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Sensor-Augmented Virtual Labs: Using Physical Interactions with Science Simulations to Promote Understanding of Gas Behavior

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Abstract

Deep learning of science involves integration of existing knowledge and normative science concepts. Past research demonstrates that combining physical and virtual labs sequentially or side by side can take advantage of the unique affordances each provides for helping students learn science concepts. However, providing simultaneously connected physical and virtual experiences has the potential to promote connections among ideas. This paper explores the effect of augmenting a virtual lab with physical controls on high school chemistry students’ understanding of gas laws. We compared students using the augmented virtual lab to students using a similar sensor-based physical lab with teacher-led discussions. Results demonstrate that students in the augmented virtual lab condition made significant gains from pretest and posttest and outperformed traditional students on some but not all concepts. Results provide insight into incorporating mixed-reality technologies into authentic classroom settings.

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References

  • Abrahamson D, Lindgren R (2014) Embodiment and embodied design. In: Sawyer RK (ed) The Cambridge handbook of the learning sciences, 2nd edn. Cambridge University Press, Cambridge

    Google Scholar 

  • Abrahamson D, Gutiérrez J, Charoenying T, Negrete A, Bumbacher E (2012) Fostering hooks and shifts: tutorial tactics for guided mathematical discovery. Technol Knowl Learn 17(1–2):61–86. doi:10.1007/s10758-012-9192-7

    Article  Google Scholar 

  • Akpan JP, Andre T (2000) Using a computer simulation before dissection to help students learn anatomy. J Comput Math Sci Teach 19(3):297–313

    Google Scholar 

  • Alfieri L, Brooks PJ, Aldrich NJ, Tenenbaum HR (2011) Does discovery-based instruction enhance learning? J Educ Psychol 103(1):1–18

    Article  Google Scholar 

  • Antle AN, Wise AF (2013) Getting down to details: using theories of cognition and learning to inform Tangible User Interface design. Interact Comput 25(1):1–20. doi:10.1093/iwc/iws007

    Google Scholar 

  • Benson DL, Wittrock MC, Baur ME (1993) Students’ preconceptions of the nature of gases. J Res Sci Teach 30(6):587–597

    Article  Google Scholar 

  • Ben-Zvi R, Eylon B, Silbemein J (1986) Is an atom of copper malleable? J Chem Educ 63(1):64–66

    Article  Google Scholar 

  • Bivall P, Ainsworth S, Tibell LAE (2011) Do haptic representations help complex molecular learning? Sci Educ 95(4):700–719. doi:10.1002/sce.20439

    Article  Google Scholar 

  • Blikstein P (2014). Bifocal modeling: promoting authentic scientific inquiry through exploring and comparing real and ideal systems linked in real-time. Playful User Interfaces, pp 317–352

  • Bodner GM (1991) I have found you an argument: the conceptual knowledge of beginning chemistry graduate students. J Chem Educ 68(5):385–388

    Article  Google Scholar 

  • Bouwma-Gearhart J, Stewart J, Brown K (2009) Student misapplication of a gas-like model to explain particle movement in heated solids: implications for curriculum and instruction towards students’ creation and revision of accurate explanatory models. Int J Sci Educ 31(9):1157–1174. doi:10.1080/09500690902736325

    Article  Google Scholar 

  • Bransford JD, Brown AL, Cocking RR (2000) How people learn: brain, mind, experience, and school. National Academy Press, Washington

    Google Scholar 

  • Chen S, Chang WH, Lai CH, Tsai CY (2014) A comparison of students’ approaches to inquiry, conceptual learning, and attitudes in simulation-based and microcomputer-based laboratories. Sci Educ 98(5):905–935. doi:10.1002/sce.21126

    Article  Google Scholar 

  • Chien K, Tsai C, Chen H, Chang W, Chen S (2015) Learning differences and eye fixation patterns in virtual and physical science laboratories. Comput Educ 82:191–201. doi:10.1016/j.compedu.2014.11.023

