Abstract
This study investigated the efficacy of a real-time, interactive visuohaptic simulation to teach students particulate motion and the concepts of thermal energy, pressure, and random motion. Students were able to experience forces through their own somatosensory system in real time. Participants included 78 middle school students who completed a pre-, post-, and delayed post-assessment of knowledge and a post-assessment of attitudes and investigated particle motion using either the visuohaptic or a control visual simulation. The results showed that there were significant gains in the knowledge of thermal energy, pressure, and random motion for both groups of students from pre- to post-assessment. There were no significant differences in post scores between those students that used visuohaptic technology compared to those in the control group who used only a visual simulation. However, students in the visuohaptic group reported that the investigation was highly interesting and enabled them to better understand particle motion as well as visualize movement. The role of haptic instructional technologies as tools to teach micro- and human-scale phenomena is discussed.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Anderson, M. A. (2007). How to study the mind: An introduction to embodied cognition. In: F. Santoianni, & C. Sabatano (Eds.), Brain development in Learning Environments: Embodied and Perceptual Advancements (1st ed., pp. 65–82). Newcastle-upon-Tyne: Cambridge Scholars Publishing.
Batanero, C., Green, D., & Serrano, L. (1998). Randomness, its meanings and educational implications. International Journal of Mathematical Education in Science and Technology, 29(1), 113–123.
Clough, E. E., & Driver, R. (1985). Secondary students’ conceptions of the conduction of heat: Bringing together scientific and personal views. The Physical Educator, 20, 176–182.
de Jong, T., & Njoo, M. (1992). Learning and instruction with computer simulation: Learning processes involved. In E. de Corte, M. C. Linn, H. Mandl, & L. Verschaffel (Eds.), Computer-based learning environments and problem solving (pp. 411–427). Berlin: Springer.
de Koning, B., & Tabbers, H. (2011). Facilitating understanding of movements in dynamic visualizations: An embodied perspective. Educational Psychology Review, 23, 501–521.
Erickson, G. L. (1979). Children’s conceptions of heat and temperature. Science Education, 63, 221–230.
Erickson, G., & Tiberghien, A. (1985). Heat and temperature. In R. Driver, E. Guesne, & A. Tiberghien (Eds.), Children’s ideas in science (pp. 52–83). Philadelphia: Open University Press.
Finkelstein, N. D., Adams, W. K., Keller, C. J., Kohl, P. B., Perkins, K. K., Podolefsky, N. S., Reid, S., & LeMaster, R. (2005). When learning about the real world is better done virtually: A study of substituting computer simulations for laboratory equipment. Physical Review Special Topics – Physics Education Research, 1, 1–8.
Garvin-Doxas, K., & Klymkosky, M. (2008). Understanding randomness and its impact on student learning: Lessons learned from building the biology concept inventory (BCI). CBE-Life Sciences Education, 7, 227–233.
Harris, M. A., Peck, R. F., Colton, S., Morris, J., Neto, E. C., & Kallio, J. (2009). A combination of hand-held models and computer imaging programs helps students answer oral questions about molecular structure and function : A controlled investigation of student learning. Spring, 8, 29–43.
Harrison, A., & Treagust, D. (1996). Secondary students’ mental models of atoms and molecules: Implications for teaching chemistry. Science Education, 80, 509–534.
Harrison, A., Grayson, D., & Treagust, D. (1999). Investigating a Grade 11 student’s evolving concepts of heat and temperature. Journal of Research in Science Teaching, 36, 55–87.
Hsu, Y.-S., & Thomas, R. A. (2002). The impacts of a web-aided instructional simulation on science learning. International Journal of Science Education, 24, 955–979.
Huppert, J., & Lazarowitz, R. (2002). Computer simulations in the high school: Students’ cognitive stages, science process skills and academic achievement in microbiology. International Journal of Science Education, 24, 803–821.
Jones, M. G., Minogue, J., Tretter, T., Negishi, A., & Taylor, R. (2006). Haptic augmentation of science instruction: Does touch matter? Science Education, 90, 111–123.
Kesidou, S., & Duit, R. (1993). Students’ conceptions of the second law of thermodynamics: An interpretive study. Journal of Research in Science Teaching, 30, 85–106.
Klatzky, R. L., Lederman, S. J., & Matula, D. E. (1991). Imagined haptic exploration in judgments of object properties. Journal of Experimental Psychology. Learning, Memory, and Cognition, 17, 314–322.
Lakoff, G. (2012). Explaining embodied cognition results. Topics in Cognitive Science, 4(4), 773–785.
Lakoff, G., & Johnson, M. (1999). Philosophy in the flesh: The embodied mind and its challenge to western thought. New York: Basic Books.
Lederman, S. J., & Klatzky, R. L. (1987). Hand movements: A window into haptic object recognition. Cognitive Psychology, 19, 342–368.
