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Artículos

Vol. 25 Núm. 3 (2022): Noviembre

RELACIÓN ENTRE PERCEPCIONES DE LA ENSEÑANZA, SEXO Y ACTITUDES HACÍA LAS MATEMÁTICAS DE ESTUDIANTES

DOI
https://doi.org/10.12802/relime.22.2533
Enviado
junio 20, 2023
Publicado
2023-06-21

Resumen

Este artículo explora la relación entre las percepciones de estudiantes sobre el tipo de enseñanza que experimentan en matemáticas [más o menos centrada en el estudiantado] y sus emociones, autoconcepto y disposición hacia las matemáticas. También considera la pregunta de si existen diferencias en esta relación con respecto al sexo del estudiantado. Utiliza datos de casi 300 estudiantes de Chile de 7 año, agrupados en 8 aulas de clases. El análisis correlacional sugiere la existencia de una asociación positiva y significativa entre cuán centrada en los estudiantes es percibida la enseñanza y actitudes más positivas del estudiantado hacia las matemáticas. Sin embargo, este efecto es independiente del sexo, sugiriendo que la enseñanza centrada en estudiantes no necesariamente ofrecen una ventaja para las niñas, sino que son positivas tanto para alumnas como para alumnos.

Citas

  1. "Aeschlimann, B., Herzog, W. y Makarova, E. (2016). How to foster students’ motivation in mathematics and science classes and promote students’ STEM career choice. A study in Swiss high schools. International Journal of Educational Research, 79, 31-41. https://doi.org/10.1016/j.ijer.2016.06.004
  2. Aguinis, H. (1995). Statistical power with moderated multiple regression in management research. Journal of Management, 21(6), 1141-1158. https://doi.org/10.1177/014920639502100607
  3. Askew, M., Brown, M., Rhodes, V., Johnson, D. y Wiliam, D. (1997). Effective teachers of numeracy. Kings College.
  4. Bartholomew, H., Darragh, L., Ell, F. y Saunders, J. (2011). ‘I’m a natural and I do it for love!’: exploring students’ accounts of studying mathematics. International Journal of Mathematical Education in Science and Technology, 42(7), 915-924. https://doi.org/10.1080/0020739X.2011.608863
  5. Bassi, M., Blumberg, R. L. y Díaz, M. (2016). Under the"" Cloak of Invisibility"": Gender bias in teaching practices and learning outcomes. IDB Working Paper Series. Inter-American Development Bank. https://doi.org/10.18235/0000446
  6. Becker, J. R. (1995). Women’s ways of knowing in mathematics. En G. Kaiser y P. Rogers, (Eds.), Equity in mathematics education: Influences of feminism and culture (pp. 163–174). The Falmer Press. https://files.eric.ed.gov/fulltext/ED391849.pdf
  7. Belenky, M., Clinchy, B., Goldberger, N. y Tarule, J. (1986). Women’s ways of knowing: the development of self, voice and mind. Basic Books.
  8. Black, L. (2004). Differential participation in whole-class discussions and the construction of marginalised identities. Journal of Educational Enquiry, 5(1), 34–54. https://ojs.unisa.edu.au/index.php/EDEQ/article/view/516
  9. Blázquez, C., Álvarez, P., Bronfman, N. y Espinosa, J. F. (2009). Factores que influencian la motivación de escolares por las áreas tecnológicas e ingeniería. Calidad en la Educación, 31, 46-64. https://doi.org/10.31619/caledu.n31.162
  10. Boaler, J. (2002). Experiencing School Mathematics: Traditional and Reform Approaches to Teaching and Their Impact on Student Learning. Lawrence Erlbaum Associates. https://doi.org/10.4324/9781410606365
  11. Boaler, J. y Greeno, G. G. (2000). Identity, agency, and knowing in mathematics worlds. En J. Boaler (Ed.), Multiple perspectives on mathematics teaching and learning (pp. 171–200). Ablex Publishing.
