculty of Science and Technology, and is currently completing her degree at the University of British Columbia.

References

Ainsworth, S., Bibby, P., & Wood, D. (2002). Examining the effects of different multiple representational systems in learning primary mathematics. Journal of Learning Sciences, 11, 25-61.

Åkerlind, G. S., Bowden, J., & Green, P. (2005). Learning to do phenomenography: A reflective discussion. In J. A. Bowden & P. Green (Eds.), Doing developmental phenomenography (pp. 74-102). Melbourne, Australia: RMIT University Press.

Andretta, S. (2007). Phenomenography: A conceptual framework for information literacy education. Aslib Proceedings, 59(2), 152-168.

Booth, S. (1997). On phenomenography, learning and teaching. Higher Education Research and Development, 16(2), 135-158.

Booth, S. (2008). Researching learning in networked learning—Phenomenography and variation theory as empirical and theoretical approaches. Proceedings of the 6th International Conference on Networked Learning, 450-455.

Bowden, J. A. (2000). The nature of phenomenographic research. In J. A. Bowden & E. Walsh (Eds.), Phenomenography (1-18). Melbourne, Australia: RMIT University.

Bowden, J. A. (2005). Reflections on the phenomenographic team research process. In J. A. Bowden & P. Green (Eds.), Doing developmental phenomenography (11-31). Melbourne, Australia: RMIT University Press.

Bruce, C. (1997). The seven faces of information literacy. Adelaide: Auslib Press.

Dunkin, R. (2000). Using phenomenography to study organisational change. In J. A. Bowden & E. Walsh (Eds.), Phenomenography (pp. 137-152). Melbourne, Australia: RMIT University.

Edwards, S. (2007). Phenomenography: ‘Follow the yellow brick road!’ In S. Lipu, K. Williamson & A. Lloyd (Eds.), Exploring methods in information literacy research (pp. 87-110). Wagga Wagga, New South Wales: Centre for Information Studies.

Entwistle, N. (1997). Introduction: Phenomenography in higher education. Higher Education Research & Development, 16(2), 127-134.

Gick, M. L., & Holyoak, K. J. (1980). Analogical problem solving. Cognitive Psychology, 12, 306-355.

Gick, M. L., & Holyoak, K. J. (1983). Schema induction and analogical transfer. Cognitive Psychology, 15, 1-38.

Gillespie, R. J. (1963). The valence-shell electron-pair repulsion (VSEPR) theory of directed valency. Journal of Chemical Education, 40, 295-301.

Glaser, B. G., & Strauss, A. L. (1967). The discovery of grounded theory: Strategies for qualitative research. Aldine: Chicago.

Goodwin, W. M. (2008). Structural formulas and explanation in organic chemistry. Foundations of Chemistry, 10, 117-127.

Habraken, C. L. (2004). Integrating into chemistry teaching today’s student’s visuospatial talents and skills, and the teaching of today’s chemistry’s graphical language. Journal of Science Education and Technology, 13, 89-94.

Jonassen, D. H. (1997). Instructional design models for well-structured and ill- structured problem-solving learning outcomes. Educational Technology Research and Development, 45(1), 65-94.

Jonassen, D. H. (2000). Toward a design theory of problem solving. Educational Technology Research and Development, 48(4), 63-85.

Jonassen, D. H. (2014). Assessing problem solving. In J. M. Spector, M. D. Merrill, J. Elen, & M. J. Bishop (Eds.), Handbook of research on educational communications and technology (pp. 269-288). New York: Springer.

Kaberman, Z., Dori, Y. J. (2009). Question posing, inquiry and modeling skills of chemistry students in the casebased computerized laboratory environment. International Journal of Science and Mathematics Education, 7, 597-625.

Kozma, R., & Russell, J. (1997). Multimedia and understanding: Expert and novice responses to different representations of chemical phenomena. Journal of Research in Science Teaching, 34, 949-968.

Laurillard, D. (1993). Rethinking university teaching: A framework for the effective use of educational technology. London: Routledge.

Limberg, L. (2000). Phenomenography: a relational approach to research on information needs, seeking and use. The New Review of Information Behaviour Research, 1, 51-67.

MacMillan, M. (2014). Student connections with academic texts: A phenomenographic study of reading. Teaching in Higher Education. 19(8), 943-954.

Mann, H. B., & Whitney, D. R. (1947). On a test of whether one of two random variables is stochastically larger than the other. Annals of Mathematical Statistics 18(1), 50-60.

Marton, F. (1981). Phenomenography—Describing conceptions of the world around us. Instructional Science, 10, 177-200.

Marton, F. (1986). Phenomenography—A research approach to investigating different understandings of reality. Journal of Thought, 21(3), 28-49.

Marton, F., (1994). Phenomenography. In T. Husen, & T. N. Postlethwaite (Eds.); The international encyclopedia of education (2nd ed., Vol. 8) (pp. 4424-4429). Oxford, UK: Pergamon.

