Portrait of Middle School Students' Implicit Beliefs about Intelligence: A Qualitative View

Öz

This research is concerned with the meanings attributed to the nature of personal characteristics such as intelligence. These meaning systems were examined by using observation, interview and academic diary data for 15 weeks on a study group of 5 students and an attempt was made to reveal a portrait of 6th grade middle school students' implicit beliefs about intelligence. In this process, which was conducted as a qualitative case study, a single case-holistic design was used. The research data were analyzed with the content analysis approach in MAXQUDA Analytics Pro 2022 package program. The findings showed that students accepted intelligence as a very limited concept and that this understanding was related to implicit beliefs about intelligence. It was concluded that being fixed mindset-oriented does not depend on the belief that intelligence is a natural ability, but as the implicit theory predicts, mindsets play a role in the efficiency of students' learning lives (motivational orientations, persistence behavior, etc.). The results are discussed in the context of the mediating role of these ways of thinking on the structural features and outcomes of learning. Suggestions were made for expanding the scope of research to understand the ages at which implicit beliefs about intelligence are formed, their origins, how they develop and their relationship with personality traits.

Anahtar Kelimeler

• growth mindset
• motivation to learn
• implicit theories of intelligence
• fixed mindset
• mindsets

Ortaokul Öğrencilerinin Zekâ Hakkındaki Örtük İnançlarının Portresi: Nitel Bir Bakış

Öz

Bu araştırma, zekâ gibi kişisel niteliklerin doğasına atfedilen anlamlarla ilgilidir. Bu anlam sistemleri, 5 öğrenciden oluşan bir çalışma grubu üzerinde 15 hafta boyunca gözlem, görüşme ve akademik günlük verileri kullanılarak incelenmiş ve ortaokul 6. sınıf öğrencilerinin zekâya ilişkin örtük inançlarının bir portresi ortaya koyulmaya çalışılmıştır. Nitel durum çalışması olarak yürütülen bu süreçte, bütüncül tek durum deseni kullanılmıştır. Araştırma verileri, MAXQUDA Analytics Pro 2022 paket programında içerik analizi yaklaşımı ile analiz edilmiştir. Bulgular, öğrencilerin zekâyı oldukça sınırlı bir kavram olarak kabul ettiklerini ve bu anlayışın zekâya ilişkin örtük inançlarla ilişkili olduğunu göstermiştir. Sabit zihniyet odaklı olmanın zekânın doğal bir yetenek olduğu inancına bağlı olmadığı ancak örtük teorinin öngördüğü gibi zihniyetlerin, öğrencilerin öğrenme yaşamlarının (motivasyonel yönelimler, sebat davranışı vb.) verimliliğinde rol oynadığı sonucuna ulaşılmıştır. Sonuçlar, bu düşünce tarzlarının öğrenmenin yapısal özellikleri ve sonuçları üzerindeki aracı rolü bağlamında tartışılmıştır. Zekâya ilişkin örtük inançların hangi yaşlarda oluştuğu, kökenleri, nasıl geliştikleri ve kişilik özellikleriyle ilişkilerinin anlaşılması için araştırma kapsamının genişletilmesine yönelik önerilerde bulunulmuştur.

Anahtar Kelimeler

• gelişim zihniyeti
• öğrenme motivasyonu
• örtük zekâ teorileri
• sabit zihniyet
• zihniyetler

Kaynakça

1. Allegrini, A. G., Selzam, S., Rimfeld, K., von Stumm, S., Pingault, J. B., & Plomin, R. (2019). Genomic prediction of cognitive traits in childhood and adolescence. Molecular psychiatry, 24(6), 819–827. https://doi.org/10.1038/s41380-019-0394-4
2. Ames, C. (1992). Achievement goals and the classroom motivational climate. D. H. Schunk & J. L. Meece (Eds.), Student perceptions in the classroom içinde (ss. 327–348). Lawrence Erlbaum Associates, Inc
3. Bejjani, C., DePasque, S., & Tricomi, E. (2019). Intelligence mindset shapes neural learning signals and memory. Biological Psychology, 146, Article 107715. https://doi.org/10.1016/j.biopsycho.2019.06.003
4. Birt, L., Scott, S., Cavers, D., Campbell, C., & Walter, F. (2016). Member checking: A tool to enhance trustworthiness or merely a nod to validation? Qualitative Health Research, 26(13), 1802–1811. https://doi.org/10.1177/1049732316654870
5. Blackwell, L. S., Trzesniewski, K. H. & Dweck, C. S. (2007). Implicit theories of intelligence predict achievement across an adolescent transition: A longitudinal study and an intervention. Child Development, 78(1), 246–263. https://doi.org/10.1111/j.1467-8624.2007.00995.x
6. Boaler, J. (2016). Mathematical mindsets: Unleashing students' potential through creative math, inspiring messages and innovative teaching. Jossey-Bass.
