Evaluation of engineering students' translation skills in Newton's laws of motion using Newman's error analysis

Felicia Katerina Pasno; Floyd Rey Plando

Keywords:

translation skills

representations

Newton's laws of motion

Newman's error analysis

physics education

Abstract

This study evaluated the translation skills of 178 Engineering students across Newton’s laws of motion representations using a standardized diagnostic test. A quantitative approach using statistical analysis of diagnostic exam results, graded with a specialized rubric, was employed. Results showed that students excelled in solving problems involving diagrams but struggled with equations and textual descriptions. Newman’s error analysis identified transformation errors as the participants’ most frequent mistakes, followed by encoding and process skills errors. Significant effects of year-level and program of study on test scores were found. The study highlights the importance of translation skills in Physics education, aiming to improve teaching methods for better comprehension of scientific principles.
References
1. Abu Mansor, S. N., Samsudin, N., & Ahmad Shukri, F. N. (2021). Newman’s Error Analysis of Common Errors in Solving Convergence of Power Series Using Ratio Test. International Journal of Academic Research in Business and Social Sciences, 11(9). https://doi.org/10.6007/ijarbss/v11-i9/11077
2. Adu‐Gyamfi, K., Stiff, L. V., & Bossé, M. J. (2012). Lost in translation: Examining translation errors associated with mathematical representations. School Science and Mathematics, 112(3), 159–170. https://doi.org/10.1111/j.1949-8594.2011.00129.x
3. Ainsworth, S. (2021). The Multiple Representations Principle in Multimedia Learning. The Cambridge Handbook of Multimedia Learning, 158–170.
4. Am, M. A., & Istiyono, E. (2022). Multiple representation ability of high school students in physics: A study of modern response theory. Thabiea: Journal of Natural Science Teaching, 5(1), 85–97. https://doi.org/10.21043/thabiea.v5i1.12550
5. Angell, C., Guttersrud, Ø., Henriksen, E. K., & Isnes, A. (2004). Physics: Frightful, but fun. pupils’ and teachers’ views of physics and physics teaching. Science Education, 88(5), 683–706. https://doi.org/10.1002/sce.10141
6. Arhin, J., & Hokor, E. K. (2021). Analysis of High School Students’ Errors in Solving Trigonometry Problems. Journal of Mathematics and Science Teacher, 1(1), em003. https://doi.org/10.29333/mathsciteacher/11076
7. Campos, E., Zavala, G., Zuza, K., & Guisasola, J. (2019). Electric field lines: The implications of students’ interpretation on their understanding of the concept of electric field and of the superposition principle. American Journal of Physics, 87(8), 660–667. https://doi.org/10.1119/1.5100588
8. Chang, J. Y., Cheng, M. F., Lin, S. Y., & Lin, J. L. (2021). Exploring students’ translation performance and use of intermediary representations among multiple representations: Example from torque and rotation. Teaching and Teacher Education, 97. https://doi.org/10.1016/j.tate.2020.103209
9. Danish, J. A., & Enyedy, N. (2006). Negotiated representational mediators: How young children decide what to include in their science representations. Science Education, 91(1), 1–35. https://doi.org/10.1002/sce.20166
10. Duval, R. (2006). A cognitive analysis of problems of comprehension in a learning of mathematics. In Educational Studies in Mathematics (Vol. 61, Issues 1–2, pp. 103–131). https://doi.org/10.1007/s10649-006-0400-z
11. Eilam, B., & Poyas, Y. (2008). Learning with multiple representations: Extending multimedia learning beyond the lab. Learning and Instruction, 18(4), 368–378. https://doi.org/10.1016/j.learninstruc.2007.07.003
12. Erickson, T. (2006). Stealing from physics: Modeling with mathematical functions in data-rich contexts. Teaching Mathematics and Its Applications: An International Journal of the IMA, 25(1), 23–32. https://doi.org/10.1093/teamat/hri025
13. Hahn, L., & Klein, P. (2023). The impact of multiple representations on students’ understanding of vector field concepts: Implementation of simulations and sketching activities into lecture-based recitations in undergraduate physics. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.1012787