  12. Boaler, J. y Staples, M. (2008). Creating Mathematical Futures through an Equitable Teaching Approach: The Case of Railside School. The Teachers College Record, 110(3), 608–645. https://doi.org/10.1177/016146810811000302
  13. Bond, T. G. y Fox, C. M. (2001). Applying the Rasch Model: Fundamental Measurement in the Human Sciences. Lawrence Erlbaum Associates.
  14. Bordón, P., Canals, C. y Mizala, A. (2020). The gender gap in college major choice in Chile. Economics of Education Review, 77(102011), 1-27. https://doi.org/10.1016/j.econedurev.2020.102011
  15. Buerk, D. (1985). The voices of women making meaning in mathematics. Journal of Education, 16(3), 59-70. https://doi.org/10.1177/002205748516700304
  16. Buschor, C. B., Berweger, S., Frei, A. K. y Kappler, C. (2014). Majoring in STEM-What Accounts for Women's Career Decision Making? A Mixed Methods Study. Journal of Educational Research, 107(3), 167-176, https://doi.org/10.1080/00220671.2013.788989
  17. Carrasco Salazar, E. y Valenzuela Vidal, D. (2021). Mujeres que eligen ciencias: autoeficacia, expectativas de resultado, barreras y apoyos percibidos para la elección de carrera universitaria. Calidad en la Educación, (54), 271-302. http://dx.doi.org/10.31619/caledu.n54.994
  18. Ceci, S. J., Williams, W. M. y Barnett, S. M. (2009). Women's underrepresentation in science: sociocultural and biological considerations. Psychological bulletin, 135(2), 218. https://doi.org/10.1037/a0014412
  19. Cerinsek, G., Hribar, T., Glodez, N. y Dolinsek, S. (2013). Which are my future career priorities and what influenced my choice of studying science, technology, engineering or mathematics? Some insights on educational choice—case of Slovenia. International Journal of Science Education, 35(17), 2999-3025. https://doi.org/10.1080/09500693.2012.681813
  20. Cheryan, S. y Plaut, V. C. (2010). Explaining underrepresentation: A theory of precluded interest. Sex roles, 63(7), 475-488. https://doi.org/10.1007/s11199-010-9835-x
  21. Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159. https://doi.org/10.1037/0033-2909.112.1.155
  22. Conicyt (2017). Diagnóstico Igualdad de Género en Ciencia, Tecnología e Innovación en Chile. Levantando evidencias, construyendo avances y proponiendo recomendaciones desde la colaboración pública y privada. Comisión Nacional de Investigación Científica y Tecnológica de Chile. https://www.conicyt.cl/wp-content/uploads/2015/03/Diagnostico-Equidad-de-Genero-en-CTI-MESA-CONICYT_2017.pdf
  23. Cooper, K. S. (2013). Eliciting Engagement in the High School Classroom A Mixed-Methods Examination of Teaching Practices. American Educational Research Journal, 51(2), 363-402. https://doi.org/10.3102/0002831213507973
  24. Crawford, J. R. y Henry, J. D. (2004). The Positive and Negative Affect Schedule (PANAS): Construct validity, measurement properties and normative data in a large non-clinical sample. British Journal of Clinical Psychology, 43(3), 245. https://doi.org/10.1348/0144665031752934
  25. Cvencek, D., Meltzoff, A. y Greenwald, A. (2011). Math-Gender stereotypes in elementary school children. Child Development, 82(3), 766-779. https://doi.org/10.1111/j.1467-8624.2010.01529.x
  26. Darragh, L. (2015). Recognising ‘good at mathematics’: using a performative lens for identity. Mathematics Education Research Journal, 27(1), 83-102. https://doi.org/10.1007/s13394-014-0120-0
  27. Daniels, L. M., Stupnisky, R. H., Pekrun, R., Haynes, T. L., Perry, R. P. y Newall, N. E. (2009). A longitudinal analysis of achievement goals: From affective antecedents to emotional effects and achievement outcomes. Journal of Educational Psychology, 101(4), 948-963. https://doi.org/10.1037/a0016096
  28. Del Río, M. F. y Strasser, K. (2013). Preschool children’s beliefs about gender differences in academic skills. Sex Roles, 68(3-4), 231-238. https://doi.org/10.1007/s11199-012-0195-6
