Secondary school students’ calibration in a written test: the effect of sex
Abstract
During the last decades, important sex differences have been found in the context of science education. Besides, self-assessment is crucial in the cycle of self-regulated learning and, consequently, in students’ performance. The main goal of the present investigation is to analyze secondary school students’ metacognition and, in particular, the effect of gender. To this aim, a sample of 507 students took part in our study. Our analyses show that girls are better calibrated than boys in spite of being the latter more confident in their predictions. A general tendency towards overestimations has been found for both sexes. Moreover, high-achieving students tend to be more precise and underestimate their performance and low-achieving students tend to be less precise and overestimate their grade in the test. Although this effect was found in both sexes, the size effect was large in the case of girls. In light of our results, high-achieving students make a better use of self-generated feedback than low-achievers. Sex differences in calibration could be explained by the different attitudes and motivations of boys and girls towards science.
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References
Abraham, J. y Barker, K. (2015). Exploring gender difference in motivation, engagement and enrolment behavior of senior secondary physics students in New South Wales. Research in Science Education, 45(1), 59-73, doi: 10.1007/s11165-014-9413-2.
Acar Ö., Türkmen L., y Bilgin A., (2015). Examination of Gender Differences on Cognitive and Motivational Factors that Influence 8th Graders’ Science Achievement in Turkey. Eurasia Journal of Mathematics Science Technology Education, 11(5), 1027–1040, doi: 10.12973/eurasia.2015.1372a
Baars, M., Vink, S., van Gog, T., de Bruin, A., y Paas, F. (2014). Effects of training self-assessment and using assessment standards on retrospective and prospective monitoring of problem solving. Learning and Instruction, 33, 92–107, doi: 10.1016/j.learninstruc.2014.04.004
Bol, L., Hacker, D. J., Walck, C. C., y Nunnery, J. A. (2012). The effects of individual or group guidelines on the calibration accuracy and achievement of high school biology students. Contemporary Educational Psychology, 37(4), 280–287, doi: 10.1016/j.cedpsych.2012.02.004
Brannick, M. T., Miles, D. E., y Kisamore, J. L. (2005). Calibration between student mastery and self‐efficacy. Studies in Higher Education, 30(4), 473–483, doi: 10.1080/03075070500160244
Brown, G. T. L., Andrade, H. L., y Chen, F. (2015). Accuracy in student self-assessment: directions and cautions for research. Assessment in Education: Principles, Policy & Practice, 22(4), 444–457, doi: 10.1080/0969594X.2014.996523
Chiu, M. M., y Klassen, R. M. (2010). Relations of mathematics self-concept and its calibration with mathematics achievement: Cultural differences among fifteen-year-olds in 34 countries. Learning and Instruction, 20(1), 2–17, doi: 10.1016/j.learninstruc.2008.11.002
de Bruin, A. B. H., Kok, E. M., Lobbestael, J. y de Grip, A. (2017). The impact of an online tool for monitoring and regulating learning at university: overconfidence, learning strategy, and personality. Metacognition and Learning, 12(1), 21–43, doi: 10.1007/s11409-016-9159-5
Dent, A. L., y Koenka, A. C. (2016). The Relation Between Self-Regulated Learning and Academic Achievement Across Childhood and Adolescence: A Meta-Analysis. Educational Psychology Review, 28(3), 425–474, doi: 10.1007/s10648-015-9320-8
Dunlosky, J., y Metcalfe, J. (2008). Metacognition. Los Angeles, CA: SAGE Publications
Dunning, D. (2005). Self-insights: Roadblocks and detours on the path of knowing thyself. New York: Psychology Press.
Eddy, S. L., y Brownell, S. E. (2016). Beneath the numbers: A review of gender disparities in undergraduate education across science, technology, engineering, and math disciplines. Physical Review Physics Education Research, 12(2), 020106, doi: 10.1103/PhysRevPhysEducRes.12.020106
Erickson, S., y Heit, E. (2015). Metacognition and confidence: comparing math to other academic subjects. Frontiers in Psychology, 6, 742, doi: 10.3389/fpsyg.2015.00742
Fischer, F., Schult, J., y Hell, B. (2013). Sex differences in secondary school success: Why female students perform better. European journal of psychology of education, 28(2), 529-543, doi: 10.1007/s10212-012-0127-4
Follmer, D. J., y Sperling, R. A. (2016). The mediating role of metacognition in the relationship between executive function and self-regulated learning. British Journal of Educational Psychology, 86(4), 559–575, doi: 10.1111/bjep.12123
Glynn, S. M., Brickman, P., Armstrong, N., y Taasoobshirazi, G. (2011). Science motivation questionnaire II: Validation with science majors and nonscience majors. Journal of Research in Science Teaching, 48(10), 1159–1176, doi: 10.1002/tea.20442
Gutiérrez, A. P., y Price, A. F. (2017). Calibration between undergraduate students' prediction of and actual performance: The role of gender and performance attributions. The Journal of Experimental Education, 85(3), 486-500, doi: 10.1080/00220973.2016.1180278
Gutierrez, A. P., Schraw, G., Kuch, F., y Richmond, A. S. (2016). A two-process model of metacognitive monitoring: Evidence for general accuracy and error factors. Learning and Instruction, 44, 1–10, doi: 10.1016/j.learninstruc.2016.02.006
Hacker, D. J., Bol, L., y Bahbahani, K. (2008). Explaining calibration accuracy in classroom contexts: the effects of incentives, reflection, and explanatory style. Metacognition and Learning, 3(2), 101–121, doi: 10.1007/s11409-008-9021-5
Hacker, D. J., Bol, L., Horgan, D. D., y Rakow, E. A. (2000). Test prediction and performance in a classroom context. Journal of Educational Psychology, 92(1), 160–170, doi: 10.1037/0022-0663.92.1.160
Hacker, D. J., Bol, L., y Keener, M. C. (2008). Metacognition in education: A focus on calibration. In J. Dunlosky y R. A. Bjork (Eds.), Handbook of metamemory and memory (p. 429455). New York: Taylor & Francis Group.