7. Bogdan, R. C. & Biklen, S. K. (1998). Qualitative research for education: An introduction to theory and methods (3rd Edition). Boston, Allyn and Bacon.
8. Bolger, N., Davis, A., & Rafaeli, E. (2003). Diary Methods: Capturing Life as it is Lived. Annual Review of Psychology, 54(1), 579–616. https://doi.org/10.1146/annurev.psych.54.101601.145030

9. Boroshok, A. L., Park, A. T., Fotiadis, P., Velasquez, G. H., Tooley, U. A., Simon, K. R., Forde, J. C. P., Delgado Reyes, L. M., Tisdall, M. D., Bassett, D. S., Cooper, E. A., & Mackey, A. P. (2022). Individual differences in frontoparietal plasticity in humans. Npj Science of Learning, 7(1), 1–10. https://doi.org/10.1038/s41539-022-00130-1
10. Bouchard T. J., Jr (2009). Genetic influence on human intelligence (Spearman's g): how much?. Annals of human biology, 36(5), 527–544. https://doi.org/10.1080/03014460903103939
11. Bouchard, T., Lykken, D., McGue, M., Segal, N., & Tellegen, A. (1990). Sources of human psychological differences: the Minnesota Study of Twins Reared Apart. Science, 250(4978), 223–228. https://doi.org/10.1126/science.2218526
12. Brinch, C. N., & Galloway, T. A. (2011). Schooling in adolescence raises IQ scores. Proceedings of the National Academy of Sciences, 109(2), 425–430. https://doi.org/10.1073/pnas.1106077109
13. Burnette, J. L., Billingsley, J., Banks, G. C., Knouse, L. E., Hoyt, C. L., Pollack, J. M., & Simon, S. (2023). A systematic review and meta-analysis of growth mindset interventions: For whom, how, and why might such interventions work? Psychological Bulletin, 149(3-4), 174–205. https://doi.org/10.1037/bul0000368
14. Charmaz, K. (2014). Constructing grounded theory. Sage publications.
15. Cheesman, R., Borgen, N.T., Lyngstad, T.H. et al. A population-wide gene-environment interaction study on how genes, schools, and residential areas shape achievement. npj Sci. Learn. 7, 29 (2022). https://doi.org/10.1038/s41539-022-00145-8
16. Cohen, L., Manion, L., & Morrison, K. (2018). Research Methods in Education (8th ed.). London: Routledge. https://doi.org/10.4324/9781315456539
17. Cook, D. A., Castillo, R. M., Gas, B., & Artino, A. R. (2017). Measuring achievement goal motivation, mindsets and cognitive load: Validation of three instruments’ scores. Medical Education, 51(10), 1061–1074. https://doi.org/10.1111/medu.13405
18. Costa, A., & Faria, L. (2018). Implicit theories of intelligence and academic achievement: A meta-analytic review. Frontiers in Psychology, 9, Article 829. https://doi.org/10.3389/fpsyg.2018.00829
19. Costa, A., & Faria, L. (2023). Implicit Theories of Emotional Intelligence and Students’ Emotional and Academic Outcomes. Psychological Reports, 0(0). https://doi.org/10.1177/00332941231183327
20. Covington, M. V., & Omelich, C. L. (1979). Effort: The double-edged sword in school achievement. Journal of Educational Psychology, 71(2), 169–182. https://doi.org/10.1037/0022-0663.71.2.169
21. Creswell, J. W. (2012). Educational research: Planning, conducting, and evaluating quantitative and qualitative research (4th ed.). Pearson.