  29. Del Río, M. F., Susperreguy, M. I., Strasser, K. y Salinas, V. (2017). Distinct influences of mothers and fathers on kindergartners’ numeracy performance: The role of math anxiety, home numeracy practices, and numeracy expectations. Early Education and Development, 28(8), 939-955. https://doi.org/10.1080/10409289.2017.1331662
  30. Desimone, L. y Long, D. A. (2010). Teacher effects and the achievement gap: Do teacher and teaching quality influence the achievement gap between Black and White and high-and low-SES students in the early grades. Teachers College Record, 112(12), 3024-3073. https://doi.org/10.1177/016146811011201206
  31. Desimone, L., Smith, T. y Frisvold, D. (2009). Survey measures of classroom instruction: Comparing student and teacher reports. Educational Policy, 24(2), 267-329. https://doi.org/10.1177/0895904808330173
  32. Dufey, M. y Fernández, A. M. (2012). Validez y confiabilidad del Positive Affect and Negative Affect Schedule (PANAS) en estudiantes universitarios chilenos. Revista Iberoamericana de Diagnóstico y Evaluación Psicológica, 34(2), 157-173. https://www.redalyc.org/articulo.oa?id=459645438008
  33. Eccles, J. S. y Wang, M. T. (2016). What motivates females and males to pursue careers in mathematics and science? International Journal of Behavioral Development, 40(2), 100-106. https://doi.org/10.1177/0165025415616201
  34. Eccles, J., Wigfield, A., Harold, R. D. y Blumenfeld, P. (1993). Age and Gender Differences in Children's Self- and Task Perceptions during Elementary School. Child Development, 64, 830-847. https://doi.org/10.2307/1131221
  35. Ellis, M. W., Malloy, C. E., Meece, J. L. y Sylvester, P. R. (2007). Convergence of observer ratings and student perceptions of reform practices in sixth-grade mathematics classrooms. Learning Environments Research, 10(1), 1-15. https://doi.org/10.1007/s10984-007-9022-3
  36. Espinoza, A. M. y Taut, S. (2016). El rol del género en las interacciones pedagógicas de aulas de matemática chilenas. Psykhe, 25(2), 1-18. https://doi.org/10.7764/psykhe.25.2.858
  37. Espinoza, A. M. y Taut, S. (2020). Gender and psychological variables as key factors in mathematics learning: A study of seventh graders in Chile. International Journal of Educational Research, 103(101611), 1-16. https://doi.org/10.1016/j.ijer.2020.101611
  38. Evans, J. (2000). Adult’s mathematical thinking and emotions: A study of numerate practises. Routledge Falmer.
  39. Fennema, E. y Sherman, J. (1977). Sex-related differences in mathematics achievement, spatial visualisation and affective factors. American Educational Research Journal, 14(1), 51-71. https://doi.org/10.2307/1162519
  40. Fernández, M. C., Briceño, C. y Mora, G. (2020). Segregación de género en elección de estudios superiores. Proyecto Fondecyt N.° 1191585.
  41. Franklin, D. (2013). A Practical Guide to Gender Diversity for Computer Science Faculty. Synthesis Lectures on Professionalism and Career Advancement for Scientists and Engineers, 1(2), 1–81. https://doi.org/10.1007/978-3-031-02508-2
  42. Fredricks, J. A. y Eccles, J. S. (2002). Children's competence and value beliefs from childhood through adolescence: growth trajectories in two male-sex-typed domains. Developmental psychology, 38(4), 519–533. https://doi.org/10.1037/0012-1649.38.4.519
  43. Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H. y Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering, and mathematics. Proceedings of the National Academy of Sciences, 111(23), 8410-8415. https://doi.org/10.1073/pnas.1319030111
  44. French, J. y French, P. (1984). Gender Imbalances in the Primary Classroom: An Interactional Account. Educational Research 2(2), 127-36. https://doi.org/10.1080/0013188840260209
  45. Frenzel, A. C., Pekrun, R. y Goetz, T. (2007). Girls and mathematics—A “hopeless” issue? A control-value approach to gender differences in emotions towards mathematics. European Journal of Psychology of Education, 22(4), 497-514. https://doi.org/10.1007/BF03173468
  46. Geist, K. (2008). Different, Not Better: Gender Differences in Mathematics Learning and Achievement. Journal of Instructional Psychology, 35(1), 43–52.