    Article  Google Scholar 

  • Chini JJ, Madsen A, Gire E, Rebello NS, Puntambekar S (2012) Exploration of factors that affect the comparative effectiveness of physical and virtual manipulatives in an undergraduate laboratory. Phys Rev Special Topics Phys Educ Res 8(1):1–12. doi:10.1103/PhysRevSTPER.8.010113

    Article  Google Scholar 

  • Chiu JL (2010). Promoting links and developing students’ criteria for visualizations by prompting judgments of fidelity. In ICLS’10 Proceedings of the 9th international conference of the learning sciences. Chicago, IL, vol 2, pp 230–230

  • Chiu JL, Linn MC (2012) Supporting self-monitoring with dynamic visualizations. In: Dori J, Zohar A (eds) Metacognition and science education. Lawrence Erlbaum, Mahwah, pp 133–164

    Chapter  Google Scholar 

  • Chiu JL, Linn MC (2014) Supporting knowledge integration in chemistry with a visualization-enhanced inquiry unit. J Sci Educ Technol 23(1):37–58. doi:10.1007/s10956-013-9449-5

    Article  Google Scholar 

  • Chiu JL, DeJaegher CJ, Chao J (2015) The effects of augmented virtual science laboratories on middle school students’ understanding of gas properties. Comput Educ 85:59–73. doi:10.1016/j.compedu.2015.02.007

    Article  Google Scholar 

  • Clark DB (2006) Longitudinal conceptual change in students’ understanding of thermal equilibrium: an examination of the process of conceptual restructuring. Cognit Inst 24(4):467–563

    Article  Google Scholar 

  • Clark DB, Jorde D (2004) Helping students revise disruptive experientially supported ideas about thermodynamics: computer visualizations and tactile models. J Res Sci Teach 41(1):1–23. doi:10.1002/tea.10097

    Article  Google Scholar 

  • Cohen J (1968) Weighed kappa: nominal scale agreement with provision for scaled disagreement or partial credit. Psychol Bull 70(4):213–220

    Article  Google Scholar 

  • Colburn A (2000) An inquiry primer. Sci Scope 23(6):42–44

    Google Scholar 

  • De Jong T, Linn MC, Zacharia ZC (2013) Physical and virtual laboratories in science and engineering education. Science (New York, NY) 340(6130):305–308. doi:10.1126/science.1230579

    Article  Google Scholar 

  • Finkelstein N, Adams W, Keller C, Kohl P, Perkins KK, Podolefsky N, LeMaster R (2005) When learning about the real world is better done virtually: a study of substituting computer simulations for laboratory equipment. Phys Rev Spec Topics Phys Educ Res 1(1):1–8. doi:10.1103/PhysRevSTPER.1.010103

    Google Scholar 

  • Gabel DL, Sherwood RD, Enochs L (1984) Problem-solving skills of high school chemistry students. J Res Sci Teach 21(2):221–233. doi:10.1002/tea.3660210212

    Article  Google Scholar 

  • Gabel DL, Samuel KV, Hunn D (1987) Understanding the particulate nature of matter. J Chem Educ 64(8):695. doi:10.1021/ed064p695

    Article  Google Scholar 

  • Hammer D (2000) Student resources for learning introductory physics. Am J Phys 68(S1):S52. doi:10.1119/1.19520

    Article  Google Scholar 

  • Han I, Black JB (2011) Incorporating haptic feedback in simulation for learning physics. Comput Educ 57(4):2281–2290. doi:10.1016/j.compedu.2011.06.012

    Article  Google Scholar 

  • Hmelo-Silver CE, Duncan RG, Chinn CA (2007) Scaffolding and achievement in problem-based and inquiry learning: a response to Kirschner, Sweller, and Clark (2006). Educ Psycholog 42(2):99–107. doi:10.1080/00461520701263368

    Article  Google Scholar 

  • Hofstein A, Lunetta VN (2004) The laboratory in science education: foundations for the twenty-first century. Sci Educ 88(1):28–54. doi:10.1002/sce.10106

    Article  Google Scholar 

  • Honey MA, Hilton M (2011) Learning science through computer games and simulations. National Academies Press, Washington

