Pathways from parental stimulation of children’s curiosity to high school science course accomplishments and science career interest and skill

International Journal of Science Education

Volumn 38, Issue 12, 2016, Pages 1972-1995

  Gottfried, Adele Eskeles ^a   Preston, Kathleen Suzanne Johnson ^b   Gottfried, Allen W ^b   Oliver, Pamella H ^b   Delany, Danielle E ^c   Ibrahim, Sirena M ^d  

^a CALIFORNIA STATE UNIVERSITY   (United States)

^b CALIFORNIA STATE UNIVERSITY   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

^d STONY BROOK UNIVERSITY   (United States)

Author keywords

and skill; career interest; children s curiosity; Fullerton Longitudinal Study; Parental stimulation; science courses

Indexed keywords

EID: 84984611681     PISSN: 09500693     EISSN: 14645289     Source Type: Journal    
DOI: 10.1080/09500693.2016.1220690     Document Type: Article

References (115)

1. T.M.Achenbach, & L.A.Rescorla, (2001). Manual for the ASEBA school-age forms & profiles. Burlington:University of Vermont, Research Center for Children, Youth, & Families.
2. M.Ainley, & J.Ainley, (2015). Early science learning experiences:Triggered and maintained interest. In K.A.Renninger, M.Nieswandt, & S.Hidi (Eds.), Interest in mathematics and science learning (pp. 17–31). Washington, DC:American Educational Research Association.
3. B.Alberts, (2013). Prioritizing science education. Science, 340, 249. doi:10.1126/science.1239041
4. P.A.Alexander, & E.M.Grossnickle, (2016). Positioning interest and curiosity within a model of academic development. In K.R.Wentzel, & D.B.Miele (Eds.), Handbook of motivation at school (2nd ed., pp. 188–208). New York, NY:Routledge.
5. L.Archer, J.DeWitt, J.Osborne, J.Dillon, B.Willis, & B.Wong, (2010). ‘Doing’ science versus ‘being’ a scientist:Examining 10/11-year-old schoolchildren’s constructions of science through the lens of identity. Science Education, 94, 617–639. doi:10.1002/sce.20399
6. L.Archer, J.DeWitt, J.Osborne, J.Dillon, B.Willis, & B.Wong, (2012). Science aspirations, capital, and family habitus:How families shape children’s engagement and identification with science. American Educational Research Journal, 49, 881–908. doi:10.3102/0002831211433290
7. A.Baram-Tsabari, (2015). Promoting information seeking and questioning in science. In K.A.Renninger, M.Nieswandt, & S.Hidi (Eds.), Interest in mathematics and science learning (pp. 135–152). Washington, DC:American Educational Research Association.
8. A.Beaujean, (2012). BaylorEdPsych:R package for Baylor University Educational Psychology Quantitative Courses. R package version 0.5. Retrieved from http://CRAN.R-project.org/package=BaylorEdPsych
9. J.Bennett, & S.Hogarth, (2009). Would you want to talk to a scientist at a party? High school students’ attitudes to school science and to science. International Journal of Science Education, 31, 1975–1998. doi:10.1080/09500690802425581
10. P.M.Bentler, (2007). On tests and indices for evaluation structural models. Personality and Individual Differences, 42, 825–829. doi:10.1016-j.paid.2006.09.024
11. P.M.Bentler, (In press). EQS 6 structural equations program manual. Encino, CA:Multivariate Software.
12. P.M.Bentler, & D.G.Bonett, (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88, 588–606. doi:10.1037/0033-2909.88.3.588
13. D.E.Berlyne, (1971). What next? Concluding summary. In H.I.Day, D.E.Berlyne, & D.E.Hunt (Eds.), Intrinsic motivation:A new direction in education (pp. 186–196). Toronto:Holt, Rinehart & Winston of Canada.
14. K.A.Bollen, (1989). Structural models with latent variables. New York, NY:Wiley.
15. K.A.Bollen, (2002). Latent variables in psychology and the social sciences. Annual Review of Psychology, 53, 605–634. doi:10.1146/annurev.psych.53.100901.135239
16. M.H.Bornstein, (2015). Children’s parents. In M.H.Bornstein & T.Leventhal (Eds.), Ecological settings and processes in developmental systems, Vol. 4 of the Handbook of child psychology and developmental science (7th ed.). Editor-in-chief:R. M. Lerner (pp. 55–132). Hoboken, NJ:Wiley.
