Mechanistic reasoning in science education: A literature review

Rayendra Wahyu Bachtiar; Ralph F. G. Meulenbroeks; Wouter R. van Joolingen

doi:10.29333/ejmste/12512

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Rayendra Wahyu Bachtiar ¹ ² ^* , Ralph F. G. Meulenbroeks ¹ , Wouter R. van Joolingen ¹

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¹ Freudenthal Institute, Utrecht University, Utrecht, THE NETHERLANDS² Faculty of Teacher Training and Education, University of Jember, Jember, East Java, INDONESIA^* Corresponding Author

Abstract

There is a growing research interest in mechanistic reasoning (MR) in the field of science education, as this type of reasoning is perceived as an essential thinking skill for science education. This literature review synthesized 60 science education studies on MR published from 2006 to 2021. The findings showed three common aspects of conceptualizations of MR in science education: (1) causality in relation to MR, (2) use of entities and their associated activities, and (3) use of entities at (at least) one scale level below the scale level of a target phenomenon. While most of the reviewed studies related the importance of MR to cognitive aspects, a smaller number associated its value with scientific modelling. Three main difficulties in generating MR were categorized: (1) identifying and using unobservable entities, (2) assigning activities to entities, and (3) identifying and using an appropriate number of entities. Various types of support for fostering MR were identified. Implications and future studies are discussed.

Keywords

Mechanistic reasoning
mechanistic explanations
science education
literature review

