Development and Validation of a Concept Inventory for Interpreting Kinematics Graphs in the Tanzanian Context
This paper discusses the development and validation of a concept inventory for interpreting kinematics graphs in the Tanzanian context. The study invo.
- Pub. date: April 15, 2023
- Pages: 673-693
- 460 Downloads
- 748 Views
- 2 Citations
This paper discusses the development and validation of a concept inventory for interpreting kinematics graphs in the Tanzanian context. The study involved 61 participants comprising physics pre-service teachers, secondary school teachers, diploma college tutors, and a university lecturer from Tanzania. We developed 25 multiple-choice questions for interpreting kinematics graphs. The different steps in the development process used are selecting the topic, setting objectives, constructing questions, validating questions, and reliability testing. We carried out descriptive and inferential statistical analysis by using Statistical Package for Social Science (SPSS) version 22 followed by item analysis for pre-and post-piloting. Findings revealed normal distribution scores with a mean and standard deviation of 39.28±10.893 for pre-piloting and 40.16±8.08 for post-piloting. It also revealed no significant difference between pre-and post-piloting results with a p-value of 0.414. In addition, correlation coefficients for test re-test reliability were .783 and .878 for single and average measures respectively. Moreover, item analysis in terms of difficulty index, discrimination index, and distractor efficiency agreed with the published standards. Based on these findings, the study recommends the use of developed and validated kinematics graphs concept inventory by physics educators in both research and classroom instructions in the Tanzanian context.
Keywords: Concept inventory, kinematics graphs, Physics teachers, Tanzania context.
References
Adams, W. K., & Wieman, C. E. (2011). Development and validation of instruments to measure learning of expert‐like thinking. International Journal of Science Education, 33(9), 1289-1312. https://doi.org/10.1080/09500693.2010.512369
Amin, B. D., Sahib, E. P., Harianto, Y. I., Patandean, A. J., Herman, H., & Sujiono, E. (2020). The interpreting ability on science kinematics graphs of senior high school students in South Sulawesi, Indonesia. Indonesian Journal of Science Education/Jurnal Pendidikan IPA Indonesia, 9(2), 179-186. https://doi.org/10.15294/jpii.v9i2.23349
Andrade, C. (2019). The p-value and statistical significance: Misunderstandings, explanations, challenges, and alternatives. Indian Journal of Psychological Medicine, 41(3), 210-215. https://doi.org/10.4103/IJPSYM.IJPSYM_193_19
Antwi, V. (2015). Impact of the use of MBL, simulation and graph samples in improving Ghanaian SHS science students understanding in describing kinematics graphs. Advance in Life Science and Technology, 31(1), 24-33. https://l24.im/TRE8em
Antwi, V., Savelsbergh, E., & Eijkelhof, H. (2018). Understanding kinematics graphs using MBL tools, simulations and graph samples in an interactive engagement context in a Ghanaian university. Journal of Physics: Conference Series. 1076, Article 012002. https://doi.org/10.1088/1742-6596/1076/1/012002
Beichner, R. J. (1994). Testing student interpretation of kinematics graphs. American Journal of Physics, 62(8), 750-762. https://doi.org/10.1119/1.17449
Bonett, D. G., & Wright, T. A. (2015). Cronbach's alpha reliability: Interval estimation, hypothesis testing, and sample size planning. Journal of Organizational Behavior, 36(1), 3-15. https://doi.org/10.1002/job.1960
Bowen, P., Rose, R., & Pilkington, A. (2017). Mixed methods-theory and practice: Sequential, explanatory approach. International Journal of Quantitative and Qualitative Research Methods, 5(2), 10-27. https://bit.ly/3FX9aaI
Creswell, J. W., & Clark, V. L. P. (2017). Designing and conducting mixed methods research. Sage publications. https://l24.im/FVjW
Ding, L., Chabay, R., Sherwood, B., & Beichner, R. (2006). Evaluating an electricity and magnetism assessment tool: Brief electricity and magnetism assessment. Physical Review Special Topics. Physics Education Research, 2, Article 010105. https://doi.org/10.1103/PhysRevSTPER.2.010105
Ghasemi, A., & Zahediasl, S. (2012). Normality tests for statistical analysis: A guide for non-statisticians. International Journal of Endocrinology and Metabolism, 10(2), 486–489. https://doi.org/10.5812/ijem.3505
Gorman, G. E., Clayton, P. R., Shep, S. J., & Clayton, A. (2005). Qualitative research for the information professional: A practical handbook. Facet Publishing. https://l24.im/mlA
Halloun, I. A., & Hestenes, D. (1985). Common sense concepts about motion. American Journal of Physics, 53(11), 1056-1065. https://doi.org/10.1119/1.14031
Hestenes, D., Wells, M., & Swackhammer, G. (1992). Force concept inventory. The Physics Teacher, 30(3), 141-158. https://doi.org/10.1119/1.2343497
Hingorjo, M. R., & Jaleel, F. (2012). Analysis of one-best MCQs: The difficulty index, discrimination index and distractor efficiency. Journal of the Pakistan Medical Association, 62(2), 142-147. https://l24.im/drfqG
