Trajectories of change in students’ self-concepts of ability and values in math and college major choice

Educational Research and Evaluation

Volumn 21, Issue 4, 2015, Pages 343-370

  Musu Gillette, Lauren E ^a   Wigfield, Allan ^a   Harring, Jeffrey R ^a   Eccles, Jacquelynne S ^b  

^a UNIVERSITY OF MARYLAND   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

college major; self concept of ability; task value

Indexed keywords

EID: 84942990869     PISSN: 13803611     EISSN: 17444187     Source Type: Journal    
DOI: 10.1080/13803611.2015.1057161     Document Type: Article

References (58)

1. J.Allen,, & S.B.Robbins, (2008). Prediction of college major persistence based on vocational interests, academic preparation, and first-year academic performance. Research in Higher Education, 49, 62–79. doi:10.1007/s11162-007-9064-5
2. I.Archambault,, J.S.Eccles,, & M.N.Vida, (2010). Ability self-concepts and subjective value in literacy: Joint trajectories from grades 1 through 12. Journal of Educational Psychology, 102, 804–816. doi:10.1037/a0021075
3. X.Chen, (2013). STEM attrition: College students’ paths into and out of STEM fields (NCES 2014-001). Washington, DC: National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Retrieved from http://nces.ed.gov/pubs2014/2014001rev.pdf
4. A.M.Durik,, M.Vida,, & J.S.Eccles, (2006). Task values and ability beliefs as predictors of high school literacy choices: A developmental analysis. Journal of Educational Psychology, 98, 382–393. doi:10.1037/0022-0663.98.2.382
5. J.S.Eccles, (2007). Where are all the women? Gender differences in participation in physical sciences and engineering. In S.J.Ceci & W.M.Williams (Eds.), Why aren't more women in science? Top researchers debate the evidence (pp. 199–210). Washington, DC: APA Press.
6. J.S.Eccles,, B.Barber,, & D.Jozefowicz, (1999). Linking gender to education, occupation, and recreational choices: Applying the Eccles et al. model of achievement-related choices. In W.B.Swann, J.H.Langlois, & L.A.Gilbert (Eds.), Sexism and stereotypes in modern society: The gender science of Janet Taylor Spence (pp. 153–192). Washington, DC: APA Press.
7. J.S.Eccles,, & C.Midgley, (1989). Stage/environment fit: Developmentally appropriate classrooms for early adolescents. In R.Ames & C.Ames (Eds.), Research on motivation in education (Vol. 3, pp. 139–181). New York, NY: Academic Press.
8. J.S.Eccles,, M.N.Vida,, & B.Barber, (2004). The relation of early adolescents’ college plans and both academic ability and task-value beliefs to subsequent college enrollment. The Journal of Early Adolescence, 24, 63–77. doi:10.1177/0272431603260919
9. J.Eccles,, & A.Wigfield, (1995). In the mind of the achiever: The structure of adolescents’ achievement task values and expectancy-related beliefs. Personality and Social Psychology Bulletin, 21, 215–225.
10. J.Eccles,, A.Wigfield,, R.Harold,, & P.Blumenfeld, (1993). Age and gender differences in children's self and task perceptions during elementary school. Child Development, 64, 830–847. doi: 10.2307/1131221
11. J.Eccles-Parsons,, T.F.Adler,, R.Futterman,, S.B.Goff,, C.M.Kaczala,, J.L.Meece,, & C.Midgley, (1983). Expectancies, values, and academic behaviors. In J.T.Spence (Ed.), Achievement and achievement motivations (pp. 75–147). San Francisco, CA: W. H. Freeman.
12. G.M.Fitzmaurice,, N.M.Laird,, & J.H.Ware, (2011). Applied longitudinal analysis (2nd ed.). Boston, MA: Wiley.