  47. Gilbert, M. C., Musu-Gillette, L. E., Woolley, M. E., Karabenick, S. A., Strutchens, M. E. y Martin, W. G. (2014). Student perceptions of the classroom environment: Relations to motivation and achievement in mathematics. Learning Environments Research, 17(2), 287-304. https://doi.org/10.1007/s10984-013-9151-9
  48. Gjicali, K. y Lipnevich, A. A. (2021). Got math attitude? (In) direct effects of student mathematics attitudes on intentions, behavioral engagement, and mathematics performance in the US PISA. Contemporary Educational Psychology, 67, 102019. https://doi.org/10.1016/j.cedpsych.2021.102019
  49. Goetz, T., Frenzel, A. C., Hall, N. C. y Pekrun, R. (2008). Antecedents of academic emotions: Testing the internal/external frame of reference model for academic enjoyment. Contemporary Educational Psychology, 33(1), 9-33. https://doi.org/10.1016/j.cedpsych.2006.12.002
  50. Graddol, D. y Swann, J. (1989). Gender voices. Cambridge University Press
  51. Hamilton, L. S., McCaffrey, D. F., Stecher, B. M., Klein, S. P., Robyn, A. y Bugliari, D. (2003). Studying large-scale reforms of instructional practice: An example from mathematics and science. Educational Evaluation and Policy Analysis, 25(1), 1–29. https://doi.org/10.3102/01623737025001001
  52. Han, S. (2017). Korean students’ attitudes toward STEM project-based learning and major selection. Educational Sciences: Theory & Practice, 17(2), 529–548. https://doi.org/10.12738/estp.2017.2.0264
  53. Hannula, M. S. (2012). Exploring new dimensions of mathematics-related affect: embodied and social theories. Research in Mathematics Education, 14(2), 137-161. https://doi.org/10.1080/14794802.2012.694281
  54. Heyd-Metzuyanim, E. y Sfard, A. (2012). Identity struggles in the mathematics classroom: On learning mathematics as an interplay of mathematizing and identifying. International Journal of Educational Research, 51, 128-145. https://doi.org/10.1016/j.ijer.2011.12.015
  55. Ireson, J. y Hallam, S. (2005). Pupils' liking for school: Ability grouping, self‐concept and perceptions of teaching. British Journal of Educational Psychology, 75(2), 297-311. https://doi.org/10.1348/000709904X24762
  56. Jacobs, J. E., Lanza, S., Osgood, D. W., Eccles, J. S. y Wigfield, A. (2002). Changes in children’s self-competence and values: Gender and domain differences across grades one through twelve. Child Development, 73(2), 509-527. https://doi.org/10.1111/1467-8624.00421
  57. Kahle, J. B., Meece, J. y Scantlebury, K. (2000). Urban African‐American middle school science students: Does standards‐based teaching make a difference? Journal of Research in Science Teaching, 37(9), 1019-1041. https://doi.org/10.1002/1098-2736(200011)37:9%3C1019::AID-TEA9%3E3.0.CO;2-J
  58. Kember, D. y Gow, L. (1994). Orientations to teaching and their effect on the quality of student learning. The Journal of Higher Education, 65(1) 58-74. https://doi.org/10.2307/2943877
  59. Le, V. N., Lockwood, J. R., Stecher, B. M., Hamilton, L. S. y Martinez, J. F. (2009). A longitudinal investigation of the relationship between teachers’ self-reports of reform-oriented instruction and mathematics and science achievement. Educational Evaluation and Policy Analysis, 31(3), 200-220. https://doi.org/10.3102/0162373709336238
  60. Lent, R., Brown, S., Sheu, H., Schmidt, J., Brenner, B., Gloster, C. y Treistman, D. (2005). Social cognitive predictors of academic interests and goals in engineering: Utility for women and students at historically black universities. Journal of Counseling Psychology, 52(1), 84-92. https://psycnet.apa.org/doi/10.1037/0022-0167.52.1.84
  61. Lent, R. W., Sheu, H. B., Miller, M. J., Cusick, M. E., Penn, L. T. y Truong, N. N. (2018). Predictors of science, technology, engineering, and mathematics choice options: A meta-analytic path analysis of the social–cognitive choice model by gender and race/ethnicity. Journal of Counseling Psychology, 65(1), 17-35. https://psycnet.apa.org/doi/10.1037/cou0000243