22. Creswell, J. W. (2016). 30 essential skills for the qualitative researcher. Sage.
23. Creswell, J. W., & Poth, C. N. (2018). Qualitative inquiry and research design: Choosing among five approaches. Sage publications.
24. Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. Harper & Row.
25. Cury, F., Da Fonseca, D., Zahn, I., & Elliot, A. (2008). Implicit theories and IQ test performance: A sequential mediational analysis. Journal of Experimental Social Psychology, 44(3), 783–791.
26. Deary, I. J., Strand, S., Smith, P., & Fernandes, C. (2007). Intelligence and educational achievement. Intelligence, 35(1), 13–21. https://doi.org/10.1016/j.intell.2006.02.001
27. Denzin, N. K., & Lincoln, Y. S. (2011). The SAGE handbook of qualitative research. Sage publications.
28. DePasque, S., & Tricomi, E. (2015). Effects of intrinsic motivation on feedback processing during learning. NeuroImage, 119, 175–186.
29. Detterman D. K. (2016). Education and Intelligence: Pity the Poor Teacher because Student Characteristics are more Significant than Teachers or Schools. The Spanish journal of psychology, 19, E93. https://doi.org/10.1017/sjp.2016.88
30. Devi, S.P., Mishra, A.K. The Testing Effect: Looking Through Implicit Theories’ Perspectives. Psychol Stud 68, 92–100 (2023). https://doi.org/10.1007/s12646-022-00710-6
31. Diener, C. I., & Dweck, C. S. (1978). An analysis of learned helplessness: Continuous changes in performance, strategy, and achievement cognitions following failure. Journal of Personality and Social Psychology, 36(5), 451–462. https://doi.org/10.1037/0022-3514.36.5.451
32. Donati, G., Dumontheil, I., Pain, O. et al. Evidence for specificity of polygenic contributions to attainment in English, maths and science during adolescence. Sci Rep 11, 3851 (2021). https://doi.org/10.1038/s41598-021-82877-y
33. Dong, L., Jia, X., & Fei, Y. (2023). How growth mindset influences mathematics achievements: A study of Chinese middle school students. Frontiers in psychology, 14, 1148754. https://doi.org/10.3389/fpsyg.2023.1148754
34. Donohoe, C., Topping, K., & Hannah, E. (2012). The impact of an online intervention (Brainology) on the mindset and resiliency of secondary school pupils: a preliminary mixed methods study. Educational Psychology, 32(5), 641–655. https://doi.org/10.1080/01443410.2012.675646
35. Downe‐Wamboldt, B. (1992). Content analysis: Method, applications, and issues. Health Care for Women International, 13(3), 313–321. https://doi.org/10.1080/07399339209516006
36. Dunkel, C. S., van der Linden, D., & Kawamoto, T. (2023). Maternal supportiveness is predictive of childhood general intelligence. Intelligence, 98(101754), 101754. https://doi.org/10.1016/j.intell.2023.101754
37. Dweck, C. S. (1975). The role of expectations and attributions in the alleviation of learned helplessness. Journal of Personality and Social Psychology, 31(4), 674–685. https://doi.org/10.1037/h0077149
38. Dweck, C. S. (1986). Motivational processes affecting learning. American Psychologist, 41(10), 1040–1048. https://doi.org/10.1037/0003-066X.41.10.1040
39. Dweck, C. S. (1999). Self-theories: Their role in motivation, personality, and development. Psychology Press.
40. Dweck, C. S. (2006). Mindset: The new psychology of success. Random House.
41. Dweck, C. S. (2012). Implicit theories. P. A. M. Van Lange, A. W. Kruglanski, & E. T. Higgins (Eds.), Handbook of theories of social psychology içinde (ss. 43-61). Sage Publications Ltd. https://doi.org/10.4135/9781446249222.n28
42. Dweck, C. S., & Leggett, E. L. (1988). A social-cognitive approach to motivation and personality. Psychological Review, 95(2), 256–273. https://doi.org/10.1037/0033-295X.95.2.256
43. Dweck, C. S., & Molden, D. C. (2017). Mindsets: Their impact on competence motivation and acquisition. A. J.
44. Elliot, C. S. Dweck, & D. S. Yeager (Eds.), Handbook of competence and motivation: Theory and application içinde (ss. 135–154). The Guilford Press.