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Review Article

EURASIA J Math Sci Tech Ed, 2022, Volume 18, Issue 11, Article No: em2178

https://doi.org/10.29333/ejmste/12512

Publication date: 06 Oct 2022

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References

Bachtiar, R. W., Meulenbroeks, R. F. G., & van Joolingen, W. R. (2021). Stimulating mechanistic reasoning in physics using student-constructed stop-motion animations. Journal of Science Education and Technology, 30(6), 777-790. https://doi.org/10.1007/s10956-021-09918-z
Balabanoff, M. E., Al Fulaiti, H., Bhusal, S., Harrold, A., & Moon, A. C. (2020). An exploration of chemistry students’ conceptions of light and light-matter interactions in the context of the photoelectric effect. International Journal of Science Education, 42(6), 861-881. https://doi.org/10.1080/09500693.2020.1736358
Becker, N., Noyes, K., & Cooper, M. (2016). Characterizing students’ mechanistic reasoning about London dispersion forces. Journal of Chemical Education, 93(10), 1713-1724. https://doi.org/10.1021/acs.jchemed.6b00298
Bolger, M. S., Kobiela, M., Weinberg, P. J., & Lehrer, R. (2012). Children’s mechanistic reasoning. Cognition and Instruction, 30(2), 170-206. https://doi.org/10.1080/07370008.2012.661815
Brown, S. A., Ronfard, S., & Kelemen, D. (2020). Teaching natural selection in early elementary classrooms: Can a storybook intervention reduce teleological misunderstandings? Evolution: Education and Outreach, 13, 12. https://doi.org/10.1186/s12052-020-00127-7
Caspari, I., Kranz, D., & Graulich, N. (2018a). Resolving the complexity of organic chemistry students’ reasoning through the lens of a mechanistic framework. Chemistry Education Research and Practice, 19(4), 1117-1141. https://doi.org/10.1039/c8rp00131f
Caspari, I., Weinrich, M. L., Sevian, H., & Graulich, N. (2018b). This mechanistic step is “productive”: Organic chemistry students’ backward-oriented reasoning. Chemistry Education Research and Practice, 19(1), 42-59. https://doi.org/10.1039/c7rp00124j
Cooper, M. M., Kouyoumdjian, H., & Underwood, S. M. (2016). Investigating students’ reasoning about acid-base reactions. Journal of Chemical Education, 93(10), 1703-1712. https://doi.org/10.1021/acs.jchemed.6b00417
Crandell, O. M., Kouyoumdjian, H., Underwood, S. M., & Cooper, M. M. (2019). Reasoning about reactions in organic chemistry: Starting it in general chemistry. Journal of Chemical Education, 96(2), 213-226. https://doi.org/10.1021/acs.jchemed.8b00784
Crandell, O. M., Lockhart, M. A., & Cooper, M. M. (2020). Arrows on the page are not a good gauge: Evidence for the importance of causal mechanistic explanations about nucleophilic substitution in organic chemistry. Journal of Chemical Education, 97(2), 313-327. https://doi.org/10.1021/acs.jchemed.9b00815
Craver, C. F., & Darden, L. (2001). Discovering mechanisms in neurobiology: The case of spatial memory. In P. K. Machamer, R. Grush, & P. McLaughlin (Eds.), Theory and method in the neurosciences (pp. 112-137). University of Pittsburgh Press.
de Andrade, V., Shwartz, Y., Freire, S., & Baptista, M. (2021). Students’ mechanistic reasoning in practice: Enabling functions of drawing, gestures, and talk. Science Education, 106(1), 199-225. https://doi.org/10.1002/sce.21685
Dickes, A. C., Sengupta, P., Farris, A. V., & Basu, S. (2016). Development of mechanistic reasoning and multilevel explanations of ecology in third grade using agent-based models. Science Education, 100(4), 734-776. https://doi.org/10.1002/sce.21217
Ding, L. (2018). Progression trend of scientific reasoning from elementary school to university: A large-scale cross-grade survey among Chinese students. International Journal of Science and Mathematics Education, 16(8), 1479-1498. https://doi-org/10.1007/s10763-017-9844-0
Dood, A. J., Dood, J. C., Cruz-Ramírez De Arellano, D., Fields, K. B., & Raker, J. R. (2020). Analyzing explanations of substitution reactions using lexical analysis and logistic regression techniques. Chemistry Education Research and Practice, 21(1), 267-286. https://doi.org/10.1039/c9rp00148d
Duncan, R. G., & Reiser, B. J. (2007). Reasoning across ontologically distinct levels: Students’ understandings of molecular genetics. Journal of Research in Science Teaching, 44(7), 938-959. https://doi.org/10.1002/tea.20186
Geller, B. D., Gouvea, J., Dreyfus, B. W., Sawtelle, V., Turpen, C., & Redish, E. F. (2019). Bridging the gaps: How students seek disciplinary coherence in introductory physics for life science. Physical Review Physics Education Research, 15(2), 020142. https://doi.org/10.1103/PhysRevPhysEducRes.15.020142
Haskel-Ittah, M., Duncan, R. G., Vázquez-Ben, L., & Yarden, A. (2020a). Reasoning about genetic mechanisms: Affordances and constraints for learning. Journal of Research in Science Teaching, 57(3), 342-367. https://doi.org/10.1002/tea.21595