    Google Scholar 

  • Jaakkola T, Nurmi S, Veermans K (2011) A comparison of students’ conceptual understanding of electric circuits in simulation only and simulation-laboratory contexts. J Res Sci Teach 48(1):71–93. doi:10.1002/tea.20386

    Article  Google Scholar 

  • Johnson-Glenberg MC, Birchfield D, Tolentino L, Koziupa T (2014) Collaborative embodied learning in mixed reality motion-capture environments: two science studies. J Educ Psychol 106(1):86–104. doi:10.1037/a0034008

    Article  Google Scholar 

  • Johnstone AH (1991) Why is science difficult to learn? Things are seldom what they seem. J Comput Assist Learn 7(2):75–83

    Article  Google Scholar 

  • Jones MG, Minogue J, Tretter TR, Negishi A, Taylor RM (2006) Haptic augmentation of science instruction: does touch matter? Sci Educ 90(1):111–123. doi:10.1002/sce.20086

    Article  Google Scholar 

  • Kim Y, Park S, Kim H, Jeong H, Ryu J (2011) Effects of different haptic modalities on students’ understanding of physical phenomena. In: 2011 IEEE World haptics conference (pp. 379–384). IEEE. doi:10.1109/WHC.2011.5945516

  • Koehler MJ, Mishra P (2009) What is technological pedagogical content knowledge (TPACK)? Contemp Issues Technol Teach Educ 9(1):60–70. doi:10.1016/j.compedu.2010.07.009

    Google Scholar 

  • Kozma RB, Russell J (1997) Multimedia and understanding: expert and novice responses to different representations of chemical phenomena. J Res Sci Teach 34(9):949–968. doi:10.1002/(SICI)1098-2736(199711)34:9<949:AID-TEA7>3.0.CO;2-U

    Article  Google Scholar 

  • Lazonder AW, Ehrenhard S (2014) Relative effectiveness of physical and virtual manipulatives for conceptual change in science: How falling objects fall. J Comput Assist Learn 30(2):110–120. doi:10.1111/jcal.12024

    Article  Google Scholar 

  • Lee O, Eichinger DC, Anderson CW, Berkheimer GD, Blakeslee TD (1993) Changing middle school students’ conceptions of matter and molecules. J Res Sci Teach 30(3):249–270

    Article  Google Scholar 

  • Levy ST, Wilensky U (2009) Students’ learning with the connected chemistry (CC1) curriculum: navigating the complexities of the particulate world. J Sci Educ Technol 18(3):243–254. doi:10.1007/s10956-009-9145-7

    Article  Google Scholar 

  • Lin H, Cheng H (2000) The assessment of students and teachers’ understanding of gas laws. J Chem Educ 77(2):235–238

    Article  Google Scholar 

  • Lindgren R, Johnson-Glenberg MC (2013) Emboldened by embodiment: six precepts for research on embodied learning and mixed reality. Educ Res 42(8):445–452. doi:10.3102/0013189X13511661

    Article  Google Scholar 

  • Linn MC, Eylon BS (2006) Science education: integrating views of learning and instruction. In: Alexander PA, Winne PH (eds) Handbook of educational psychology, 2nd edn. Lawrence Erlbaum Associates, Mahwah, pp 511–544

    Google Scholar 

  • Linn MC, Eylon BS (2011) Science learning and instruction: taking advantage of technology to promote knowledge integration. Routledge, New York

    Google Scholar 

  • Linn MC, Davis EA, Eylon B (2004) The scaffolded knowledge integration framework for instruction. In: Linn MC, Davis EA, Bell P (eds) Internet environments for science education. Lawrence Erlbaum Associates Inc, Mahwah, pp 47–72

    Google Scholar 

  • Liu X (2006) Effects of combined hands-on laboratory and computer modeling on student learning of gas laws: a quasi-experimental study. J Sci Educ Technol 15(1):89–100. doi:10.1007/s10956-006-0359-7

    Article  Google Scholar 

  • Liu OL, Lee H-S, Hofstetter C, Linn MC (2008) Assessing knowledge integration in science: Construct, measures, and evidence. Educ Assessm 13(1): 33–55. Retrieved from http://www.tandfonline.com/doi/abs/10.1080/10627190801968224

