Propuesta metodológica para la caracterización del Razonamiento Inductivo en la Primera Infancia desde el enfoque de la Educación STEM
ilustraciones, fotografías a color
- Autores:
-
Hernández Urrego, Isabel Astrid
- Tipo de recurso:
- Doctoral thesis
- Fecha de publicación:
- 2023
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/83552
- Palabra clave:
- 100 - Filosofía y Psicología::107 - Educación, investigación, temas relacionados
150 - Psicología::155 - Psicología diferencial y del desarrollo
370 - Educación::371 - Escuelas y actividades; educación especial
Cognición en niños
Percepción en niños
Cognition in children
Perception in children
Razonamiento inductivo eficaz
Habilidad inferencial temprana
Desarrollo conceptual
Coonceptual development
Socialización de la cognición
Socialization of cognition
Effective inductive Reasoning
Early inferential ability
- Rights
- openAccess
- License
- Atribución-NoComercial-SinDerivadas 4.0 Internacional
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Propuesta metodológica para la caracterización del Razonamiento Inductivo en la Primera Infancia desde el enfoque de la Educación STEM |
| dc.title.translated.none.fl_str_mv |
Methodological proposal for the characterization of Inductive Reasoning in Early Childhood from the STEM Education approach |
| title |
Propuesta metodológica para la caracterización del Razonamiento Inductivo en la Primera Infancia desde el enfoque de la Educación STEM |
| spellingShingle |
Propuesta metodológica para la caracterización del Razonamiento Inductivo en la Primera Infancia desde el enfoque de la Educación STEM 100 - Filosofía y Psicología::107 - Educación, investigación, temas relacionados 150 - Psicología::155 - Psicología diferencial y del desarrollo 370 - Educación::371 - Escuelas y actividades; educación especial Cognición en niños Percepción en niños Cognition in children Perception in children Razonamiento inductivo eficaz Habilidad inferencial temprana Desarrollo conceptual Coonceptual development Socialización de la cognición Socialization of cognition Effective inductive Reasoning Early inferential ability |
| title_short |
Propuesta metodológica para la caracterización del Razonamiento Inductivo en la Primera Infancia desde el enfoque de la Educación STEM |
| title_full |
Propuesta metodológica para la caracterización del Razonamiento Inductivo en la Primera Infancia desde el enfoque de la Educación STEM |
| title_fullStr |
Propuesta metodológica para la caracterización del Razonamiento Inductivo en la Primera Infancia desde el enfoque de la Educación STEM |
| title_full_unstemmed |
Propuesta metodológica para la caracterización del Razonamiento Inductivo en la Primera Infancia desde el enfoque de la Educación STEM |
| title_sort |
Propuesta metodológica para la caracterización del Razonamiento Inductivo en la Primera Infancia desde el enfoque de la Educación STEM |
| dc.creator.fl_str_mv |
Hernández Urrego, Isabel Astrid |
| dc.contributor.advisor.none.fl_str_mv |
Taborda Osorio, Hernando González García, Luz Mery |
| dc.contributor.author.none.fl_str_mv |
Hernández Urrego, Isabel Astrid |
| dc.contributor.orcid.spa.fl_str_mv |
Hernández Urrego Isabel Astrid [0000-0002-8018-1897] |
| dc.subject.ddc.spa.fl_str_mv |
100 - Filosofía y Psicología::107 - Educación, investigación, temas relacionados 150 - Psicología::155 - Psicología diferencial y del desarrollo 370 - Educación::371 - Escuelas y actividades; educación especial |
| topic |
100 - Filosofía y Psicología::107 - Educación, investigación, temas relacionados 150 - Psicología::155 - Psicología diferencial y del desarrollo 370 - Educación::371 - Escuelas y actividades; educación especial Cognición en niños Percepción en niños Cognition in children Perception in children Razonamiento inductivo eficaz Habilidad inferencial temprana Desarrollo conceptual Coonceptual development Socialización de la cognición Socialization of cognition Effective inductive Reasoning Early inferential ability |
| dc.subject.lemb.spa.fl_str_mv |
Cognición en niños Percepción en niños |
| dc.subject.lemb.eng.fl_str_mv |
Cognition in children Perception in children |
| dc.subject.proposal.spa.fl_str_mv |
Razonamiento inductivo eficaz Habilidad inferencial temprana Desarrollo conceptual Coonceptual development Socialización de la cognición Socialization of cognition |
| dc.subject.proposal.eng.fl_str_mv |
Effective inductive Reasoning Early inferential ability |
| description |
ilustraciones, fotografías a color |
| publishDate |
2023 |
| dc.date.accessioned.none.fl_str_mv |
2023-02-23T20:57:16Z |
| dc.date.available.none.fl_str_mv |
2023-02-23T20:57:16Z |
| dc.date.issued.none.fl_str_mv |
2023-01-26 |
| dc.type.spa.fl_str_mv |
Trabajo de grado - Doctorado |
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info:eu-repo/semantics/doctoralThesis |
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info:eu-repo/semantics/acceptedVersion |
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http://purl.org/coar/resource_type/c_db06 |
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Text |
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http://purl.org/redcol/resource_type/TD |
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http://purl.org/coar/resource_type/c_db06 |
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acceptedVersion |
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https://repositorio.unal.edu.co/handle/unal/83552 |
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Universidad Nacional de Colombia |
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Repositorio Institucional Universidad Nacional de Colombia |
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https://repositorio.unal.edu.co/ |
| url |
https://repositorio.unal.edu.co/handle/unal/83552 https://repositorio.unal.edu.co/ |
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Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia |
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spa |
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Aguiar, N. R., Stoess, C. J., y Taylor, M. (2012). The development of children’s ability to fill the gaps in their knowledge by consulting experts. Child Development, 83, 1368- 1381. https://doi.org/10.1111/j.1467-8624.2012.01782.x Ahl, R. y Keil, F. (2017). Diverse Effects, Complex Causes: Children Use Information About Machines' Functional Diversity to Infer Internal Complexity. Child Development, 88 (3), 828-845. https://doi.org/10.1111/cdev.12613 Anderson, R., y Branstetter, S. (2012). Adolescents, parents, and monitoring: A review of constructs with attention to process and theory. Journal of Family Theory y Review, 4, 1-19. https://doi. org/10.1111/j.1756-2589.2011.00112.x American Educational Research Association, American Psychological Association y National Council on Measurement in Education (2014). Standards for Educational and Psychological Testing. Washington, United States: Author. Avila, C. y Barragan, G. (2018). Artículo de Experiencia en el Aula: Educación STEM una ruta hacia la innovación. Revista electrónica TicALS, 4, 146 - 162 www.als.edu.co/revistaticals Barkl, S., Porter, A., y Ginns, P. (2012). Cognitive training for children: Effects on inductive reasoning, deductive reasoning, and mathematics achievement in an Australian school setting. Psychology In The Schools, 49(9), 828-842. https://doi.org/10.1002/pits.21638 Baillargeon, R., Scott, R. M., y Bian, L. (2016). Psychological reasoning in infancy. Annual Review of Psychology, 67. doi.org/10.1146/annurev-psych-010213-115033pabli Barbey, A. K., y Sloman, S. A. (2007). Base-rate respect: From ecological rationality to dual processes. Behavioral and Brain Sciences, 30, 3, 241-254. https://doi.org/10.1017/S0140525X07001653 Bascandziev, I., y Harris, P.L. (2016). The beautiful and the accurate: Are children’s selective trust decisions biased?. Journal of Experimental Child Psychology, Vol. 152, 92-105, doi.org/10.1016/j.jecp.2016.06.017 Batanero, C., y Chernoff, E. J. (2018). Teaching and Learning Stochastics: Advances in Probability Education Research. https://doi.org/10.1007/978-3-319-72871-1 Batanero, C., Chernoff, E. J., Engel, J., Lee, H. S., y Sánchez, E. (2016). Research on Teaching and Learning Probability. Cham: Springer International Publishing. Bogdan Toma, R. y Meneses Villagrá, J. Á. (2019). Preferencia por contenidos científicos de física o de biología en Educación Primaria: un análisis clúster. Revista Eureka Sobre Enseñanza y Divulgación de Las Ciencias, 16(1),1, http://unal.edu.co/10.25267/Rev_Eureka_ensen_divulg_cienc.2019.v16.i1.1104 Bolt, D. (2007). The Present and Future of IRT-Based Cognitive Diagnostic Models (ICDMs) and Related Methods. Journal Of Educational Measurement, (4). 377. Bonawitz, E. B., y Lombrozo, T. (2012). Occam's rattle: Children's use of simplicity and probability to constrain inference. Developmental Psychology, 48, 4, 1156-1164. https://doi.org/10.1037/a0026471 Bonawitz, E., Ullman, T. D., Bridgers, S., Gopnik, A., y Tenenbaum, J. B. (2019). Sticking to the Evidence? A Behavioral and Computational Case Study of Micro‐Theory Change in the Domain of Magnetism. Cognitive Science, 43(8). https://doi.org/10.1111/cogs.12765 Bonett, D.G., Wright, T.A. Sample size requirements for estimating pearson, kendall and spearman correlations. Psychometrika 65, 23–28 (2000). https://doi.org/10.1007/BF02294183 Bonnefon J-F y Billaut E. (2016). Individual Differences in Reasoning beyond Ability and Disposition Cap. 11 En Macchi, Laura, Bagassi, Maria y Viale, Riccardo. Cognitive unconscious and human rationality. Toppan Best-set Premedia Limited. United States of America. Massachusetts Institute of Technology Bouwmeester, S., y Sijtsma, K. (2004). Measuring the ability of transitive reasoning, using product and strategy information. Psychometrika, 69(1), 123. https://doi.org/10.1007/BF02295843 Borovcnik M., Kapadia R. (2018) Reasoning with Risk: Teaching Probability and Risk as Twin Concepts. En: Batanero C., Chernoff E. (eds) Teaching and Learning Stochastics. ICME-13 Monographs. Springer, Cham. Badger, J. R., y Shapiro, L. R. (2012). Evidence of a transition from perceptual to category induction in 3- to 9-year-old children. Journal of Experimental Child Psychology, 113(1), 131–146. https://doi.org/10.1016/j.jecp.2012.03.004 Brandone, A. C. (2017). Changes in Beliefs About Category Homogeneity and Variability Across Childhood. Child Development, 88(3), 846-866. https://doi.org/10.1111/cdev.12616 Bramley, N., Gerstenberg, T., Tenenbaum, J. y Gureckis, T. (2018). Intuitive experimentation in the physical world. Cognitive. Psychology, 105, 9-38. https://doi.org/10.1016/j.cogpsych.2018.05.001 Brenneman, K., y Louro, I. F. (2008). Science Journals in the Preschool Classroom. Early Childhood Education Journal, 36(2), 113–119. https://doi.org/10.1007/s10643-008-0258-z Bryant, P. y Nunes, T. (2012). Children’s understanding of probability: A literature review. London, England: Nuffield Foundation.how Bulloch, M. J. y Opfer, J. E. (2009). What makes relational reasoning smart? Revisiting the perceptual-to-relational shift in the development of generalization. Developmental Science, 12, 1, 114-122. https://doi.org/10.1111/j.1467-7687.2008.00738.x Bumeltshammer, K.S., y Kirkham, N.Z. (2013). Learning to look: probabilistic variation and noise guide infants’ eye movements. Developmental Science, 16, 760–771. https://doi.org/10.1111/desc.12064 Burris, V. (1982). The Child’s Conception of Economic Relations; A Study of Cognitive Socialization. Sociological Focus, 15(4), 307–325. https://doi.org/10.1080/00380237.1982.10570424 Butler, L. P., y Markman, E. M. (2012). Preschoolers Use Intentional and Pedagogical Cues to Guide Inductive Inferences and Exploration. Child Development, 83(4), 1416-1428. https://doi.org/10.1111/j.1467-8624.2012.01775.x Cánavos, G. C. (1999). Probabilidad y Estadística: Aplicaciones y Métodos. México: McGraw-Hill. Carey, S. (2009). The Origin of Concepts. Oxford Series in Cognitive Development. Clark, E. V. (2004). How language acquisition builds on cognitive development. Trends in Cognitive Sciences, 8(10), 472–478. https://doi.org/10.1016/j.tics.2004.08.012 Cerchiaro-Ceballos, E., y Puche-Navarro, R. (2018). Funcionamientos inferenciales en niños caminadores: un acercamiento al microdesarrollo en una tarea de resolución de problemas. Revista Colombiana de Psicología, 27, 117-135. https://doi.org/10.15446/rcp.v27n2.66054 Csapo, B. (1997). The Development of Inductive Reasoning: Cross-sectional Assessments in an Educational Context. International journal of behavioral development, (4). 609. https://journals.sagepub.com/doi/10.1080/016502597385081 Cosmides L, Tooby J. (2013). Evolutionary psychology: New perspectives on cognition and motivation. Annu. Rev. Psychol. 64:201-29. DOI: 10.1146/annurev.psych.121208.131628 Colberg, M., Nester, M. A., y Cormier, S. M. (1982). Inductive reasoning in psychometrics: A philosophical corrective. Intelligence, 6139-164. https://doi.org/10.1016/0160-2896(82)90011-3 Colberg, M., Nester, M., y Trattner, M. (1985). Convergence of the Inductive and Deductive Models in the Measurement of Reasoning Abilities. Journal Of Applied Psychology, 70(4), 681-694. https://doi.org/10.1037/0021-9010.70.4.681 Corral, Y. (2009). Validez y confiabilidad de los instrumentos de investigación para la recolección de datos. Revista Ciencias de la Educación, 19(33), 228-247.https://bit.ly/1T1z0ct Culbertson M. (2016). Bayesian Networks in Educational Assessment: The State of the Field. Applied Psychological Measurement, 40(1) 3–21 https://doi.org/ 10.1177/0146621615590401 Cummins D. (2004). The Evolution of Reasoning. En Leighton, J.P. y Sternberg R. J. (Ed.).