13. A.C.Frenzel,, T.Goetz,, R.Pekrun,, & H.M.G.Watt, (2010). Development of mathematics interest in adolescence: Influences of gender, family, and school context. Journal of Research on Adolescence, 20, 507–537. doi:10.1111/j.1532-7795.2010.00645.x
14. P.M.Frome,, C.J.Alfeld,, J.S.Eccles,, & B.L.Barber, (2006). Why don't they want a male-dominated job? An investigation of young women who changed their occupational aspirations. Educational Research and Evaluation, 12, 359–372. doi:10.1080/13803610600765786
15. R.D.Goldman,, & B.N.Hewitt, (1976). The scholastic aptitude test “explains” why college men major in science more often than college women. Journal of Counseling Psychology, 23, 50–54. doi:10.1037/0022-0167.23.1.50
16. A.E.Gottfried,, J.S.Fleming,, & A.W.Gottfried, (2001). Continuity of academic intrinsic motivation from childhood through late adolescence: A longitudinal study. Journal of Educational Psychology, 93, 3–13. doi:10.1037/0022-0663.93.1.3
17. A.E.Gottfried,, G.A.Marcoulides,, A.W.Gottfried,, & P.H.Oliver, (2013). Longitudinal pathways from math intrinsic motivation and achievement to math course accomplishments and educational attainment. Journal of Research on Educational Effectiveness, 6, 68–92. doi:10.1080/19345747.2012.698376
18. A.E.Gottfried,, G.A.Marcoulides,, A.W.Gottfried,, P.H.Oliver,, & D.W.Guerin, (2007). Multivariate latent chance modeling of developmental decline in academic intrinsic math motivation and achievement: Childhood through adolescence. International Journal of Behavioral Development, 31, 317–324. doi:10.1177/0165025407077752
19. J.W.Graham, (2009). Missing data analysis: Making it work in the real world. Annual Review of Psychology, 60, 549–576. doi:10.1146/annurev.psych.58.11045.085530
20. J.M.Harackiewicz,, K.E.Barron,, J.M.Tauer,, & A.J.Elliot, (2002). Predicting success in college: A longitudinal study of achievement goals and ability measures as predictors of interest and performance from freshman year through graduation. Journal of Educational Psychology, 94, 562–575. doi:10.1037/0022-0663.94.3.562
21. S.Harter, (2006). The self. In W.Damon & R.M.Lerner (Series Eds.) and N.Eisenberg (Vol. Ed.), Handbook of child psychology (6th ed., Vol. 3, pp. 505–570). New York, NY: Wiley.
22. C.S.Hulleman,, O.Godes,, B.Hendricks,, & J.M.Harackiewicz, (2010). Enhancing interest and performance with a utility value intervention. Journal of Educational Psychology, 102, 880–895. doi: 10.1037/a0019506
23. C.S.Hulleman,, & J.M.Harackiewicz, (2009). Making education relevant: Increasing interest and performance in high school science classes. Science, 326, 1410–1412. doi: 10.1126/science.1177067
24. J.E.Jacobs,, S.Lanza,, D.W.Osgood,, J.S.Eccles,, & A.Wigfield, (2002). Changes in children's self-competence and values: Gender and domain differences across grades one through twelve. Child Development, 73, 509–527. doi:10.1111/1467-8624.00421
25. L.M.Larson,, T.Wu,, D.C.Bailey,, F.H.Borgen,, & C.E.Gasser, (2010). Male and female college students’ college majors: The contribution of basic vocational confidence and interests. Journal of Career Assessment, 18, 16–33. doi:10.1016/j.jvb.2009.10.007
26. Y.Li,, C.Alfeld,, R.P.Kennedy,, & M.Putallaz, (2009). Effects of summer academic programs in middle school on high school test scores, course-taking, and college major. Journal of Advanced Academics, 20, 404–436. doi: 10.1177/1932202X0902000303
27. X.Ma,, & W.Johnson, (2008). Mathematics as the critical filter: Curricular effects on gendered career choices. In H.M.G.Watt & J.S.Eccles (Eds.), Gender and occupational outcomes: Longitudinal assessments of individual, social, and cultural influences (pp. 55–83). Washington, DC: American Psychological Association.