45. Dweck, C. S., & Sorich, L. A. (1999). Mastery-oriented thinking. C. R. Snyder (Ed.), Coping: The psychology ofwhat works içinde (ss. 232-251). Oxford University Press.
46. Elliot, A. J., & Church, M. A. (1997). A hierarchical model of approach and avoidance achievement motivation. Journal of Personality and Social Psychology, 72(1), 218–232. https://doi.org/10.1037/0022-3514.72.1.218
47. Elliott, E. S., & Dweck, C. S. (1988). Goals: An approach to motivation and achievement. Journal of Personality and Social Psychology, 54(1), 5–12. https://doi.org/10.1037/0022-3514.54.1.5
48. Elo, S., Kääriäinen, M., Kanste, O., Pölkki, T., Utriainen, K., & Kyngäs, H. (2014). Qualitative Content Analysis. SAGE Open, 4(1), 215824401452263. https://doi.org/10.1177/2158244014522633
49. Erlandson, D. A., Harris, E. L., Skipper, B. L., & Allen, S. D. (1993). Doing naturalistic inquiry: A guide to methods. Sage Publications, Inc.
50. Festinger, L. (1957). A theory of cognitive dissonance. Stanford University Press.
51. Flick, U. (2018). The SAGE handbook of qualitative data collection. Sage publications.
52. Gal É, Tóth-Király I and Orosz G (2022) Fixed Intelligence Mindset, Self-Esteem, and Failure-Related Negative Emotions: A Cross-Cultural Mediation Model. Front. Psychol. 13:852638. https://doi.org/10.3389/fpsyg.2022.852638
53. Gardner, H. (2011) Frames of mind: The theory of multiple intelligences. Basic Books.
54. Garlick D. (2002). Understanding the nature of the general factor of intelligence: the role of individual differences in neural plasticity as an explanatory mechanism. Psychological review, 109(1), 116–136. https://doi.org/10.1037/0033-295x.109.1.116
55. Glesne c. (2016). Becoming qualitative researchers an introduction (5th ed.). Pearson.
56. Godard, A., Arciszewski, T., Énéa-Drapeau, C., & Perret, P. (2023). Les théories implicites de l’intelligence : une question de perspectives ? Psychologie française, 68(1), 137–155. https://doi.org/10.1016/j.psfr.2021.09.001
57. Gouëdard, P. (2021), Can a growth mindset help disadvantaged students close the gap?, PISA in Focus, No. 112, OECD Publishing, https://doi.org/10.1787/20922f0d-en
58. Güngör, İ. C. (2023). Mindsets of secondary school teachers: A look at intelligence in the context of implicit theories. Anadolu Journal of Educational Sciences International, 13(2), 303-338. https://doi.org/10.18039/ajesi.1238526
59. Haimovitz, K., & Dweck, C. S. (2016). What predicts children’s fixed and growth intelligence mind-sets? Not their parents’ views of intelligence but their parents’ views of failure. Psychological Science, 27(6), 859–869. https://doi.org/10.1177/0956797616639727
60. Hart, S. A., Little, C., & van Bergen, E. (2021). Nurture might be nature: cautionary tales and proposed solutions. Npj Science of Learning, 6(1), 1–12. https://doi.org/10.1038/s41539-020-00079-z
61. Hertel, S., & Karlen, Y. (2021). Implicit theories of self‐regulated learning: Interplay with students’ achievement goals, learning strategies, and metacognition. British Journal of Educational Psychology, 91(3), 972–996. https://doi.org/10.1111/bjep.12402
62. Hokoda, A., & Fincham, F. D. (1995). Origins of children's helpless and mastery achievement patterns in the family. Journal of Educational Psychology, 87(3), 375–385. https://doi.org/10.1037/0022-0663.87.3.375
63. Hong, Y.-y., Chiu, C.-y., Dweck, C. S., Lin, D. M.-S., & Wan, W. (1999). Implicit theories, attributions, and coping: A meaning system approach. Journal of Personality and Social Psychology, 77(3), 588–599. https://doi.org/10.1037/0022-3514.77.3.588
64. Hsieh, PH. (2011). Mastery Orientation. Goldstein, S., Naglieri, J.A. (eds). Encyclopedia of Child Behavior and Development. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-79061-9_1722
65. Ivchenko, G. I., & Honov, S. A. (1998). On the jaccard similarity test. Journal of Mathematical Sciences, 88(6), 789-794.