  62. Linacre, J. M. (2002). Optimizing rating scale category effectiveness. Journal of Applied Measurement, 3(1), 85-106.
  63. López-Bassols, V., Grazzi, M., Guillard, C. y Salazar, M. (2018). Las brechas de género en ciencia, tecnología e innovación en América Latina y el Caribe. Resultados de una recolección piloto y propuesta metodológica para la medición. Banco Interamericano de Desarrollo. http://dx.doi.org/10.18235/0001082
  64. Marsh, H. W. (1990). Causal ordering of academic self-concept and academic achievement: A multiwave, longitudinal panel analysis. Journal of Educational Psychology, 82(4), 646-656. https://psycnet.apa.org/doi/10.1037/0022-0663.82.4.646
  65. Marsh, H. W. (2007). Self-concept theory, measurement and research into practice: The role of self-concept in educational psychology. British Psychological Society.
  66. Marsh, H. W., Trautwein, U., Lüdtke, O. y Köller, O. (2008). Social comparison and big- fish-little-pond effects on self-concept and other self-belief constructs: Role of general- ized and specific others. Journal of Educational Psychology, 100(3), 510–524. https://psycnet.apa.org/doi/10.1037/0022-0663.100.3.510
  67. McClelland, G. H. y Judd, C. M. (1993). Statistical difficulties of detecting interactions and moderator effects. Psychological Bulletin, 114(2), 376-390. https://psycnet.apa.org/doi/10.1037/0033-2909.114.2.376
  68. McCombs, B. L. y Quiat, M. (2002). What makes a comprehensive school reform model learner centered? Urban Education, 37(4), 476-496. https://doi.org/10.1177/0042085902374002
  69. McEwan, P. J. (2001). The effectiveness of public, catholic, and non-religious private schools in Chile's voucher system. Education Economics, 9(2), 103-128. https://doi.org/10.1080/09645290110056958
  70. Mendick, H. (2005). A beautiful myth? The gendering of being/doing ‘good at maths’. Gender and Education, 17(2), 203-219. https://doi.org/10.1080/0954025042000301465
  71. Moriondo, M., Palma, P., Medrano, L. y Murillo, P. (2012). Adaptación de la Escala de Afectividad Positiva y Negativa (PANAS) a la población de adultos de la ciudad de Córdoba: Análisis psicométricos preliminares. Universitas Psychologica, 11(1), 187-196. https://doi.org/10.11144/Javeriana.upsy11-1.aeap
  72. Nagy, G., Trautwein, U., Baumert, J., Ko ̈ller, O. y Garrett, J. (2006). Gender and course selection in upper secondary education: Effects of academic self-concept and intrinsic value. Educational Research and Evaluation, 12(4), 323–345. https://doi.org/10.1080/13803610600765687
  73. Noyes, A. (2012). It matters which class you are in: student-centred teaching and the enjoyment of learning mathematics. Research in Mathematics Education, 14(3), 273-290. https://doi.org/10.1080/14794802.2012.734974
  74. OECD (2016). PISA 2015 Results (Volume I): Excellence and Equity in Education. PISA, OECD Publishing. https://doi.org/10.1787/9789264266490-en
  75. Op’t Eynde, P., De Corte, E. y Verschaffel, L. (2006). “Accepting emotional complexity”: A socio-constructivist perspective on the role of emotions in the mathematics classroom. Educational Studies in Mathematics, 63(2), 193-207. https://doi.org/10.1007/s10649-006-9034-4