Haskel-Ittah, M., Duncan, R. G., & Yarden, A. (2020b). Students’ understanding of the dynamic nature of genetics: Characterizing undergraduates’ explanations for interaction between genetics and environment. CBE—Life Sciences Education, 19(3), 1-13. https://doi.org/10.1187/cbe.19-11-0221
Haskel-Ittah, M., & Yarden, A. (2018). Students’ conception of genetic phenomena and its effect on their ability to understand the underlying mechanism. CBE—Life Sciences Education, 17(3), ar36. https://doi.org/10.1187/cbe.18-01-0014
Houchlei, S. K., Bloch, R. R., & Cooper, M. M. (2021). Mechanisms, models, and explanations: Analyzing the mechanistic paths students take to reach a product for familiar and unfamiliar organic reactions. Journal of Chemical Education, 98(9), 2751-2764. https://doi.org/10.1021/acs.jchemed.1c00099
Hsiao, L., Lee, I., & Klopfer, E. (2019). Making sense of models: How teachers use agent-based modeling to advance mechanistic reasoning. British Journal of Educational Technology, 50(5), 2203-2216. https://doi.org/10.1111/bjet.12844
Keiner, L., & Graulich, N. (2020). Transitions between representational levels: Characterization of organic chemistry students’ mechanistic features when reasoning about laboratory work-up procedures. Chemistry Education Research and Practice, 21(1), 469-482. https://doi.org/10.1039/c9rp00241c
Keiner, L., & Graulich, N. (2021). Beyond the beaker: Students’ use of a scaffold to connect observations with the particle level in the organic chemistry laboratory. Chemistry Education Research and Practice, 22(1), 146-163. https://doi.org/10.1039/d0rp00206b
Krist, C., Schwarz, C. V., & Reiser, B. J. (2019). Identifying essential epistemic heuristics for guiding mechanistic reasoning in science learning. Journal of the Learning Sciences, 28(2), 160-205. https://doi.org/10.1080/10508406.2018.1510404
Lawson, A. E. (2010). Basic inferences of scientific reasoning, argumentation, and discovery. Science Education, 94(2), 336-364.
Louca, T. L., & Papademetri-Kachrimani, C. (2012). Asking for too much too early? Promoting mechanistic reasoning in early childhood science and mathematics education. In J. van Aalst, K. Thompson, M. J. Jacobson, & P. Reimann (Eds.), Proceedings of the 10^th International Conference of the Learning Sciences: The Future of Learning (pp. 513-514). International Society of the Learning Sciences.
Machamer, P., Darden, L., & Craver, C. F. (2000). Thinking about mechanisms. Philosophy of Science, 67(1), 1-25. https://doi.org/10.1086/392759
Macrie-Shuck, M., & Talanquer, V. (2020). Exploring students’ explanations of energy transfer and transformation. Journal of Chemical Education, 97(12), 4225-4234. https://doi.org/10.1021/acs.jchemed.0c00984
Martín-Martín, A., Orduna-Malea, E., Thelwall, M., & López-Cózar, E. D. (2018). Google Scholar, Web of Science, and Scopus: A systematic comparison of citations in 252 subject categories. Journal of Informetrics, 12(4), 1160-1177. https://doi.org/10.1016/j.joi.2018.09.002
Mathayas, N., Brown, D. E., & Lindgren, R. (2021). “I got to see, and I got to be a part of it”: How cued gesturing facilitates middle-school students’ explanatory modeling of thermal conduction. Journal of Research in Science Teaching, 58(10), 1557-1589. https://doi.org/10.1002/tea.21718
Mathayas, N., Brown, D. E., Wallon, R. C., & Lindgren, R. (2019). Representational gesturing as an epistemic tool for the development of mechanistic explanatory models. Science Education, 103(4), 1047-1079. https://doi.org/10.1002/sce.21516
Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. Journal of Clinical Epidemiology, 62(10), 1006-1012. https://doi.org/10.1016/j.jclinepi.2009.06.005
Moore, C. (2021). Designing a curriculum for the networked knowledge facet of systems thinking in secondary biology courses: A pragmatic framework. Journal of Biological Education. https://doi.org/10.1080/00219266.2021.1909641
Moreira, P., Marzabal, A., & Talanquer, V. (2019). Using a mechanistic framework to characterize chemistry students’ reasoning in written explanations. Chemistry Education Research and Practice, 20(1), 120-131. https://doi.org/10.1039/c8rp00159f
National Research Council. (2012). A framework for K-12 science education: Practices, crosscutting concepts, and core ideas. National Academies Press.
Nawani, J., von Kotzebue, L., Spangler, M., & Neuhaus, B. J. (2019). Engaging students in constructing scientific explanations in biology classrooms: A lesson-design model. Journal of Biological Education, 53(4), 378-389. https://doi.org/10.1080/00219266.2018.1472131
Newman, D. L., Coakley, A., Link, A., Mills, K., & Wright, L. K. (2021). Punnett squares or protein production? The expert–novice divide for conceptions of genes and gene expression. CBE Life Sciences Education, 20(4), 1-10. https://doi.org/10.1187/CBE.21-01-0004