66. Jensen, A. R. (1998). The g factor: The science of mental ability. Praeger Publishers/Greenwood Publishing Group.
67. Jia, X., Hao, L., He, L., Li, P., Liu, M., Zhang, Y., & Qiu, J. (2023). Regional Gray Matter Volume Is Associated with Growth Mindset: A Voxel-Based Morphometry Study. Neuroscience, 509, 96–102. https://doi.org/10.1016/j.neuroscience.2022.11.020
68. Johnson, W., Deary, I. J., & Iacono, W. G. (2009). Genetic and environmental transactions underlying educational attainment. Intelligence, 37(5), 466–478. https://doi.org/10.1016/j.intell.2009.05.006
69. Jose, P. E., & Bellamy, M. A. (2011). Relationships of Parents’ Theories of Intelligence With Children’s Persistence/Learned Helplessness. Journal of Cross-Cultural Psychology, 43(6), 999–1018. https://doi.org/10.1177/0022022111421633
70. Judd, N., Sauce, B. & Klingberg, T. Schooling substantially improves intelligence, but neither lessens nor widens the impacts of socioeconomics and genetics. npj Sci. Learn. 7, 33 (2022). https://doi.org/10.1038/s41539-022-00148-5
71. Kahneman, D. (2011). Thinking, fast and slow. Farrar, Straus and Giroux.
72. Kahneman, D., & Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica, 47(2), 263. https://doi.org/10.2307/1914185
73. King R. B. (2020). Mindsets are contagious: The social contagion of implicit theories of intelligence among classmates. The British journal of educational psychology, 90(2), 349–363. https://doi.org/10.1111/bjep.12285
74. King, R. B. (2017). A fixed mindset leads to negative affect: The relations between implicit theories of intelligence and subjective well-being. Zeitschrift Für Psychologie, 225(2), 137–145. https://doi.org/10.1027/2151-2604/a000290
75. Kuckartz, U., Rädiker, S. (2019). Working with Bibliographic Information and Creating Literature Reviews. Analyzing Qualitative Data with MAXQDA. Springer. https://doi.org/10.1007/978-3-030-15671-8_14
76. Kyngäs, H. (2020). Inductive content analysis. Kyngäs, H., Mikkonen, K., Kääriäinen, M. (eds) The Application of Content Analysis in Nursing Science Research içinde. (ss.13-21). Springer, Cham. https://doi.org/10.1007/978-3-030-30199-6_2
77. Lavrijsen, J., Vansteenkiste, M., Boncquet, M., & Verschueren, K. (2022). Does motivation predict changes in academic achievement beyond intelligence and personality? A multitheoretical perspective. Journal of Educational Psychology, 114(4), 772–790. https://doi.org/10.1037/edu0000666
78. Lee, H. Y., & Yeager, D. S. (2020). Adolescents with an entity theory of personality are more vigilant to social status and use relational aggression to maintain social status. Social development (Oxford, England), 29(1), 273–289. https://doi.org/10.1111/sode.12393
79. Li, Y., & Bates, T. C. (2020). Testing the association of growth mindset and grades across a challenging transition: Is growth mindset associated with grades? Intelligence, 81, 101471. https://doi.org/10.1016/j.intell.2020.101471
