Modeling the control of variables in proportionality problems through finite automata: Two case studies

Modelado del control de variables en problemas de proporcionalidad a través de autómatas finitos: dos casos de estudio

Main Article Content

Dr. Rocío Abello Correa
Dr. Hugo Escobar Melo
Jorge Castaño Garcia
Dr. Cesar Julio Bustacara-Medina
Abstract

This paper presents the process of modeling how problem-solvers of different ages and educational levels control variables while solving a problem of proportionality in a situation of constant linear motion; the modelling is done with the Finite Deterministic Automata (FDA) technique. The cognitive ability of controlling variables is vital to the development of scientific reasoning, a necessary condition of modern education. The study aims to characterize and explain cognitive change when solving proportionality tasks delivered via an interactive software. To show the potential of the FDA technique, three cases are analyzed here along with the evidence of intersubjective variation in 130 problem-solvers, in terms of the frequency of transition toward different forms of variable controlling.

Downloads

Download data is not yet available.

Article Details

Author Biography / See

Dr. Rocío Abello Correa, Pontificia Universidad Javeriana

Artículo producto de la investigación, “Variación de los procedimientos y de las formas de representación que permiten explicar el cambio como novedad cognitiva en la solución de tareas, equivalentes y de diferente contenido, que involucran relaciones de proporcionalidad simple en resolutores de la educación básica y media.” Proyecto de investigación con financiación interna (ID
PPTA 00007250, ID PRY 000000000007423). Financiada por la Vicerrectoría de Investigación, Pontificia Universidad Javeriana – Bogotá, D.C., Colombia. La investigación pertenece a la línea de investigación de Desarrollo y procesos cognitivos en contextos del Grupo de Investigación Desarrollo, Afectividad y Cognición.

References

Aho, A. V, Hopcroft, J. E., & Ullman, J. D. (1988). Estructura de datos y algoritmos. Addison-Wesley.

Alvarado Carrillo, S. (2011). El razonamiento proporcional en la educación primaria: un estudio con alumnos de 6 grado en una escuela pública del distrito federal. Universidad Pedagogica Nacional.

Bullock, M., & Ziegler, A. (1999). Scientific reasoning: Developmental and individual differences. In Individual development from 3 to 12: Findings from the Munich Longitudinal Study (pp. 38–54). Cambridge University Press.

Chen, Z., & Klahr, D. (1999). All Other Things Being Equal : Acquisition and Transfer of the Control of Variables Strategy. Child Development, 70(5), 1098–1120. DOI: https://doi.org/10.1111/1467-8624.00081

Corona Cruz, A., Sanchez Campos, M., González, E., & Slisko, J. (2012). Habilidades cognitivas y la resolución de un problema de cinemática: Un estudio comparativo entre los estudiantes de secundaria, bachillerato y universidad. Latin-American Journal of Physics Education, 6(2), 292–299. http://www.lajpe.org/june12/LAJPE_665_Adrian_Corona.pdf

Croker, S., & Buchanan, H. (2011). Scientific reasoning in a real-world context: The effect of prior belief and outcome on children’s hypothesis-testing strategies. British Journal of Developmental Psychology, 29(3), 409–424. https://doi.org/10.1348/026151010X496906 DOI: https://doi.org/10.1348/026151010X496906

Delgado Reyes, G., Martinez Valdez, J., & Guevara López, P. (2011). Autómatas finitos : su aplicación para describir la trayectoria de un vehículo evasor de obstáculos. Revista de Divulgacion Cientifica y Tecnologica, 16(60), 30–40.

Dengel, A., Buchner, J., Mulders, M., & Pirker, J. (2021). Beyond the horizon: Integrating immersive learning environments in the everyday classroom. Proceedings of 2021 7th International Conference of the Immersive Learning Research Network, ILRN 2021. https://doi.org/10.23919/iLRN52045.2021.9459368 DOI: https://doi.org/10.23919/iLRN52045.2021.9459368

Eichmann, B., Goldhammer, F., Greiff, S., Brandhuber, L., & Naumann, J. (2020). Using process data to explain group differences in complex problem solving. Journal of Educational Psychology, 112(8), 1546–1562. https://doi.org/10.1037/edu0000446 DOI: https://doi.org/10.1037/edu0000446

Escobar Melo, H. A., Abello Correa, R., & Castaño García, J. (2016). Trayectorias de control y covariación de variables como expresión del cambio cognitivo en la solución de un problema. Universitas Psychologica, 15(1), 281–302. https://doi.org/10.11144/Javeriana.upsy15-1.tccv DOI: https://doi.org/10.11144/Javeriana.upsy15-1.tccv

Fischer, A., Greiff, S., & Funke, J. (2017). The history of complex problem solving. In The Nature of Problem Solving: Using Research to Inspire 21st Century Learning (Issue May, pp. 107–121). OECD Publishing. https://doi.org/10.1787/9789264273955-9-en DOI: https://doi.org/10.1787/9789264273955-9-en

Hopcroft, J. E., & Ullman, J. D. (1969). Formal Languages and their Relation to Automata. Addison-Wesley.

Hopcroft, J., Motwani, R., & Ullman, J. (2008). Introducción a la teoría de autómatas, lenguajes y computación (3rd ed.). Pearson Prentice-Hall.