NGSS Lead States. (2013). Next generation science standards: For states, by states. National Academies Press. http://www.nextgenscience.org/get-to-know
Odden, T. O. B., & Russ, R. S. (2019). Defining sensemaking: Bringing clarity to a fragmented theoretical construct. Science Education, 103(1), 187-205. https://doi.org/10.1002/sce.21452
Richards, J., Elby, A., & Gupta, A. (2014). Characterizing a new dimension of change in attending and responding to the substance of student thinking. In J. L. Polman, E. A. Kyza, D. K. O’Neill, I. Tabak, W. R. Penuel, A. S. Jurow, K. O’Connor, T. Lee, & L. D’Amico (Eds.), Proceedings of the 11^th International Conference of the Learning Sciences: Learning and Becoming in Practice (pp. 286-293). International Society of the Learning Sciences.
Robertson, A. D., & Shaffer, P. S. (2016). University student reasoning about the basic tenets of kinetic-molecular theory, Part II: Pressure of an ideal gas. American Journal of Physics, 84(10), 795-809. https://doi.org/10.1119/1.4960215
Russ, R. S., Coffey, J. E., Hammer, D., & Hutchison, P. (2009). Making classroom assessment more accountable to scientific reasoning: A case for attending to mechanistic thinking. Science Education, 93(5), 875-891. https://doi.org/10.1002/sce.20320
Russ, R. S., & Hutchison, P. (2006). It’s okay to be wrong: Recognizing mechanistic reasoning during student inquiry. In S. A. Barab, K. E. Hay, & D. T. Hickey (Eds.), Proceedings of the 7^th International Conference of the Learning Sciences (pp. 641-647). International Society of the Learning Sciences.
Russ, R. S., Scherr, R. E., Hammer, D., & Mikeska, J. (2008). Recognizing mechanistic reasoning in student scientific inquiry: A framework for discourse analysis developed from philosophy of science. Science Education, 92(3), 499-525. https://doi.org/10.1002/sce.20264
Scalco, K. C., Talanquer, V., Kiill, K. B., & Cordeiro, M. R. (2018). Making sense of phenomena from sequential images versus illustrated text. Journal of Chemical Education, 95(3), 347-354. https://doi.org/10.1021/acs.jchemed.7b00716
Scherr, R. E., & Robertson, A. D. (2015). Productivity of “collisions generate heat” for reconciling an energy model with mechanistic reasoning: A case study. Physical Review Special Topics-Physics Education Research, 11(1), 010111. https://doi.org/10.1103/PhysRevSTPER.11.010111
Schwarz, C., Cooper, M., Long, T., Trujillo, C., Noyes, K., de Lima, J., Kesh, J., & Stolzfus, J. (2020). Mechanistic explanations across undergraduate chemistry and biology courses. In M. Gresalfi, & I. S. Horn (Eds.), Proceedings of the 14^th International Conference of the Learning Sciences: Interdisciplinarity of the Learning Sciences (pp. 625-628). International Society of the Learning Sciences.
Schwarz, C. V., Ke, L., Lee, M., & Rosenberg, J. (2014). Developing mechanistic model-based explanations of phenomena: Case studies of two fifth grade students’ epistemologies in practice over time. In J. L. Polman, E. A. Kyza, D. K. O’Neill, I. Tabak, W. R. Penuel, A. S. Jurow, K. O’Connor, T. Lee, & L. D’Amico (Eds.), Proceedings of the 11^th International Conference of the Learning Sciences: Learning and Becoming in Practice (pp. 182-189). International Society of the Learning Sciences.
Schwarz, C. V., Reiser, B. J., Davis, E. A., Kenyon, L., Achér, A., Fortus, D., Shwartz, Y., Hug, B., & Krajcik, J. (2009). Developing a learning progression for scientific modeling: Making scientific modeling accessible and meaningful for learners. Journal of Research in Science Teaching, 46(6), 632-654. https://doi.org/10.1002/tea.20311
Scott, E. E., Anderson, C. W., Mashood, K. K., Matz, R. L., Underwood, S. M., & Sawtelle, V. (2018). Developing an analytical framework to characterize student reasoning about complex processes. CBE—Life Sciences Education, 17(3), ar49. https://doi.org/10.1187/cbe.17-10-0225
Sevian, H., Hugi-Cleary, D., Ngai, C., Wanjiku, F., & Baldoria, J. M. (2018). Comparison of learning in two context-based university chemistry classes. International Journal of Science Education, 40(10), 1239-1262. https://doi.org/10.1080/09500693.2018.1470353
Southard, K., Espindola, M. R., Zaepfel, S. D., & Bolger, M. S. (2017). Generative mechanistic explanation building in undergraduate molecular and cellular biology. International Journal of Science Education, 39(13), 1795-1829. https://doi.org/10.1080/09500693.2017.1353713
Southard, K., Wince, T., Meddleton, S., & Bolger, M. S. (2016). Features of knowledge building in biology: Understanding undergraduate students’ ideas about molecular mechanisms. CBE—Life Sciences Education, 15(1), ar7. https://doi.org/10.1187/cbe.15-05-0114