80. Liamputtong, P. (2013). Qualitative Research Methods (4th ed.). South Melbourne: Oxford University Press.
81. Limeri, L. B., Carter, N. T., Choe, J., Harper, H. G., Martin, H. R., Benton, A., & Dolan, E. L. (2020). Growing a growth mindset: characterizing how and why undergraduate students’ mindsets change. International Journal of STEM Education, 7(1). https://doi.org/10.1186/s40594-020-00227-2
82. Lincoln, Y.S. & Guba, E.G. (1985). Naturalistic inquiry. SAGE.
83. Liu WC (2021) Implicit Theories of Intelligence and Achievement Goals: A Look at Students’ Intrinsic Motivation and Achievement in Mathematics. Front. Psychol. 12:593715. https://doi.org/10.3389/fpsyg.2021.593715
84. Macnamara, B. N., & Burgoyne, A. P. (2023). Do growth mindset interventions impact students’ academic achievement? A systematic review and meta-analysis with recommendations for best practices. Psychological Bulletin, 149(3-4), 133–173. https://doi.org/10.1037/bul0000352
85. Mangels, J. A., Butterfield, B., Lamb, J., Good, C., & Dweck, C. S. (2006). Why do beliefs about intelligence influence learning success? A social cognitive neuroscience model. Social Cognitive and Affective Neuroscience, 1(2), 75–86.
86. Mangels, J. A., Butterfield, B., Lamb, J., Good, C., & Dweck, C. S. (2006). Why do beliefs about intelligence influence learning success? A social cognitive neuroscience model. Social Cognitive and Affective Neuroscience, 1(2), 75–86. https://doi.org/10.1093/scan/nsl013
87. Marzano, R. J., & Kendall, J. S. (2007). The new taxonomy of educational objectives. Corwin.
88. Maxwell, J.A. (2013). Qualitative research design. An interactive approach (3rd ed.). SAGE
89. Merriam, S. B. (2009). Qualitative research: A guide to design and implementation. John Wiley & Sons. Mollon J, David AS, Zammit S, Lewis G, Reichenberg A. (2018). Course of cognitive development from infancy to early adulthood in the psychosis spectrum. JAMA Psychiatry, 75(3):270–279. https://doi.org/10.1001/jamapsychiatry.2017.4327
90. Moser, J. S., Schroder, H. S., Heeter, C., Moran, T. P., & Lee, Y. H. (2011). Mind your errors: evidence for a neural mechanism linking growth mind-set to adaptive posterror adjustments. Psychological science, 22(12), 1484–1489. https://doi.org/10.1177/0956797611419520
91. Myers, C. A., Wang, C., Black, J. M., Bugescu, N., & Hoeft, F. (2016). The matter of motivation: Striatal resting-state connectivity is dissociable between grit and growth mindset. Social Cognitive and Affective Neuroscience, 11(10), 1521–1527. https://doi.org/10.1093/scan/nsw065
92. Neuman, W. L. (2014). Social research methods: Qualitative and quantitive approaches (7th Ed). Pearson. Nisbett, R. E., Aronson, J., Blair, C., Dickens, W., Flynn, J., Halpern, D. F., & Turkheimer, E. (2012). Group differences in IQ are best understood as environmental in origin. American Psychologist, 67(6), 503–504. https://doi.org/10.1037/a0029772
93. Oeberst, A., & Imhoff, R. (2023). Toward Parsimony in Bias Research: A Proposed Common Framework of Belief-Consistent Information Processing for a Set of Biases. Perspectives on Psychological Science, 0(0). https://doi.org/10.1177/17456916221148147
94. OECD. (2019). PISA 2018 results (Volume III): What school life means for students’ lives. OECD Publishing. https://doi.org/10.1787/acd78851-en
95. OECD. (2021). PISA 2018: Sky's the limit—growth mindset, students, and schools in PISA. OECD Publishing. https://www.oecd.org/pisa/growth-mindset.pdf 05.012.2023 tarihinde erişilmiştir.