(2004). The nature of reasoning. Cambridge University Press. Damon, W. (1990). Social Relations and Childrens Thinking Skills. Contributions to Human Development. En Kuhn D (ed). Developmental Perspectives on Teaching and Learning Thinking Skills, pp 95–107. https://doi.org/10.1159/000418983 Darling, N., y Steinberg, L. (1993). Parenting style as context: An integrative model. Psychological Bulletin, 113(3), 487–496. https://doi.org/10.1037/0033-2909.113.3.487 Dasgupta, I., Schulz, N., Goodman, D. y Gershman, S. (2018). Remembrance of inferences past: Amortization in human hypothesis generation, Cognition, 178, 67-81. https://doi.org/10.1016/j.cognition.2018.04.017 De Koning, E., Sijtsma, K., y Hamers, J. M. (2003). Construction and Validation of a Test for Inductive Reasoning. European Journal Of Psychological Assessment, (1). 24. https://doi.org/10.1027//1015-5759.19.1.24 De Koning, E., Sijtsma, K., y Hamers, J. M. (2003). Construction and Validation of a Test for Inductive Reasoning. European Journal Of Psychological Assessment, (1). 24. https://doi.org/10.1027//1015-5759.19.1.24 Denison, S. y Xu, F. (2012). Probabilistic Inference in Human Infants. En T. Kushnir, y F. Xu (Eds.), Advances in child development and behavior: Rational constructivism in cognitive development. Academic Press, Elsevier. doi.org/10.1016/B978-0-12-397919-3.00002-2 Dean Jr., D., y Kuhn, D. (2007). Direct instruction vs. discovery: The long view. Science Education, 91(3), 384–397. https://doi.org/10.1002/sce.20194 Dienes, Z., y Perner, J. (1999) A theory of implicit and explicit knowledge. Behavioural and Brain Sciences, 22,735-755. DOI: 10.1017/s0140525x99002186 Denison, S., y Xu, F. (2014). The origins of probabilistic inference in human infants. Cognition, 130, 335–347. https://doi.org/ 10.1016/j.cognition.2013.12.001 Duque Aristizábal, C. P., Aristizábal, C. P. D., Márquez, Á. V. V., y Gutiérrez, A. P. H. (2010). Comprensión inferencial de textos narrativos en primeros lectores: una revisión de la literatura. Ocnos: Revista De Estudios Sobre Lectura, (6), 35. https://doi.org/10.18239/OCNOS_2010.06.03 Ebersbach, M., y Resing, W. M. (2008). Implicit and Explicit Knowledge of Linear and Exponential Growth in 5- and 9-Year-Olds. Journal Of Cognition y Development, 9(3), 286-309. https://doi.org/10.1080/15248370802247962 Einav, S. y Robinson E. J. (2010). Children’s sensitivity to error magnitude when evaluating informants. Cognitive Development 25, 218–232, https://doi.org/10.1016/j.cogdev.2010.04.002 Eichler, A., y Vogel, M. (2012). Basic modelling of uncertainty: Young students’ mental models. ZDM Mathematics Education, 44(7), 841–854. https://doi.org/10.1007/s11858-012-0451-9 Elosua Oliden, P. y Zumbo, B.D. (2008). Coeficientes de fiabilidad para escalas de respuesta categórica ordenada. Psicothema, 20(4), 896-901 http://www.redalyc.org/articulo.oa?id=72720458 Epstein, N., y Fischer, M. R. (2017). Academic career intentions in the life sciences: Can research self-efficacy beliefs explain low numbers of aspiring physician and female scientists?. PLOS ONE, 12(9), e0184543. https://doi.org/10.1371/journal.pone.0184543 Erickson, J. E., Keil, F. C., y Lockhart, K. L. (2010). Sensing the Coherence of Biology in Contrast to Psychology: Young Children’s Use of Causal Relations to Distinguish Two Foundational Domains. Child Development, 81(1), 390-409. https://doi.org/10.1111/j.1467-8624.2009.01402.x Evans, J. St. B. T. (2020). Hypothetical thinking: Dual processes in reasoning and judgment. Psychology Press and Routledge Classic Editions. Evans, J. St. B. T., y Over, D. E. (2013). Reasoning to and from belief: Deduction and induction are still distinct. Thinking & Reasoning, 19 (3), 267-283. https://cogentoa.tandfonline.com/doi/full/10.1080/13546783.2012.745450 Ferrar, S. J., Stack, D. M., Dickson, D. J., Serbin, L. A., Ledingham, J., y Schwartzman, A. E. (2019). Maternal Socialization Responses to Preschoolers’ Success and Struggle: Links to Contextual Factors and Academic and Cognitive Outcomes. Journal of Research in Childhood Education, 1–19. https://doi.org/10.1080/02568543.2019.1607787 Fiorini, M., y Keane, M. P. (2014). How the Allocation of Children’s Time Affects Cognitive and Noncognitive Development. Journal of Labor Economics, 32(4), 787–836. https://doi.org/10.1086/677232 Fisher, A. V., Godwin, K. E., Matlen, B. J. y Unger, L. (2015). Development of category-based induction and semantic knowledge. Child Development, 86(1), 48-62. https://doi.org/10.1111/cdev.12277 Fischer, F., Kollar, I., Ufer, S., Sodian, B., Hussmann, H., Pekrun, R., ... Eberle, J. (2014). Scientific reasoning and argumentation: Advancing an interdisciplinary research agenda in education. Frontline Learning Research, 5, 28–45. http://dx.doi.org/10.14786/flr.v2i3.96 Fischbein, E. (1975). The intuitive sources of probabilistic thinking in children. Dordrecht; Reidel Publishing Company. Fizke, E., Butterfill, S., Van de Loo, L., Reindl, E., y Rakoczy, H. (2017). Are there signature limits in early theory of mind?. Journal Of Experimental Child Psychology, 209. https://doi.org/10.1016/j.jecp.2017.05.005 Foster-Hanson E, Moty K, Cardarelli A, Ocampo JD, y Rhodes M. (2020). Developmental Changes in Strategies for Gathering Evidence About Biological Kinds. Cogn Sci. 2020 May; 44 (5). https://doi.org/ 10.1111/cogs.12837. Frost, R., Armstrong, B. C., y Christiansen, M. H. (2019). Statistical learning research: A critical review and possible new directions. Psychological Bulletin, 145(12), 1128–1153. doi.org/10.1037/bul0000210 Gandhi H. (2018). Understanding Children’s Meanings of Randomness in Relation to Random Generators. En: Batanero, C., y Chernoff, E. J. (Eds.). (2018). Teaching and Learning Stochastics: Advances in Probability Education Research. doi.org/10.1007/978-3-319-72871-1 Gelman, S. A. (1988). The development of induction within natural kind and artifact categories. Cognitive Psychology, 20, 65–96. https://doi.org/10.1016/0010-0285(88)90025-4 Gelman, S. A. (2003). The essential child: Origins of essentialism in everyday life. New York, NY: Oxford University Press. Gelman, R., y Brenneman, K. (2012). Moving young “scientists-in-waiting” onto science learning pathways: Focus on observation. In J. Shrager y S. Carver (Eds.), The journey from child to scientist: Integrating cognitive development and the education sciences. 155–169. American Psychological Association. https://doi.org/10.1037/13617-008 Gelman, S. A., y Davidson, N. S. (2013). Conceptual influences on category-based induction. Cognitive Psychology, (3), 327. https://doi.org/10.1016/j.cogpsych.2013.02.001 Gelman, S. A., Leslie, S.-J., Was, A. M., y Koch, C. M. (2015). Children’s interpretations of general quantifiers, specific quantifiers and generics. Language, Cognition, and Neuroscience, 30, 448–461. https://doi.org/10.1080/23273798.2014.931591 Gennari , S., Sloman S., Malt , B. , y Fitch, W. ( 2002 ). Motion events in language and cognition. Cognition, 83 ( 1 ), 49 – 79. DOI:10.1016/S0010-0277(01)00166-4 Gigerenzer, G. (2015). Calculated risks: How to know when numbers deceive you. New York: Simon y Schuster Audio Gil Chaves, L., y Flórez Romero, R. (2013). Desarrollo de habilidades de pensamiento inferencial y comprensión de lectura en niños de tres a seis años. Panorama, 5(9). https://doi.org/10.15765/pnrm.v5i9.39 Girotto, V., y Gonzalez, M. (2007). How to elicit sound probabilistic reasoning: Beyond word problems. Behavioral and Brain Sciences, 30, 3, 268. doi 10.1017_S0140525X07001768 Gómez, R. L. (2017). Do infants retain the statistics of a statistical learning experience? Insights from a developmental cognitive neuroscience perspective. Phil. Trans. R. Soc. B, 372 (1711). doi.org/10.1098/rstb.2016.0054. Gopnik, A. (2011). The Theory of Theory 2.0: Probabilistic Models and Cognitive Development. Child Development Perspectives. 5, 3, 161-163, HTTPS://DOI.ORG/ 10.1111/j.1750-8606.2011.00179.xs Gopnik, A. (2012). Scientific Thinking in Young Children: Theoretical Advances, Empirical Research, and Policy Implications. Science, Sep. 28;337(6102): 1623-7. https://doi.org/10.1126/science.1223416 Gopnik, A., y Tenenbaum, J. B. (2007). Bayesian networks, Bayesian learning and cognitive development. Developmental Science, 10(3), 281–287. https://doi.org/10.1111/j.1467-7687.2007.00584.x Gopnik, A., Sobel, D.M., Schulz L.E., Glymour C. (2001). Causal Learning Mechanisms in Very Young Children: Two-, Three-, and Four-Year-Olds Infer Causal Relations From Patterns of Variation and Covariation Developmental Psychology . 37, (5), 620-629. https://doi.org/ 10.1037//0012-1649.37.5.620 Gopnik, A., Glymour, C., Sobel, D. M., Schulz, L. E., Kushnir, T., y Danks, D. (2004). A Theory of Causal Learning in Children: Causal Maps and Bayes Nets. Psychological Review, 111(1), 3–32. https://doi.org/10.1037/0033-295x.111.1.3 Goswami, U. (ed.). (2003). Wiley-Blackwell handbook of childhood cognitive development. New York: Wiley Goswami, U. (Ed.). (2010). Wiley-Blackwell handbook of childhood cognitive development. (2nd ed,). Wiley. Granovskiy, B. (2018). Science, Technology, Engineering, and Mathematics (STEM) Education: An Overview. Code R45223; Congressional Research Service, USA. www. crs.gov Greiff, S., Wüstenberg, S., Csapó, B., Demetriou, A., Hautamäki, J., Graesser, A.C. y Martin, R. (2014). Domain-general problem solving skills and education in the 21st century, Educational Research Review https://doi.org/ http://dx.doi.org/10.1016/j.edurev.2014.10.002 Griffiths, T. L., Tenenbaum, J. B., y Kemp, C. (2012). Bayesian inference. The Oxford handbook of thinking and reasoning, 22-35. Griffin, P., McGaw, B., y Care, E. (Eds.) (2012). Assessment and teaching of 21st century skills. Dordrecht: Springer. Grigorenko E., Sternberg R.J., y Strauss, S. (2006). Practical intelligence and elementary-school teacher Thinking Skills and Creativity Volume 1 issue 1 doi 10.1016_j.tsc.2005.03.001 Gweon, H., Tenenbaum, J. B., y Schulz, L. E. (2010). Infants consider both the sample and the sampling process in inductive generalization. Proceedings of the National Academy of Sciences, 107(20), 9066–9071. www.pnas.org/content/pnas/107/20/9066.full.pdf Hasson U. (2017). The neurobiology of uncertainty: implications for statistical learning. Phil. Trans. R. Soc. B, 372 (1711). https://doi.org/doi 10.1098_rstb.2016.0048 Hayes, B. K., McKinnon, R., y Sweller, N. (2008). The development of category-based induction: Reexamining conclusions from the induction then recognition (ITR) paradigm. Developmental Psychology, 44(5), 1430–1441. https://doi.org/10.1037/0012-1649.44.5.1430 Hayes, B. K., Stephens, R. G., Ngo, J., y Dunn, J. C. (2018). The Dimensionality of Reasoning: Inductive and Deductive Inference can be Explained by a Single Process. Journal Of Experimental Psychology. Learning, Memory, And Cognition, https://doi.org/10.1037/xlm0000527 Heller, J., Stefanutti, L., Anselmi, P., y Robusto, E. (2015). On the Link between Cognitive Diagnostic Models and Knowledge Space Theory. Psychometrika, (4), 995. https://doi.org/10.1007/s11336-015-9457-x Heit, E. (2000). Properties of inductive reasoning. Psychonomic Bulletin y Review, 7, 569– 592. https://doi.org/10.3758/bf03212996 Hernández I. (2010). Factores psicosociales asociados al alto nivel de logro académico de dos Estudiantes sensibles al medio. Tesis presentada para optar al Título de Magíster. Repositorio institucional de la Universidad Pedagógica Nacional. Colombia. Hernández I. y Pacheco P. (2013). Experiencias de innovación didáctica en la enseñanza de la Estadística. En: Inclusión social con responsabilidad, reformas educativas y profesionalización del Docente- Tomo III de la colección “Investigación Educativa y Políticas Públicas”. Universidad de Nayarit- México. ISBN 978-607-7868-70-5. 2014. Herro, D., y Quigley, C. (2016). Exploring teachers’ perceptions of STEAM teaching through professional development: implications for teacher educators. Professional Development in Education, 43(3), 416–438. https://doi.org/10.1080/19415257.2016.1205507 Holland, J., Holyoak, K., Nisbett, R. y Thagard, P. (1989). Induction Processes of Inference, Learning, and Discovery. Michigan; The MIT Press. Howe, C. Nunes, T. y Bryant, P. (2011). Rational Number and Proportional Reasoning. International Journal of Science and Mathematics Education, 9, 2, 391-417. doi 10.1007_s10763-010-9249-9pil Ifenthaler, D., y Seel, N. M. (2011). A longitudinal perspective on inductive reasoning tasks. Illuminating the probability of change. Learning and Instruction, 21(4), 538–549. https://doi.org/10.1016/J.LEARNINSTRUC.2010.08.004 Jacobs, J. E., y Narloch, R. H. (2001). Children’s use of sample size and variability to make social inferences. Journal of Applied Developmental Psychology, 22(3), 311–331. https://doi.org/10.1016/s0193-3973(01)00086-7 Jara-Ettinger, J., Gweon, H., Tenenbaum, J. B., y Schulz, L. E. (2015). Children's understanding of the costs and rewards underlying rational action. Cognition, 14. https://doi.org/10.1016/j.cognition.2015.03.00 Johnson-Laird, P. N. (1980). Mental models in cognitive science. Cognitive Science, 4, 71-115. https://www.sciencedirect.com/science/article/pii/S0364021381800055 Johnson, S. G. B., y Ahn, W. (2017). Causal mechanisms. En M. R. Waldmann (Ed.), Oxford handbook of causal reasoning, p 127-146. Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199399550.013.12 Kahneman, D., Slovic, P. y Tversky, A. (eds.) (1982). Judgment under Uncertainty, Heuristics and Biases. Cambridge University Press. Klauer, K. J., Willmes, K., y Phye, G. D. (2002). Inducing Inductive Reasoning: Does It Transfer to Fluid Intelligence?. Contemporary Educational Psychology, (1). 