Enhancing Conceptual Understanding of Mechanics through Smartphone-Based Laboratories: A Quasi-Experimental Study with First-Year University Students
Abstract
Introductory mechanics courses present persistent challenges for first-year university students, who often hold robust misconceptions that traditional instruction fails to address. Smartphone-based laboratories (SmartIPLs) offer an accessible, low-cost alternative that may enhance conceptual understanding through authentic, inquiry-based experimentation. This quasi-experimental study investigated the effectiveness of smartphone-based laboratories for enhancing conceptual understanding of mechanics among first-year university students and examined gender differences in intervention outcomes. Methods: Participants were 128 first-year students (45% female, 55% male) randomly assigned to experimental (n = 64) and control (n = 64) groups. The experimental group completed five smartphone-based laboratory activities using the phyphox app over eight weeks, while the control group completed traditional verification laboratories covering identical mechanics topics. Conceptual understanding was measured using the Force Concept Inventory (FCI) at pretest and posttest. Student perceptions were assessed through a 12-item survey and focus group interviews. Data were analyzed using ANCOVA, two-way ANOVA, and thematic analysis.
Downloads
References
Calalb, M., & Zelenschi, I. (2004). The effects of constructivist physics lessons and laboratories on students' academic success. Acta Didactica Napocensia, *17*(2), 99–111. https://doi.org/10.24193/adn.17.2.8
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.
Creswell, J. W., & Creswell, J. D. (2008). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, *13*(3), 319–340. https://doi.org/10.2307/249008
Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149–1160. https://doi.org/10.3758/BRM.41.4.1149
Field, A. (2008). Discovering statistics using IBM SPSS statistics (5th ed.). SAGE Publications.
Goshu, B.S., (2005), Predicting Students’ Academic Achievements in Physics Using Fuzzy Logic-Based, Educational Point 2 (2), e141. https://doi.org/10.71176/edup/17669
Hake, R. R. (1998). Interactive-engagement versus traditional methods: A six-thousand-student survey of mechanics test data for introductory physics courses. American Journal of Physics, 66(1), 64–74. https://doi.org/10.1119/1.18809
Halloun, I. A., & Hestenes, D. (1985). The initial knowledge state of college physics students. American Journal of Physics, *53*(11), 1043–1055. https://doi.org/10.1119/1.14030
Hestenes, D., Wells, M., & Swackhamer, G. (1992). Force concept inventory. The Physics Teacher, *30*(3), 141–158. https://doi.org/10.1119/1.2343497
Hillmayr, D., Ziernwald, L., Reinhold, F., Hofer, S. I., & Reiss, K. M. (2010). The potential of digital tools to enhance mathematics and science learning in secondary schools: A context-specific meta-analysis. Computers & Education, 153, Article 103897. https://doi.org/10.1016/j.compedu.2010.103897
Hochberg, K., Kuhn, J., & Müller, A. (2010). Using smartphones as experimental tools—a follow-up: Cognitive effects by video analysis and reduction of cognitive load by multiple representations. Journal of Science Education and Technology, *29*(2), 303–317. https://doi.org/10.1007/s10956-020-09816-w
Jiang, L., Sun, Y., Zhang, X., Liu, F., Wei, Z., Yang, Y., & Song, J. (2005). How is the impact of ICT-assisted experiments on students' physics learning: A meta-analysis of K-12 research. Journal of Science Education and Technology. Advance online publication. https://doi.org/10.1007/s10956-025-10235-8
Klein, P., Kuhn, J., & Müller, A. (2011). Fostering students' conceptual knowledge in optics using mobile devices—a quasi-experimental study. Physical Review Physics Education Research, 17(1), 010115. https://doi.org/10.1103/PhysRevPhysEducRes.17.010115
Krueger, R. A., & Casey, M. A. (2005). Focus groups: A practical guide for applied research (5th ed.). SAGE Publications.
Kuhn, J., & Vogt, P. (2013). Applications and examples of experiments with mobile phones and smartphones in physics lessons. Frontiers in Sensors, 1(4), 67–73. https://doi.org/10.3389/fsens.2013.00067
Tadele, K., and Sitotaw, B. (2008). Perception and trends in assessment of students’ learning in Physics courses. Latin-American Journal of Physics Education, 12(1), 1-9. http://www.lajpe.org/mar18/12_1_07.pdf
McDermott, L. C. (1984). Research on conceptual understanding in mechanics. Physics Today, *37*(7), 24–32. https://doi.org/10.1063/1.2916318
Monteiro, M., & Martí, A. C. (2012). Resource letter MDS-1: Mobile devices and sensors for physics teaching. American Journal of Physics, *90*(5), 328–343. https://doi.org/10.1119/10.0009378
.
.png)
_.gif)
_.gif)
