Abstract
Control of Variables Strategy (CVS) is the process of isolating the effect of single variables when conducting scientific inquiry. We assess how CVS can help student achieve different levels of understanding when implemented in different parts of the inquiry process. 148 students worked with minimally-guided inquiry activities using virtual labs on two different physics topics. The virtual labs allowed for exploration, data collection, and graphical analysis. Using student log data, we identified how CVS manifests itself through these phases of students’ inquiry process. We found that students using CVS during data collection and plotting was associated with students achieving more qualitative and quantitative models, respectively. This did not hold, however, for more complicated mathematical relationships, emphasizing the importance of mathematical and graphical interpretation skills when doing CVS.
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References
Bumbacher, E., Salehi, S., Wierzchula, M., Blikstein, P.: Learning environments and inquiry behaviors in science inquiry learning: how their interplay affects the development of conceptual understanding in physics. In: International Educational Data Mining Society, pp. 61–68 (2015)
Chen, Z., Klahr, D.: All other things being equal: acquisition and transfer of the control of variables strategy. Child Dev. 70(5), 1098–1120 (1999)
Cohen, J.: A coefficient of agreeement for nominal scales. Educ. Psychol. Meas. 20(1), 37–46 (1960)
De Jong, T.: Technological advances in inquiry learning. Science 312, 532–533 (2006)
De Jong, T., Van Joolingen, W.R.: Scientific discovery learning with computer simulations of conceptual domains. Rev. Educ. Res. 68(2), 179–201 (1998)
Gobert, J.D.: Microworlds. In: Gunstone, R. (ed.) Encyclopedia of Science Education, p. 638. Springer, Dordrecht (2021)
McHugh, M.L.: Interrater reliability: the kappa statistic. Biochem. Med. 22, 276–282 (2012)
Pedaste, M., Mäeots, M., Siiman, L.A., De Jong, T., van Riesen, S.A.N., Kamp, E.T., Manoli, C.C., Zacharia, Z.C., Tsourlidaki, E.: Phases of inquiry-based learning: definitions and the inquiry cycle. Educ. Res. Rev. 14, 47–61 (2015)
Perez, S., Massey-Allard, J., Butler, D., Ives, J., Bonn, D., Yee, N., Roll, I.: Identifying productive inquiry in virtual labs using sequence mining. In: André, E., Baker, R., Hu, X., Rodrigo, M.M.T., du Boulay, B. (eds.) AIED 2017. LNCS (LNAI), vol. 10331, pp. 287–298. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-61425-0_24
Roll, I., Butler, D., Yee, N., Welsh, A., Perez, S., Briseno, A., Perkins, K., Bonn, D.: Understanding the impact of guiding inquiry: the relationship between directive support, student attributes, and transfer of knowledge, attitudes, and behaviours in inquiry learning. Instr. Sci. 46, 1–28 (2017)
Sao Pedro, M.A., Gobert, J.D., Raziuddin, J.J.: Comparing pedagogical approaches for the acquisition and long-term robustness of the control of variables strategy. J. Learn. Sci., 1024–1031 (2010)
Schwichow, M., Croker, S., Zimmerman, C., Höffler, T., Härtig, H.: Teaching the control-of-variables strategy: a meta-analysis. Dev. Rev. 39, 37–63 (2016)
Wieman, C.E., Adams, W.K., Perkins, K.K.: PhET: simulations that enhance learning. Science 322, 682–683 (2008)
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Perez, S. et al. (2018). Control of Variables Strategy Across Phases of Inquiry in Virtual Labs. In: Penstein Rosé, C., et al. Artificial Intelligence in Education. AIED 2018. Lecture Notes in Computer Science(), vol 10948. Springer, Cham. https://doi.org/10.1007/978-3-319-93846-2_50
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DOI: https://doi.org/10.1007/978-3-319-93846-2_50
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