96. Orosz G, Péter-Szarka S, Bőthe B, Tóth-Király I and Berger R (2017) How Not to Do a Mindset Intervention: Learning from a Mindset Intervention among Students with Good Grades. Front. Psychol. 8:311. https://doi.org/10.3389/fpsyg.2017.00311
97. Palminteri, S., Khamassi, M., Joffily, M. et al. Contextual modulation of value signals in reward and punishment learning. Nat Commun 6, 8096 (2015). https://doi.org/10.1038/ncomms9096
98. Palys, T. (2008). Purposive sampling. L. M. Given (Ed.) The Sage Encyclopedia of Qualitative Research Methods Vol. 2 içinde. (ss. 697-698). Sage.
99. Patton. M. Q. (2002). Qualitative research and evaluation methods (3rd ed.). Thousand Oaks, CA: Sage Publications.
100. Pinker, S. (2003) The blank slate: The modern denial of human nature. Penguin Books, London.
101. Pintrich, P. R. (2000). The role of goal orientation in self-regulated learning. M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation içinde (ss. 451–502). Academic Press. https://doi.org/10.1016/B978-012109890-2/50043-3
102. Procopio, Francesca, Quan Zhou, Ziye Wang, Agnieska Gidziela, Kaili Rimfeld, Margherita Malanchini, and Robert Plomin. 2022. The genetics of specific cognitive abilities. Intelligence 95: 101689. https://doi.org/10.1016/j.intell.2022.101689
103. Putnick, D. L., Hahn, C.‐S., Hendricks, C., Suwalsky, J. T. D., & Bornstein, M. H. (2020). Child, mother, father, and teacher beliefs about child academic competence: Predicting math and reading performance in European American adolescents. Journal of Research on Adolescence, 30(Suppl 2), 298–314. https://doi.org/10.1111/jora.12477
104. Ramsden, S., Richardson, F., Josse, G. et al. (2011). Verbal and non-verbal intelligence changes in the teenage brain. Nature 479, 113–116. https://doi.org/10.1038/nature10514
105. Reeve, J. (2018). Understanding motivation and emotion, (7th ed). John Wiley & Sons, Inc.
106. Rimfeld, K., Malanchini, M., Krapohl, E. et al. The stability of educational achievement across school years is largely explained by genetic factors. npj Science Learn 3, 16 (2018). https://doi.org/10.1038/s41539-018-0030-0
107. Ritchie, S. J., & Tucker-Drob, E. M. (2018). How much does education ımprove ıntelligence? A meta-analysis. Psychological Science, 29(8), 1358–1369. https://doi.org/10.1177/0956797618774253
108. Ritchie, S. J., Bates, T. C., & Deary, I. J. (2015). Is education associated with improvements in general cognitive ability, or in specific skills?. Developmental psychology, 51(5), 573–582. https://doi.org/10.1037/a0038981
109. Romero, C., Master, A., Paunesku, D., Dweck, C. S., & Gross, J. J. (2014). Academic and emotional functioning in middle school: The role of implicit theories. Emotion, 14(2), 227–234. https://doi.org/10.1037/a0035490
110. Rönnlund, M., Sundström, A., & Nilsson, L.-G. (2015). Interindividual differences in general cognitive ability from age 18 to age 65years are extremely stable and strongly associated with working memory capacity. Intelligence, 53, 59–64. https://doi.org/10.1016/j.intell.2015.08.011
111. Sarkar, T. (2021). Intelligence is not just good grades: Re-examining the mindset revolution in Indian classrooms. Compare: A Journal of Comparative and International Education, 53(5). https://doi.org/10.1080/03057925.2021.1965467
112. Schroder, H. S., Fisher, M. E., Lin, Y., Lo, S. L., Danovitch, J. H., & Moser, J. S. (2017). Neural evidence for enhanced attention to mistakes among school-aged children with a growth mindset. Developmental Cognitive Neuroscience, 24, 42–50. https://doi.org/10.1016/j.dcn.2017.01.004
113. Schunk, D. H., & Zimmerman, B. J. (2007). Influencing children's self-efficacy and self-regulation of reading and writing through modeling. Reading & Writing Quarterly: Overcoming Learning Difficulties, 23(1), 7–25. https://doi.org/10.1080/10573560600837578