Klahr, D., Chen, Z., & Toth, E. (2001). From Cognition to Instruction to Cognition: A Case Study in Elementary School Science Instruction. In Designing for Science : Implications From Everyday, Classroom, and Professional Settings (pp. 209–250). Lawrence Erlbaum Associates, Inc.

Klahr, D., & Nigam, M. (2004). The equivalence of learning paths in early science instruction: Effects of direct instruction and discovery learning. Psychological Science, 15(10), 661–667. https://doi.org/10.1111/j.0956-7976.2004.00737.x DOI: https://doi.org/10.1111/j.0956-7976.2004.00737.x

Kuhn, D., Iordanou, K., Pease, M., & Wirkala, C. (2008). Beyond control of variables: What needs to develop to achieve skilled scientific thinking? Cognitive Development, 23(4), 435–451. https://doi.org/10.1016/j.cogdev.2008.09.006 DOI: https://doi.org/10.1016/j.cogdev.2008.09.006

Mochón Cohen, S. (2012). Enseñanza del razonamiento proporcional y alternativas para el manejo de la regla de tres. Educación Matemática, 24(1), 133–157. DOI: https://doi.org/10.24844/EM2401.05

Neubert, J. C., Kretzschmar, A., Wüstenberg, S., & Greiff, S. (2014). Extending the Assessment of Complex Problem Solving to Finite State Automata. European Journal of Psychological Assessment, 31(3), 181–194. https://doi.org/10.1027/1015-?‐5759/a000224 DOI: https://doi.org/10.1027/1015-5759/a000224

Osterhaus, C., Koerber, S., & Sodian, B. (2016). Scientific thinking in elementary school: Children’s social cognition and their epistemological understanding promote experimentation skills. Developmental Psychology, 53(3), 450–462. https://doi.org/10.1037/dev0000260 DOI: https://doi.org/10.1037/dev0000260

Piekny, J., & Maehler, C. (2013). Scientific reasoning in early and middle childhood: The development of domain-general evidence evaluation, experimentation, and hypothesis generation skills. British Journal of Developmental Psychology, 31(2), 153–179. https://doi.org/10.1111/j.2044-835X.2012.02082.x DOI: https://doi.org/10.1111/j.2044-835X.2012.02082.x

Puzzella, A., Pandiella, S., Díaz, L., Nappa, N., Alborch, A., & Pandiella, P. (2012). El “Saber Hacer” como Contenido de Aprendizaje. Estudio Exploratorio en una Escuela Secundaria. Revista Electrónica Iberoamericana de Educación En Ciencias y Tecnología, 3(2), 11–31.

Ruiz-Estrada, H., Fuchs-Gómez, O. L., & Raggi Cárdenas, G. (2006). El desarrollo del pensamiento científico de los ingresantes a las licenciaturas de la FCFM-BUAP y su adaptación a los estudios. III Encuentro Participación de La Mujer En La Ciencia.

Schoppek, W., & Fischer, A. (2015). Complex problem solving-single ability or complex phenomenon? Frontiers in Psychology, 6(1), 1–4. https://doi.org/10.3389/fpsyg.2015.01669 DOI: https://doi.org/10.3389/fpsyg.2015.01669

Schwichow, M., Croker, S., Zimmerman, C., Höffler, T., & Härtig, H. (2016). Teaching the control-of-variables strategy: A meta-analysis. Developmental Review, 39, 37–63. https://doi.org/10.1016/j.dr.2015.12.001 DOI: https://doi.org/10.1016/j.dr.2015.12.001

Sodian, B., Zaitchik, D., & Carey, S. (1991). Young Children’s Differentiation of Hypothetical Beliefs from Evidence. Child Development, 62(4), 753–766. https://doi.org/10.1111/j.1467-8624.1991.tb01567.x DOI: https://doi.org/10.1111/j.1467-8624.1991.tb01567.x

Stadler, M., Fischer, F., & Greiff, S. (2019). Taking a closer look: An exploratory analysis of successful and unsuccessful strategy use in complex problems. Frontiers in Psychology, 10(MAY), 1–10. https://doi.org/10.3389/fpsyg.2019.00777 DOI: https://doi.org/10.3389/fpsyg.2019.00777

Tschirgi, J. E. (1980). Sensible Reasoning : A Hypothesis about Hypotheses. Child Development, 51(1), 1–10. DOI: https://doi.org/10.1111/j.1467-8624.1980.tb02502.x

Uribe, C., Quintero, M., & Rodriguez, A. M. (2005). Intervención en el desarrollo cognitivo mediante las ciencias naturales: comparación de dos casos. Enseñanza de Las Ciencias, Perkins 1992, 1–5.

Vanegas, C., Jiménez, L. S., & Puertas, F. A. (2018). Un estudio exploratorio de la covariación proporcional directa a partir de situaciones problema en estudiantes de grado quinto del colegio La Palestina I.E.D. Pontificia Universidad Javeriana.

Wüstenberg, S., Greiff, S., & Funke, J. (2012). Complex problem solving - More than reasoning? Intelligence, 40(1), 1–14. https://doi.org/10.1016/j.intell.2011.11.003 DOI: https://doi.org/10.1016/j.intell.2011.11.003

Citaciones