1. https://doi.org/10.1006/ceps.2001.1079 Keith, T. Z., y Reynolds, M. R. (2010). Cattell–Horn–Carroll abilities and cognitive tests: What we've learned from 20 years of research. Psychology In The Schools, 47(7), 635-650. DOI:10.1002/pits.20496 Kelly, A., Lesh, A. y Baek J. (eds) (2010). Handbook of Design Research Methods in Education_ Innovations in Science, Technology, Engineering, and Mathematics Learning and Teaching. Mahwah, New York Kemp, C., y Jern, A. (2014). A taxonomy of inductive problems. Psychonomic Bulletin y Review, 21(1), 23-46. https://doi.org/10.3758/s13423-013-0467-3 Kim, S., Kalish, C., Harris, P. (2012). Speaker reliability guides children's inductive inferences about novel properties, Cognitive Development, 27, (2), 114-125, https://doi.org/10.1016/j.cogdev.2011.10.004. Kinnear, V., y Clark, J. (2014). Probabilistic reasoning and prediction with young children. In J. Anderson, M. Cavanagh, y A. Prescott (Eds.), Curriculum in focus: Research guided practice (pp. 335–342). MERGA. Koenig, M. A., Cole, C. A., Meyer, M., Ridge, K. E., Kushnir, T., y Gelman, S. A. (2015). Reasoning about knowledge: Children’s evaluations of generality and verifiability. Cognitive Psychology, 83, 22–39. https://doi.org/10.1016/j.cogpsych.2015.08.007 Köksal-Tuncer, Ö., y Sodian, B. (2018). The development of scientific reasoning: Hypothesis testing and argumentation from evidence in young children. Cognitive Development, 48, 135–145. doi-org.ezproxy.unal.edu.co/10.1016/j.cogdev.2018.06.011lei Koslowski B. y Masnick A. (2010). Causal Reasoning and Explanation. En: U. Goswami, (Series Ed.). Wiley-Blackwell handbook of childhood cognitive development, (2nd ed.), pp. 341 – 419. New York : Wiley.xu Kühhirt, M. y Klein, M. (2018). Early Maternal Employment and Children's Vocabulary and Inductive Reasoning Ability: A Dynamic Approach. Child Development, 89 (2), 91-106. https://doi.org/ 10.1111/cdev.12796 Kushnir, T., Wellman, H. M., y Gelman, S. A. (2008). The role of preschoolers’ social understanding in evaluating the informativeness of causal interventions. Cognition, 107(3), 1084–1092. https://doi.org/10.1016/j.cognition.2007.10.004 Kushnir, T., Wellman, H. M., y Gelman, S. A. (2009). A self-agency bias in preschoolers’ causal inferences. Developmental Psychology, 45(2), 597–603. https://doi.org/10.1037/a0014727 Kuhn, D. (2005). Education for thinking. Cambridge, MA: Harvard University Press. Kuhn, D. (2010). Teaching and learning science as argument. Science Education, 94(5), 810–824. https://doi.org/10.1002/sce.20395 Kuhn D. (2010). What is Scientific Thinking and How Does it Develop?. En: U. Goswami, (Series Ed.). Wiley-Blackwell handbook of childhood cognitive development, (2nd ed., pg. 341 – 419). New York: Wiley. Kuhn, D., y Dean, D. J. (2004). Connecting Scientific Reasoning and Causal Inference. Journal of Cognition and Development, 5, 2, 261-288. https://doi.org/10.1207/s15327647jcd0502_5 Kuhn, D. y Franklin S. (2006). The Second Decade: What Develops (And How), En: W. Damon (Editor-in-Chief ), D. Kuhn y R. Siegler (Vol. Eds.), Handbook of child psychology: Vol. 2. Cognition, perception, and language (6th ed., pg. 953–993). New York: Wiley. Kuhn, D., Iordanou, K., Pease, M. y Wirkala, C. (2008). Beyond control of variables: What needs to develop to achieve skilled scientific thinking?. Cognitive Development, 23, 435–451. doi-org.ezproxy.unal.edu.co/10.1016/j.cogdev.2008.09.006 Kuhn, D., Ramsey, S., y Arvidsson, T. S. (2015). Developing multivariable thinkers. Cognitive Development, 35, 92-110. doi 10.1016_j.cogdev.2014.11.003 Kuhn, D., Schauble, L., y Garcia-Mila, M. (1992). Cross-Domain Development of Scientific Reasoning. Cognition and Instruction, 9(4), 285–327. https://doi.org/10.1207/s1532690xci0904_1 Kushnir, T., Xu, F., y Wellman, H. M. (2010). Young children use statistical sampling to infer the preferences of other people. Psychological Science, 21, 1134–1140. Lakin, J. y Gambrell, J. (2012). Distinguishing verbal, quantitative, and figural facets of fluid intelligence in young students, Intelligence, 40, 6, 560-570, doi.org/10.1016/j.intell.2012.07.005 Lane, J. D., Ronfard, S., Francioli, S. P., y Harris, P. L. (2016). Children’s imagination and belief: Prone to flights of fancy or grounded in reality? Cognition, 152, 127–140. http://dx.doi.org/10.1016/j.cognition.2016.03.022 Lane, J. y Shafto, P. (2017). Young children’s attributions of causal power to novel invisible entities. Journal of Experimental Child Psychology, 162, 268-281, doi.org/10.1016/j.jecp.2017.05.015. Lawson, C. A. (2014). Three-year-olds obey the sample size principle of induction: The influence of evidence presentation and sample size disparity on young children’s generalizations. Journal of Experimental Child Psychology, 123, 147–154. https://doi.org/10.1016/j.jecp.2013.12.004 Lawson, C. (2017). The Influence of Task Dynamics on Inductive Generalizations: How wSequential and Simultaneous Presentation of Evidence Impacts the Strength and Scope of Property Projections. Journal Of Cognition y Development, 18 (4), 493-513. https://doi.org/10.1080/15248372.2017.1339707 Legare, C.H. (2014). The Contributions of Explanation and Exploration to Children's Scientific Reasoning. Child Development Perspectives. Vol. 8, (2) 101-106. HTTPS://DOI.ORG/ 10.1111/cdep.12070 Leighton, J.P. y Sternberg R. J. (Ed.).(2004). The nature of reasoning. Cambridge University Press. Leighton, J. P., y Gierl, M. J. (2007). Defining and Evaluating Models of Cognition Used in Educational Measurement to Make Inferences about Examinees' Thinking Processes. Educational Measurement: Issues And Practice, 26(2), 3-16. Legare, C. H., y Lombrozo, T. (2014). Selective effects of explanation on learning during early childhood. Journal of Experimental Child Psychology, 126, 198–212. https://doi.org/10.1016/j.jecp.2014.03.001 Lo, Y., Sides, A., Rozelle, J. y Osherson, D. (2002). Evidential diversity and premise probability in young children’s inductive judgments. Cognitive Science - A Multidisciplinary Journal, 26, 181-206. www.elsevier.com/locate/cogsci Lombrozo, T. (2016). Explanatory Preferences Shape Learning and Inference. Trends in Cognitive Sciences, 20(10), 748–759. https://doi.org/10.1016/j.tics.2016.08.001 Low, J. y Perner J. (2012). Implicit and explicit theory of mind: State of the art. British Journal of Developmental Psychology, (2012), 30, 1–13. HTTPS://DOI.ORG/10.1111/j.2044-835X.2011.02074.x Lundberg, S. (2020). Educational gender gaps. Southern Economic Journal, Volume: 87 Issues: 2 416—439. HTTPS://DOI.ORG/ 10.1002/soej.12460 Markovits, H., y Barrouillet, P. (2004). Introduction: Why is understanding the development of reasoning important?. En Thinking y Reasoning, 10(2), 113–121. https://doi.org/10.1080/13546780442000006 Marcovitch, S. y Lewkowicz, D. J. (2009), Sequence learning in infancy: the independent contributions of conditional probability and pair frequency information. Developmental Science, 12: 1020-1025. https://doi.org/10.1111/j.1467-7687.2009.00838.x McGuinness Institute, Wellington, New Zealand. (2015). The future of scientific thought, Journal of the Royal Society of New Zealand, 45 (2), 95-100, https://doi.org/ 10.1080/03036758.2015.1013142 McCormack, T., Bramley, N., Frosch, C., Fiona, P. y Lagnado, D. (2016). Children’s use of interventions to learn causal structure. Journal of Experimental Child Psychology, 141, 1–22. dx.doi.org/10.1016/j.jecp.2015.06.017 Medin, D. L., Coley, J. D., Storms, G., y Hayes, B. L. (2003). A relevance theory of induction. Psychonomic Bulletin y Review, 10(3), 517–532. https://doi.org/10.3758/bf03196515 Mercer, N. (2013). The Social Brain, Language, and Goal-Directed Collective Thinking: A Social Conception of Cognition and Its Implications for Understanding How We Think, Teach, and Learn. Educational Psychologist, 48(3), 148–168. https://doi.org/10.1080/00461520.2013.804394 Miller, M. R., Giesbrecht, G. F., Müller, U., McInerney, R. J., y Kerns, K. A. (2012). A Latent Variable Approach to Determining the Structure of Executive Function in Preschool Children. Journal Of Cognition y Development, 13(3), 395-423. https://doi.org/10.1080/15248372.2011.585478 Ministerio de Educación Nacional. (2009). Desarrollo infantil y competencias en la primera infancia. Colombia. Documento Nº 10, MEN. Ministerio de Educación Nacional. (2011). Valoración del desarrollo en contextos educativos. Documento base, MEN: Colombia. Ministerio de Educación Nacional (2012). Una propuesta de trabajo pedagógico en la educación inicial, documento base para la construcción del lineamiento pedagógico de educación inicial. Documento de trabajo, MEN: Colombia. Mohlhenrich, E., Samsonau, S. y Spencer, R. (2018). Integrating Science Through Authentic Research in Secondary Schools. IEEE Integrated STEM Education Conference (ISEC) - Princeton, NJ, USA . doi 10.1109%2FISECon.2018.8340465 Moore, B. (2009). Emotional Intelligence for School Administrators: A Priority for School Reform? American Secondary Education, 37(3), 20–28. http://www.jstor.org/stable/41406313 Moore, J.D., Dorofy, P., Jabot, M., y Bouaynaya N. (2018). Earth SySTEM: Investigating Earth from Space, IEEE Integrated STEM Education Conference (ISEC) - Princeton, NJ, USA. doi 10.1109%2FISECon.2018.8340492 Morewedge, C.K. y Kahneman D. (2010). Associative processes in intuitive judgment. Trends in Cognitive Sciences, Vol. 14 (10), 435-440 Moshman, D. (2004). From inference to reasoning: The construction of rationality. Thinking y Reasoning, 10(2), 221–239. https://doi.org/10.1080/13546780442000024 Moulines, U. (2011). El desarrollo moderno de la Filosofía de la Ciencia (1890-2000). México: Instituto de Investigaciones Filosóficas UNAM. Muniz, M., Seabra, A. G., y Primi, R. (2012). Validity and Reliability of the Inductive Reasoning Test for Children - IRTC. Psicologia-Reflexao E Critica, 25(2), 275-285. Nancekivell, S.H. y Friedman, O. (2017). She Bought the Unicorn From the Pet Store: Six- to Seven-Year-Olds Are Strongly Inclined to Generate Natural Explanations. Dev. Psychol. Vol. 53, No. 6, https://doi.org/1079–1087/dev0000311 National Science Foundation. (2007). Women, Minori- ties, and Persons with Disabilities in Science and Engineering. National Science Foundation, Division of Science Resource Statistics. Arlington: U.S.A. Nguyen, S. P. (2012). Inductive Selectivity in Children's Cross-Classified Concepts. Child Development, 83(5), 1748-1761. https://doi.org/10.1111/j.1467-8624.2012.01812.x Nguyen, S., Gordbron C., Chevalier, T. y Girgis, H. (2016). Trust and doubt: An examination of children’s decision to believe what they are told about food, Journal of Experimental Child Psychology, 144, 66-83. dx.doi.org/10.1016/j.jecp.2015.10.015 Nisbett, R. E., Krantz, D. H., Jepson, C., y Kunda, Z. (1983). The use of statistical heuristics in everyday inductive reasoning. Psychological Review, 90(4), 339–363. https://doi.org/10.1037/0033-295x.90.4.339 Nisbett, R. y Ross, L. (1986). Human Inference: Strategies And Shortcomings Of Social Judgment. New Jersey: Prentice-Hall. Nisbett, R. E., Choi, I., Peng, K., y Norenzayan, A. (2001). Culture and Systems of Thought: Holistic Versus Analytic Cognition. Psychological Review, (2), 291-310. https://doi.org/10.1037//0033-295X.108.2.291 Nisbett, R., Krantz, D., Jepson,C. y Fong G. T. (1982). Improving inductive inference. En Kahneman, D., Paul Slovic, Amos Tversky (eds.) (1982). Judgment under Uncertainty, Heuristics and Biases. Cambridge University Press. Nisbett, R. E., Aronson, J., Blair, C., Dickens,W., Flynn, J., Halpern, D., et al. (2012). Intelligence: New findings and theoretical developments. American Psychologist, 67, 2, 130–159 doi 10.1037/a0026699. Noyes, A., y Christie, S. (2016). Children Prefer Diverse Samples for Inductive Reasoning in the Social Domain. Child Development, 87(4), 1090-1098. https://doi.org/10.1111/cdev.12522 OECD. (2009). Programme for International Student Assessment. An overview. Paris: OECD. OECD (2012a). Better skills, better jobs, better lives. A strategic approach to skills policies. Paris: OECD. OECD (2013a). PISA 2012 assessment and analytical framework. Paris: OECD Publishing. OECD. (2015) The ABC of Gender Equality in Education: Aptitude, Behaviour, Confidence. PISA: OECD Publishing. https://doi.org/10.1787/9789264229945-en Opfer, J. E., y Bulloch, M. J. (2007). Causal relations drive young children’s induction, naming, and categorization. Cognition, 105, 206–217. https://doi.org/10.1016/j.cognition.2006.08.006 Osborne, J. (2013). The 21st century challenge for science education: Assessing scientific reasoning. Thinking Skills and Creativity, 10, 265-279. dx.doi.org/10.1016/j.tsc.2013.07.006 Palejwala, M. H., y Fine, J. G. (2015). Gender differences in latent cognitive abilities in children aged 2 to 7. Intelligence, 4896-108. https://doi.org/10.1016/j.intell.2014.11.004 Palmquist, C. M., y Jaswal, V. K. (2015). Preschoolers’ inferences about pointers and labelers: The modality matters. Cognitive Development, 35, 178–185. https://doi.org/10.1016/j.cogdev.2015.06.003 Pavlidou, E. V., y Bogaerts, L. (2019). Implicit Statistical Learning across Modalities and its Relationship with Reading in Childhood. Front Psychol. https://doi.org/10.3389/fpsyg.2019.01834 Perner, J. y Dienes, Z. (2002). Implicit Versus Explicit Representation and Intra‐ Versus Inter‐Modular Processing. Computational Intelligence, 18: 55-58. https://doi.org/10.1111/1467-8640.00182 Perret, P. (2015). Children’s Inductive Reasoning: Developmental and Educational perspectives. Journal of Cognitive Education and Psychology, 14 (3), 389 - 408. 