17. M.H.Bornstein, & R.H.Bradley, (2003). Socioeconomic status, parenting, and child development. Mahwah, NJ:Lawrence Erlbaum Associates.
18. R.H.Bradley, R.F.Corwyn, M.Burchinal, H.P.McAdoo, & C.García Coll, (2001). The home environments of children in the United States part I:Variations by age, ethnicity, and poverty status. Child Development, 72, 1844–1867. doi:10.1111/1467-8624.t01-1-00382
19. B.A.Brown, J.M.Reveles, & G.J.Kelly, (2005). Scientific literacy and discursive identity:A theoretical framework for understanding science learning. Science Education, 89, 779–802. doi:10.1002/sce.20069
20. M.W.Browne, & R.Cudeck, (1993). Alternative ways of assessing model fit. In K.A.Bollen & J.S.Long (Eds.), Testing structural equation models (pp. 136–162). Newbury Park, CA:Sage.
21. M.W.Browne, R.Cudeck, K.Tateneni, & G.Mels, (2009). CEFA:Comprehensive exploratory factor analysis (version 3.03). Retrieved from http://faculty.psy.ohio-state.edu/browne/software.php
22. B.M.Caldwell, & R.H.Bradley, (1984). Administration manual (revised edition) of the Home Observation for Measurement of the Environment. Little Rock:University of Arkansas.
23. D.Campbell, S.A.Hyne, & D.L.Nilsen, (1992). Manual for the Campbell Interest and Skill Survey. Minneapolis, MN:National Computer Systems.
24. A.Chak, (2007). Teachers’ and parents’ conceptions of children’s curiosity and exploration. International Journal of Early Years Education, 15, 141–159. doi:10.1080/09669760701288690
25. C.Chin, & J.Osborne, (2008). Students’ questions:A potential resource for teaching and learning science. Studies in Science Education, 44, 1–39. doi:10.1080/03057260701828101
26. The College Board. (2016). Honors and AP courses—Preparing students for college. Retrieved from https://professionals.collegeboard.org/guidance/prepare/honors-ap
27. K.P.Dabney, D.Chakraverty, & R.H.Tai, (2013). The association of family influence and initial interest in science. Science Education, 97, 395–409. doi:10.1002/sce.21060
28. B.Dalton, S.J.Ingels, J.Downing, R.Bozick, & S.Owings, (2007). Advanced mathematics and science coursetaking in the spring high school senior classes of 1982, 1992, and 2004:Statistical analysis report, NCES 2007–312. Washington, DC:National Center for Education Statistics, Institute for Education Sciences, U.S. Department of Education.
29. J.DeWitt, L.Archer, & J.Osborne, (2014). Science-related aspirations across the primary–secondary divide:Evidence from two surveys in England. International Journal of Science Education, 36, 1609–1629. doi:10.1080/09500693.2013.871659
30. A.Dinno, (2012). paran:Horn’s test of principal components/factors. R package version 1.5.1. Retrieved from http://CRAN.R-project.org/packages=paran
31. A.M.Dotterer, S.M.McHale, & A.C.Crouter, (2009). The development and correlates of academic interests from childhood through adolescence. Journal of Educational Psychology, 101, 509–519. doi:10.1037/a0013987
32. S.Engel, (2011). Children’s need to know:Curiosity in schools. Harvard Educational Review, 81, 625–645. doi:10.17763/haer.81.4.h054131316473115
33. S.Engel, (2015). The hungry mind:The origins of curiosity in childhood. Cambridge, MA:Harvard University Press.
34. B.Freeman, S.Marginson, & R.Tytler, (2015). The age of STEM:Educational policy and practice across the world in Science, Technology, Engineering and Mathematics. New York, NY:Routledge.
35. J.P.Gee, (2000–2001). Identity as an analytic lens for research in education. Review of Research in Education, 25, 99–125. doi:10.3102/0091732X025001099
36. L.W.Glorfeld, (1995). An improvement on Horn’s parallel analysis methodology for selecting the correct number of factors to retain. Educational and Psychological Measurement, 55, 377–393. doi:10.1177/0013164495055003002