Hawker, M. J., Dysleski, L., y Rickey, D. (2016). Investigating General Chemistry Students’ Metacognitive Monitoring of Their Exam Performance by Measuring Postdiction Accuracies over Time. Journal of Chemical Education, 93(5), 832–840, doi: 10.1021/acs.jchemed.5b00705
Jacobs, J.E. (2005). Twenty-five years of research on gender and ethnic differences in math and science career choices: What havewe learned? En J.E. Jacobs & S.D. Simpkins (Eds.), New Directions for Child and Adolescent Development, 110, 85–94. doi: 10.1002/cd.151
Karatjas, A. G. (2013). Comparing College Students’ Self-Assessment of Knowledge in Organic Chemistry to Their Actual Performance. Journal of Chemical Education, 90(8), 1096–1099, doi: 10.1021/ed400037p
Karatjas, A. G. (2014). Use of Student Self-Assessment of Exams To Investigate Student Learning in Organic Chemistry Classes. En Kendhammer, L. K. y Murphy, K. L. (Eds.) Innovative Uses of Assessments for Teaching and Research (pp. 133–143). American Chemical Society, doi: 10.1021/bk-2014-1182.ch008
Karatjas, A. G., y Webb, J. (2015). The Role of Gender in Grade Perception in Chemistry Courses. Journal of College Science Teaching, 45(2), 30–35, doi: 10.20429/ijsotl.2017.110214
Kruger, J., y Dunning, D. (1999). Unskilled and unaware of it: How difficulties in recognizing one’s own incompetence lead to inflated self-assessments. Journal of Personality and Social Psychology, 77(6), 1121–1134.
Lindsey, B. A., y Nagel, M. L. (2015). Do students know what they know? Exploring the accuracy of students’ self-assessments. Physical Review Special Topics - Physics Education Research, 11(2), 20103, doi: 10.1103/PhysRevSTPER.11.020103
Mujtaba, T., y Reiss, M. J. (2013). What Sort of Girl Wants to Study Physics After the Age of 16? Findings from a Large-scale UK Survey. International Journal of Science Education, 35(17), 2979–2998, doi: 10.1080/09500693.2012.681076
Nietfeld, J. L., Shores, L. R., y Hoffmann, K. F. (2014). Self-regulation and gender within a game-based learning environment. Journal of Educational Psychology, 106(4), 961–973, doi: 10.1037/a0037116
Palmer T.-A., Burke P. F., y Aubusson P. (2017). Why school students choose and reject science: a study of the factors that students consider when selecting subjects. Int. J. Sci. Educ., 39(6), 645–662, doi: 10.1080/09500693.2017.1299949
Pirmohamed, S., Debowska, A., y Boduszek, D. (2017). Gender differences in the correlates of academic achievement among university students. Journal of Applied Research in Higher Education, 9(2), 313-324. doi: 10.1108/JARHE-03-2016-0015
Potvin P., y Hasni A., (2014). Interest, motivation and attitude towards science and technology at K-12 levels: a systematic review of 12 years of educational research. Studies in Science Education, 50(1), 85–129, doi: 10.1080/03057267.2014.881626
Schraw, G., Potenza, M. T., y Nebelsick-Gullet, L. (1993). Constraints on the calibration of performance. Contemporary Educational Psychology, 18(4), 455–463, doi: 10.1006/ceps.1993.1034
Sharma, M. D., y Bewes, J. (2011). Self-monitoring: Confidence, academic achievement and gender differences in Physics. Journal of Learning Design, 4(3), 1–13, doi: 10.5204/jld.v4i3.76
Schumm, M. F., y Bogner, F. X. (2016). Measuring adolescent science motivation. International Journal of Science Education, 38(3), 434–449, doi: 10.1080/09500693.2016.1147659
Vázquez Alonso, Á., y Manassero Más, M. (2015). La elección de estudios superiores científico-técnicos: análisis de algunos factores determinantes en seis países. Revista Eureka sobre enseñanza y divulgación de las ciencias, 12(2), 264-277.
Volz-Sidiropoulou, E., y Gauggel, S. (2012). Do subjective measures of attention and memory predict actual performance? Metacognition in older couples. Psychology and Aging, 27(2), 440–450, doi: 10.1037/a0025384
Zamora Á., y Ardura D., (2014). ¿En qué medida utilizan los estudiantes de Física de Bachillerato sus propios errores para aprender? Una experiencia de autorregulación en el aula de secundaria. Enseñanza de las ciencias, 32(2), 253–268, doi: 10.5565/rev/ensciencias.1067
Zamora Á., Suárez J. M., y Ardura D., (2018). Error detection and self-assessment as mechanisms to promote self-regulation of learning among secondary education students. Journal of Educational Research, 111(2), 175–185, doi: 10.1080/00220671.2016.1225657
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