10.1891/1945-8959.14.3.389 Primi, R., Rocha da Silva, M. C., Rodrigues, P., Muniz, M., y Almeida, L. S. (2013). The use of the bi-factor model to test the uni-dimensionality of a battery of reasoning tests. Psicothema, 25(1), 115-122. https://doi.org/10.7334/psicothema2011.393 Pavlidou, E., y Bogaerts, L. (2019). Implicit statistical learning across modalities and its relationship with reading in childhood. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2019.01834 Perret, P. (2015). Children’s Inductive Reasoning: Developmental and Educational perspectives. Journal of Cognitive Education and Psychology, 14 (3), 389 - 408. https://doi.org/10.1891/1945-8959.14.3.389 Petticrew, M. y Roberts, H. (2006). Systematic reviews in the social sciences. A practical guide. Oxford: Blackwell Publishing. Pillow, B. (2002). Children's and adults' evaluation of the certainty of deductive inferences, inductive inferences, and guesses. Child Development, 3, 779-792. Quinn P. (2010). Born to Categorize. In U. Goswami, (Series Ed.). Wiley-Blackwell handbook of childhood cognitive development., New York: Wiley (2nd ed, p. 129). doi.org/10.1111/1467-8624.00438 Ricco, R. B. (2015). The Development of Reasoning. Handbook of Child Psychology and Developmental Science, 1–52. https://doi.org/10.1002/9781118963418.CHILDPSY213 Rhodes, M., l, S. A., y Brickman, D. (2008). Developmental Changes in the Consideration of Sample Diversity in Inductive Reasoning. Journal Of Cognition y Development, 9(1), 112-143. https://doi.org/10.1080/15248370701836626dien Rhodes, M., y Liebenson, P. (2015). Continuity and change in the development of category-based induction: The test case of diversity-based reasoning. Cognitive Psychology, 74. https://doi.org/10.1016/j.cogpsych.2015.07.003 Ruffman, T., Taumoepeau, M., y Perkins, C. (2012). Statistical learning as a basis for social understanding in children. British Journal of Developmental Psychology, 30, 87–104, https://doi.org/10.1111/j.2044-835X.2011.02045.x Saffran, J. R., y Kirkham, N. Z. (2018). Infant statistical learning. Annual Review of Psychology, 69, 181–208. http://dx.doi.org/10.1146/annurev-psych-122216-011805. Samarapungavan, A., Vosniadou, S., y Brewer, W. F. (1996). Mental models of the earth, sun, and moon: Indian children’s cosmologies. Cognitive Development, 11(4), 491–521. https://doi.org/10.1016/s0885-2014(96)90015-5 Samarapungavan, A. Mantzicopoulos P. y Patrick H. (2008). Learning science through inquiry in kindergarten. Science Education. 92, 5, 868-908. doi 10.1002%2Fsce.20275 Schulz, L. (2012). The origins of inquiry: inductive inference and exploration in early childhood. Trends in Cognitive Sciences, 16, 7, 382-389. https://doi.org /10.1016/j.tics.2012.06.004 Schauble, L. (1996). The development of scientific reasoning in knowledge-rich contexts. Developmental Psychology, 32(1), 102–119. https://doi.org/10.1037/0012-1649.32.1.102 Schulz, L., Goodman, N., Tenenbaum, J. y Jenkins, A. (2008). Going beyond the evidence: Abstract laws and preschoolers' responses to anomalous data. Cognition, 109(2), 211-223. https://doi.org/10.1016/j.cognition.2008.07.017 Schulz, L. E., y Sommerville, J. (2006). God does not play dice: Causal determinism and preschoolers’ causal inferences. Child Development, 77(2), 427–442. https://pubmed.ncbi.nlm.nih.gov/16611182 Schwichow, M., Croker, S., Zimmerman, C., Hoffler, T. y Hartig, H. (2016). Teaching the control-of-variables strategy: A meta-analysis. Developmental Review, 37. doi-org.ezproxy.unal.edu.co/10.1016/j.dr.2015.12.001 Setoh, P., Wu, D., Baillargeon, R., y Gelman, R. (2013). Young infants have biological expectations about animals. Proceedings of the National Academy of Sciences, USA, 110 (40), 15937-15942. https://doi.org/ 10.1073/pnas.1314075110 Shafto, P., Kemp, C., Bonawitz, E. B., Coley, J. D., y Tenenbaum, J. B. (2008). Inductive reasoning about causally transmitted properties. Cognition, 109175-192. https://doi.org/10.1016/j.cognition.2008.07.006 Strand-Cary, M., y Klahr, D. (2008). Developing elementary science skills: Instructional effectiveness and path independence. Cognitive Development, 23(4), 488–511. https://doi.org/10.1016/j.cogdev.2008.09.005 Siler, S. A., Klahr, D., y Price, N. (2012). Investigating the mechanisms of learning from a constrained preparation for future learning activity. Instructional Science, 41(1), 191–216. https://doi.org/10.1007/s11251-012-9224-7 Simon, H. A., y Lea, G. (1974). Problem solving and rule induction: A unified view. In L. W. Gregg (Ed.), Knowledge and cognition (pp. 105-127). Potomac, MD: Erlbaum. Singh, M. (2021). Acquisition of 21st Century Skills Through STEAM Education. Academia Letters. https://doi.org/10.20935/AL712 Shipley, E. y Shepperson, B. (2006). Test Sample Selection by Preschool Children: Honoring Diversity. Memory and Cognition, 34(7), 1444 -1451, doi.org/10.3758/BF03195909 Shtulman, A., y Schulz, L. (2008). The relation between essentialist beliefs and evolutionary reasoning. Cognitive Science, 32 (6), 1049–1062. https://doi.org/10.1080/03640210801897864 Shye, S. (1988). Inductive and Deductive Reasoning: A Structural Reanalysis of Ability Tests. Journal Of Applied Psychology, 73(2), 308-311 Slone, L.K., Johnson, S. P. (2018). When learning goes beyond statistics: Infants represent visual sequences in terms of chunks, Cognition, Volume 178, 2018, Pages 92-102, ISSN 0010-0277, https://doi.org/10.1016/j.cognition.2018.05.016. Sloman, S. A. (2005) Causal models: how people think about the world and its alternatives. Oxford University Press, Inc. : New York Sloutsky, V. M., Wei D., Fisher, A. y Kloos, H. (2015). Conceptual influences on induction: A case for a late onset, Cognitive Psychology, 82, 1-31. dx.doi.org/10.1016/j.cogpsych.2015.08.005 Sobel, D.M. y Buchanan D.W. (2009). Bridging the gap: Causality-at-a-distance in children’s categorization and inferences about internal properties. Cognitive Development, 24, 274–283 https://doi.org/10.1016/j.cogdev.2009.03.003 Sobel, D.M., Erbb, C.D., Tassina, T. y Skolnick Weisberg D. (2017). The Development of Diagnostic Inference About Uncertain Causes. Journal of Cognition and Development, Vol. 18, No. 5, 556–576 https://doi.org/10.1080/15248372.2017.1387117 Sobel, D. M., y Legare, C. (2014). Causal learning in children. WIRE-Cognitive Science, 5, 413–427. https://doi.org/10.1002/wcs.1291 Sternberg , R. (Ed.) ( 1984 ). Mechanisms of cognitive development. New York: Freeman Sternberg, R. (2010). Individual Differences in Cognitive Development. En U. Goswami, (Series Ed.).Wiley-Blackwell handbook of childhood cognitive development. New York: Wiley. Sternberg, R., y Gardner, M. (1983). Unities in inductive reasoning. Journal Of Experimental Psychology: General, 112(1), 80-116. https://doi.org/10.1037/0096-3445.112.1.80 Sternberg, R. y Prezt, J. (Ed.) (2005). Cognition and Intelligence: Identifying the Mechanisms of the Mind. New York: Cambridge University Press. Sternberg, R. J., Sternberg, K., y Mio, J. S. (2012). Cognitive psychology. Australia: Wadsworth/Cengage Learning. Sü, H. M., Oberauer, K., Wittmann, W. W., Wilhelm, O., y Schulze, R. (2002). Working-memory capacity explains reasoning ability-and a little bit more. Intelligence -Norwood- Mutidisciplinary Journal. (3). 261- 276. https://www.sciencedirect.com/science/article/pii/S0160289601001003 Sutherland, S. L. y Cimpian, A. (2017). Inductive generalization relies on category representations. Psychonomic Bulletin y Review, 24(2), 632-636. https://doi.org/10.3758/s13423-015-0951-z Tenenbaum, J. B., Kemp, C., Griffiths, T. L., y Goodman, N. D. (2011). How to Grow a Mind: Statistics, Structure, and Abstraction. Science, 331(6022), 1279–1285. https://doi.org/10.1126/science.1192788 Teglas, E., Vul, E., Girotto, V., Gonzalez, M., Tenenbaum, J. B., y Bonatti, L. L. (2011). Pure reasoning in 12-month-old infants as probabilistic inference. Science, 332, 1054–1058. https://doi.org/10.1126/science.1196404 Tummeltshammer, K.S., y Kirkham, N.Z. (2013). Learning to look: probabilistic variation and noise guide infants’ eye movements. Developmental Science, 16, 760–771. https://doi.org/10.1111/desc.12064 Tomasello, M. (2010). Language Development. In U. Goswami, (Series Ed.). Wiley-Blackwell handbook of childhood cognitive development .New York : Wiley Tummeltshammer, K., Amso, D., French, R. M., y Kirkham, N. Z. (2016). Across space and time: infants learn from backward and forward visual statistics. Developmental Science, 1–9. doi.org/10.1111/desc.12474. Thurstone, L. L. y Thurstone, T. G. (1941). Factorial studies of intelligence. Chicago: University of Chicago Press. Turiel, E. (2012). Moral reasoning, cultural practices, and social inequalities. Innovación Educativa, 12 (59), pp 17-32. www.scielo.org.mx/pdf/ie/v12n59/v12n59a3.pdf UNESCO. (2005). Towards knowledge societies. Paris: United Nations Educational, Scientific, and Cultural Organization. UNESCO (2015). Replantear la educación: Hacia un bien común mundial?. Disponible en: (www.unesco.org/open-access/terms-use-ccbysa-sp) UNESCO. (2017) Cracking the code: Girls’ and women’s education in science, technology, engineering and mathematics (STEM). París: United Nations Educational, Scientific and Cultural Organization. http://unesdoc.unesco.org/images/0025/002534/253479e.pdf Vandekerckhove, J. (2014). A cognitive latent variable model for the simultaneous analysis of behavioral and personality data. Journal Of Mathematical Psychology, 6058-71. https://doi.org/10.1016/j.jmp.2014.06.004 van Laar, E., Deursen, A., Van Dijk, J. y Haan, J. (2020). Determinants of 21st-Century Skills and 21st-Century Digital Skills for Workers: A Systematic Literature Review. SAGE Open. 10. 1-14. 10.1177/2158244019900176. Vega E. (2018). The Wisdom of our Native American Tribes: Advanced Math, Science and Culture for the Future. IEEE Integrated STEM Conference (ISEC). www.linkedin.com/in/ernesto-vega-janica-50231319 Vygotsky, L. S. (1988). El desarrollo de los procesos psicológicos superiores. Barcelona, España: Crítica. (Año de publicación del original: 1931) Waismeyer, A., y Meltzoff, A. N. (2017). Learning to make things happen: Infants' observational learning of social and physical causal events. Journal Of Experimental Child Psychology, 58. https://doi.org/10.1016/j.jecp.2017.04.018 Waismeyer, A., Meltzoff, A. N., y Gopnik, A. (2015). Causal learning from probabilistic events in 24-month-olds: An action measure. Developmental Science, 18, 175–182. https://doi.org/10.1111/desc.12208 Washer, P. (2007). Revisiting Key Skills: A Practical Framework for Higher Education. Quality in Higher Education, 13(1), 57–67. https://doi.org/10.1080/13538320701272755 Watson, G., y Glaser, E. M. (1964). Manual for the Watson-Glaser critical thinking appraisal. New York: Harcourt, Brace, Jovanovich Waxman, S. (2010). Early Word-Learning and Conceptual Development: Everything Had a Name, and Each Name Gave Birth to a New Thought. In U. Goswami, (Series Ed.). Wiley-Blackwell handbook of childhood cognitive development . (2nd ed.). New York: Wiley. Waldmann, M. y Hagmayer, Y. (2006). Categories and causality: The neglected direction. Cognitive Wellman, H. M. (2014). Making Minds: How Theory of Mind Develops. Oxford University Press : New York Wild y Pfannkuch (1999), Statistical Thinking in Empirical Enquiry, International Statistical Review, 67, pp. 223 –265. doi.org/10.1111/j.1751-5823.1999.tb00442.x Wilkening, F., y Cacchione, T. (2010). Children's intuitive physics. In U. Goswami (Ed.), The Wiley-Blackwell handbook of childhood cognitive development (pp. 473–496). Wiley-Blackwell. World Economic Forum. (2020). Schools of the Future: Defining New Models of Education for the Fourth Industrial Revolution, 2020. WEF_Schools_of_the_Future_Report_2019.pdf (weforum.org) World Economic Forum. (2021). Building A Common Language for Skills at Work: A Global Taxonomy. https://www.weforum.org/reports/building-a-common-language-for-skills-at-work-a-global-taxonomy Wu R, Gopnik A, Richardson DC, Kirkham NZ. (2011). Infants learn about objects from statistics and people. Dev. Psychol. 47(5):1220–29. https://doi.org/ 10.1037/a0024023 Xu, F. y Garcia, V. (2008). Intuitive Statistics by 8-Month-Old Infants. Proceedings Of The National Academy Of Sciences Of The United States Of America, 105 (13), 5012-5015. https://doi.org/10.1073/pnas.0704450105 Xu, F., y Griffiths, T. L. (2011). Probabilistic models of cognitive development: towards a rational constructivist approach to the study of learning and development. Cognition, 120 (3), 299–301 doi.org/10.1016/j.cognition.2011.06.008 Xu, F. y Kushnir, T. (Eds.). (2012). Rational Constructivism in Cognitive Development. Waltham, MA: Academic Press. Zheng, D., Shu G., y Wong, K. W. (2018). Global Engineering. Education Conference (EDUCON) - Santa Cruz de Tenerife, Islas Canarias, España. https://doi.org/10.1109%2FEDUCON.2018.8363268 Zhu, L., y Gigerenzer, G. (2006). Children can solve Bayesian problems: The role of representation in mental computation. Cognition, 98(3), 287–308. https://doi.org/10.1016/j.cognition.2004.12.003 Zimmerman, C. (2000). The Development of Scientific Reasoning Skills. Developmental Review, (20), 99-149. https://doi.org/10.1006/drev.1999.0497 Zimmerman, C. (2007). The development of scientific thinking skills in elementary and middle school. Developmental Review, 2, 172-223. https://doi.org/10.1016/j.dr.2006.12.001 |