  76. Ortega Ferrand, L., Treviño, E. y Gelber, D. (2020). La inclusión de las niñas en las aulas de matemáticas chilenas: sesgo de género en las redes de interacciones profesor-estudiante. Journal for the Study of Education and Development / Infancia y Aprendizaje, 44(3), 623-674. https://doi.org/10.1080/02103702.2020.1773064
  77. Palardy, G. J. y Rumberger, R. W. (2008). Teacher effectiveness in first grade: The importance of background qualifications, attitudes, and instructional practices for student learning. Educational Evaluation and Policy Analysis, 30(2), 111–140. https://doi.org/10.3102/0162373708317680
  78. Pampaka, M., Kleanthous, I., Hutcheson, G. D. y Wake, G. (2011). Measuring mathematics self-efficacy as a learning outcome. Research in Mathematics Education, 13(2), 169-190. https://doi.org/10.1080/14794802.2011.585828
  79. Pampaka, M. y Williams, J. (2016). Mathematics teachers’ and students’ perceptions of transmissionist teaching and its association with students’ dispositions. Teaching Mathematics and its Applications: An International Journal of the IMA, 35(3), 118-130. https://doi.org/10.1093/teamat/hrw007
  80. Pampaka, M., Williams, J. S., Hutchenson, G., Black, L., Davis, P., Hernandez-Martines, P. y Wake, G. (2013). Measuring alternative learning outcomes: Dispositions to study in higher education. Journal of Applied Measurement, 14(2), 197-218.
  81. Pampaka, M., Williams, J., Hutcheson, G., Wake, G., Black, L., Davis, P. y Hernandez‐Martinez, P. (2011). The association between mathematics pedagogy and learners’ dispositions for university study. British Educational Research Journal, 38(3), 473-496. https://doi.org/10.1080/01411926.2011.555518
  82. Pampaka, M. y Wo, L. (2014). Revisiting Mathematical Attitudes of Students in Secondary Education. En P. Liljedahl, S. Oesterle, C. Nicol y D. Allan (Eds.), Proceedings of the Joint Meeting of PME 38 and PME-NA 36 (Vol. 4, pp. 385-392). PME. https://files.eric.ed.gov/fulltext/ED599969.pdf
  83. Parker, P. D., Marsh, H. W., Ciarrochi, J., Marshall, S. y Abduljabbar, A. S. (2014). Juxtaposing math self-efficacy and self-concept as predictors of long-term achievement outcomes. Educational Psychology, 34(1), 29-48. https://doi.org/10.1080/01443410.2013.797339
  84. Radovic, D. (2018). Diferencias de género en rendimiento matemático en Chile: el efecto del nivel socioeconómico y el establecimiento educacional en el bajo rendimiento de las niñas. Revista Colombiana de Educación, 74, 221-242. https://doi.org/10.17227/rce.num74-6907
  85. Radovic, D., Black, L., Salas, C. y Williams, J. (2017). Being a girl mathematician: Analysis of the diversity of positive mathematical identities in a secondary classroom. JRME - Journal for Research in Mathematics Education, 48(4), 434-464. https://doi.org/10.5951/jresematheduc.48.4.0434
  86. Raîche, G. (2005). Critical Eigenvalue Sizes in Standardized Residual Principal Components Analysis. Rasch Measurement Transactions, 19(1), 1012.