28. C.A.Malgwi,, M.A.Howe,, & P.A.Burnaby, (2005). Influences of students’ choice of college major. Journal of Education for Business, 80, 275–282. doi: 10.3200/JOEB.80.5.275-282
29. G.A.Marcoulides,, A.E.Gottfried,, A.W.Gottfried,, & P.H.Oliver, (2008). A latent transition analysis of academic intrinsic motivation from childhood through adolescence. Educational Research and Evaluation, 14, 411–427. doi:10.1080/13803610802337665
30. J.L.Meece,, A.Wigfield,, & J.S.Eccles, (1990). Predictors of math anxiety and its influence on young adolescents’ course enrollment intentions and performance in mathematics. Journal of Educational Psychology, 82, 60–70. doi:10.1037/0022-0663.82.1.60
31. C.Midgley,, H.Feldlaufer,, & J.S.Eccles, (1989). Student/teacher relations and attitudes toward mathematics before and after the transition to junior high school. Child Development, 60, 981–992. doi: 10.2307/1131038
32. B.Muthén, (2004). Latent variable analysis: Growth mixture modeling and related techniques for longitudinal data. In D.Kaplan (Ed.), Handbook of quantitative methodology for the social sciences (pp. 345–368). Newbury Park, CA: Sage.
33. L.K.Muthén,, & B.O.Muthén, (2011). Mplus user's guide (5th ed.). Los Angeles, CA: Authors.
34. D.S.Nagin, (1999). Analyzing developmental trajectories: A semiparametric, group-based approach. Psychological Methods, 4, 139–157. doi:10.1037/1082-989X.4.2.139
35. G.Nagy,, J.Garrett,, U.Trautwein,, K.S.Cortina,, J.Baumert,, & J.S.Eccles, (2008). Gendered high school course selection as a precursor of gendered careers: The mediating role of self-concept and intrinsic value. In H.M.G.Watt & J.S.Eccles (Eds.), Gender and occupational outcomes: Longitudinal assessments of individual, social, and cultural influences (pp. 115–144). Washington, DC: American Psychological Association.
36. G.Nagy,, U.Trautwein,, J.Baumert,, O.Köller,, & J.Garrett, (2006). Gender and course selection in upper secondary education: Effects of academic self-concept and intrinsic value. Educational Research and Evaluation, 12, 323–345. doi:10.1080/13803610600765687
37. National Science Board. (2012). Science and engineering indicators 2012. Arlington, VA: National Science Foundation. Retrieved from http://www.nsf.gov/statistics/seind12/pdfstart.htm
38. J.G.Nicholls, (1979). Development of perception of own attainment and causal attributions for success and failure in reading. Journal of Educational Psychology, 71, 94–99. doi: 10.1037/0022-0663.71.1.94
39. K.L.Nylund,, T.Asparouhov,, & B.O.Muthén, (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling, 14, 535–569. doi:10.1080/10705510701575396
40. F.Pajares,, & D.M.Miller, (1995). Mathematics self-efficacy and mathematics performance: The need for specificity of assessment. Journal of Counseling Psychology, 42, 190–198. doi:10.1037/0022-0167.42.2.190
41. H.Petras,, & K.Masyn, (2010). General growth mixture analysis with antecedents and consequences of change. In A.R.Piquero & D.Weisburd (Eds.), Handbook of quantitative criminology (pp. 69–100). New York, NY: Spring Science and Business Media, LLC.
42. J.L.Schafer,, & J.Graham, (2002). Missing data: Our view of the state of the art. Psychological Methods, 7, 147–177. doi:10.1037///1082-989X.7.2.147
43. S.D.Simpkins,, P.E.Davis-Kean,, & J.S.Eccles, (2006). Math and science motivation: A longitudinal examination of the links between choices and beliefs. Developmental Psychology, 42, 70–83. doi:10.1037/0012-1649.42.1.70
