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Correcting Students’ Misconceptions about Automobile Braking Distances and Video Analysis Using Interactive Program Tracker

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Abstract

The present paper informs about an analysis of students’ conceptions about car braking distances and also presents one of the novel methods of learning: an interactive computer program Tracker that we used to analyse the process of braking of a car. The analysis of the students’ conceptions about car braking distances consisted in obtaining their estimates of these quantities before and after watching a video recording of a car braking from various initial speeds to a complete stop and subsequent application of mathematical statistics to the obtained sets of students’ answers. The results revealed that the difference between the value of the car braking distance estimated before watching the video and the real value of this distance was not caused by a random error but by a systematic error which was due to the incorrect students’ conceptions about the car braking process. Watching the video significantly improved the students’ estimates of the car braking distance, and we show that in this case, the difference between the estimated value and the real value of the car braking distance was due only to a random error, i.e. the students’ conceptions about the car braking process were corrected. Some of the students subsequently performed video analysis of the braking processes of cars of various brands and under various conditions by means of Tracker that gave them exact knowledge of the physical quantities, which characterize a motor vehicle braking. Interviewing some of these students brought very positive reactions to this novel method of learning.

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References

  • Beichner RJ (1996) The impact of video motion analysis on kinematic graph interpretation skills. Am J Phys 64(10):1272–1277

    Article  Google Scholar 

  • Bradáč A et al (1997) Judicial engineering, Academic Publisher CERM, s. r. o., Brno, ISBN 80-7204-057-X

  • Bussei P, Merlino S (2003) European workshop on multimedia in physics teaching and learning. Europhys News 34(3):116–117

    Google Scholar 

  • Ciubotariu D, Neculaiasa V (2011) Contributions regarding the study of the braking system of cars. J Eng Stud Res 17(2):37–44

    Google Scholar 

  • Dudáček J, Ondruš J (2010) Results of measurements of the braking characteristics of the passenger automobile Citroën C6. Exper Road Traffic Electr Eng Mech Eng Other Tech Fields 11(1):27–30. ISSN 1335-1133. ISSN 0031-921X

  • Ebersbach M, Van Dooren W, Verschaffel L (2010) Knowledge on accelerated motion as measured by implicit and explicit tasks in 5 to 16 year olds. Int J Sci Math Educ 9(1):25–46

    Article  Google Scholar 

  • Echeverría A, Barrios E, Nussbaum M, Améstica M, Leclerc S (2012) The atomic intrinsic integration approach: a structured methodology for the design of games for the conceptual understanding of physics. Comput Educ 59(2):806–816

    Article  Google Scholar 

  • Felder RM, Brent R (2003) Learning by doing. Chem Eng Educ 37(4):282–283

    Google Scholar 

  • Finkelstein ND, Adams WK, Keller CJ, Kohl PB, Perkins KK, Podolefsky NS, Reid S, 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 Top Phys Educ Res 1(1):1–7

    Google Scholar 

  • Gavin K (2011) Case study of a project-based learning course in civil engineering design. Eur J Eng Edu 36(6):547–558

  • Hake RR (1998) Interactive-engagement versus traditional methods: a six-thousand-student survey of mechanics test data for introductory physics courses. Am J Phys 66(1):64–74

    Article  Google Scholar 

  • Halloun I, Hestenes D (1985) The initial knowledge state of college physics students. Am J Phys 53(11):1043–1055

  • Haugland OA (2013) Car stopping distance on a tabletop. Phys Teach 51(5):268

    Article  Google Scholar 

  • Hestenes D, Wells M, Swackhamer G (1992) Force concept inventory. Phys Teach 30(3):141–158

    Article  Google Scholar 

  • Hockicko P (2010) Nontraditional approach to studying science and technology. Communications 12(3):66–71

    Google Scholar 

  • Hockicko P (2012) Attractiveness of learning physics by means of video analysis and modeling tools. In: Proceedings of the 40th SEFI annual conference engineering education 2020: meet the future, 2012, Thessaloniki, Greece

  • Hockicko P (2013) Video-analysis based tasks in physics. University of Žilina, EDIS, Žilina. http://hockicko.uniza.sk/Priklady/video_tasks.htm

  • Hockicko P, Krišťák Ľ, Němec M (2014) Development of students’ conceptual thinking by means of video analysis and interactive simulations at technical universities. Eur J Eng Educ (in press). doi:10.1080/03043797.2014.941337

  • Hodge H, Hinton HS, Lightner M (2001) Virtual circuit laboratory. J Eng Educ 90(4):507–511

    Article  Google Scholar 

  • Karlubík A (2010) Video-measurements in physics teaching (thesis). Bratislava, p. 61

  • Kim Y.-M, Kim Y.-G, Kim S.-W, Park C.-K, and Park T.-W (2010) Estimation of the adhesion force for a disk brake in a skid control condition. Int J Automot Technol 11(5):673–680

    Article  Google Scholar 

  • Kozhevnikov M, Thornton R (2006) Real-time data display, spatial visualization ability, and learning force and motion concepts. J Sci Educ Technol 15(1):111–132

    Article  Google Scholar 

  • Kozhevnikov M, Motes MA, Hegarty M (2007) Spatial visualization in physics problem solving. Cogn Sci 31(4):549–579

    Article  Google Scholar 

  • Krišťák Ľ, Němec M, Danihelová Z (2014) Interactive method of teaching physics at technical universities. Inf Educ 13(1):51–71