14. Handayani, W., Setiawan, W., Sinaga, P., & Suhandi, A. (2019). Translation among modes of representation by pre-service physics teacher on magnetic force on particle concept. Journal of Physics: Conference Series, 1157(3). https://doi.org/10.1088/1742-6596/1157/3/032058
15. Herholdt, R. (2014). An error analysis in the early grades mathematics-A learning opportunity? Background: Teachers learning from child assessment in national tests. South African Journal of Childhood Education |, 4(1).
16. Hubber, P., Tytler, R., & Haslam, F. (2010). Teaching and learning about force with a representational focus: Pedagogy and teacher change. Research in Science Education, 40(1), 5–28. https://doi.org/10.1007/s11165-009-9154-9
17. Kind, P. M., Angell, C., & Guttersrud, Ø. (2017). Teaching and learning representations in upper secondary physics. Models and Modeling in Science Education, 25–45. https://doi.org/10.1007/978-3-319-58914-5_2
18. Kristianti, L. W., & Retnawati, H. (2020). An analysis of students’ error in completing the contextual problems based on Newman’s procedure. Journal of Physics: Conference Series, 1511(1). https://doi.org/10.1088/1742-6596/1511/1/012036
19. Makamure, C., & Jojo, Z. M. (2022). An analysis of errors for pre-service teachers in first order ordinary differential equations. Eurasia Journal of Mathematics, Science and Technology Education, 18(6). https://doi.org/10.29333/ejmste/12074
20. Munfaridah, N., Avraamidou, L., & Goedhart, M. (2021). The Use of Multiple Representations in Undergraduate Physics Education: What Do we Know and Where Do we Go from Here? Eurasia Journal of Mathematics, Science and Technology Education, 17(1), 1–19. https://doi.org/10.29333/ejmste/9577
21. Murshed, M., Phang, F. A., & Bunyamin, M. A. H. (2021). Transformation of multiple representation in real world physics problem solving. Journal of Physics: Conference Series, 1760(1). https://doi.org/10.1088/1742-6596/1760/1/012004
22. Nurrahmawati, Sa’dijah, C., Sudirman, & Muksar, M. (2021). Assessing students’ errors in mathematical translation: From symbolic to verbal and graphic representations. International Journal of Evaluation and Research in Education, 10(1), 115–125. https://doi.org/10.11591/ijere.v10i1.20819
23. Opfermann, M., Schmeck, A., & Fischer, H. E. (2017). Multiple Representations in Physics and Science Education – Why Should We Use Them? (pp. 1–22). https://doi.org/10.1007/978-3-319-58914-5_1
24. Poluakan, C. (2019). The importance of diagrams representation in physics learning. Journal of Physics: Conference Series, 1317(1), 012175. https://doi.org/10.1088/1742-6596/1317/1/012175
25. Saleh, K., Yuwono, I., Rahman As’ari, A., & Sa’dijah, C. (n.d.). Errors analysis solving problems analogies by Newman procedure using analogical reasoning. In International Journal of Humanities and Social Sciences (Vol. 9, Issue 1). ©IJHSS. http://aajhss.org/index.php/ijhss
26. Seufert, T. (2003). Supporting coherence formation in learning from multiple representations. Learning and Instruction, 13(2), 227–237. https://doi.org/10.1016/s0959-4752(02)00022-1
27. Tang, K., Delgado, C., & Moje, E. B. (2014). An integrative framework for the analysis of multiple and multimodal representations for meaning‐making in science education. Science Education, 98(2), 305–326. https://doi.org/10.1002/sce.21099
28. Triliana, T., & Asih, E. C. M. (2019). Analysis of students’ errors in solving probability based on Newman’s error analysis. Journal of Physics: Conference Series, 1211(1). https://doi.org/10.1088/1742-6596/1211/1/012061
29. Verzosa-Quinto, E. M., & Mabansag, A. B. (2023). Error Analysis in Solving Word Problems among Grade-8 Students. International Journal of Current Science Research and Review, 06(10). https://doi.org/10.47191/ijcsrr/V6-i10-10
30. White, A. L. (2009). A revaluation of Newman's error analysis. In D. Martin, T. Fitzpatrick, R. Hunting, D. Itter, C. Lenard, T. Mills, L. Milne (Eds), Mathematics of prime importance, Proceedings of 46th Annual Conference of the Mathematics Association of Victoria (pp. 249-257). M.A.V.