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Atribución-NoComercial-SinDerivadas 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Taborda Osorio, Hernando6c37fd38026205b50007023218662d2fGonzález García, Luz Mery848571137a0f25b45cc391309eda3230Hernández Urrego, Isabel Astrid1d4a6d13e4de2fcbd9f66adac9b5dd8cHernández Urrego Isabel Astrid [0000-0002-8018-1897]2023-02-23T20:57:16Z2023-02-23T20:57:16Z2023-01-26https://repositorio.unal.edu.co/handle/unal/83552Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, fotografías a colorPropuesta metodológica para la caracterización del Razonamiento Inductivo en la Primera Infancia desde el enfoque de la Educación STEM Resumen El razonamiento inductivo (RI) se distingue de otros procesos cognitivos, por dos características: es fundamental en la generación y transformación del conocimiento, y las inferencias, mediante las cuales se hace explicito, pueden ser total, o parcialmente plausibles. Un importante volumen de evidencia empírica, proveniente de modelos de teorías ingenuas, sugiere que los bebés razonan sobre información estadística, para modificar su comportamiento, elegir y predecir en circunstancias de incertidumbre. Incluso, existe acuerdo sobre las características de experiencias y contenidos que facilitan la inferencia de causalidad, en situaciones probabilísticas cotidianas. Sin embargo, los desarrollos metodológicos, han tardado en llegar a los ámbitos de la formación del pensamiento de los niños habitantes de países pobres. Desde una perspectiva integradora, se retomaron principios de los modelos de cognición infantil que han considerado las particularidades y diferencias individuales del RI normativo, para el estudio de sus modalidades. Así, se orientó la propuesta metodológica en la creación de criterios de medición e indicadores de eficacia de las inferencias inductivas. Mediante éstos, es posible la estimación de los atributos: plausibilidad, precisión, coherencia y relevancia de la inferencia temprana. En consecuencia, los estudios que fundamentan esta disertación, sustentan la utilidad científica de un instrumento de medición de la eficacia en el RI de niños con edades entre 4 y 6 años. Los resultados de la indagación, también aportan nueva evidencia sobre la influencia de algunos hábitos familiares de formación del pensamiento, en el desarrollo conceptual y del RI eficaz de los participantes. A partir del logro de los objetivos de investigación, se discute la oportunidad de transferir conocimiento sobre desarrollo cognitivo temprano, hacia la formación de habilidades inferenciales implicadas en la comprensión e indagación científicas, desde Preescolar. Se proyecta, que la estrategia metodológica propuesta para la caracterización del RI en la infancia temprana, tendrá impacto en el cumplimiento de los propósitos de la Educación STEM del siglo XXI. (Texto tomado de lanfuenta)Methodological proposal for the characterization of Inductive Reasoning in Early Childhood from the STEM Education approach Abstract Inductive reasoning (IR) is distinguished from other cognitive processes by two characteristics: it is fundamental in the generation and transformation of knowledge, and the inferences, through which it is made explicit, can be totally or partially plausible. A substantial body of empirical evidence, from naive model theories, suggests that infants reason about statistical information to modify behavior, make choices, and predict under uncertain circumstances. There is even agreement on the characteristics of experiences and contents that facilitate the inference of causality, in everyday probabilistic situations. However, methodological developments have been slow to reach the areas of thought formation of children living in poor countries. From an integrative perspective, principles of child cognition models were taken up, which have considered the particularities and individual differences of the normative IR, for the study of its different modalities. Thus, the methodological proposal was oriented towards the creation of measurement criteria and effectiveness indicators of inductive inferences. Through these, it is possible to estimate the attributes: plausibility, precision, coherence and relevance of early inference. Consequently, the studies that support this dissertation support the scientific usefulness of an instrument for measuring efficacy in the IR of children aged between 4 and 6 years. The results of the investigation also provide new evidence on the influence of some family habits of thought formation, in the conceptual development and the effective IR of the participants. From the achievement of the research objectives, the opportunity to transfer knowledge, on early cognitive development, towards the formation of inferential skills involved in scientific understanding and inquiry, from Preschool, is discussed. It is projected that the methodological strategy proposed for the characterization of IR in early childhood will have an impact on the fulfillment of the purposes of STEM Education in the 21st century.DoctoradoDoctor en PsicologíaMaterial para evaluación del desarrollo cognitivo temprano, tablas y figuras estadisticas197 páginasapplication/pdfspaUniversidad Nacional de ColombiaBogotá - Ciencias Humanas - Doctorado en PsicologíaFacultad de Ciencias HumanasBogotá, ColombiaUniversidad Nacional de Colombia - Sede Bogotá100 - Filosofía y Psicología::107 - Educación, investigación, temas relacionados150 - Psicología::155 - Psicología diferencial y del desarrollo370 - Educación::371 - Escuelas y actividades; educación especialCognición en niñosPercepción en niñosCognition in childrenPerception in childrenRazonamiento inductivo eficazHabilidad inferencial tempranaDesarrollo conceptualCoonceptual developmentSocialización de la cogniciónSocialization of cognitionEffective inductive ReasoningEarly inferential abilityPropuesta metodológica para la caracterización del Razonamiento Inductivo en la Primera Infancia desde el enfoque de la Educación STEMMethodological proposal for the characterization of Inductive Reasoning in Early Childhood from the STEM Education approachTrabajo de grado - Doctoradoinfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_db06Texthttp://purl.org/redcol/resource_type/TDAguiar, N. R., Stoess, C. J., y Taylor, M. (2012). The development of children’s ability to fill the gaps in their knowledge by consulting experts. Child Development, 83, 1368- 1381. https://doi.org/10.1111/j.1467-8624.2012.01782.xAhl, R. y Keil, F. (2017). Diverse Effects, Complex Causes: Children Use Information About Machines' Functional Diversity to Infer Internal Complexity. Child Development, 88 (3), 828-845. https://doi.org/10.1111/cdev.12613Anderson, R., y Branstetter, S. (2012). Adolescents, parents, and monitoring: A review of constructs with attention to process and theory. Journal of Family Theory y Review, 4, 1-19. https://doi. org/10.1111/j.1756-2589.2011.00112.xAmerican Educational Research Association, American Psychological Association y National Council on Measurement in Education (2014). Standards for Educational and Psychological Testing. Washington, United States: Author.Avila, C. y Barragan, G. (2018). Artículo de Experiencia en el Aula: Educación STEM una ruta hacia la innovación. Revista electrónica TicALS, 4, 146 - 162 www.als.edu.co/revistaticalsBarkl, S., Porter, A., y Ginns, P. (2012). Cognitive training for children: Effects on inductive reasoning, deductive reasoning, and mathematics achievement in an Australian school setting. Psychology In The Schools, 49(9), 828-842. https://doi.org/10.1002/pits.21638Baillargeon, R., Scott, R. M., y Bian, L. (2016). Psychological reasoning in infancy. Annual Review of Psychology, 67. doi.org/10.1146/annurev-psych-010213-115033pabliBarbey, A. K., y Sloman, S. A. (2007). Base-rate respect: From ecological rationality to dual processes. Behavioral and Brain Sciences, 30, 3, 241-254. https://doi.org/10.1017/S0140525X07001653Bascandziev, I., y Harris, P.L. (2016). The beautiful and the accurate: Are children’s selective trust decisions biased?. Journal of Experimental Child Psychology, Vol. 152, 92-105, doi.org/10.1016/j.jecp.2016.06.017Batanero, C., y Chernoff, E. J. (2018). Teaching and Learning Stochastics: Advances in Probability Education Research. https://doi.org/10.1007/978-3-319-72871-1Batanero, C., Chernoff, E. J., Engel, J., Lee, H. S., y Sánchez, E. (2016). Research on Teaching and Learning Probability. Cham: Springer International Publishing.Bogdan Toma, R. y Meneses Villagrá, J. Á. (2019). Preferencia por contenidos científicos de física o de biología en Educación Primaria: un análisis clúster. Revista Eureka Sobre Enseñanza y Divulgación de Las Ciencias, 16(1),1, http://unal.edu.co/10.25267/Rev_Eureka_ensen_divulg_cienc.2019.v16.i1.1104Bolt, D. (2007). The Present and Future of IRT-Based Cognitive Diagnostic Models (ICDMs) and Related Methods. Journal Of Educational Measurement, (4). 377.Bonawitz, E. B., y Lombrozo, T. (2012). Occam's rattle: Children's use of simplicity and probability to constrain inference. Developmental Psychology, 48, 4, 1156-1164. https://doi.org/10.1037/a0026471Bonawitz, E., Ullman, T. D., Bridgers, S., Gopnik, A., y Tenenbaum, J. B. (2019). Sticking to the Evidence? A Behavioral and Computational Case Study of Micro‐Theory Change in the Domain of Magnetism. Cognitive Science, 43(8). https://doi.org/10.1111/cogs.12765Bonett, D.G., Wright, T.A. Sample size requirements for estimating pearson, kendall and spearman correlations. Psychometrika 65, 23–28 (2000). https://doi.org/10.1007/BF02294183Bonnefon J-F y Billaut E. (2016). Individual Differences in Reasoning beyond Ability and Disposition Cap. 11 En Macchi, Laura, Bagassi, Maria y Viale, Riccardo. Cognitive unconscious and human rationality. Toppan Best-set Premedia Limited. United States of America. Massachusetts Institute of TechnologyBouwmeester, S., y Sijtsma, K. (2004). Measuring the ability of transitive reasoning, using product and strategy information. Psychometrika, 69(1), 123. https://doi.org/10.1007/BF02295843Borovcnik M., Kapadia R. (2018) Reasoning with Risk: Teaching Probability and Risk as Twin Concepts. En: Batanero C., Chernoff E. (eds) Teaching and Learning Stochastics. ICME-13 Monographs. Springer, Cham.Badger, J. R., y Shapiro, L. R. (2012). Evidence of a transition from perceptual to category induction in 3- to 9-year-old children. Journal of Experimental Child Psychology, 113(1), 131–146. https://doi.org/10.1016/j.jecp.2012.03.004Brandone, A. C. (2017). Changes in Beliefs About Category Homogeneity and Variability Across Childhood. Child Development, 88(3), 846-866. https://doi.org/10.1111/cdev.12616Bramley, N., Gerstenberg, T., Tenenbaum, J. y Gureckis, T. (2018). Intuitive experimentation in the physical world. Cognitive. Psychology, 105, 9-38. https://doi.org/10.1016/j.cogpsych.2018.05.001Brenneman, K., y Louro, I. F. (2008). Science Journals in the Preschool Classroom. Early Childhood Education Journal, 36(2), 113–119. https://doi.org/10.1007/s10643-008-0258-zBryant, P. y Nunes, T. (2012). Children’s understanding of probability: A literature review. London, England: Nuffield Foundation.howBulloch, M. J. y Opfer, J. E. (2009). What makes relational reasoning smart? Revisiting the perceptual-to-relational shift in the development of generalization. Developmental Science, 12, 1, 114-122. https://doi.org/10.1111/j.1467-7687.2008.00738.xBumeltshammer, K.S., y Kirkham, N.Z. (2013). Learning to look: probabilistic variation and noise guide infants’ eye movements. Developmental Science, 16, 760–771. https://doi.org/10.1111/desc.12064Burris, V. (1982). The Child’s Conception of Economic Relations; A Study of Cognitive Socialization. Sociological Focus, 15(4), 307–325. https://doi.org/10.1080/00380237.1982.10570424Butler, L. P., y Markman, E. M. (2012). Preschoolers Use Intentional and Pedagogical Cues to Guide Inductive Inferences and Exploration. Child Development, 83(4), 1416-1428. https://doi.org/10.1111/j.1467-8624.2012.01775.xCánavos, G. C. (1999). Probabilidad y Estadística: Aplicaciones y Métodos. México: McGraw-Hill.Carey, S. (2009). The Origin of Concepts. Oxford Series in Cognitive Development.Clark, E. V. (2004). How language acquisition builds on cognitive development. Trends in Cognitive Sciences, 8(10), 472–478. https://doi.org/10.1016/j.tics.2004.08.012Cerchiaro-Ceballos, E., y Puche-Navarro, R. (2018). Funcionamientos inferenciales en niños caminadores: un acercamiento al microdesarrollo en una tarea de resolución de problemas. Revista Colombiana de Psicología, 27, 117-135. https://doi.org/10.15446/rcp.v27n2.66054Csapo, B. (1997). The Development of Inductive Reasoning: Cross-sectional Assessments in an Educational Context. International journal of behavioral development, (4). 609. https://journals.sagepub.com/doi/10.1080/016502597385081Cosmides L, Tooby J. (2013). Evolutionary psychology: New perspectives on cognition and motivation. Annu. Rev. Psychol. 64:201-29. DOI: 10.1146/annurev.psych.121208.131628Colberg, M., Nester, M. A., y Cormier, S. M. (1982). Inductive reasoning in psychometrics: A philosophical corrective. Intelligence, 6139-164. https://doi.org/10.1016/0160-2896(82)90011-3Colberg, M., Nester, M., y Trattner, M. (1985). Convergence of the Inductive and Deductive Models in the Measurement of Reasoning Abilities. Journal Of Applied Psychology, 70(4), 681-694. https://doi.org/10.1037/0021-9010.70.4.681Corral, Y. (2009). Validez y confiabilidad de los instrumentos de investigación para la recolección de datos. Revista Ciencias de la Educación, 19(33), 228-247.https://bit.ly/1T1z0ctCulbertson M. (2016). Bayesian Networks in Educational Assessment: The State of the Field. Applied Psychological Measurement, 40(1) 3–21 https://doi.org/ 10.1177/0146621615590401Cummins D. (2004). The Evolution of Reasoning. En Leighton, J.P. y Sternberg R. J. (Ed.).