  87. Riegle-Crumb, C., King, B., Grodsky, E. y Muller, C. (2012). The more things change, the more they stay the same? Prior achievement fails to explain gender inequality in entry into STEM college majors over time. American Educational Research Journal, 49(6), 1048-1073. https://doi.org/10.3102/0002831211435229
  88. Robles, R. y Páez, F. (2003). Estudio sobre la traducción al español y las propiedades psicométricas de las escalas de afecto positivo y negativo (panas). Salud mental, 26(1), 69-75.
  89. Roth, W. M. y Radford, L. (2011). A cultural-historical perspective on mathematics teaching and learning. Springer Science & Business Media. https://doi.org/10.1007/978-94-6091-564-2
  90. Sax, L. J., Kanny, M. A, Jacobs, J. A., Whang, H., Weintraub, D. S. y Hroch, A. (2016). Understanding the changing dynamics of the gender gap in undergraduate engineering majors. Research in Higher Education, 57(5), 570-600. https://doi.org/10.1007/s11162-015-9396-5
  91. Schuh, K. L. (2004). Learner-centered principles in teacher-centered practices? Teaching and Teacher Education, 20(8), 833–846. https://doi.org/10.1016/j.tate.2004.09.008
  92. Smith, R. M., Schumacker, R. E. y Busch, M. J (1995). Using Item Mean Squares to Evaluate Fit to the Rasch Model. En Annual Meting of the American Educational Research Asociation (pp. 1-17). American Educational Research Asociation
  93. Swan, M. (2006a). Learning GCSE mathematics through discussion: what are the effects on students? Journal of Further and Higher Education, 30(3), 229-241. https://doi.org/10.1080/03098770600802263
  94. Swan, M. (2006b). Designing and using research instruments to describe the beliefs and practices of mathematics teachers. Research in Education, 75(1), 58-70. https://doi.org/10.7227/RIE.75.5
  95. Timmermans, R. E., Van Lieshout, E. C. y Verhoeven, L. (2007). Gender-related effects of contemporary math instruction for low performers on problem-solving behavior. Learning and Instruction, 17(1), 42-54. https://doi.org/10.1016/j.learninstruc.2006.11.005
  96. UNESCO (2017). Cracking the code: girls' and women's education in science, technology, engineering and mathematics (STEM). United Nations Educational, Scientific and Cultural Organization. https://doi.org/10.54675/QYHK2407
  97. Valentine, J. C., DeBois, D. L. y Cooper, H. (2004). The relation between self-beliefs and academic achievement: A meta-analytic review. Educational Psychologist, 39(2), 37–41. https://doi.org/10.1207/s15326985ep3902_3
  98. Wang, M. T. (2012). Educational and career interests in math: A longitudinal examination of the links between classroom environment, motivational beliefs, and interests. Developmental Psychology, 48(6), 1643-1657. https://psycnet.apa.org/doi/10.1037/a0027247
  99. Watson, D., Clark, L. A. y Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: the PANAS scales. Journal of personality and social psychology, 54(6), 1063-1070. https://psycnet.apa.org/doi/10.1037/0022-3514.54.6.1063
  100. Watt, H. M. G. (2004). Development of adolescents’ self-perceptions, values, and task perceptions according to gender and domain in 7th- through 11th-grade Australian students. Child Development, 75(5), 1556-1574. https://doi.org/10.1111/j.1467-8624.2004.00757.x
  101. Wigfield, A., Battle, A., Keller, L. B. y Eccles, J. S. (2002). Sex differences in motivation, self-concept, career aspiration, and career choice: implications for cognitive development. En R. De Lisi y A. McGillicuddy-De Lisi (Eds.), The development of sex differences in cognition (pp. 93–124). Ablex Publishing.
  102. Zieky, M. J. (1993). Practical questions in the use of DIF statistics in test development. En P. W. Holland y H. Wainer (Eds.), Differential item functioning (pp. 337-47). Lawrence Erlbaum Associates.
  103. Zwick, R. J. (2012). A review of ETS differential item functioning assessment procedures: Flagging rules, minimum sample size requirements, and criterion refinement. ETS Research Report Series, 1, 1-30. https://doi.org/10.1002/j.2333-8504.2012.tb02290.x"

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