Middle School girls’ self-efficacy and motivation toward Mathematics before and after attending an all-girls summer Mathematics camp
Abstract
The purpose of this study was to investigate the influence of a five-day summer residential mathematics and technology program on the mathematics motivation and self-efficacy of 210 middle-grades girls who participated in this female-only event. Entrance measures and gain scores were examined for the study sample as a whole and for demographic groups formed by race/ethnicity, family socioeconomic status, and grade level. The results show that this program favorably influenced participants’ short-term self-efficacy and motivation for learning mathematics. Overall, significant increases appeared in self-efficacy, intrinsic motivation, and extrinsic motivation from program beginning to end. Self-efficacy showed the strongest improvements, followed by intrinsic motivation, and finally extrinsic motivation. Some differences appeared among demographic subgroups.
Keywords
Full Text:
PDFReferences
Acar Güvendir, M. (2016). Students’ extrinsic and intrinsic motivation level and its relationship with their mathematics achievement. International Journal for Mathematics Teaching & Learning, 1-21. Retrieved from http://www.cimt.org.uk/journal/guvendir.pdf.
Agirdag, O. (2018). The impact of school SES composition on science achievement and achievement growth: Mediating role of teachers’ teachability culture. Educational Research & Evaluation, 24(3-5), 264-276.
Aktop, A. (2010). Socioeconomic status, physical fitness, self-concept, attitude toward physical education, and academic achievement of children. Perceptual and Motor Skills, 110(2), 531-546.
Anaya, L., Stafford, F., & Zamarro, G. (2022). Gender gaps in math performance, perceived mathematical ability and college STEM education: The role of parental occupation. Education Economics, 30(2), 113-128.
Arens, A. K., Frenzel, A. C., & Goetz, T. (2022). Self-concept and self-efficacy in math: Longitudinal interrelations and reciprocal linkages with achievement. The Journal of Experimental Education, 90(3), 615-633.
Ashcraft, C., Eger, E., & Friend, M. (2012). Girls in IT: The facts. Boulder, CO: National Center for Women & Information Technology, University of Colorado. Retrieved from https://www.ncwit.org/resources/girls-it-facts.
Bong, M., Cho, C., Ahn, H., & Kim, H. (2012). Comparison of self-beliefs for predicting student motivation and achievement. Journal of Educational Research, 105(5), 336-352.
Brown-Jeffy, S. (2009). School effects: Examining the race gap in mathematics achievement. Journal of African American Studies, 13(4), 388-405.
Chiu, M. M. (2010). Effects of inequality, family and school on mathematics achievement: Country and student differences. Social Forces, 88(4), 1645-1676.
Cohen, J. (1992). Quantitative methods in psychology: A power primer. Psychological Bulletin, 112(1), 155-159.
Contini, D., Tommaso, M. L. D., & Mendolia, S. (2017). The gender gap in mathematics achievement: Evidence from Italian data. Economics of Education Review, 58, 32-42.
Cutumisu, M., & Bulut, O. (2017). Problem-solving attitudes and gender as predictors of academic achievement in mathematics and science for Canadian and Finnish students in the PISA 2012 assessment. Journal of Educational Multimedia & Hypermedia, 26(4), 325-342.
Cvencek, D., Meltzoff, A. N., & Greenwald, A. G. (2011). Math-gender stereotypes in elementary school children. Child Development, 82(3), 766-779.
Dang, M., & Nylund-Gibson, K. (2017). Connecting math attitudes with STEM career attainment: A latent class analysis approach. Teachers College Record, 119(6), 1-38.
Das, G. C., & Sinha, S. (2017). Effect of socioeconomic status on performance in mathematics among students of secondary schools of Guwahati city. IOSR Journal of Mathematics, 13(1), 26-33.
Dillivan, K. D., & Dillivan, M. N. (2014). Student interest in STEM disciplines: Results from a summer day camp. Journal of Extension, 52(1), 1-11.
Duncan, T. G., & McKeachie, W. J. (2005). The making of the motivated strategies for learning questionnaire. Educational Psychologist, 40(2), 117-128.
Dweck, C. S. (2006). Mindset: The new psychology of success. New York: Ballantine.
Ganley, C. M., & Lubienski, S. T. (2016). Mathematics confidence, interest, and performance: Examining gender patterns and reciprocal relations. Learning and Individual Differences, 47, 182-193.
Gillet, N., Vallerand, R. J., & Lafrenière, M.-A. K. (2012). Intrinsic and extrinsic school motivation as a function of age: The mediating role of autonomy support. Social Psychology of Education, 15(1), 77-95.
Gottfried, A. E., Marcoulides, G. A., Gottfried, A. W., & Oliver, P. H. (2009). A latent curve model of parental motivational practices and developmental decline in math and science academic intrinsic motivation. Journal of Educational Psychology, 101(3), 729-739.