37. A.W.Gottfried, (Ed.). (1984). Home environment and early cognitive development:Longitudinal research. New York, NY:Academic Press.
38. A.E.Gottfried, (1985). Academic intrinsic motivation in elementary and junior high school students. Journal of Educational Psychology, 77, 631–635. doi:10.1037/0022-0663.77.6.631
39. A.E.Gottfried, (1986). Children’s academic intrinsic motivation inventory (CAIMI). Lutz, FL:Psychological Assessment Resources.
40. A.E.Gottfried, (1990). Academic intrinsic motivation in young elementary school children. Journal of Educational Psychology, 82, 525–538. doi:10.1037/0022-0663.82.3.525
41. A.E.Gottfried, (2009). Commentary:The role of environment in contextual and social influences on motivation:Generalities, specificities, and causality. In K.Wentzel & A.Wigfield (Eds.), Handbook of motivation at school (pp. 463–475). New York, NY:Routledge.
42. M.A.Gottfried, (2015). The influence of applied STEM coursetaking on advanced mathematics and science coursetaking. The Journal of Educational Research, 108, 382–399. doi:10.1080/00220671.2014.899959
43. A.W.Gottfried, & A.E.Gottfried, (1984). Home environment and cognitive development in young children of middle-socioeconomic-status families. In A.W.Gottfried (Ed.), Home environment and early cognitive development:Longitudinal research (pp. 57–115). New York, NY:Academic Press.
44. A.Gottfried, & A.Gottfried, (2011). Paths from gifted motivation to leadership. In S.E.Murphy & R.J.Reichard (Eds.), Early development and leadership:Building the next generation of leaders (pp. 71–91). New York:Psychology Press/Routledge.
45. 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:10.1037/0011-0663.93.1.3
46. A.W.Gottfried, A.E.Gottfried, K.Bathurst, & D.Guerin, (1994). Gifted IQ:Early developmental aspects. New York, NY:Plenum Publishing.
47. A.W.Gottfried, A.E.Gottfried, K.Bathurst, D.W.Guerin, & M.Parramore, (2003). Socioeconomic status in children’s development and family environment:Infancy through adolescence. In M.Bornstein & R.H.Bradley (Eds.), Socioeconomic status and parenting (pp. 189–207). Mahwah, NJ:Lawrence Erlbaum Associates, Publishers.
48. A.W.Gottfried, A.E.Gottfried, & D.W.Guerin, (2006). The Fullerton Longitudinal Study:A long-term investigation of intellectual and motivational giftedness. Journal for the Education of the Gifted, 29, 430–450.
49. A.E.Gottfried, G.A.Marcoulides, A.W.Gottfried, & P.Oliver, (2009). A latent curve model of parental motivational practices and developmental decline in math and science academic intrinsic motivation. Journal of Educational Psychology, 101, 729–739. doi:10.1037/a0015084
50. A.E.Gottfried, G.A.Marcoulides, A.W.Gottfried, & P.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
51. A.E.Gottfried, K.Nylund-Gibson, A.W.Gottfried, D.Morovati, & A.M.Gonzalez, (in press). Trajectories from academic intrinsic motivation to need for cognition and educational attainment. The Journal of Educational Research. doi:10.1080/00220671.2016.1171199
52. A.W.Gottfried, J.Schlackman, A.E.Gottfried, & A.S.Martinez, (2015). Parental provision of early literacy environment as related to reading and educational outcomes across the academic life-span. Parenting:Science and Practice, 15, 24–38. doi:10.1080/15295192.2015.992736
53. M.J.Graham, J.Frederick, A.Byars-Winston, A.-B.Hunter, & J.Handelsman, (2013). Increasing persistence of college students in STEM. Science, 341, 1455–1456. doi:10.1126/science.1240487
54. R.A.L.F.van Griethuijsen, M.W.van Eijck, H.Haste, P.J.den Brok, N.C.Skinner, N.Mansour, …, & S.BouJaoude, (2015). Global patterns in students’ views of science and interest in science. Research in Science Education, 45, 581–603. doi:10.1007/s11165-014-9438
55. E.M.Grossnickle, (2016). Disentangling curiosity:Dimensionality, definitions, and distinctions from interest in educational contexts. Educational Psychology Review, 28, 23–60. doi:10.1007/s10648-014-9294-y