    Google Scholar 

  • Krupová I (2009) The development of natural science literacy in pupils in the first stage of basic school using the method of managed discovery. Pedagogika LIX-2009(3):259–268. ISSN 0031-3815

  • Liang LL, Fulmer GW, Majerich DM, Clevenstine R, Howanski R (2012) The effects of a model-based physics curriculum program with a physics first approach: a causal-comparative study. J Sci Educ Technol 21(1):114–124

    Article  Google Scholar 

  • Lyubenov D (2011) Stopping distance. Deceleration. VBOX 3i. GPS Data Logger. In: Proceedings of the III international scientific conference transport problems 2011, Katowice, Poland, 2011, p 199–205

  • Markechová D, Stehlíková B, Tirpáková A (2011) Statistical methods and their applications. Constantine the Philosopher University in Nitra, p 534 (in Slovak)

  • Martín-Blas T, Serrano-Fernández A (2009) The role of new technologies in the learning process: moodle as a teaching tool in physics. Comput Educ 52(1):35–44

    Article  Google Scholar 

  • Martín-Blas T, Seidel L, Serrano-Fernández A (2010) Enhancing force concept inventory diagnostics to identify dominant misconceptions in first-year engineering physics. Eur J Eng Educ 35(6):597–606

    Article  Google Scholar 

  • Mazur E (1997) Peer instruction. A user's manual. Prentice Hall, New York

    Google Scholar 

  • Nagurnas S, Mitunevičius V, Unarski J, Wach W (2007) Evaluation of veracity of car braking parameters used for the analysis of road accidents. Transport 22(4):307–311

    Google Scholar 

  • Nair CS, Patil A, Mertova P (2011) Enhancing the quality of engineering education by utilising student feedback. Eur J Eng Educ 36(1):3–12

    Article  Google Scholar 

  • Oliveira PC, Oliveira CG (2013) Using conceptual questions to promote motivation and learning in physics lectures. Eur J Eng Educ 38(4):417–424

    Article  Google Scholar 

  • Olson PL, Cleveland DE, Fancher PS, Schneider LW (1984) Parameters affecting stopping sight distance. The University of Michigan Transportation Research Institute

  • Planinic M, Milin-Sipus Z, Katic H, Susac A, Ivanjek L (2012) Comparison of student understanding of line graph slope in physics and mathematics. Int J Sci Math Educ 10(6):1393–1414

    Article  Google Scholar 

  • Pugi L, Malvezzi M, Papini S, Vettori G (2013) Design and preliminary validation of a tool for the simulation of train braking performance. J Mod Transport 21(4):247–257

    Article  Google Scholar 

  • Redish EF (2003) Teaching physics. Wiley, New York

    Google Scholar 

  • Rievaj V, Vrábel J Hudák A (2013) Tire inflation pressure influence on a vehicle stopping distances. Int J Traffic Transport Eng 2(2):9–13. ISSN 2325-0062

  • Rutten N, van Joolingen WR, van der Veen JT (2012) The learning effects of computer simulations in science education. Comput Educ 58(1):136–153

    Article  Google Scholar 

  • Sahin M (2010) Effects of problem-based learning on university students’ epistemological beliefs about physics and physics learning and conceptual understanding of newtonian mechanics. J Sci Educ Technol 19(3):266–275

    Article  Google Scholar 

  • Schmidt B (2011) Teaching engineering dynamics by use of peer instruction supported by an audience response system. Eur J Eng Educ 36(5):413–423

    Article  Google Scholar 

  • Snedecor GW, Cochran WG (1989) Statistical methods, 8th edn. Ames, Iowa State University Press

  • Sokoloff DR, Thorton RK (1997) Using interactive lecture demonstrations to create an active learning environment. Phys Teach 35(6):340–347

    Article  Google Scholar 

  • Taylor JR (1997) An introduction to error analysis. University Science Books, Sausalito

    Google Scholar 

  • Tracker (program). http://www.cabrillo.edu/~dbrown/tracker

  • Wiesner TF, Lan W (2004) Comparison of student learning in physical and simulated unit operations experiments. J Eng Educ 93(3):195–204

    Article  Google Scholar 

  • Wu Z, Liu Y, Pan G (2009) A smart car control model for brake comfort based on car following. IEEE Transp Intell Trans Syst 10(1):42–46

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by the Slovak Grant Agency KEGA on the basis of the agreements No. 035ŽU-4/2012 and by Foundation Volkswagen Slovakia (No. 052/12). It was written within the project from Operational Programme Education called Development of culture quality at the University of Žilina based on the European standards of higher education, ITMS code 26110230060 and Centre of excellence for systems and services of intelligent transport, ITMS 26220120028 supported by the Research & Development Operational Programme funded by the ERDF.

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Authors and Affiliations

  1. Department of Physics, Faculty of Electrical Engineering, University of Žilina, Žilina, Slovakia

    Peter Hockicko & Beáta Trpišová

  2. Department of Road and Urban Transports, Faculty of Operation and Economics of Transport and Communications, University of Žilina, Žilina, Slovakia

    Ján Ondruš

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  1. Peter Hockicko
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  2. Beáta Trpišová
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  3. Ján Ondruš
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Correspondence to Peter Hockicko.

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Hockicko, P., Trpišová, B. & Ondruš, J. Correcting Students’ Misconceptions about Automobile Braking Distances and Video Analysis Using Interactive Program Tracker. J Sci Educ Technol 23, 763–776 (2014). https://doi.org/10.1007/s10956-014-9510-z

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