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Cognition and Spatial Concept Formation: Comparing Non-digital and Digital Instruction Using Three-Dimensional Models in Science

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Abstract

This study compared physical and digital models of a scientific topic in order to determine representational competence, short- and long-term cognition, and the extent to which physical or digital interfaces enhance spatial ability. The DNA molecule was used as a representative spatial topic to investigate conceptual and spatial understanding. Findings suggest a significant effect among four conditions: F(3) = 3.47, p = .02. A Tukey-HSD post hoc analysis identified a significant difference between the paper instruction/paper assessment dyad and the digital instruction/digital assessment dyad (d = .78). The results of an independent-samples t test analyzing the difference between the methods of instruction regardless of method of assessment demonstrated a significant difference in the scores for paper instruction and digital instruction conditions; t(130) = 2.56, p = 0.006. These outcomes demonstrated greater 3-D representational and conceptual understanding of the DNA molecule when paper models were constructed.

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References

  • Avsec, S., & Jamšek, J. (2018). A path model of factors affecting secondary school students’ technological literacy. International Journal of Technology and Design Education, 28(1), 145–168.

    Article  Google Scholar 

  • Baddeley, A. D. (1992). Working memory. Science, 225, 556–559.

    Article  Google Scholar 

  • Baddeley, A. D. (1998). Human memory. Boston: Allyn and Bacon.

    Google Scholar 

  • Barak, M., & Hussein-Farraj, R. (2012). Integrating model-based learning and animations for enhancing students’ understand of proteins structure and function. Research of Science Education, 43, 619–636.

    Article  Google Scholar 

  • Black, J. B., Segal, A., Vitale, J., & Fadjo, C. (2012). Embodied cognition and learning environment design. In D. Jonassen & S. Lamb (Eds.), Theoretical foundations of student-centered learning environments (pp. 198–223). New York: Routledge.

    Google Scholar 

  • Bransford, J. D., Brown, A., & Cocking, R. (2000). How people learn: Mind, brain, experience, and school. Washington, DC: National Research Council.

    Google Scholar 

  • Chan, M. S., & Black, J. B. (2006). Direct-manipulation animation: Incorporating the haptic channel in the learning process to support middle school students in science learning and mental model acquisition. In Proceedings of the international conference of the learning sciences. Mahwah, NJ: LEA.

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

    Google Scholar 

  • Duckworth, E. (1996). The having of wonderful ideas and other essays on teaching and learning. New York: Teachers College Press.

    Google Scholar 

  • Editorial Projects in Education Research Center. (2016). Issues A–Z: Technology in education: An overview. Education Week. May 30, 2017 from http://www.edweek.org/ew/issues/technology-in-education/.

  • Harle, M., & Towns, M. (2010). A review of spatial ability literature, its connection to chemistry, and implications for instruction. Journal of Chemical Education, 88(3), 351–360.

    Article  Google Scholar 

  • Institute of Education Sciences. (2013). Common guidelines for education research and development: A report from the Institute of Education Sciences and the National Science Foundation. Washington, DC: U.S. Department of Education.

    Google Scholar 

  • Kaberman, Z., & Dori, Y. J. (2009). Metacognition in chemical education: Question posing in the case-based computerized learning environment. Instructional Science: An International Journal of the Learning Sciences, 37(5), 403–436.

    Article  Google Scholar 

  • Konicek-Moran, R., & Keeley, P. (2015). Teaching for conceptual understanding in science. Arlington, VA: NSTA Press.

    Google Scholar 

  • Mayer, R. E. (1981). The psychology of how novices learn computer programming. ACM Computing Surveys, 13(1), 121–141.

    Article  Google Scholar 

  • Mayer, R. E., & Moreno, R. E. (2010). Techniques that reduce extraneous cognitive load and manage intrinsic cognitive load during multimedia learning. In J. L. Plass, R. Moreno, & R. Brunken (Eds.), Cognitive load theory (pp. 131–152). New York: Cambridge University Press.

    Chapter  Google Scholar 

  • National Research Council. (2006). Learning to think spatially: GIS as a support system in the K-12 curriculum. Washington, DC: National Academies Press.

    Google Scholar 

  • National Research Council. (2007). Talking science to school: Learning and teaching science in grades K-8. Washington, DC: National Academies Press.

    Google Scholar 

  • National Research Council. (2009). Engineering in K-12 education: Understanding the status and improving the prospects. Washington, DC: National Academies Press.

    Google Scholar 

  • Ness, D., & Farenga, S. J. (2016). Blocks, bricks, and planks: Relationships between affordance and visuo-spatial constructive play objects. American Journal of Play, 8(2), 201–227.

    Google Scholar 

  • Ness, D., Farenga, S. J., & Garofalo, S. G. (2017). Spatial intelligence: Why it matters from birth through the lifespan. New York: Routledge.

    Book  Google Scholar 

  • O’Day, D. H. (2007). The value of animations in biology teaching: A study of long-term memory retention. CBE Life Science Education, 6, 217–223.

    Article  Google Scholar 

  • Paivio, A. (1986). Mental representations: A dual coding approach. New York: Oxford University Press.

    Google Scholar 

  • Piaget, J. (1977). The development of thought: Equilibration of cognitive structures (Trans A. Rosin). New York: Viking.

    Google Scholar 

  • Piaget, J. (2013). Principles of genetic epistemology: Selected works, Vol. 7. New York: Routledge.

  • Piaget, J., & Inhelder, B. (1963). The child’s conception of space: Translated from the French by FJ Lagdon and JL Lunzer. London: Routledge.

    Google Scholar 

  • Rebetez, C., Bétrancourt, M., Sangin, M., & Dillenbourg, P. (2009). Learning from animation enabled by collaboration. Instructional Science, 38, 471–485.

    Article  Google Scholar 

  • Segal, A., Black, J., & Tversky, B. (2010). Do gestural interfaces promote thinking? Congruent gestures promote performance in math. In Paper presented at the 51st annual meeting of Psychonomic Society Conference, St. Louis, MI.

  • Simon, H. (1974). How big is a chunk? Science, 183, 482–488.

    Article  Google Scholar 

  • Sweller, J., & Chandler, P. (1994). Why some material is difficult to learn. Cognition and Instruction, 12(3), 185–233.

    Article  Google Scholar 

  • van Merriënboer, J. J. G., & Ayres, P. (2005). Research on cognitive load theory and its design implications for e-learning, educational technology, research and development. Educational Technology Research and Development, 53(3), 5–13.

    Article  Google Scholar 

  • Vygotsky, L. (1978). Mind in society. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • 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(4), 817.

    Article  Google Scholar 

  • Watson, J. D. (1968). The double helix: A personal account of the discovery of the structure of DNA. New York: Atheneum.

    Google Scholar 

  • Willingham, D. T. (2007). Cognition: The thinking animal. Upper Saddle River, NJ: Pearson Prentice Hall.

    Google Scholar 

Download references

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Authors and Affiliations

  1. City University of New York at Queens College, 65-30 Kissena Blvd, Queens, NY, 11367, USA

    Salvatore G. Garofalo & Stephen J. Farenga

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  1. Salvatore G. Garofalo
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  2. Stephen J. Farenga
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Correspondence to Salvatore G. Garofalo.

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Garofalo, S.G., Farenga, S.J. Cognition and Spatial Concept Formation: Comparing Non-digital and Digital Instruction Using Three-Dimensional Models in Science. Tech Know Learn 26, 231–241 (2021). https://doi.org/10.1007/s10758-019-09425-6

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