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How to cite

Pasno, F. K., & Plando, F. R. (2025). Evaluation of engineering students’ translation skills in Newton’s laws of motion using Newman’s error analysis. Multidisciplinary Science Journal, (| Accepted Articles). Retrieved from https://malque.pub/ojs/index.php/msj/article/view/7426

[1] Abu Mansor, S. N., Samsudin, N., & Ahmad Shukri, F. N. (2021). Newman’s Error Analysis of Common Errors in Solving Convergence of Power Series Using Ratio Test. International Journal of Academic Research in Business and Social Sciences, 11(9). https://doi.org/10.6007/ijarbss/v11-i9/11077

[2] Adu‐Gyamfi, K., Stiff, L. V., & Bossé, M. J. (2012). Lost in translation: Examining translation errors associated with mathematical representations. School Science and Mathematics, 112(3), 159–170. https://doi.org/10.1111/j.1949-8594.2011.00129.x

[3] Ainsworth, S. (2021). The Multiple Representations Principle in Multimedia Learning. The Cambridge Handbook of Multimedia Learning, 158–170.

[4] Am, M. A., & Istiyono, E. (2022). Multiple representation ability of high school students in physics: A study of modern response theory. Thabiea: Journal of Natural Science Teaching, 5(1), 85–97. https://doi.org/10.21043/thabiea.v5i1.12550

[5] Angell, C., Guttersrud, Ø., Henriksen, E. K., & Isnes, A. (2004). Physics: Frightful, but fun. pupils’ and teachers’ views of physics and physics teaching. Science Education, 88(5), 683–706. https://doi.org/10.1002/sce.10141

[6] Arhin, J., & Hokor, E. K. (2021). Analysis of High School Students’ Errors in Solving Trigonometry Problems. Journal of Mathematics and Science Teacher, 1(1), em003. https://doi.org/10.29333/mathsciteacher/11076

[7] Campos, E., Zavala, G., Zuza, K., & Guisasola, J. (2019). Electric field lines: The implications of students’ interpretation on their understanding of the concept of electric field and of the superposition principle. American Journal of Physics, 87(8), 660–667. https://doi.org/10.1119/1.5100588

[8] Chang, J. Y., Cheng, M. F., Lin, S. Y., & Lin, J. L. (2021). Exploring students’ translation performance and use of intermediary representations among multiple representations: Example from torque and rotation. Teaching and Teacher Education, 97. https://doi.org/10.1016/j.tate.2020.103209

[9] Danish, J. A., & Enyedy, N. (2006). Negotiated representational mediators: How young children decide what to include in their science representations. Science Education, 91(1), 1–35. https://doi.org/10.1002/sce.20166

[10] Duval, R. (2006). A cognitive analysis of problems of comprehension in a learning of mathematics. In Educational Studies in Mathematics (Vol. 61, Issues 1–2, pp. 103–131). https://doi.org/10.1007/s10649-006-0400-z

[11] Eilam, B., & Poyas, Y. (2008). Learning with multiple representations: Extending multimedia learning beyond the lab. Learning and Instruction, 18(4), 368–378. https://doi.org/10.1016/j.learninstruc.2007.07.003

[12] Erickson, T. (2006). Stealing from physics: Modeling with mathematical functions in data-rich contexts. Teaching Mathematics and Its Applications: An International Journal of the IMA, 25(1), 23–32. https://doi.org/10.1093/teamat/hri025

[13] Hahn, L., & Klein, P. (2023). The impact of multiple representations on students’ understanding of vector field concepts: Implementation of simulations and sketching activities into lecture-based recitations in undergraduate physics. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.1012787

[14] Handayani, W., Setiawan, W., Sinaga, P., & Suhandi, A. (2019). Translation among modes of representation by pre-service physics teacher on magnetic force on particle concept. Journal of Physics: Conference Series, 1157(3). https://doi.org/10.1088/1742-6596/1157/3/032058

[15] Herholdt, R. (2014). An error analysis in the early grades mathematics-A learning opportunity? Background: Teachers learning from child assessment in national tests. South African Journal of Childhood Education |, 4(1).