Speth, E. B., Shaw, N., Momsen, J., Reinagel, A., Le, P., Taqieddin, R., & Long, T. (2014). Introductory biology students’ conceptual models and explanations of the origin of variation. CBE—Life Sciences Education, 13(3), 529-539. https://doi.org/10.1187/cbe.14-02-0020
Stevens, S. Y., Shin, N., & Peek-Brown, D. (2013). Learning progressions as a guide for developing meaningful science learning: A new framework for old ideas. Educación Química [Chemical Education], 24(4), 381-390. https://doi.org/10.1016/S0187-893X(13)72491-1
Suárez, E., & Otero, V. (2014). Leveraging the cultural practices of science for making classroom discourse accessible to emerging bilingual students. In J. L. Polman, E. A. Kyza, D. K. O’Neill, I. Tabak, W. R. Penuel, A. S. Jurow, K. O’Connor, T. Lee, & L. D’Amico (Eds.), Proceedings of the 11^th International Conference of the Learning Sciences: Learning and Becoming in Practice (pp. 800-807). International Society of the Learning Sciences.
Talanquer, V. (2010). Exploring dominant types of explanations built by general chemistry students. International Journal of Science Education, 32(18), 2393-2412. https://doi.org/10.1080/09500690903369662
Talanquer, V. (2018). Exploring mechanistic reasoning in chemistry. In J. Yeo, T. W. Teo, & K.-S. Tang (Eds.), Science education research and practice in Asia-Pacific and beyond (pp. 39-52). Springer. https://doi.org/10.1007/978-981-10-5149-4_3
Tang, X., Elby, A., & Hammer, D. (2020). The tension between pattern-seeking and mechanistic reasoning in explanation construction: A case from Chinese elementary science classroom. Science Education, 104(6), 1071-1099. https://doi.org/10.1002/sce.21594
Tate, E. D., Ibourk, A., McElhaney, K. W., & Feng, M. (2020). Middle school students’ mechanistic explanation about trait expression in rice plants during a technology-enhanced science inquiry investigation. Journal of Science Education and Technology, 29(5), 677-690. https://doi.org/10.1007/s10956-020-09846-4
van Mil, M. H. W., Boerwinkel, D. J., & Waarlo, A. J. (2013). Modelling molecular mechanisms: A framework of scientific reasoning to construct molecular-level explanations for cellular behavior. Science & Education, 22(1), 93-118. https://doi.org/10.1007/s11191-011-9379-7
van Mil, M. H. W., Postma, P. A., Boerwinkel, D. J., Klaassen, K., & Waarlo, A. J. (2016). Molecular mechanistic reasoning: Toward bridging the gap between the molecular and cellular levels in life science education. Science Education, 100(3), 517-585. https://doi.org/10.1002/sce.21215
Watts, F. M., Schmidt-McCormack, J. A., Wilhelm, C. A., Karlin, A., Sattar, A., Thompson, B. C., Gere, A. R., & Shultz, G. V. (2020). What students write about when students write about mechanisms: Analysis of features present in students’ written descriptions of an organic reaction mechanism. Chemistry Education Research and Practice, 21(4), 1148-1172. https://doi.org/10.1039/c9rp00185a
Weinberg, P. J. (2017a). Mathematical description and mechanistic reasoning: A pathway toward STEM integration. Journal of Pre-College Engineering Education Research, 7(1), 90-107. https://doi.org/10.7771/2157-9288.1124
Weinberg, P. J. (2017b). Supporting mechanistic reasoning in domain-specific contexts. Journal of Pre-College Engineering Education Research, 7(2), 27-39. https://doi.org/10.7771/2157-9288.1127
Weinberg, P. J. (2019). Assessing mechanistic reasoning: Supporting systems tracing. Journal of Pre-College Engineering Education Research, 9(1), 30-54. https://doi.org/10.7771/2157-9288.1182
Weinrich, M. L., & Talanquer, V. (2016). Mapping students’ modes of reasoning when thinking about chemical reactions used to make a desired product. Chemistry Education Research and Practice, 17(2), 394-406. https://doi.org/10.1039/c5rp00208g
Wilkerson, M. H., Shareff, R., Laina, V., & Gravel, B. (2018). Epistemic gameplay and discovery in computational model-based inquiry activities. Instructional Science, 46(1), 35-60. https://doi.org/10.1007/s11251-017-9430-4
Wilkerson-Jerde, M. H., Gravel, B. E., & Macrander, C. A. (2015). Exploring shifts in middle school learners’ modeling activity while generating drawings, animations, and computational simulations of molecular diffusion. Journal of Science Education and Technology, 24(2-3), 396-415. https://doi.org/10.1007/s10956-014-9497-5
Windschitl, M., Thompson, J., & Braaten, M. (2008). Beyond the scientific method: Model-based inquiry as a new paradigm of preference for school science investigations. Science Education, 92(5), 941-967. https://doi.org/10.1002/sce.20259
Zotos, E. K., Tyo, J. J., & Shultz, G. V. (2021). University instructors’ knowledge for teaching organic chemistry mechanisms. Chemistry Education Research and Practice, 22(3), 715-732. https://doi.org/10.1039/d0rp00300j