Graham, S. E., & Provost, L. E. (2012). Mathematics achievement gaps between suburban students and their rural and urban peers increase over time. Durham, NH: University of New Hampshire, Carsey Institute. Retrieved from https://scholars.unh.edu/carsey/172/.
Gunderson, E. A., Hamdan, N., Sorhagen, N. S., & D’Esterre, A. P. (2017). Who needs innate ability to succeed in math and literacy? Academic-domain-specific theories of intelligence about peers versus adults. Developmental Psychology, 53(6), 1188-1205.
Hand, S., Rice, L., & Greenlee, E. (2017). Exploring teachers’ and students’ gender role bias and students’ confidence in STEM fields. Social Psychology of Education, 20(4), 929-945.
Hoffman, A., McGuire, L., Rutland, A., Hartstone-Rose, A., Irwin, M. J., Winterbottom, M., Balkwill, F., Fields, G. E., & Mulvey, K. L. (2021). The relations and role of social competencies and belonging with math and science interest and efficacy for adolescents in informal STEM programs. Journal of Youth and Adolescence, 50, 314-323.
Ker, H.-W. (2017). The effects of motivational constructs and engagements on mathematics achievements: A comparative study using TIMSS 2011 data of Chinese Taipei, Singapore, and the USA. Asia Pacific Journal of Education, 37(2), 135-149.
Krishnamurthi, A., Ballard, M., & Noam, G. G. (2014). Examining the impact of afterschool STEM programs. Retrieved from http://www.afterschoolalliance.org/afterschoolsnack/ASnack.cfm?idBlog=1125505D-215A-A6B3-020A72E8BE53BA39.
Kuhfield, M., Gershoff, E., & Paschall, K. (2018). The development of racial/ethnic and socioeconomic achievement gaps during the school years. Journal of Applied Developmental Psychology, 57, 62-73.
Leaper, C., Farkas, T., Brown, C. S., & Spears, C. (2012). Adolescent girls’ experiences and gender-related beliefs in relation to their motivation in math/science and English. Journal of Youth and Adolescence, 41(3), 268-282.
Levy, H. E., Fares, L., & Rubinsten, O. (2021). Math anxiety affects females’ vocational interests. Journal of Experimental Child Psychology, 210, 105214.
Lofgran, B. B., Smith, L. K., & Whiting, E. F. (2015). Science self-efficacy and school transitions: Elementary school to middle school, middle school to high school. School Science and Mathematics, 115(7), 366-376.
Mann, L. C., & Walshaw, M. (2019). Mathematics anxiety in secondary school female students: Issues, influences and implications. New Zealand Journal of Educational Studies, 54, 101-120.
Martin, A. J., & Lazendic, G. (2018). Achievement in large-scale national numeracy assessment: An ecological study of motivation and student, home, and school predictors. Journal of Educational Psychology, 110(4), 465-482.
Martin, D. B. (2009). Does race matter? Teaching Children Mathematics, 16(3) 134-139.
Mata, M. L., Monteiro, V., & Peixoto, F. (2012). Attitudes toward mathematics: Effects of individual, motivational, and social support factors. Child Development Research, 2012, 876028.
McCreedy, D., & Dierking, L. D. (2013). Cascading influences: Long-term impacts of informal STEM experiences for girls. Philadelphia, PA: The Franklin Institute.
Mohr-Schroeder, M. J., Jackson, C., Miller, M., Walcott, B., Little, D. L., Speler, L., & ... Schroeder, D. C. (2014). Developing middle school students' interests in STEM via summer learning experiences: See Blue STEM Camp. School Science and Mathematics, 114(6), 291-301.
Moos, D. C., & Honkomp, B. (2011). Adventure learning: Motivating students in a Minnesota middle school. Journal of Research on Technology in Education, 43(3), 231-252.
Murphy, S. (2019). School location and socioeconomic status and patterns of participation and achievement in senior secondary mathematics. Mathematics Education Research Journal, 31, 219-235.
O’Sullivan, C., & Ríordáin, M. N. (2017). Examining the effect of female students’ mindset on their approach to challenges when learning mathematics. Journal of Teacher Action Research, 4(1), 2-19.
Pintrich, P. R., & De Groot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 82(1), 33-40.
Pintrich, P. R., Marx, R. W., & Boyle, R. A. (1993). Beyond cold conceptual change: The role of motivational beliefs and classroom contextual factors in the process of conceptual change. Review of Educational Research, 63(2), 167-199.
Pitsia, V., Biggart, A., & Karakolidis, A. (2017). The role of students’ self-beliefs, motivation and attitudes in predicting mathematics achievement: A multilevel analysis of the Programme for International Student Assessment data. Learning
and Individual Differences, 55, 163-173.
Potter, D., & Morris, D. (2017). Family and schooling experiences in racial/ethnic academic achievement gaps: A cumulative perspectives. Sociological Perspectives, 60(1), 132-167.