56. M.J.Gruber, B.D.Gelman, & C.Ranganath, (2014). States of curiosity modulate hippocampus-dependent learning via the dopaminergic circuit. Neuron, 84, 486–496. doi:10.1016/j.neuron.2014.08.060
57. D.W.Guerin, A.W.Gottfried, P.H.Oliver, & C.W.Thomas, (2003). Temperament:infancy through adolescence. New York, NY:Kluwer Academic/Plenum.
58. J.M.Harackiewicz, C.Rozek, C.S.Hulleman, & J.S.Hyde, (2012). Helping parents to motivate adolescents in mathematics and science:An experimental test of a utility-value intervention. Psychological Science, 23, 899–906. doi:10.1177/0956797611435530
59. M.Harway, S.A.Mednick, & B.Mednick, (1984). Research strategies:Methodological and practical problems. In S.A.Mednick, M.Harway, & K.M.Finello (Eds.), Handbook of longitudinal research:Birth and childhood cohorts (Vol. 1, pp. 22–30). New York, NY:Praeger.
60. Z.Hazari, G.Sonnert, P.M.Sadler, & M.Shanahan, (2010). Connecting high school physics experiences, outcome expectations, physics identity, and physics career choice:A gender study. Journal of Research in Science Teaching, 47, 978–1003. doi:10.1002/tea.20363
61. A.B.Hollingshead, (1975). Four-Factor Index of Social Status (Unpublished manuscript). Department of Sociology, Yale University, New Haven, CT.
62. J.L.Horn, (1965). A rationale and test for the number of factors in factor analysis. Psychometrika, 30, 179–185. doi:10.1007/BF02389447
63. L.Hu, & P.M.Bentler, (1999). Cutoff criteria for fit indices in covariance structure analysis:Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55. doi:10.1080/1070551990950118
64. J.M.Hunt, J. McV. (1971). Intrinsic motivation and psychological development. In H.M.Schroder & P.Suedfield (Eds.), Personality theory and information processing (pp. 131–177). New York, NY:Ronald Press.
65. International Baccalaureate Organization. (2013). What is an IB education? Retrieved from http://www.ibo.org/globalassets/publications/become-an-ib-school/whatisanibeducation-en.pdf
66. J.Jirout, & D.Klahr, (2012). Children’s scientific curiosity:In search of an operational definition of an elusive concept. Developmental Review, 32, 125–160. doi:10.1016/j.dr.2012.04.002
67. D.Kelly, H.Xie, C.W.Nord, F.Jenkins, J.Y.Chan, & D.Kastberg, (2013). Performance of U.S. 15-year-old students in mathematics, science, and reading literacy in an international context:First look at PISA 2012 (NCES 2014–024). Washington, DC:U.S. Department of Education, National Center for Education Statistics. Retrieved from http://nces.ed.gov/pubsearch
68. C.Kidd, & B.Y.Hayden, (2015). The psychology and neuroscience of curiosity. Neuron, 88, 449–460. doi:10.1016/j.neuron.2015.09.010
69. D.Klahr, B.Matlen, & J.Jirout, (2013). Children as scientific thinkers. In G.J.Feist, & M.E.Gorman (Eds.), Handbook of the psychology of science (pp. 243–247). New York, NY:Springer Publishing Company.
70. T.R.Koballa, Jr., & S.M.Glynn, (2007). Attitudinal and motivational constructs in science learning. In S.K.Abell & N.G.Lederman (Eds.), Handbook of research on science education (pp. 75–102). New York, NY:Routledge Taylor Francis Group.
71. R.A.Lazowski, & C.S.Hulleman, (2016). Motivation interventions in education:A meta-analytic review. Review of Educational Research, 86, 602–640. doi:10.3102/0034654315617832
72. J.L.Lemke, (2001). Articulating communities:Sociocultural perspectives on science education. Journal of Research in Science Teaching, 38, 296–316. doi:10.1002/1098-2736(200103)38:3<296::AID-TEA1007>3.0.CO;2-R
73. M.R.Lepper, J.H.Corpus, & S.S.Iyengar, (2005). Intrinsic and extrinsic motivational orientations in the classroom:Age differences and academic correlates. Journal of Educational Psychology, 97, 184–196. doi:10.1037/0022-0663.97.2.184
74. R.J.A.Little, (1988). A test of missing completely at random for multivariate data with missing values. Journal of the American Statistical Association, 83, 1198–1202. doi:10.2307/2290157