(2004). The nature of reasoning. Cambridge University Press.Damon, W. (1990). Social Relations and Childrens Thinking Skills. Contributions to Human Development. En Kuhn D (ed). Developmental Perspectives on Teaching and Learning Thinking Skills, pp 95–107. https://doi.org/10.1159/000418983Darling, N., y Steinberg, L. (1993). Parenting style as context: An integrative model. Psychological Bulletin, 113(3), 487–496. https://doi.org/10.1037/0033-2909.113.3.487Dasgupta, I., Schulz, N., Goodman, D. y Gershman, S. (2018). Remembrance of inferences past: Amortization in human hypothesis generation, Cognition, 178, 67-81. https://doi.org/10.1016/j.cognition.2018.04.017De Koning, E., Sijtsma, K., y Hamers, J. M. (2003). Construction and Validation of a Test for Inductive Reasoning. European Journal Of Psychological Assessment, (1). 24. https://doi.org/10.1027//1015-5759.19.1.24De Koning, E., Sijtsma, K., y Hamers, J. M. (2003). Construction and Validation of a Test for Inductive Reasoning. European Journal Of Psychological Assessment, (1). 24. https://doi.org/10.1027//1015-5759.19.1.24Denison, S. y Xu, F. (2012). Probabilistic Inference in Human Infants. En T. Kushnir, y F. Xu (Eds.), Advances in child development and behavior: Rational constructivism in cognitive development. Academic Press, Elsevier. doi.org/10.1016/B978-0-12-397919-3.00002-2Dean Jr., D., y Kuhn, D. (2007). Direct instruction vs. discovery: The long view. Science Education, 91(3), 384–397. https://doi.org/10.1002/sce.20194Dienes, Z., y Perner, J. (1999) A theory of implicit and explicit knowledge. Behavioural and Brain Sciences, 22,735-755. DOI: 10.1017/s0140525x99002186Denison, S., y Xu, F. (2014). The origins of probabilistic inference in human infants. Cognition, 130, 335–347. https://doi.org/ 10.1016/j.cognition.2013.12.001Duque Aristizábal, C. P., Aristizábal, C. P. D., Márquez, Á. V. V., y Gutiérrez, A. P. H. (2010). Comprensión inferencial de textos narrativos en primeros lectores: una revisión de la literatura. Ocnos: Revista De Estudios Sobre Lectura, (6), 35. https://doi.org/10.18239/OCNOS_2010.06.03Ebersbach, M., y Resing, W. M. (2008). Implicit and Explicit Knowledge of Linear and Exponential Growth in 5- and 9-Year-Olds. Journal Of Cognition y Development, 9(3), 286-309. https://doi.org/10.1080/15248370802247962Einav, S. y Robinson E. J. (2010). Children’s sensitivity to error magnitude when evaluating informants. Cognitive Development 25, 218–232, https://doi.org/10.1016/j.cogdev.2010.04.002Eichler, A., y Vogel, M. (2012). Basic modelling of uncertainty: Young students’ mental models. ZDM Mathematics Education, 44(7), 841–854. https://doi.org/10.1007/s11858-012-0451-9Elosua Oliden, P. y Zumbo, B.D. (2008). Coeficientes de fiabilidad para escalas de respuesta categórica ordenada. Psicothema, 20(4), 896-901 http://www.redalyc.org/articulo.oa?id=72720458Epstein, N., y Fischer, M. R. (2017). Academic career intentions in the life sciences: Can research self-efficacy beliefs explain low numbers of aspiring physician and female scientists?. PLOS ONE, 12(9), e0184543. https://doi.org/10.1371/journal.pone.0184543Erickson, J. E., Keil, F. C., y Lockhart, K. L. (2010). Sensing the Coherence of Biology in Contrast to Psychology: Young Children’s Use of Causal Relations to Distinguish Two Foundational Domains. Child Development, 81(1), 390-409. https://doi.org/10.1111/j.1467-8624.2009.01402.xEvans, J. St. B. T. (2020). Hypothetical thinking: Dual processes in reasoning and judgment. Psychology Press and Routledge Classic Editions.Evans, J. St. B. T., y Over, D. E. (2013). Reasoning to and from belief: Deduction and induction are still distinct. Thinking & Reasoning, 19 (3), 267-283. https://cogentoa.tandfonline.com/doi/full/10.1080/13546783.2012.745450Ferrar, S. J., Stack, D. M., Dickson, D. J., Serbin, L. A., Ledingham, J., y Schwartzman, A. E. (2019). Maternal Socialization Responses to Preschoolers’ Success and Struggle: Links to Contextual Factors and Academic and Cognitive Outcomes. Journal of Research in Childhood Education, 1–19. https://doi.org/10.1080/02568543.2019.1607787Fiorini, M., y Keane, M. P. (2014). How the Allocation of Children’s Time Affects Cognitive and Noncognitive Development. Journal of Labor Economics, 32(4), 787–836. https://doi.org/10.1086/677232Fisher, A. V., Godwin, K. E., Matlen, B. J. y Unger, L. (2015). Development of category-based induction and semantic knowledge. Child Development, 86(1), 48-62. https://doi.org/10.1111/cdev.12277Fischer, F., Kollar, I., Ufer, S., Sodian, B., Hussmann, H., Pekrun, R., ... Eberle, J. (2014). Scientific reasoning and argumentation: Advancing an interdisciplinary research agenda in education. Frontline Learning Research, 5, 28–45. http://dx.doi.org/10.14786/flr.v2i3.96Fischbein, E. (1975). The intuitive sources of probabilistic thinking in children. Dordrecht; Reidel Publishing Company.Fizke, E., Butterfill, S., Van de Loo, L., Reindl, E., y Rakoczy, H. (2017). Are there signature limits in early theory of mind?. Journal Of Experimental Child Psychology, 209. https://doi.org/10.1016/j.jecp.2017.05.005Foster-Hanson E, Moty K, Cardarelli A, Ocampo JD, y Rhodes M. (2020). Developmental Changes in Strategies for Gathering Evidence About Biological Kinds. Cogn Sci. 2020 May; 44 (5). https://doi.org/ 10.1111/cogs.12837.Frost, R., Armstrong, B. C., y Christiansen, M. H. (2019). Statistical learning research: A critical review and possible new directions. Psychological Bulletin, 145(12), 1128–1153. doi.org/10.1037/bul0000210Gandhi H. (2018). Understanding Children’s Meanings of Randomness in Relation to Random Generators. En: Batanero, C., y Chernoff, E. J. (Eds.). (2018). Teaching and Learning Stochastics: Advances in Probability Education Research. doi.org/10.1007/978-3-319-72871-1Gelman, S. A. (1988). The development of induction within natural kind and artifact categories. Cognitive Psychology, 20, 65–96. https://doi.org/10.1016/0010-0285(88)90025-4Gelman, S. A. (2003). The essential child: Origins of essentialism in everyday life. New York, NY: Oxford University Press.Gelman, R., y Brenneman, K. (2012). Moving young “scientists-in-waiting” onto science learning pathways: Focus on observation. In J. Shrager y S. Carver (Eds.), The journey from child to scientist: Integrating cognitive development and the education sciences. 155–169. American Psychological Association. https://doi.org/10.1037/13617-008Gelman, S. A., y Davidson, N. S. (2013). Conceptual influences on category-based induction. Cognitive Psychology, (3), 327. https://doi.org/10.1016/j.cogpsych.2013.02.001Gelman, S. A., Leslie, S.-J., Was, A. M., y Koch, C. M. (2015). Children’s interpretations of general quantifiers, specific quantifiers and generics. Language, Cognition, and Neuroscience, 30, 448–461. https://doi.org/10.1080/23273798.2014.931591Gennari , S., Sloman S., Malt , B. , y Fitch, W. ( 2002 ). Motion events in language and cognition. Cognition, 83 ( 1 ), 49 – 79. DOI:10.1016/S0010-0277(01)00166-4Gigerenzer, G. (2015). Calculated risks: How to know when numbers deceive you. New York: Simon y Schuster AudioGil Chaves, L., y Flórez Romero, R. (2013). Desarrollo de habilidades de pensamiento inferencial y comprensión de lectura en niños de tres a seis años. Panorama, 5(9). https://doi.org/10.15765/pnrm.v5i9.39Girotto, V., y Gonzalez, M. (2007). How to elicit sound probabilistic reasoning: Beyond word problems. Behavioral and Brain Sciences, 30, 3, 268. doi 10.1017_S0140525X07001768Gómez, R. L. (2017). Do infants retain the statistics of a statistical learning experience? Insights from a developmental cognitive neuroscience perspective. Phil. Trans. R. Soc. B, 372 (1711). doi.org/10.1098/rstb.2016.0054.Gopnik, A. (2011). The Theory of Theory 2.0: Probabilistic Models and Cognitive Development. Child Development Perspectives. 5, 3, 161-163, HTTPS://DOI.ORG/ 10.1111/j.1750-8606.2011.00179.xsGopnik, A. (2012). Scientific Thinking in Young Children: Theoretical Advances, Empirical Research, and Policy Implications. Science, Sep. 28;337(6102): 1623-7. https://doi.org/10.1126/science.1223416Gopnik, A., y Tenenbaum, J. B. (2007). Bayesian networks, Bayesian learning and cognitive development. Developmental Science, 10(3), 281–287. https://doi.org/10.1111/j.1467-7687.2007.00584.xGopnik, A., Sobel, D.M., Schulz L.E., Glymour C. (2001). Causal Learning Mechanisms in Very Young Children: Two-, Three-, and Four-Year-Olds Infer Causal Relations From Patterns of Variation and Covariation Developmental Psychology . 37, (5), 620-629. https://doi.org/ 10.1037//0012-1649.37.5.620Gopnik, A., Glymour, C., Sobel, D. M., Schulz, L. E., Kushnir, T., y Danks, D. (2004). A Theory of Causal Learning in Children: Causal Maps and Bayes Nets. Psychological Review, 111(1), 3–32. https://doi.org/10.1037/0033-295x.111.1.3Goswami, U. (ed.). (2003). Wiley-Blackwell handbook of childhood cognitive development. New York: WileyGoswami, U. (Ed.). (2010). Wiley-Blackwell handbook of childhood cognitive development. (2nd ed,). Wiley.Granovskiy, B. (2018). Science, Technology, Engineering, and Mathematics (STEM) Education: An Overview. Code R45223; Congressional Research Service, USA. www. crs.govGreiff, S., Wüstenberg, S., Csapó, B., Demetriou, A., Hautamäki, J., Graesser, A.C. y Martin, R. (2014). Domain-general problem solving skills and education in the 21st century, Educational Research Review https://doi.org/ http://dx.doi.org/10.1016/j.edurev.2014.10.002Griffiths, T. L., Tenenbaum, J. B., y Kemp, C. (2012). Bayesian inference. The Oxford handbook of thinking and reasoning, 22-35.Griffin, P., McGaw, B., y Care, E. (Eds.) (2012). Assessment and teaching of 21st century skills. Dordrecht: Springer.Grigorenko E., Sternberg R.J., y Strauss, S. (2006). Practical intelligence and elementary-school teacher Thinking Skills and Creativity Volume 1 issue 1 doi 10.1016_j.tsc.2005.03.001Gweon, H., Tenenbaum, J. B., y Schulz, L. E. (2010). Infants consider both the sample and the sampling process in inductive generalization. Proceedings of the National Academy of Sciences, 107(20), 9066–9071. www.pnas.org/content/pnas/107/20/9066.full.pdfHasson U. (2017). The neurobiology of uncertainty: implications for statistical learning. Phil. Trans. R. Soc. B, 372 (1711). https://doi.org/doi 10.1098_rstb.2016.0048Hayes, B. K., McKinnon, R., y Sweller, N. (2008). The development of category-based induction: Reexamining conclusions from the induction then recognition (ITR) paradigm. Developmental Psychology, 44(5), 1430–1441. https://doi.org/10.1037/0012-1649.44.5.1430Hayes, B. K., Stephens, R. G., Ngo, J., y Dunn, J. C. (2018). The Dimensionality of Reasoning: Inductive and Deductive Inference can be Explained by a Single Process. Journal Of Experimental Psychology. Learning, Memory, And Cognition, https://doi.org/10.1037/xlm0000527Heller, J., Stefanutti, L., Anselmi, P., y Robusto, E. (2015). On the Link between Cognitive Diagnostic Models and Knowledge Space Theory. Psychometrika, (4), 995. https://doi.org/10.1007/s11336-015-9457-xHeit, E. (2000). Properties of inductive reasoning. Psychonomic Bulletin y Review, 7, 569– 592. https://doi.org/10.3758/bf03212996Hernández I. (2010). Factores psicosociales asociados al alto nivel de logro académico de dos Estudiantes sensibles al medio. Tesis presentada para optar al Título de Magíster. Repositorio institucional de la Universidad Pedagógica Nacional. Colombia.Hernández I. y Pacheco P. (2013). Experiencias de innovación didáctica en la enseñanza de la Estadística. En: Inclusión social con responsabilidad, reformas educativas y profesionalización del Docente- Tomo III de la colección “Investigación Educativa y Políticas Públicas”. Universidad de Nayarit- México. ISBN 978-607-7868-70-5. 2014.Herro, D., y Quigley, C. (2016). Exploring teachers’ perceptions of STEAM teaching through professional development: implications for teacher educators. Professional Development in Education, 43(3), 416–438. https://doi.org/10.1080/19415257.2016.1205507Holland, J., Holyoak, K., Nisbett, R. y Thagard, P. (1989). Induction Processes of Inference, Learning, and Discovery. Michigan; The MIT Press.Howe, C. Nunes, T. y Bryant, P. (2011). Rational Number and Proportional Reasoning. International Journal of Science and Mathematics Education, 9, 2, 391-417. doi 10.1007_s10763-010-9249-9pilIfenthaler, D., y Seel, N. M. (2011). A longitudinal perspective on inductive reasoning tasks. Illuminating the probability of change. Learning and Instruction, 21(4), 538–549. https://doi.org/10.1016/J.LEARNINSTRUC.2010.08.004Jacobs, J. E., y Narloch, R. H. (2001). Children’s use of sample size and variability to make social inferences. Journal of Applied Developmental Psychology, 22(3), 311–331. https://doi.org/10.1016/s0193-3973(01)00086-7Jara-Ettinger, J., Gweon, H., Tenenbaum, J. B., y Schulz, L. E. (2015). Children's understanding of the costs and rewards underlying rational action. Cognition, 14. https://doi.org/10.1016/j.cognition.2015.03.00Johnson-Laird, P. N. (1980). Mental models in cognitive science. Cognitive Science, 4, 71-115. https://www.sciencedirect.com/science/article/pii/S0364021381800055Johnson, S. G. B., y Ahn, W. (2017). Causal mechanisms. En M. R. Waldmann (Ed.), Oxford handbook of causal reasoning, p 127-146. Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199399550.013.12Kahneman, D., Slovic, P. y Tversky, A. (eds.) (1982). Judgment under Uncertainty, Heuristics and Biases. Cambridge University Press.Klauer, K. J., Willmes, K., y Phye, G. D. (2002). Inducing Inductive Reasoning: Does It Transfer to Fluid Intelligence?. Contemporary Educational Psychology, (1). 