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APA

Bachtiar, R. W., Meulenbroeks, R. F. G., & van Joolingen, W. R. (2022). Mechanistic reasoning in science education: A literature review. Eurasia Journal of Mathematics, Science and Technology Education, 18(11), em2178. https://doi.org/10.29333/ejmste/12512

Vancouver

Bachtiar RW, Meulenbroeks RFG, van Joolingen WR. Mechanistic reasoning in science education: A literature review. EURASIA J Math Sci Tech Ed. 2022;18(11):em2178. https://doi.org/10.29333/ejmste/12512

AMA

Bachtiar RW, Meulenbroeks RFG, van Joolingen WR. Mechanistic reasoning in science education: A literature review. EURASIA J Math Sci Tech Ed. 2022;18(11), em2178. https://doi.org/10.29333/ejmste/12512

Chicago

Bachtiar, Rayendra Wahyu, Ralph F. G. Meulenbroeks, and Wouter R. van Joolingen. "Mechanistic reasoning in science education: A literature review". Eurasia Journal of Mathematics, Science and Technology Education 2022 18 no. 11 (2022): em2178. https://doi.org/10.29333/ejmste/12512

Harvard

Bachtiar, R. W., Meulenbroeks, R. F. G., and van Joolingen, W. R. (2022). Mechanistic reasoning in science education: A literature review. Eurasia Journal of Mathematics, Science and Technology Education, 18(11), em2178. https://doi.org/10.29333/ejmste/12512

MLA

Bachtiar, Rayendra Wahyu et al. "Mechanistic reasoning in science education: A literature review". Eurasia Journal of Mathematics, Science and Technology Education, vol. 18, no. 11, 2022, em2178. https://doi.org/10.29333/ejmste/12512