[16] Hubber, P., Tytler, R., & Haslam, F. (2010). Teaching and learning about force with a representational focus: Pedagogy and teacher change. Research in Science Education, 40(1), 5–28. https://doi.org/10.1007/s11165-009-9154-9

[17] Kind, P. M., Angell, C., & Guttersrud, Ø. (2017). Teaching and learning representations in upper secondary physics. Models and Modeling in Science Education, 25–45. https://doi.org/10.1007/978-3-319-58914-5_2

[18] Kristianti, L. W., & Retnawati, H. (2020). An analysis of students’ error in completing the contextual problems based on Newman’s procedure. Journal of Physics: Conference Series, 1511(1). https://doi.org/10.1088/1742-6596/1511/1/012036

[19] Makamure, C., & Jojo, Z. M. (2022). An analysis of errors for pre-service teachers in first order ordinary differential equations. Eurasia Journal of Mathematics, Science and Technology Education, 18(6). https://doi.org/10.29333/ejmste/12074

[20] Munfaridah, N., Avraamidou, L., & Goedhart, M. (2021). The Use of Multiple Representations in Undergraduate Physics Education: What Do we Know and Where Do we Go from Here? Eurasia Journal of Mathematics, Science and Technology Education, 17(1), 1–19. https://doi.org/10.29333/ejmste/9577

[21] Murshed, M., Phang, F. A., & Bunyamin, M. A. H. (2021). Transformation of multiple representation in real world physics problem solving. Journal of Physics: Conference Series, 1760(1). https://doi.org/10.1088/1742-6596/1760/1/012004

[22] Nurrahmawati, Sa’dijah, C., Sudirman, & Muksar, M. (2021). Assessing students’ errors in mathematical translation: From symbolic to verbal and graphic representations. International Journal of Evaluation and Research in Education, 10(1), 115–125. https://doi.org/10.11591/ijere.v10i1.20819

[23] Opfermann, M., Schmeck, A., & Fischer, H. E. (2017). Multiple Representations in Physics and Science Education – Why Should We Use Them? (pp. 1–22). https://doi.org/10.1007/978-3-319-58914-5_1

[24] Poluakan, C. (2019). The importance of diagrams representation in physics learning. Journal of Physics: Conference Series, 1317(1), 012175. https://doi.org/10.1088/1742-6596/1317/1/012175

[25] Saleh, K., Yuwono, I., Rahman As’ari, A., & Sa’dijah, C. (n.d.). Errors analysis solving problems analogies by Newman procedure using analogical reasoning. In International Journal of Humanities and Social Sciences (Vol. 9, Issue 1). ©IJHSS. http://aajhss.org/index.php/ijhss

[26] Seufert, T. (2003). Supporting coherence formation in learning from multiple representations. Learning and Instruction, 13(2), 227–237. https://doi.org/10.1016/s0959-4752(02)00022-1

[27] Tang, K., Delgado, C., & Moje, E. B. (2014). An integrative framework for the analysis of multiple and multimodal representations for meaning‐making in science education. Science Education, 98(2), 305–326. https://doi.org/10.1002/sce.21099

[28] Triliana, T., & Asih, E. C. M. (2019). Analysis of students’ errors in solving probability based on Newman’s error analysis. Journal of Physics: Conference Series, 1211(1). https://doi.org/10.1088/1742-6596/1211/1/012061

[29] Verzosa-Quinto, E. M., & Mabansag, A. B. (2023). Error Analysis in Solving Word Problems among Grade-8 Students. International Journal of Current Science Research and Review, 06(10). https://doi.org/10.47191/ijcsrr/V6-i10-10

[30] White, A. L. (2009). A revaluation of Newman's error analysis. In D. Martin, T. Fitzpatrick, R. Hunting, D. Itter, C. Lenard, T. Mills, L. Milne (Eds), Mathematics of prime importance, Proceedings of 46th Annual Conference of the Mathematics Association of Victoria (pp. 249-257). M.A.V.

Abstract

References

How to cite