  • Lowe R (2004) Interrogation of a dynamic visualization during learning. Learn Inst 14(3):257–274. doi:10.1016/j.learninstruc.2004.06.003

    Article  Google Scholar 

  • Lui M, Slotta JD (2013) Immersive simulations for smart classrooms: exploring evolutionary concepts in secondary science. Technol Pedagogy Educ. doi:10.1080/1475939X.2013.838452

    Google Scholar 

  • Lunetta VN, Hofstein A, Clough MP (2007) Learning and teaching in the school science laboratory: an analysis of research, theory, and practice. In: Abell SK, Lederman NH (eds) Handbook of research on science education. Lawrence Erlbaum Associates, Mahwah, pp 393–441

    Google Scholar 

  • Marshall J, Young ES (2006) Preservice teachers’ theory development in physical and simulated environments. J Res Sci Teach 43(9):907–937. doi:10.1002/tea.20124

    Article  Google Scholar 

  • McBride DL, Murphy S, Zollman DA (2010) Student understanding of the correlation between hands-on activities and computer visualizations of NMR/MRI. In AIP conference proceedings, vol 225, pp 225–228. doi:10.1063/1.3515207

  • McElhaney KW, Linn MC (2011) Investigations of a complex, realistic task: intentional, unsystematic, and exhaustive experimenters. J Res Sci Teach 48(7):745–770

    Article  Google Scholar 

  • McElhaney KW, Chang H-Y, Chiu JL, Linn MC (2015) Evidence for effective uses of dynamic visualisations in science curriculum materials. Stud Sci Educ 51(1):49–85

    Article  Google Scholar 

  • Milgram P, Kishino F (1994) A taxonomy of mixed reality visual displays. IEICE Trans Inform Syst E77-D(12):1321–1329

    Google Scholar 

  • Minogue J, Borland D (2012). Investigating students’ ideas about buoyancy and the influence of haptic feedback. In: Paper presented at the annual international conference of the National Association for Research in Science Teaching, Indianapolis, IN, pp 1–12

  • Minogue J, Jones MG (2009) Measuring the impact of haptic feedback using the SOLO taxonomy. Int J Sci Educ 31(10):1359–1378. doi:10.1080/09500690801992862

    Article  Google Scholar 

  • Minogue J, Jones MG, Broadwell B, Oppewall T (2006) The impact of haptic augmentation on middle school students’ conceptions of the animal cell. Virtual Real 10(3–4):293–305. doi:10.1007/s10055-006-0052-4

    Article  Google Scholar 

  • Moher, T. (2006). Embedded phenomena: Supporting science learning with classroom-sized distributed simulations. In Proceedings of the SIGCHI conference on human factors in computing systems—CHI’06 (pp. 691–700)

  • Moher T, Wiley J, Jaeger A, Silva BL, Novellis F (2010) Spatial and temporal embedding for science inquiry: An empirical study of student learning. In ICLS’10 proceedings of the 9th international conference of the learning sciences—volume 1, pp 826–833)

  • Nakhleh MB (1992) Why some students don’t learn chemistry: chemical misconceptions. J Chem Educ 69(3):191–196. doi:10.1021/ed069p191

    Article  Google Scholar 

  • National Research Council (2006) America’s lab report: investigations in high school science. National Academy Press, Washington

    Google Scholar 

  • NGSS Lead States (2013) Next generation science standards: for states, by states. The National Academies Press, Washington

    Google Scholar 

  • Noh T, Scharmann LC (1997) Instructional influence of a molecular-level pictorial presentation of matter on students’ conceptions and problem-solving ability. J Res Sci Teach 34(2):199–217. doi:10.1002/(SICI)1098-2736(199702)34:2<199:AID-TEA6>3.0.CO;2-O

    Article  Google Scholar 

  • Novellis, F., & Moher, T. (2011). How real is “real enough”? Designing artifacts and procedures for embodied simulations of science practices. In Proceedings of the 10th international conference on interaction design and children—IDC’11, pp 90–98