Lee, S. W. S., & Schwarz, N. (2012). Bidirectionality, mediation, and moderation of metaphorical effects: The embodiment of social suspicion and fishy smells. Journal of Personality and Social Psychology, 103(5), 737–749.
Lee, O., Eichinger, D., Anderson, C., Berkheimer, G., & Blakeslee, T. (1993). Changing middle school students’ concepts of matter and molecules. Journal of Research in Science Teaching, 30(3), 249–270.
Loomis, J. M., & Lederman, S. J. (1986). Tactual perception. In K. R. Boff, L. Kaufman, & J. P. Thomas (Eds.), Handbook of perception and human performance (Cognitive processes and performance, Vol. 2, pp. 31.1–31.41). New York: Wiley.
Merleau-Ponty, M. (1962/1945). Phenomenology of perception (C. Smith, Trans.). New York/London: Routledge. Originally published in French as Phénoménologie de la Perception.
Minogue, J., & Jones, M. G. (2009). Measuring the impact of haptic feedback using the SOLO taxonomy. International Journal of Science Education, 31(10), 1359–1378.
Minogue, J., Jones, M. G., Broadwell, B., & Oppewal, T. (2006). The impact of haptic augmentation on middle school students’ conceptions of the animal cell. Journal of Virtual Reality, 10(3–4), 293–305.
Nunnally, J. C. (1988). Psychometric theory. Englewood Cliffs: McGraw-Hill.
Paparistodemou, E., & Noss, R. (2004). Designing for local and global meanings of randomness. In Proceedings of the 28th conference of the International Group for the Psychology of Mathematics Education (Vol. 3, pp. 497–504). Bergen: Bergen University College.
Piaget, J., & Inhelder, B. (1967). The child’s conception of space. New York: W. W. Norton.
Pratt, D. (1998). The co-ordination of meanings for randomness. For the Learning of Mathematics, 18(3), 2–11.
Sathian, K., Zangaladze, A., Hoffman, J., & Grafton, S. (1997). Feeling with the mind’s eye. Neuroreport, 8, 3877–3881.
Schönborn, K. J., Bivall, P., & Tibell, L. (2011). Exploring relationships between students’ interaction and learning with a haptic virtual biomolecular model. Computers & Education, 57(3), 2095–2105.
Shepardson, D., & Moje, E. (1994). The impact of a science demonstration on children’s understandings of air pressure. Journal of Research in Science Teaching, 31(3), 243–258.
Stull, A., Barrett, T., & Hegarty, M. (2011). Usability of concrete and virtual models in chemistry education. Computers and Human Behavior, 29, 2546–2556.
Sun, Y., & Wang, H. (2010). Perception of randomness: On the time of streaks. Cognitive Psychology, 61, 333–342.
Sweller, J. (1994). Cognitive load theory, learning difficulty and instructional design. Learning and Instruction, 4, 295–312.
Tao, P., & Gunstone, R. (1999). The process of conceptual change in force and motion during computer supported physics instruction. Journal of Research in Science Teaching, 36, 859–882.
Tiberghien, A. (1985). Heat and temperature: Part B: The development of ideas with teaching. In R. Driver, E. Guesne, & A. Tiberghien (Eds.), Children’s ideas in science (pp. 67–84). Milton Keynes: Open University Press.
Wiebe, E. N., Minogue, J., Jones, M. G., Cowley, J., & Krebs, D. (2009). Haptic feedback and students’ learning about levers: Unraveling the effect of simulated touch. Computers and Education, 53, 667–676.
Wilson, M. (2002). Six views of embodied cognition. Psychonomic Bulletin & Review, 9(4), 625–636.
Zacharia, Z. C. (2003). Beliefs, attitudes, and intentions of science teachers regarding the educational use of computer simulations and inquiry-based experiments in physics. Journal of Research in Science Teaching, 40, 792–823.
Zacharia, Z. C. (2005). The impact of interactive computer simulations on the nature and quality of postgraduate science teachers’ explanations in physics. International Journal of Science Education, 27, 1741–1767.
Zacharia, Z. C., & Anderson, O. R. (2003). The effects of an interactive computer-based simulations prior to performing a laboratory inquiry-based experiments on students’ conceptual understanding of physics. American Journal of Physics, 71, 618–629.
Acknowledgment
This work was supported in part by NSF grant DRL-1043026.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Jones, M.G., Childers, G., Emig, B., Chevrier, J., Stevens, V., Tan, H. (2016). The Efficacy of Visuohaptic Simulations in Teaching Concepts of Thermal Energy, Pressure, and Random Motion. In: Papadouris, N., Hadjigeorgiou, A., Constantinou, C. (eds) Insights from Research in Science Teaching and Learning. Contributions from Science Education Research, vol 2. Springer, Cham. https://doi.org/10.1007/978-3-319-20074-3_6
Download citation
DOI: https://doi.org/10.1007/978-3-319-20074-3_6
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-20073-6
Online ISBN: 978-3-319-20074-3
eBook Packages: EducationEducation (R0)