44. B.Spinath,, & F.M.Spinath, (2005). Longitudinal analysis of the link between learning motivation and competence beliefs among elementary school children. Learning and Instruction, 15, 87–102. doi:10.1016/j.learninstruc.2005.04.008
45. B.Spinath,, & R.Steinmayr, (2008). Longitudinal analysis of intrinsic motivation and competence beliefs: Is there a relation over time? Child Development, 79, 1555–1569. doi:10.1111/j.1467-8624.2008.01205.x
46. U.Trautwein,, H.W.Marsh,, B.Nagengast,, O.Lüdtke,, G.Nagy,, & K.Jonkmann, (2012). Probing for the multiplicative term in modem expectancy-value theory: A latent interaction modeling study. Journal of Educational Psychology, 104, 763–777. doi: 10.1037/a0027470
47. K.A.Updegraff,, J.S.Eccles,, B.L.Barber,, & K.M.O'Brien, (1996). Course enrollment as self-regulatory behavior: Who takes optional high school math courses. Learning and Individual Differences, 8, 239–259. doi: 10.1016/S1041-6080(96)90016-3
48. US Department of Education, National Center for Education Statistics. (2009). The nation's report card: Mathematics 2009, national assessment of educational progress at grade 4 and 8 (NCES Publication No. 2010-451). Retrieved from http://nces.ed.gov/nationsreportcard/pdf/main2009/2010451.pdf
49. H.M.G.Watt, (2006). The role of motivation in gendered educational and occupational trajectories related to maths. Educational Research and Evaluation, 12, 305–322. doi:10.1080/13803610600765562
50. H.M.G.Watt, (2008). A latent growth curve modeling approach using an accelerated longitudinal design: The ontogeny of boys’ and girls’ talent perceptions and intrinsic values through adolescence. Educational Research and Evaluation, 14, 287–304. doi:10.1080/13803610802249316
51. A.Wigfield,, J.B.Byrnes,, & J.S.Eccles, (2006). Adolescent development. In P.A.Alexander & P.Winne (Eds.), Handbook of educational psychology (2nd ed., pp. 87–113). Mahwah, NJ: Erlbaum.
52. A.Wigfield,, & J.S.Eccles, (1992). The development of achievement task values: A theoretical analysis. Developmental Review, 12, 265–310. doi:10.1016/0273-2297(92)90011-P
53. A.Wigfield,, & J.S.Eccles, (2000). Expectancy-value theory of motivation. Contemporary Educational Psychology, 25, 68–81. doi: 10.1006/ceps.1999.1015
54. A.Wigfield,, J.S.Eccles,, J.Fredricks,, S.Simpkins,, R.Roeser,, & U.Schiefele, (in press). Development of achievement motivation and engagement. In R.Lerner (Series ed.) & M.Lamb & C.Garcia Coll (Vol. Eds.), Handbook of child psychology (7th ed., Vol. 3). New York, NY: Wiley.
55. A.Wigfield,, J.S.Eccles,, U.Schiefele,, R.W.Roeser,, & P.Davis-Kean, (2006). Development of achievement motivation. In N.Eisenberg (Ed.), Handbook of child psychology (Vol. 3, pp. 933–1002). New York, NY: John Wiley.
56. A.Wigfield,, J.S.Eccles,, K.S.Yoon,, R.D.Harold,, A.J.A.Arbreton,, C.Freedman-Doan,, & P.C.Blumenfeld, (1997). Change in children's competence beliefs and subjective task values across the elementary school years: A 3-Year Study. Journal of Educational Psychology, 89, 451–469. doi:10.1037/0022-0663.89.3.451
57. A.Wigfield,, S.Tonks,, & S.L.Klauda, (2009). Expectancy-Value Theory. In K.R.Wentzel & A.Wigfield (Eds.), Handbook of motivation at school (pp. 55–75). New York, NY: Routledge.
58. D.S.Yeager,, & G.M.Walton, (2011). Social-psychological interventions in education: They're not magic. Review of Educational Research, 81, 267–301. doi:10.3102/0034654311405999