Prast, E. J., Van de Weijer-Bergsma, E., Miočević, M., Kroesbergen, E. H., & Van Luit, J. E. H. (2018). Relations between mathematics achievement and motivation in students of diverse achievement levels. Contemporary Education Psychology, 55, 84-96.
Rao, N., & Sachs, J. (1999). Confirmatory factor analysis of the Chinese version of the Motivated Strategies for Learning Questionnaire. Educational and Psychological Measurement, 59(6), 1016-1029.
Recber, S., Isiksal, M., & Koç, Y. (2018). Investigating self-efficacy, anxiety, attitudes and mathematics achievement regarding gender and school type. Anales de Psicología, 34(1), 41-51.
Reilly, D., Neumann, D. L., & Andrews, G. (2019). Investigating gender differences in mathematics and science: Results from the 2011 Trends in Mathematics and Science Survey. Research in Science Education, 49(1), 25-50.
Rozgonjuk, D., Kraav, T., Mikkor, K., Orav-Puurand, K., & Täht, K. (2020). Mathematics anxiety among STEM and social sciences students: The roles of mathematics self-efficacy, and deep and surface approach to learning. International Journal of STEM Education, 7, 46.
Sandy, J., & Duncan, K. (2010). Examining the achievement test score gap between urban and suburban students. Education Economics, 18(3), 297-315.
Saw, G., Chang, C.-N., & Chan, H.-Y. (2018). Cross-sectional and longitudinal disparities in STEM career aspirations at the intersection of gender, race/ethnicity, and socioeconomic status. Educational Researcher, 47(8), 525-531.
Schunk, D. H., & DiBenedetto, M. K. (2021). Self-efficacy and human motivation. In A. J. Elliot (Ed.), Advances in Motivation Science (vol. 8, pp. 153-179). Elsevier Academic Press.
Shapiro, M., Grossman, D., Carter, S., Martin, K., Deyton, P., & Hammer, D. (2015). Middle school girls and the “leaky pipeline” to leadership. Middle School Journal, 46(5), 3-13.
Stewart, L. (2009). Achievement differences between large and small schools in Texas. The Rural Educator, 30(2), 20-28.
Stuij, M. (2015). Habitus and social class: A case study on socialisation into sports and exercise. Sport, Education and Society, 20(6), 780-798.
Traphagen, K. (2014). Grantmakers and thought leaders on out-of-school time: Survey and interview report. Portland, OR: Grantmakers for education’s out-of-school time funder network. Retrieved from: http://www.wallacefoundation.org/knowledge-center/advancing-philanthropy/Pages/Grantmakers-and-Thought-Leaders-on-Out-of-School-Time.aspx.
United States House of Representatives. (2008). H. Res. (House Resolution) 1180. Retrieved from www.gpo.gov/fdsys/pkg/BILLS-110hres1180eh/pdf/BILLS-110hres1180eh.pdf.
Vansteenkiste, M., Soenens, B., Verstuyf, J., & Lens, W. (2009). ‘What is the usefulness of your schoolwork?’ The differential effects of intrinsic and extrinsic goal framing on optimal learning. Theory and Research in Education, 7(2), 155-163.
von Stumm, S. (2017). Socioeconomic status amplifies the achievement gap throughout compulsory education independent of intelligence. Intelligence, 60, 57-62.
Wang, M.-T., & Degol, J. (2017). Gender gap in science, technology, engineering, and mathematics (STEM): Current knowledge, implications for practice, policy, and future directions. Educational Psychology Review, 29(1), 119-140.
Weinberg, A. E., Basile, C. G., & Albright, L. (2011). The effect of an experiential learning program on middle school students’ motivation toward mathematics and science. Research in Middle Level Education, 35(3), 1-12.
Wiest, L. R., Crawford-Ferre, H. G., & Sanchez, J. E. (2021). Out-of-school-time STEM programs for females: Implications for education research and practice (Vol. II: Short-Term Programs). Charlotte, NC: Information Age Publishing.
You, S., & Sharkey, J. D. (2012). Advanced mathematics course-taking: A focus on gender equifinality. Learning and Individual Differences, 22(4), 484-489.
Yu, M. V. B., Hsieh, T-y., Lee, G., Jiang, S., & Pantano, A. (2022). Promoting Latinx adolescents’ math motivation through competence support: Culturally responsive practices in an afterschool program context. Contemporary Educational Psychology, 68(1),102028.
DOI: https://doi.org/10.26220/rev.4165
View Counter: Abstract | 602 | times, and PDF | 259 | times
Re S M ICT E | ISSN: 1792-3999 (electronic), 1791-261X (print) | Laboratory of Didactics of Sciences, Mathematics and ICT, Department of Educational Sciences and Early Childhood Education - University of Patras.
Pasithee | Library & Information Center | University of Patras