1. https://doi.org/10.1006/ceps.2001.1079Keith, T. Z., y Reynolds, M. R. (2010). Cattell–Horn–Carroll abilities and cognitive tests: What we've learned from 20 years of research. Psychology In The Schools, 47(7), 635-650. DOI:10.1002/pits.20496Kelly, A., Lesh, A. y Baek J. (eds) (2010). Handbook of Design Research Methods in Education_ Innovations in Science, Technology, Engineering, and Mathematics Learning and Teaching. Mahwah, New YorkKemp, C., y Jern, A. (2014). A taxonomy of inductive problems. Psychonomic Bulletin y Review, 21(1), 23-46. https://doi.org/10.3758/s13423-013-0467-3Kim, S., Kalish, C., Harris, P. (2012). Speaker reliability guides children's inductive inferences about novel properties, Cognitive Development, 27, (2), 114-125, https://doi.org/10.1016/j.cogdev.2011.10.004.Kinnear, V., y Clark, J. (2014). Probabilistic reasoning and prediction with young children. In J. Anderson, M. Cavanagh, y A. Prescott (Eds.), Curriculum in focus: Research guided practice (pp. 335–342). MERGA.Koenig, M. A., Cole, C. A., Meyer, M., Ridge, K. E., Kushnir, T., y Gelman, S. A. (2015). Reasoning about knowledge: Children’s evaluations of generality and verifiability. Cognitive Psychology, 83, 22–39. https://doi.org/10.1016/j.cogpsych.2015.08.007Köksal-Tuncer, Ö., y Sodian, B. (2018). The development of scientific reasoning: Hypothesis testing and argumentation from evidence in young children. Cognitive Development, 48, 135–145. doi-org.ezproxy.unal.edu.co/10.1016/j.cogdev.2018.06.011leiKoslowski B. y Masnick A. (2010). Causal Reasoning and Explanation. En: U. Goswami, (Series Ed.). Wiley-Blackwell handbook of childhood cognitive development, (2nd ed.), pp. 341 – 419. New York : Wiley.xuKühhirt, M. y Klein, M. (2018). Early Maternal Employment and Children's Vocabulary and Inductive Reasoning Ability: A Dynamic Approach. Child Development, 89 (2), 91-106. https://doi.org/ 10.1111/cdev.12796Kushnir, T., Wellman, H. M., y Gelman, S. A. (2008). The role of preschoolers’ social understanding in evaluating the informativeness of causal interventions. Cognition, 107(3), 1084–1092. https://doi.org/10.1016/j.cognition.2007.10.004Kushnir, T., Wellman, H. M., y Gelman, S. A. (2009). A self-agency bias in preschoolers’ causal inferences. Developmental Psychology, 45(2), 597–603. https://doi.org/10.1037/a0014727Kuhn, D. (2005). Education for thinking. Cambridge, MA: Harvard University Press.Kuhn, D. (2010). Teaching and learning science as argument. Science Education, 94(5), 810–824. https://doi.org/10.1002/sce.20395Kuhn D. (2010). What is Scientific Thinking and How Does it Develop?. En: U. Goswami, (Series Ed.). Wiley-Blackwell handbook of childhood cognitive development, (2nd ed., pg. 341 – 419). New York: Wiley.Kuhn, D., y Dean, D. J. (2004). Connecting Scientific Reasoning and Causal Inference. Journal of Cognition and Development, 5, 2, 261-288. https://doi.org/10.1207/s15327647jcd0502_5Kuhn, D. y Franklin S. (2006). The Second Decade: What Develops (And How), En: W. Damon (Editor-in-Chief ), D. Kuhn y R. Siegler (Vol. Eds.), Handbook of child psychology: Vol. 2. Cognition, perception, and language (6th ed., pg. 953–993). New York: Wiley.Kuhn, D., Iordanou, K., Pease, M. y Wirkala, C. (2008). Beyond control of variables: What needs to develop to achieve skilled scientific thinking?. Cognitive Development, 23, 435–451. doi-org.ezproxy.unal.edu.co/10.1016/j.cogdev.2008.09.006Kuhn, D., Ramsey, S., y Arvidsson, T. S. (2015). Developing multivariable thinkers. Cognitive Development, 35, 92-110. doi 10.1016_j.cogdev.2014.11.003Kuhn, D., Schauble, L., y Garcia-Mila, M. (1992). Cross-Domain Development of Scientific Reasoning. Cognition and Instruction, 9(4), 285–327. https://doi.org/10.1207/s1532690xci0904_1Kushnir, T., Xu, F., y Wellman, H. M. (2010). Young children use statistical sampling to infer the preferences of other people. Psychological Science, 21, 1134–1140.Lakin, J. y Gambrell, J. (2012). Distinguishing verbal, quantitative, and figural facets of fluid intelligence in young students, Intelligence, 40, 6, 560-570, doi.org/10.1016/j.intell.2012.07.005Lane, J. D., Ronfard, S., Francioli, S. P., y Harris, P. L. (2016). Children’s imagination and belief: Prone to flights of fancy or grounded in reality? Cognition, 152, 127–140. http://dx.doi.org/10.1016/j.cognition.2016.03.022Lane, J. y Shafto, P. (2017). Young children’s attributions of causal power to novel invisible entities. Journal of Experimental Child Psychology, 162, 268-281, doi.org/10.1016/j.jecp.2017.05.015.Lawson, C. A. (2014). Three-year-olds obey the sample size principle of induction: The influence of evidence presentation and sample size disparity on young children’s generalizations. Journal of Experimental Child Psychology, 123, 147–154. https://doi.org/10.1016/j.jecp.2013.12.004Lawson, C. (2017). The Influence of Task Dynamics on Inductive Generalizations: How wSequential and Simultaneous Presentation of Evidence Impacts the Strength and Scope of Property Projections. Journal Of Cognition y Development, 18 (4), 493-513. https://doi.org/10.1080/15248372.2017.1339707Legare, C.H. (2014). The Contributions of Explanation and Exploration to Children's Scientific Reasoning. Child Development Perspectives. Vol. 8, (2) 101-106. HTTPS://DOI.ORG/ 10.1111/cdep.12070Leighton, J.P. y Sternberg R. J. (Ed.).(2004). The nature of reasoning. Cambridge University Press.Leighton, J. P., y Gierl, M. J. (2007). Defining and Evaluating Models of Cognition Used in Educational Measurement to Make Inferences about Examinees' Thinking Processes. Educational Measurement: Issues And Practice, 26(2), 3-16.Legare, C. H., y Lombrozo, T. (2014). Selective effects of explanation on learning during early childhood. Journal of Experimental Child Psychology, 126, 198–212. https://doi.org/10.1016/j.jecp.2014.03.001Lo, Y., Sides, A., Rozelle, J. y Osherson, D. (2002). Evidential diversity and premise probability in young children’s inductive judgments. Cognitive Science - A Multidisciplinary Journal, 26, 181-206. www.elsevier.com/locate/cogsciLombrozo, T. (2016). Explanatory Preferences Shape Learning and Inference. Trends in Cognitive Sciences, 20(10), 748–759. https://doi.org/10.1016/j.tics.2016.08.001Low, J. y Perner J. (2012). Implicit and explicit theory of mind: State of the art. British Journal of Developmental Psychology, (2012), 30, 1–13. HTTPS://DOI.ORG/10.1111/j.2044-835X.2011.02074.xLundberg, S. (2020). Educational gender gaps. Southern Economic Journal, Volume: 87 Issues: 2 416—439. HTTPS://DOI.ORG/ 10.1002/soej.12460Markovits, H., y Barrouillet, P. (2004). Introduction: Why is understanding the development of reasoning important?. En Thinking y Reasoning, 10(2), 113–121. https://doi.org/10.1080/13546780442000006Marcovitch, S. y Lewkowicz, D. J. (2009), Sequence learning in infancy: the independent contributions of conditional probability and pair frequency information. Developmental Science, 12: 1020-1025. https://doi.org/10.1111/j.1467-7687.2009.00838.xMcGuinness Institute, Wellington, New Zealand. (2015). The future of scientific thought, Journal of the Royal Society of New Zealand, 45 (2), 95-100, https://doi.org/ 10.1080/03036758.2015.1013142McCormack, T., Bramley, N., Frosch, C., Fiona, P. y Lagnado, D. (2016). Children’s use of interventions to learn causal structure. Journal of Experimental Child Psychology, 141, 1–22. dx.doi.org/10.1016/j.jecp.2015.06.017Medin, D. L., Coley, J. D., Storms, G., y Hayes, B. L. (2003). A relevance theory of induction. Psychonomic Bulletin y Review, 10(3), 517–532. https://doi.org/10.3758/bf03196515Mercer, N. (2013). The Social Brain, Language, and Goal-Directed Collective Thinking: A Social Conception of Cognition and Its Implications for Understanding How We Think, Teach, and Learn. Educational Psychologist, 48(3), 148–168. https://doi.org/10.1080/00461520.2013.804394Miller, M. R., Giesbrecht, G. F., Müller, U., McInerney, R. J., y Kerns, K. A. (2012). A Latent Variable Approach to Determining the Structure of Executive Function in Preschool Children. Journal Of Cognition y Development, 13(3), 395-423. https://doi.org/10.1080/15248372.2011.585478Ministerio de Educación Nacional. (2009). Desarrollo infantil y competencias en la primera infancia. Colombia. Documento Nº 10, MEN.Ministerio de Educación Nacional. (2011). Valoración del desarrollo en contextos educativos. Documento base, MEN: Colombia.Ministerio de Educación Nacional (2012). Una propuesta de trabajo pedagógico en la educación inicial, documento base para la construcción del lineamiento pedagógico de educación inicial. Documento de trabajo, MEN: Colombia.Mohlhenrich, E., Samsonau, S. y Spencer, R. (2018). Integrating Science Through Authentic Research in Secondary Schools. IEEE Integrated STEM Education Conference (ISEC) - Princeton, NJ, USA . doi 10.1109%2FISECon.2018.8340465Moore, B. (2009). Emotional Intelligence for School Administrators: A Priority for School Reform? American Secondary Education, 37(3), 20–28. http://www.jstor.org/stable/41406313Moore, J.D., Dorofy, P., Jabot, M., y Bouaynaya N. (2018). Earth SySTEM: Investigating Earth from Space, IEEE Integrated STEM Education Conference (ISEC) - Princeton, NJ, USA. doi 10.1109%2FISECon.2018.8340492Morewedge, C.K. y Kahneman D. (2010). Associative processes in intuitive judgment. Trends in Cognitive Sciences, Vol. 14 (10), 435-440Moshman, D. (2004). From inference to reasoning: The construction of rationality. Thinking y Reasoning, 10(2), 221–239. https://doi.org/10.1080/13546780442000024Moulines, U. (2011). El desarrollo moderno de la Filosofía de la Ciencia (1890-2000). México: Instituto de Investigaciones Filosóficas UNAM.Muniz, M., Seabra, A. G., y Primi, R. (2012). Validity and Reliability of the Inductive Reasoning Test for Children - IRTC. Psicologia-Reflexao E Critica, 25(2), 275-285.Nancekivell, S.H. y Friedman, O. (2017). She Bought the Unicorn From the Pet Store: Six- to Seven-Year-Olds Are Strongly Inclined to Generate Natural Explanations. Dev. Psychol. Vol. 53, No. 6, https://doi.org/1079–1087/dev0000311National Science Foundation. (2007). Women, Minori- ties, and Persons with Disabilities in Science and Engineering. National Science Foundation, Division of Science Resource Statistics. Arlington: U.S.A.Nguyen, S. P. (2012). Inductive Selectivity in Children's Cross-Classified Concepts. Child Development, 83(5), 1748-1761. https://doi.org/10.1111/j.1467-8624.2012.01812.xNguyen, S., Gordbron C., Chevalier, T. y Girgis, H. (2016). Trust and doubt: An examination of children’s decision to believe what they are told about food, Journal of Experimental Child Psychology, 144, 66-83. dx.doi.org/10.1016/j.jecp.2015.10.015Nisbett, R. E., Krantz, D. H., Jepson, C., y Kunda, Z. (1983). The use of statistical heuristics in everyday inductive reasoning. Psychological Review, 90(4), 339–363. https://doi.org/10.1037/0033-295x.90.4.339Nisbett, R. y Ross, L. (1986). Human Inference: Strategies And Shortcomings Of Social Judgment. New Jersey: Prentice-Hall.Nisbett, R. E., Choi, I., Peng, K., y Norenzayan, A. (2001). Culture and Systems of Thought: Holistic Versus Analytic Cognition. Psychological Review, (2), 291-310. https://doi.org/10.1037//0033-295X.108.2.291Nisbett, R., Krantz, D., Jepson,C. y Fong G. T. (1982). Improving inductive inference. En Kahneman, D., Paul Slovic, Amos Tversky (eds.) (1982). Judgment under Uncertainty, Heuristics and Biases. Cambridge University Press.Nisbett, R. E., Aronson, J., Blair, C., Dickens,W., Flynn, J., Halpern, D., et al. (2012). Intelligence: New findings and theoretical developments. American Psychologist, 67, 2, 130–159 doi 10.1037/a0026699.Noyes, A., y Christie, S. (2016). Children Prefer Diverse Samples for Inductive Reasoning in the Social Domain. Child Development, 87(4), 1090-1098. https://doi.org/10.1111/cdev.12522OECD. (2009). Programme for International Student Assessment. An overview. Paris: OECD.OECD (2012a). Better skills, better jobs, better lives. A strategic approach to skills policies. Paris: OECD.OECD (2013a). PISA 2012 assessment and analytical framework. Paris: OECD Publishing.OECD. (2015) The ABC of Gender Equality in Education: Aptitude, Behaviour, Confidence. PISA: OECD Publishing. https://doi.org/10.1787/9789264229945-enOpfer, J. E., y Bulloch, M. J. (2007). Causal relations drive young children’s induction, naming, and categorization. Cognition, 105, 206–217. https://doi.org/10.1016/j.cognition.2006.08.006Osborne, J. (2013). The 21st century challenge for science education: Assessing scientific reasoning. Thinking Skills and Creativity, 10, 265-279. dx.doi.org/10.1016/j.tsc.2013.07.006Palejwala, M. H., y Fine, J. G. (2015). Gender differences in latent cognitive abilities in children aged 2 to 7. Intelligence, 4896-108. https://doi.org/10.1016/j.intell.2014.11.004Palmquist, C. M., y Jaswal, V. K. (2015). Preschoolers’ inferences about pointers and labelers: The modality matters. Cognitive Development, 35, 178–185. https://doi.org/10.1016/j.cogdev.2015.06.003Pavlidou, E. V., y Bogaerts, L. (2019). Implicit Statistical Learning across Modalities and its Relationship with Reading in Childhood. Front Psychol. https://doi.org/10.3389/fpsyg.2019.01834Perner, J. y Dienes, Z. (2002). Implicit Versus Explicit Representation and Intra‐ Versus Inter‐Modular Processing. Computational Intelligence, 18: 55-58. https://doi.org/10.1111/1467-8640.00182Perret, P. (2015). Children’s Inductive Reasoning: Developmental and Educational perspectives. Journal of Cognitive Education and Psychology, 14 (3), 389 - 408. 10.1891/1945-8959.14.3.389Primi, R., Rocha da Silva, M. C., Rodrigues, P., Muniz, M., y Almeida, L. S. (2013). The use of the bi-factor model to test the uni-dimensionality of a battery of reasoning tests. Psicothema, 25(1), 115-122. https://doi.org/10.7334/psicothema2011.393Pavlidou, E., y Bogaerts, L. (2019). Implicit statistical learning across modalities and its relationship with reading in childhood. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2019.01834Perret, P. (2015). Children’s Inductive Reasoning: Developmental and Educational perspectives. Journal of Cognitive Education and Psychology, 14 (3), 389 - 408. https://doi.org/10.1891/1945-8959.14.3.389Petticrew, M. y Roberts, H. (2006). Systematic reviews in the social sciences. A practical guide. Oxford: Blackwell Publishing.Pillow, B. (2002). Children's and adults' evaluation of the certainty of deductive inferences, inductive inferences, and guesses. Child Development, 3, 779-792.Quinn P. (2010). Born to Categorize. In U. Goswami, (Series Ed.). Wiley-Blackwell handbook of childhood cognitive development., New York: Wiley (2nd ed, p. 129). doi.org/10.1111/1467-8624.00438Ricco, R. B. (2015). The Development of Reasoning. Handbook of Child Psychology and Developmental Science, 1–52. https://doi.org/10.1002/9781118963418.CHILDPSY213Rhodes, M., l, S. A., y Brickman, D. (2008). Developmental Changes in the Consideration of Sample Diversity in Inductive Reasoning. Journal Of Cognition y Development, 9(1), 112-143. https://doi.org/10.1080/15248370701836626dienRhodes, M., y Liebenson, P. (2015). Continuity and change in the development of category-based induction: The test case of diversity-based reasoning. Cognitive Psychology, 74. https://doi.org/10.1016/j.cogpsych.2015.07.003Ruffman, T., Taumoepeau, M., y Perkins, C. (2012). Statistical learning as a basis for social understanding in children. British Journal of Developmental Psychology, 30, 87–104, https://doi.org/10.1111/j.2044-835X.2011.02045.xSaffran, J. R., y Kirkham, N. Z. (2018). Infant statistical learning. Annual Review of Psychology, 69, 181–208. http://dx.doi.org/10.1146/annurev-psych-122216-011805.Samarapungavan, A., Vosniadou, S., y Brewer, W. F. (1996). Mental models of the earth, sun, and moon: Indian children’s cosmologies. Cognitive Development, 11(4), 491–521. https://doi.org/10.1016/s0885-2014(96)90015-5Samarapungavan, A. Mantzicopoulos P. y Patrick H. (2008). Learning science through inquiry in kindergarten. Science Education. 92, 5, 868-908. doi 10.1002%2Fsce.20275Schulz, L. (2012). The origins of inquiry: inductive inference and exploration in early childhood. Trends in Cognitive Sciences, 16, 7, 382-389. https://doi.org /10.1016/j.tics.2012.06.004Schauble, L. (1996). The development of scientific reasoning in knowledge-rich contexts. Developmental Psychology, 32(1), 102–119. https://doi.org/10.1037/0012-1649.32.1.102Schulz, L., Goodman, N., Tenenbaum, J. y Jenkins, A. (2008). Going beyond the evidence: Abstract laws and preschoolers' responses to anomalous data. Cognition, 109(2), 211-223. https://doi.org/10.1016/j.cognition.2008.07.017Schulz, L. E., y Sommerville, J. (2006). God does not play dice: Causal determinism and preschoolers’ causal inferences. Child Development, 77(2), 427–442. https://pubmed.ncbi.nlm.nih.gov/16611182Schwichow, M., Croker, S., Zimmerman, C., Hoffler, T. y Hartig, H. (2016). Teaching the control-of-variables strategy: A meta-analysis. Developmental Review, 37. doi-org.ezproxy.unal.edu.co/10.1016/j.dr.2015.12.001Setoh, P., Wu, D., Baillargeon, R., y Gelman, R. (2013). Young infants have biological expectations about animals. Proceedings of the National Academy of Sciences, USA, 110 (40), 15937-15942. https://doi.org/ 10.1073/pnas.1314075110Shafto, P., Kemp, C., Bonawitz, E. B., Coley, J. D., y Tenenbaum, J. B. (2008). Inductive reasoning about causally transmitted properties. Cognition, 109175-192. https://doi.org/10.1016/j.cognition.2008.07.006Strand-Cary, M., y Klahr, D. (2008). Developing elementary science skills: Instructional effectiveness and path independence. Cognitive Development, 23(4), 488–511. https://doi.org/10.1016/j.cogdev.2008.09.005Siler, S. A., Klahr, D., y Price, N. (2012). Investigating the mechanisms of learning from a constrained preparation for future learning activity. Instructional Science, 41(1), 191–216. https://doi.org/10.1007/s11251-012-9224-7Simon, H. A., y Lea, G. (1974). Problem solving and rule induction: A unified view. In L. W. Gregg (Ed.), Knowledge and cognition (pp. 105-127). Potomac, MD: Erlbaum.Singh, M. (2021). Acquisition of 21st Century Skills Through STEAM Education. Academia Letters. https://doi.org/10.20935/AL712Shipley, E. y Shepperson, B. (2006). Test Sample Selection by Preschool Children: Honoring Diversity. Memory and Cognition, 34(7), 1444 -1451, doi.org/10.3758/BF03195909Shtulman, A., y Schulz, L. (2008). The relation between essentialist beliefs and evolutionary reasoning. Cognitive Science, 32 (6), 1049–1062. https://doi.org/10.1080/03640210801897864Shye, S. (1988). Inductive and Deductive Reasoning: A Structural Reanalysis of Ability Tests. Journal Of Applied Psychology, 73(2), 308-311Slone, L.K., Johnson, S. P. (2018). When learning goes beyond statistics: Infants represent visual sequences in terms of chunks, Cognition, Volume 178, 2018, Pages 92-102, ISSN 0010-0277, https://doi.org/10.1016/j.cognition.2018.05.016.Sloman, S. A. (2005) Causal models: how people think about the world and its alternatives. Oxford University Press, Inc. : New YorkSloutsky, V. M., Wei D., Fisher, A. y Kloos, H. (2015). Conceptual influences on induction: A case for a late onset, Cognitive Psychology, 82, 1-31. dx.doi.org/10.1016/j.cogpsych.2015.08.005Sobel, D.M. y Buchanan D.W. (2009). Bridging the gap: Causality-at-a-distance in children’s categorization and inferences about internal properties. Cognitive Development, 24, 274–283 https://doi.org/10.1016/j.cogdev.2009.03.003Sobel, D.M., Erbb, C.D., Tassina, T. y Skolnick Weisberg D. (2017). The Development of Diagnostic Inference About Uncertain Causes. Journal of Cognition and Development, Vol. 18, No. 5, 556–576 https://doi.org/10.1080/15248372.2017.1387117Sobel, D. M., y Legare, C. (2014). Causal learning in children. WIRE-Cognitive Science, 5, 413–427. https://doi.org/10.1002/wcs.1291Sternberg , R. (Ed.) ( 1984 ). Mechanisms of cognitive development. New York: FreemanSternberg, R. (2010). Individual Differences in Cognitive Development. En U. Goswami, (Series Ed.).Wiley-Blackwell handbook of childhood cognitive development. New York: Wiley.Sternberg, R., y Gardner, M. (1983). Unities in inductive reasoning. Journal Of Experimental Psychology: General, 112(1), 80-116. https://doi.org/10.1037/0096-3445.112.1.80Sternberg, R. y Prezt, J. (Ed.) (2005). Cognition and Intelligence: Identifying the Mechanisms of the Mind. New York: Cambridge University Press.Sternberg, R. J., Sternberg, K., y Mio, J. S. (2012). Cognitive psychology. Australia: Wadsworth/Cengage Learning.Sü, H. M., Oberauer, K., Wittmann, W. W., Wilhelm, O., y Schulze, R. (2002). Working-memory capacity explains reasoning ability-and a little bit more. Intelligence -Norwood- Mutidisciplinary Journal. (3). 261- 276. https://www.sciencedirect.com/science/article/pii/S0160289601001003Sutherland, S. L. y Cimpian, A. (2017). Inductive generalization relies on category representations. Psychonomic Bulletin y Review, 24(2), 632-636. https://doi.org/10.3758/s13423-015-0951-zTenenbaum, J. B., Kemp, C., Griffiths, T. L., y Goodman, N. D. (2011). How to Grow a Mind: Statistics, Structure, and Abstraction. Science, 331(6022), 1279–1285. https://doi.org/10.1126/science.1192788Teglas, E., Vul, E., Girotto, V., Gonzalez, M., Tenenbaum, J. B., y Bonatti, L. L. (2011). Pure reasoning in 12-month-old infants as probabilistic inference. Science, 332, 1054–1058. https://doi.org/10.1126/science.1196404Tummeltshammer, K.S., y Kirkham, N.Z. (2013). Learning to look: probabilistic variation and noise guide infants’ eye movements. Developmental Science, 16, 760–771. https://doi.org/10.1111/desc.12064Tomasello, M. (2010). Language Development. In U. Goswami, (Series Ed.). Wiley-Blackwell handbook of childhood cognitive development .New York : WileyTummeltshammer, K., Amso, D., French, R. M., y Kirkham, N. Z. (2016). Across space and time: infants learn from backward and forward visual statistics. Developmental Science, 1–9. doi.org/10.1111/desc.12474.Thurstone, L. L. y Thurstone, T. G. (1941). Factorial studies of intelligence. Chicago: University of Chicago Press.Turiel, E. (2012). Moral reasoning, cultural practices, and social inequalities. Innovación Educativa, 12 (59), pp 17-32. www.scielo.org.mx/pdf/ie/v12n59/v12n59a3.pdfUNESCO. (2005). Towards knowledge societies. Paris: United Nations Educational, Scientific, and Cultural Organization.UNESCO (2015). Replantear la educación: Hacia un bien común mundial?. Disponible en: (www.unesco.org/open-access/terms-use-ccbysa-sp)UNESCO. (2017) Cracking the code: Girls’ and women’s education in science, technology, engineering and mathematics (STEM). París: United Nations Educational, Scientific and Cultural Organization. http://unesdoc.unesco.org/images/0025/002534/253479e.pdfVandekerckhove, J. (2014). A cognitive latent variable model for the simultaneous analysis of behavioral and personality data. Journal Of Mathematical Psychology, 6058-71. https://doi.org/10.1016/j.jmp.2014.06.004van Laar, E., Deursen, A., Van Dijk, J. y Haan, J. (2020). Determinants of 21st-Century Skills and 21st-Century Digital Skills for Workers: A Systematic Literature Review. SAGE Open. 10. 1-14. 10.1177/2158244019900176.Vega E. (2018). The Wisdom of our Native American Tribes: Advanced Math, Science and Culture for the Future. IEEE Integrated STEM Conference (ISEC). www.linkedin.com/in/ernesto-vega-janica-50231319Vygotsky, L. S. (1988). El desarrollo de los procesos psicológicos superiores. Barcelona, España: Crítica. (Año de publicación del original: 1931)Waismeyer, A., y Meltzoff, A. N. (2017). Learning to make things happen: Infants' observational learning of social and physical causal events. Journal Of Experimental Child Psychology, 58. https://doi.org/10.1016/j.jecp.2017.04.018Waismeyer, A., Meltzoff, A. N., y Gopnik, A. (2015). Causal learning from probabilistic events in 24-month-olds: An action measure. Developmental Science, 18, 175–182. https://doi.org/10.1111/desc.12208Washer, P. (2007). Revisiting Key Skills: A Practical Framework for Higher Education. Quality in Higher Education, 13(1), 57–67. https://doi.org/10.1080/13538320701272755Watson, G., y Glaser, E. M. (1964). Manual for the Watson-Glaser critical thinking appraisal. New York: Harcourt, Brace, JovanovichWaxman, S. (2010). Early Word-Learning and Conceptual Development: Everything Had a Name, and Each Name Gave Birth to a New Thought. In U. Goswami, (Series Ed.). Wiley-Blackwell handbook of childhood cognitive development . (2nd ed.). New York: Wiley.Waldmann, M. y Hagmayer, Y. (2006). Categories and causality: The neglected direction. CognitiveWellman, H. M. (2014). Making Minds: How Theory of Mind Develops. Oxford University Press : New YorkWild y Pfannkuch (1999), Statistical Thinking in Empirical Enquiry, International Statistical Review, 67, pp. 223 –265. doi.org/10.1111/j.1751-5823.1999.tb00442.xWilkening, F., y Cacchione, T. (2010). Children's intuitive physics. In U. Goswami (Ed.), The Wiley-Blackwell handbook of childhood cognitive development (pp. 473–496). Wiley-Blackwell.World Economic Forum. (2020). Schools of the Future: Defining New Models of Education for the Fourth Industrial Revolution, 2020. WEF_Schools_of_the_Future_Report_2019.pdf (weforum.org)World Economic Forum. (2021). Building A Common Language for Skills at Work: A Global Taxonomy. https://www.weforum.org/reports/building-a-common-language-for-skills-at-work-a-global-taxonomyWu R, Gopnik A, Richardson DC, Kirkham NZ. (2011). Infants learn about objects from statistics and people. Dev. Psychol. 47(5):1220–29. https://doi.org/ 10.1037/a0024023Xu, F. y Garcia, V. (2008). Intuitive Statistics by 8-Month-Old Infants. Proceedings Of The National Academy Of Sciences Of The United States Of America, 105 (13), 5012-5015. https://doi.org/10.1073/pnas.0704450105Xu, F., y Griffiths, T. L. (2011). Probabilistic models of cognitive development: towards a rational constructivist approach to the study of learning and development. Cognition, 120 (3), 299–301 doi.org/10.1016/j.cognition.2011.06.008Xu, F. y Kushnir, T. (Eds.). (2012). Rational Constructivism in Cognitive Development. Waltham, MA: Academic Press.Zheng, D., Shu G., y Wong, K. W. (2018). Global Engineering. Education Conference (EDUCON) - Santa Cruz de Tenerife, Islas Canarias, España. https://doi.org/10.1109%2FEDUCON.2018.8363268Zhu, L., y Gigerenzer, G. (2006). Children can solve Bayesian problems: The role of representation in mental computation. Cognition, 98(3), 287–308. https://doi.org/10.1016/j.cognition.2004.12.003Zimmerman, C. (2000). The Development of Scientific Reasoning Skills. Developmental Review, (20), 99-149. https://doi.org/10.1006/drev.1999.0497Zimmerman, C. (2007). The development of scientific thinking skills in elementary and middle school. Developmental Review, 2, 172-223. https://doi.org/10.1016/j.dr.2006.12.001EstudiantesGrupos comunitariosInvestigadoresMaestrosMedios de comunicaciónPadres y familiasPersonal de apoyo escolarORIGINAL52381071.2023.pdf52381071.2023.pdfTesis de Doctorado en Psicologíaapplication/pdf4561703https://repositorio.unal.edu.co/bitstream/unal/83552/2/52381071.2023.pdfb1450db0a8dde68278a6baa9ff296d82MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-85879https://repositorio.unal.edu.co/bitstream/unal/83552/3/license.txteb34b1cf90b7e1103fc9dfd26be24b4aMD53THUMBNAIL52381071.2023.pdf.jpg52381071.2023.pdf.jpgGenerated Thumbnailimage/jpeg5308https://repositorio.unal.edu.co/bitstream/unal/83552/4/52381071.2023.pdf.jpg3351b92c5565651b8c3719e25d32bfb8MD54unal/83552oai:repositorio.unal.edu.co:unal/835522024-08-17 00:00:18.917Repositorio Institucional Universidad Nacional de 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