KJEMI nr. 3 - 2025

29 KJEMI 3 2025 og tydeligere koblinger mellom matematikk og kjemi. Gjennom simuleringer og beregninger kan studenter undersøke fenomener de ellers ikke ville hatt tilgang til, enten fordi eksperimentene er for farlige, for dyre eller for tidkrevende. Vi kan også bruke korte beregningsøvelser som deler av øvrig undervisning, ikke bare som en egen lab. Ved å jobbe med kjemiske eksperimenter på datamaskinen, kan studenter raskt endre parametere og teste hypoteser, og på den måten utvikle en mer eksperimentell og nysgjerrighetsdrevet holdning til kjemi. Ikke minst kan datamaskinen bidra til å koble det abstrakte og det konkrete på en måte som styrker kjemiforståelsen. Ved å integrere beregningskjemi inn i kjemiundervisningen kan vi altså legge til rette for en helhetlig kjemiundervisning som både ivaretar ferdighetstrening, forståelse og forskningsnær tenkning. ● Litteratur (1) C etin, P. S. Effectiveness of Inquiry Based Laboratory Instruction on Developing Secondary Students’ Views on Scientific Inquiry. J. Chem. Educ. 2021, 98 (3), 756–762. https://doi.org/10.1021/acs.jchemed.0c01364. (2) H ofstein, A.; Mamlok-Naaman, R. The Laboratory in Science Education: The State of the Art. Chem. Educ. Res. Pract. 2007, 8 (2), 105–107. https://doi.org/10.1039/B7RP90003A. (3) G ray, C.; Price, C. W.; Lee, C. T.; Dewald, A. H.; Cline, M. A.; McAnany, C. E.; Columbus, L.; Mura, C. Known Structure, Unknown Function: An Inquiry-based Undergraduate Biochemistry Laboratory Course. Biochem Mol Biol Educ 2015, 43 (4), 245–262. https://doi.org/10.1002/ bmb.20873. (4) H osbein, K.; Walker, J. Assessment of Scientific Practice Proficiency and Content Understanding Following an Inquiry-Based Laboratory Course. J. Chem. Educ. 2022, 99 (12), 3833–3841. https://doi.org/10.1021/acs.jchemed.2c00578. (5) Correia, A.-P.; Koehler, N.; Thompson, A.; Phye, G. The Application of PhET Simulation to Teach Gas Behavior on the Submicroscopic Level: Secondary School Students’ Perceptions. Research in Science & Technological Education 2019, 37 (2), 193–217. https://doi.org/10.1080/026351 43.2018.1487834. (6) S pitznagel, B.; Pritchett, P. R.; Messina, T. C.; Goadrich, M.; Rodriguez, J. An Undergraduate Laboratory Activity on Molecular Dynamics Simulations: Undergraduate Lab Activity on MD Simulations. Biochem. Mol. Biol. Educ. 2016, 44 (2), 130–139. https://doi.org/10.1002/ bmb.20939. (7) Salame, I. I.; Samson, D. Examining the Implementation of PhET Simulations into General Chemistry Laboratory. (8) H araldsrud, A.; Odden, T. O. B. Using Feedback Loops from Computational Simulations as Resources for Sensemaking: A Case Study from Physical Chemistry. Chem. Educ. Res. Pract. 2024, 25, 760–774. https://doi.org/10.1039/D4RP00017J. (9) C annady, M. A.; Vincent-Ruz, P.; Chung, J. M.; Schunn, C. D. Scientific Sensemaking Supports Science Content Learning across Disciplines and Instructional Contexts. Contemporary Educational Psychology 2019, 59, 101802. https://doi.org/10.1016/j.cedpsych.2019.101802. (10) Easley, K. Simulations and Sensemaking in Elementary Project-Based Science. Thesis, 2020. http://deepblue.lib.umich.edu/handle/2027.42/155050 (accessed 2023-04-28). (11) H unter, K. H.; Rodriguez, J.-M. G.; Becker, N. M. Making Sense of Sensemaking: Using the Sensemaking Epistemic Game to Investigate Student Discourse during a Collaborative Gas Law Activity. Chem. Educ. Res. Pract. 2021, 22 (2), 328–346. https://doi.org/10.1039/D0RP00290A. (12) Odden, T. O. B.; Russ, R. S. Defining Sensemaking: Bringing Clarity to a Fragmented Theoretical Construct. Sci. Ed. 2019, 103 (1), 187–205. https://doi.org/10.1002/sce.21452. (13) Wu, M.-Y. M.; Yezierski, E. J. Pedagogical Chemistry Sensemaking: A Novel Conceptual Framework to Facilitate Pedagogical Sensemaking in Model-Based Lesson Planning. Chem. Educ. Res. Pract. 2022, 23 (2), 287–299. https://doi.org/10.1039/D1RP00282A. (14) Johnstone, A. H. Why Is Science Difficult to Learn? Things Are Seldom What They Seem. Computer Assisted Learning 1991, 7 (2), 75–83 https://doi.org/10.1111/j.1365-2729.1991.tb00230.x. (15) Ho, F. M.; Elmgren, M.; Rodriguez, J.-M. G.; Bain, K. R.; Towns, M. H. Graphs: Working with Models at the Crossroad between Chemistry and Mathematics. In It’s Just Math: Research on Students’ Understanding of Chemistry and Mathematics; ACS Symposium Series; American Chemical Society, 2019; Vol. 1316, pp 47–67. https://doi.org/10.1021/bk-2019-1316.ch004. (16) Potgieter, M.; Harding, A.; Engelbrecht, J. Transfer of Algebraic and Graphical Thinking between Mathematics and Chemistry. J. Res. Sci. Teach. 2008, 45 (2), 197–218. https://doi.org/10.1002/tea.20208. (17) Rodriguez, J. M. G.; Santos-Diaz, S.; Bain, K.; Towns, M. H. Using Symbolic and Graphical Forms to Analyze Students’ Mathematical Reasoning in Chemical Kinetics. Journal of Chemical Education 2018, 95 (12), 2114–2125. https://doi.org/10.1021/acs.jchemed.8b00584. (18) Becker, N.; Towns, M. Students’ Understanding of Mathematical Expressions in Physical Chemistry Contexts: An Analysis Using Sherin’s Symbolic Forms. Chemistry Education Research and Practice 2012, 13 (3), 209–220. https://doi.org/10.1039/c2rp00003b. (19) Jones, S. R. What Education Research Related to Calculus Derivatives and Integrals Implies for Chemistry Instruction and Learning. In It’s Just Math: Research on Students’ Understanding of Chemistry and Mathematics; ACS Symposium Series; American Chemical Society, 2019; Vol. 1316, pp 187–212. https://doi.org/10.1021/bk-2019-1316.ch012. (20) It’s Just Math: Research on Students’ Understanding of Chemistry and Mathematics; It is just math; Washington, DC: American Chemical Society: Washington, DC, 2019; Vol. 1316. https://doi.org/10.1021/bk-2019-1316. (21) Haraldsrud, A.; Odden, T. O. B. From Integrated Rate Laws to Integrating Rate Laws: Computation as a Conceptual Catalyst. J. Chem. Educ. 2023, acs.jchemed.2c00881. https://doi.org/10.1021/acs.jchemed.2c00881. Figur 4: Numeriske beregninger kan fungere som en brobygger mellom symbolnivået og det konseptuelle kjeminivået.

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