Kalas, P., O’Neill, A., Pollock, C., & Birol, G. (2013). Development of a meiosis concept inventory. CBE—Life Sciences Education, 12(4), 655-664. https://doi.org/10.1187/cbe.12-10-0174
Kirya, K. R., Mashood, K. K., & Yadav, L. L. (2021). A methodological analysis for the development of a circular-motion concept inventory in a Ugandan context by using the Delphi technique. International Journal of Learning, Teaching and Educational Research, 20(10), 61-68. https://doi.org/10.26803/ijlter.20.10.4
Knight, J. K. (2010). Biology concept assessment tools: Design and use. Microbiology Australia, 31(1), 5-8. https://doi.org/10.1071/MA10005
Libarkin, J.C., Anderson, S.W., Kortemeyer, G., & Raeburn, S. P. (2011). Revisiting the geoscience concept inventory: A call to the community. GSA Today, 21(8), 26-28. https://doi.org/10.1130/G110GW.1
Lindell, R. S., Peak, E., & Foster, T. M. (2007). Are they all created equal? A comparison of different concept inventory development methodologies. American Institute of Physics Conference Proceedings 883(1), 14-17. https://doi.org/10.1063/1.2508680
Manurung, S. R., Mihardi, S., Rustaman, N. Y., & Siregar, N. (2018). Improvement of graph interpretation ability using hypertext-assisted kinematic learning and formal thinking ability. Jurnal Pendidikan Fisika Indonesia, 14(1), 1-6. https://doi.org/10.15294/jpfi.v14i1.9444
Mashood, K. K., & Singh, V. A. (2013). Development of a concept inventory in rotational kinematics: initial phases and some methodological concerns. In G. Nagarjuna, A. Jamakhandi & E. M. Sam (Eds.), Proceedings of EpiSTEME 5–International Conference to Review Research on Science, Technology and Mathematics Education (pp. 139-144). Homi Bhabha Centre for Science Education-Tata Institute of Fundamental Research.
McDermott, L. C., Rosenquist, M. L., & Van Zee, E. H. (1987). Student difficulties in connecting graphs and physics: Examples from kinematics. American Journal of Physics, 55(6), 503-513. https://doi.org/10.1119/1.15104
Ministry of Education and Vocational Training. (2007). Physics syllabus for ordinary level secondary education form I-IV. https://l24.im/oxy
National Examination Council of Tanzania. (2019a). Students’ response item analysis report for form two national assessment: Physics. https://l24.im/Xaqk
National Examination Council of Tanzania. (2019b). Candidates’ response item analysis report for form four national examination: Physics. https://l24.im/kvQKq
National Examination Council of Tanzania. (2020a). Students’ response item analysis report for form two national assessment: Physics. https://l24.im/mswjI
National Examination Council of Tanzania. (2020b). Candidates’ response item analysis report for form four national examination: Physics. https://l24.im/U5sM64
Ndihokubwayo, K., Uwamahoro, J., Ndayambaje, I., & Ralph, M. (2020). Light phenomena conceptual assessment: An inventory tool for teachers. Physics Education, 55, Article 035009. https://doi.org/10.1088/1361-6552/ab6f20
Phage, I. B., Lemmer, M., & Hitge, M. (2017). Probing factors influencing students’ graph comprehension regarding four operations in kinematics graphs. African Journal of Research in Mathematics, Science and Technology Education, 21(2), 200-210. https://doi.org/10.1080/18117295.2017.1333751
Planinic, L,, Lvanjek, L., & Susac, A. (2013). Comparison of university students’ understanding of graphs in different contexts Maja. Physics Education Research, 9, 213-221. https://doi.org/10.1103/PhysRevSTPER.9.020103
President's Office - Regional Administration and Local Government. (2019). Regional BEST 2019. https://l24.im/QD95
President's Office - Regional Administration and Local Government. (2020). Regional BEST 2020. https://l24.im/nOruCe
Shoji, Y., Munejiri, S., & Kaga, E. (2021). Validity of Force Concept Inventory evaluated by students’ explanations and confirmation using modified item response curve. Physical Review Physics Education Research, 17, Article 020120. https://doi.org/jw9m
Taib, F., & Yusoff, M. S. B. (2014). Difficulty index, discrimination index, sensitivity and specificity of long case and multiple-choice questions to predict medical students’ examination performance. Journal of Taibah University Medical Sciences, 9(2), 110-114. https://doi.org/10.1016/j.jtumed.2013.12.002
Tanzania Institute of Education. (2021). Physics for secondary school student's book form two. Tanzania Institute of Education.
Taylor, C., Clancy, M., Webb, K. C., Zingaro, D., Lee, C., & Porter, L. (2020). The practical details of building a CS concept inventory. In Proceedings of the 51st ACM Technical Symposium on Computer Science Education. Association for Computing Machinery. https://doi.org/10.1145/3328778.3366903
Thornton, R. K., & Sokoloff, D. R. (1998). Assessing student learning of Newton’s laws: The force and motion conceptual evaluation and the evaluation of active learning laboratory and lecture curricula. American Journal of Physics, 66(4), 338-352. https://doi.org/10.1119/1.18863
Yang, F. M. (2014). Item response theory for measurement validity. Shanghai Archives of Psychiatry, 26(3), 171-177.
Zavala, G., Tejeda, S., Barniol, P., & Beichner, R. J. (2017). Modifying the test of understanding graphs in kinematics. Physical Review Physics Education Research, 13, Article 020111. https://doi.org/gdzz3d