75. S.Liu, M.J.Rovine, & P.C.M.Molenaar, (2012). Selecting a linear model for longitudinal data:Repeated measures analysis of variance, covariance pattern model, and growth curve approaches. Psychological Methods, 17, 15–30. doi:10.1037/a0026971
76. R.C.MacCallum, M.W.Browne, & H.M.Sugawara, (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1, 130–149. doi:10.1037/1082-989X.1.2.130
77. A.V.Maltese, G.Potvin, F.D.Lung, & C.D.Hochbein, (2015). STEM and STEM education in the United States. In B.Freeman, S.Marginson, & R.Tytler (Eds.), The age of STEM:Educational policy and practice across the world in Science, Technology, Engineering and Mathematics (pp. 102–133). New York, NY:Routledge.
78. A.V.Maltese, & R.H.Tai, (2010). Eyeballs in the fridge:Sources of early interest in science. International Journal of Science Education, 32, 669–685. doi:10.1080/09500690902792385
79. K.V.Mardia, (1974). Applications of some measures of multivariate skewness and kurtosis in testing normality and robustness studies. Sankhya, 36B, 115–128.
80. A.Markey, & G.Loewenstein, (2014). Curiosity. In R.Pekrun & L.Linnenbrink-Garcia (Eds.), International handbook of emotions in education (pp. 228–245). New York, NY:Routledge.
81. M.O.Martin, I.V.S.Mullis, P.Foy, & G.M.Stanco, (2012). TIMSS 2011 international results in science. Chestnut Hill, MA/Amsterdam:TIMSS & PIRLS International Study Center, Lynch School of Education, Boston College/International Association for the Evaluation of Educational Achievement (IEA), IEA Secretariat.
82. A.Master, S.Cheryan, & A.Meltzoff, (2016). Motivation and identity. In K.R.Wentzel & D.B.Miele (Eds.), Handbook of motivation at school (2nd ed., pp. 300–319). New York, NY:Routledge.
83. D.McCullough, (2015). The Wright brothers. New York, NY:Simon and Schuster.
84. M.Moch, (1987). Asking questions:An expression of epistemological curiosity in children. In D.Görlitz & J.F.Wohlwill (Eds.), Curiosity, imagination, and play:On the development of spontaneous cognitive and motivational processes (pp. 198–211). Hillsdale, NJ:Lawrence Erlbaum.
85. Multivariate Software, Inc. (2008). EQS—Structural equation modeling software [Computer software]. Encino, CA:Author.
86. National Academy of Sciences. (2010). Rising above the gathering storm, Revisited:Rapidly approaching category 5. Retrieved from http://www.nap.edu/catalog.php?record_id=12999
87. National Center for Education Statistics. (2012). The Nation’s Report Card:Science 2011. National assessment of educational progress at grade 8 (NCES-465). Institute of Education Sciences, U.S. Department of Education.
88. National Research Council. (2012). A framework for K-12 science education:Practices, crosscutting concepts, and core ideas. Committee on Conceptual Framework for the new K-12 science education standards. Retrieved from http://www.nap.edu/catalog.php?record_id=13165
89. National Science Teachers Association. (2009). NTSA position statement:Parent involvement in science learning. Retrieved from http://www.nsta.org/about/positions/parents.aspx
90. NGSS Lead States. (2013). Next generation science standards:For states, by states. Washington, DC:The National Academies Press.
91. S.B.Nolen, & T.M.Haladyna, (1990). Motivation and studying in high school science. Journal of Research in Science Teaching, 27, 115–126. doi:10.1002/tea.3660270204
92. J.Osborne, S.Simon, & S.Collins, (2003). Attitudes towards science:A review of the literature and its implications. International Journal of Science Education, 25, 1049–1079. doi:10.1080/0950069032000032199
93. T.Perez, J.G.Cromley, & A.Kaplan, (2014). The role of identity, values, and costs in college STEM retention. Journal of Educational Psychology, 106, 315–329. doi:10.1037/a0034027
94. S.Provasnik, D.Kastberg, D.Ferraro, N.Lemanski, S.Roey, & F.Jenkins, (2012). Highlights from TIMSS 2011:Mathematics and science achievement of U.S. fourth- and eighth-grade students in an international context (NCES 2013-009). Washington, DC:National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education.