  • Novick S, Nussbaum J (1981) Pupils’ understanding of the particulate nature of matter: a cross-age study. Sci Educ 65(2):187–196

    Article  Google Scholar 

  • Nurrenbem SC, Pickering M (1987) Concept learning versus problem solving: Is there a difference? J Chem Educ 64(6):508–510

    Article  Google Scholar 

  • Okamura AM, Richard C, Cutkosky MR (2002) Feeling is believing: using a force-feedback joystick to teach dynamic systems. J Eng Educ 91(3):345–349

    Article  Google Scholar 

  • Olympiou G, Zacharia ZC (2010) Comparing the use of virtual and physical manipulatives in physics education. In Paper presented at the international conference on education, training and informatics. Orlando, FL

  • Olympiou G, Zacharia ZC (2012) Blending physical and virtual manipulatives: an effort to improve students’ conceptual understanding through science laboratory experimentation. Sci Educ 96(1):21–47. doi:10.1002/sce.20463

    Article  Google Scholar 

  • Özmen H (2013) A cross-national review of the studies on the particulate nature of matter and related concepts. Eurasian J Phys Chem Educ 5(2):81–110

    Google Scholar 

  • Padilla K (2009) Visualization: theory and practice in science education. Int J Sci Educ 31(10):1417–1420. doi:10.1080/09500690802673768

    Article  Google Scholar 

  • Podolefsky NS, Perkins KK, Adams WK (2010) Factors promoting engaged exploration with computer simulations. Phys Rev Spec Topics Phys Educ Res 6(2):020117. doi:10.1103/PhysRevSTPER.6.020117

    Article  Google Scholar 

  • Price S, Falcão TP (2011) Where the attention is: discovery learning in novel tangible environments. Interact Comput 23(5):499–512. doi:10.1016/j.intcom.2011.06.003

    Article  Google Scholar 

  • Price S, Sheridan JG, Falcão TP, Roussos G (2008) Towards a framework for investigating tangible environments for learning. Int J Arts Technol 1(3/4):351. doi:10.1504/IJART.2008.022367

    Article  Google Scholar 

  • Price, S., Falcão, T. P., Sheridan, J. G., & Roussos, G. (2009). The effect of representation location on interaction in a tangible learning environment. Proceedings of the 3rd international conference on Tangible and embedded interaction—TEI’09, p 85. doi:10.1145/1517664.1517689

  • Robins LI, Villagomez G, Dockter D, Christopher E, Ortiz C, Passmore C, Smith MH (2009) Teacher research: challenging our assumptions–An investigation into student understanding of the gas laws. Sci Teach (September), 35–40

  • Sanger MJ, Phelps AJ (2007) What are students thinking when they pick their answer? A content analysis of students’ explanations of gas properties. J Chem Educ 84(5):870–874

    Article  Google Scholar 

  • Sanger MJ, Phelps AJ, Fienhold J (2000) Using a computer animation to improve students’ conceptual understanding of a can-crushing demonstration. J Chem Educ 77(11):1517–1520

    Article  Google Scholar 

  • Sarabando C, Cravino JP, Soares A (2014) Contribution of a computer simulation to students’ learning of the physics concepts of weight and mass. Proc Technol 13:112–121. doi:10.1016/j.protcy.2014.02.015

    Article  Google Scholar 

  • Schneider B, Wallace J, Blikstein P, Pea R (2013) Preparing for future learning with a Tangible User interface: the case of neuroscience. IEEE Trans Learn Technol 6(2):117–129. doi:10.1109/TLT.2013.15

    Article  Google Scholar 

  • Shelley T, Lyons L, Zellner M, Minor E (2011). Evaluating the embodiment benefits of a paper-based tui for educational simulations. In Proceedings of the 2011 annual conference extended abstracts on Human factors in computing systems—CHI EA’11. ACM Press, New York, pp 1375–1380. doi:10.1145/1979742.1979777

  • Smith, G. W., & Puntambekar, S. (2010). Examining the combination of physical and virtual experiments in an inquiry science classroom. In Proceedings of the conference on computer based learning in science. Warsaw, Poland