Marton, F., & Booth, S. (1997). Learning and awareness. Mahwah, NJ: L. Erlbaum Associates.

Mayer R. E., (2005), Cognitive theory of multimedia learning. In R. E. Mayer (Ed.), Cambridge handbook of multimedia learning. Cambridge, UK: Cambridge University Press.

McCollum, B. M., Regier, L., Leong, J., Simpson, S., & Sterner, S. (2014). The effects of using touch-screen devices on students’ molecular visualization and representational competence skills. Journal of Chemical Education, 91(11), 1810-1817.

Moore, E. B., Herzog, T. A., & Perkins, K. K. (2013). Interactive simulations as implicit support for guided-inquiry. Chemistry Education Research and Practice, 14, 257-268.

Moran, D. (2000). Introduction to phenomenology. London: Routledge.

Morsch, L., & Lewis, M. (2015). Engaging organic chemistry students using ChemDraw for iPad. Journal of Chemical Education. Articles ASAP, DOI: 10.1021/acs.jchemed.5b00054.

Morse, J. (1994). Designing funded research. In N. Denzin & Y. Lincoln (Eds.), Handbook of qualitativerResearch (pp. 220-235). Thousand Oaks, California: Sage Publications.

Pang, M. F. (2003) Two faces of variation: On continuity in the phenomenographic movement. Scandinavian Journal of Educational Research, 47(2) 145-156.

Peters, M., & Battista, C. (2008). Applications of mental rotation figures of the Shepard and Metzler type and description of a mental rotation stimulus library. Brain and Cognition, 66(3), 260-264.

Säljö, R. (1997). Talk as data and practice—A critical look at phenomenographic inquiry and the appeal to experience. Higher Education Research & Development, 16(2), 173-190.

Sandberg, J. (2000). Understanding human competence at work: An interpretative approach. Academy of Management Journal, 43(1), 9-25.

Sandbergh, J. (1997). Are phenomenographic results reliable? Higher Education Research & Development, 16(2), 203-212.

Schunk, D. H., & Ertmer, P. A. (2000). Self-regulation and academic learning: Self-efficacy enhancing interventions. In M. Boekaerts, P. R. Pintrich & M. Zeidner (Eds.), Handbook of self-regulation (pp. 631-649). San Diego, CA, US: Academic Press.

Shelton, G. R., & Jones, R. (2013). Project iPad: Evaluating impact on student learning across multiple campuses. Abstracts of Papers of the American Chemical Society. 245.

Sinnott, J. D. (1989). A model for solution of ill-structured problems: Implications for everyday and abstract problem solving. In J. D. Sinnott (Ed.), Everyday problem solving: Theory and applications (pp. 72-99). New York: Praeger.

Stieff, M., Hegarty, M., & Deslongchamps, G. (2011). Identifying representational competence with multirepresentational displays. Cognition and Instruction, 29, 123-145.

Stieff, M., Ryu, M., Dixon, B., & Hegarty, M. (2012). The role of spatial ability and strategy preference for spatial problem solving in organic chemistry. Journal of Chemical Education, 89, 854-859.

Sweller J., (2008), Human cognitive architecture, In J. M. Spector, M. D. Merrill, J. van Merrienboer, & M. P. Driscoll (Eds.), Handbook of Research on Educational Communications and Technology (3rd ed.) (pp. 369-381). New York: Routledge.

Torres Gil, A. (2011). Best Practices Using iPad as a Teaching Tool Learning Chemistry.

Trigwell, K. (1994). The first stage of a phenomenographic study of phenomenography. In J. A. Bowden & E. Walsh (Eds.), Phenomenographic research: Variations in method (pp. 56-72). Melbourne, Australia: Office of the Director EQARD, RMIT.

Trigwell, K. (2000). A phenomenographic interview on phenomenography. In J. A. Bowden & E. Walsh (Eds.), Phenomenography (pp. 62-82). Melbourne, Australia: RMIT.

Uttal, D. H., & Cohen, C. A. (2012). Spatial thinking and STEM education: When, why, and how? Psychology of Learning and Motivation, 57, 147-181.

Wai, J., Lubinski, D., & Benbow, C. P. (2009). Spatial ability for STEM domains: Aligning over 50 years of cumulative psychological knowledge solidifies its importance. Journal of Educational Psychology, 101, 817-835.

Yates, C., Partridge, H., & Bruce, C. (2012). Exploring information experiences through phenomenography. Library and Information Research, 36(112), 96-119.

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Published

2016-09-01

How to Cite

McCollum, Brett, Ana Sepulveda, and Yuritzel Moreno. 2016. “Representational Technologies and Learner Problem-Solving Strategies in Chemistry”. Teaching and Learning Inquiry 4 (2):105-21. https://doi.org/10.20343/teachlearninqu.4.2.10.