95. R Core Team. (2014). R:A language and environment for statistical computing. Vienna:R Foundation for Statistical Computing. Retrieved from http://www.R-project.org/
96. V.S.Ramachandran, (2004). The making of a scientist. In J.Brockman (Ed.), Curious minds:How a child becomes a scientist. (pp. 211–218). New York:NY:Pantheon Books.
97. T.Raykov, & G.A.Marcoulides, (2006). A first course in structural equation modeling (2nd ed.). Mahwah, NJ:Lawrence Erlbaum Associates.
98. Z.Said, L.R.Summers, F.Abd-El-Khalick, & S.Wang, (2016). Attitudes toward science among grades 3 through 12 Arab students in Qatar:Findings from a cross-sectional national study. International Journal of Science Education, 38, 621–643. doi:10.1080/09500693.2016.1156184
99. P.W.Schultz, P.R.Hernandez, A.Woodcock, M.Estrada, R.C.Chance, M.Aguilar, & R.T.Serpe, (2011). Patching the pipeline:Reducing educational disparities in the sciences through minority training programs. Educational Evaluation and Policy Analysis, 33, 95–114. doi:10.3102/0162373710392371
100. E.Shonstrom, (2016). Wild curiosity:How to unleash creativity and encourage lifelong learning. New York, NY:Rowman & Littlefield.
101. J.Sjaastad, (2012). Sources of inspiration:The role of significant persons in young people’s choice of science in higher education. International Journal of Science Education, 34, 1615–1636. doi:10.1080/09500693.2011.590543
102. J.Sjaastad, (2013). Measuring the ways significant persons influence attitudes towards science and mathematics. International Journal of Science Education, 35, 192–212. doi:10.1080.09500693.2012.672775
103. 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
104. B.Spinath, & R.Steinmayr, (2012). The roles of competence beliefs and goal orientations for change in intrinsic motivation. Journal of Educational Psychology, 104, 1135–1148. doi:10.1037/a0028115
105. S.Sy, A.W.Gottfried, & A.E.Gottfried, (2013). A transactional model of parental involvement and children’s achievement from early childhood through adolescence. Parenting:Science and Practice, 13, 133–152. doi:10.1080/15295192.2012.709155
106. R.H.Tai, C.Q.Liu, A.V.Maltese, & X.Fan, (2006). Planning early for careers in science. Science, 312, 1143–1144. doi:10.1126/science.1128690
107. P.Tamir, (1988). The relationship between cognitive preferences, student background and achievement in science. Journal of Research in Science Teaching, 25, 201–216. doi:10.1002/tea.3660250305
108. J.Trusty, (2002). Effects of high school course-taking and other variables on choice of science and mathematics college majors. Journal of Counseling and Development, 80, 464–474. doi:10.1002/j.1556-6678,2002,tb00213.X
109. M.S.Turner, (2014). The power of curiosity. Science, 344, 449. doi:10.1126/science.1255182
110. R.Tytler, (2014). Attitudes, identity, and aspirations toward science. In N.G.Lederman & S.K.Abell (Eds.), Handbook of research on science education (Vol. II, pp. 82–103). New York, NY:Routledge.
111. J.B.Ullman, (2006). Structural equation modeling:Reviewing the basics and moving forward. Journal of Personality Assessment, 87, 35–50. doi:10.1207/s15327752jpa8701_03
112. J.B.Ullman, (2012). Structural equation modeling. In B.G.Tabachnick & L.S.Fidell (Eds.), Using multivariate statistics (6th ed., pp. 681–786). San Francisco, CA:Pearson.
113. G.Venville, L.Rennie, C.Hanbury, & N.Longnecker, (2013). Scientists reflect on why they chose to study science. Research in Science Education, 43, 2207–2233. doi:10.1007/s11165-013-9352-3
114. H.-G.Voss, & H.Keller, (1983). Curiosity and exploration. New York, NY:Academic Press.
115. X.Wang, (2013). Why students choose STEM majors:Motivation, high school learning, and postsecondary context of support. American Educational Research Journal, 50, 1081–1121. doi:10.3102/0002831213488622