  • Snir J, Smith CL, Raz G (2003) Linking phenomena with competing underlying models: a software tool for introducing students to the particulate model of matter. Sci Educ 87(6):794–830. doi:10.1002/sce.10069

    Article  Google Scholar 

  • Tanhua-piiroinen, E., Pystynen, J., & Raisamo, R. (2010). Haptic applications as physics teaching tools. In IEEE international symposium on haptic audio-visual environments and games, Phoenix, AZ, pp 1–6

  • Tien LT, Teichert MA, Rickey D (2007) Effectiveness of a MORE laboratory module in prompting students to revise their molecular-level ideas about solutions. J Chem Educ 84(1):175. doi:10.1021/ed084p175

    Article  Google Scholar 

  • Tolentino L, Birchfield D, Megowan-Romanowicz C, Johnson-Glenberg MC, Kelliher A, Martinez C (2009) Teaching and learning in the mixed-reality science classroom. J Sci Educ Technol 18(6):501–517. doi:10.1007/s10956-009-9166-2

    Article  Google Scholar 

  • Trundle KC, Bell RL (2010) The use of a computer simulation to promote conceptual change: a quasi-experimental study. Comput Educ 54(4):1078–1088. doi:10.1016/j.compedu.2009.10.012

    Article  Google Scholar 

  • White RT, Gunstone RF (1992) Probing understanding. Falmer, London

    Google Scholar 

  • Wiebe EN, Minogue J, Jones MG, Cowley J, Krebs D (2009) Haptic feedback and students’ learning about levers: unraveling the effect of simulated touch. Comput Educ 53(3):667–676. doi:10.1016/j.compedu.2009.04.004

    Article  Google Scholar 

  • Williams RL, Chen M, Seaton JM (2003) Haptics-augmented simple-machine educational tools. J Sci Educ Technol 12(1):1–12

    Article  Google Scholar 

  • Xie, C. (2012). Framing mixed-reality labs. Retrieved from http://concord.org/publications/newsletter/2012-spring/framing-mixed-reality-labs

  • Zacharia ZC (2007) Comparing and combining real and virtual experimentation: an effort to enhance students’ conceptual understanding of electric circuits. J Comput Assist Learn 23(2):120–132

    Article  Google Scholar 

  • Zacharia ZC, de Jong T (2014) The effects on students’ conceptual understanding of electric circuits of introducing virtual manipulatives within a physical manipulatives-oriented curriculum. Cognit Inst 32(2):101–158

    Article  Google Scholar 

  • Zacharia ZC, Olympiou G, Papaevripidou M (2008) Effects of experimenting with physical and virtual manipulatives on students’ conceptual understanding in heat and temperature. J Res Sci Teach 45(9):1021–1035. doi:10.1002/tea.20260

    Article  Google Scholar 

  • Zhang ZH, Linn MC (2011) Can generating representations enhance learning with dynamic visualizations? J Res Sci Teach 48(10):1177–1198. doi:10.1002/tea.20443

    Article  Google Scholar 

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Acknowledgments

This research was supported by the National Science Foundation under grant IIS-1123868. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. The authors would like to thank the teachers and students who participated in this project. Special thanks to Charles Xie and Edmund Hazzard at the Concord Consortium for design and development of the Frame technology and curriculum used in this study.

Conflict of interest

The authors declare that they have no conflict of interest.

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Authors and Affiliations

  1. The Concord Consortium, 25 Love Ln, Concord, MA, 01742, USA

    Jie Chao

  2. University of Virginia, Charlottesville, VA, USA

    Jennifer L. Chiu

  3. University of Notre Dame, Notre Dame, IN, USA

    Crystal J. DeJaegher

  4. Immersion Consulting, Annapolis, MD, 21401, USA

    Edward A. Pan

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  1. Jie Chao
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Chao, J., Chiu, J.L., DeJaegher, C.J. et al. Sensor-Augmented Virtual Labs: Using Physical Interactions with Science Simulations to Promote Understanding of Gas Behavior. J Sci Educ Technol 25, 16–33 (2016). https://doi.org/10.1007/s10956-015-9574-4

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