114. Seale, C. (2004). The quality of qualitative research. Sage publications.
115. Seblova, D., Eng, C., Avila-Rieger, J. F., Dworkin, J. D., Peters, K., Lapham, S., Zahodne, L. B., Chapman, B., Prescott, C. A., Gruenewald, T. L., Arpawong, T. E., Gatz, M., Jones, R. J., Glymour, M. M., & Manly, J. J. (2023). High school quality is associated with cognition 58 years later. Alzheimer's & dementia (Amsterdam, Netherlands), 15(2), e12424. https://doi.org/10.1002/dad2.12424
116. Seligman, M. E. P. (1975). Helplessness: On depression, development, and death. W H Freeman/Times Books/ Henry Holt & Co
117. Selzam, S., Dale, P. S., Wagner, R. K., DeFries, J. C., Cederlöf, M., O'Reilly, P. F., Krapohl, E., & Plomin, R. (2017). Genome-wide polygenic scores predict reading performance throughout the school years. Scientific Studies of Reading, 21(4), 334–349. https://doi.org/10.1080/10888438.2017.1299152
118. Silventoinen, K., Jelenkovic, A., Sund, R. et al. Genetic and environmental variation in educational attainment: an individual-based analysis of 28 twin cohorts. Sci Rep 10, 12681 (2020). https://doi.org/10.1038/s41598-020-69526-6
119. Skeide, M. A., Wehrmann, K., Emami, Z., Kirsten, H., Hartmann, A. M., & Rujescu, D. (2020). Neurobiological origins of individual differences in mathematical ability. PLOS Biology, 18(10), e3000871.
120. Sniekers, S., Stringer, S., Watanabe, K. et al. Genome-wide association meta-analysis of 78,308 individuals identifies new loci and genes influencing human intelligence. Nat Genet 49, 1107–1112 (2017). https://doi.org/10.1038/ng.3869
121. Snipes, J., & Tran, L. (2017). Growth mindset, performance avoidance, and academic behaviors in Clark County School District (REL 2017–226). Washington, DC: U.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance, Regional Educational Laboratory West.
122. Song, Y, Barger, M. M. & Bub, K. L. (2022). The Association Between Parents’ Growth Mindset and Children’s Persistence and Academic Skills. Front. Educ. 6:791652. https://doi.org/10.3389/feduc.2021.791652
123. Spradley, J. (1980). Participant Observation. Holt, Rinehart and Winston
124. Stanek, K. C. & Ones, D. S. (2023). Meta-analytic relations between personality and cognitive ability. PNAS, 120(23) e2212794120. https://doi.org/10.1073/pnas.2212794120
125. Steinhauser, M., & Yeung, N. (2010). Decision processes in human performance monitoring. The Journal of neuroscience : The official journal of the Society for Neuroscience, 30(46), 15643–15653. https://doi.org/10.1523/JNEUROSCI.1899-10.2010
126. Sternberg, R. J. (1986). A triangular theory of love. Psychological Review, 93(2), 119–135. https://doi.org/10.1037/0033-295X.93.2.119
127. Stipek, D., & Gralinski, J. H. (1996). Children's beliefs about intelligence and school performance. Journal of Educational Psychology, 88(3), 397–407. https://doi.org/10.1037/0022-0663.88.3.397
128. Su, A., Wan, S., He, W. & Dong, L. (2021). Effect of Intelligence Mindsets on Math Achievement for Chinese Primary School Students: Math Self-Efficacy and Failure Beliefs as Mediators. Front. Psychol. 12:640349. https://doi.org/10.3389/fpsyg.2021.640349
129. Sun, X., Nancekivell, S., Gelman, S. A., & Shah, P. (2021). Growth mindset and academic outcomes: a comparison of US and Chinese students. Npj Science of Learning, 6(1), 1–9. https://doi.org/10.1038/s41539-021-00100-z
130. Svensen, E. (2023). Mindset as a potential link between family background and high-school achievement. Acta Sociologica, 66(3), 322–342. https://doi.org/10.1177/00016993221145427
131. Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1207/s15516709cog1202_4
132. Sweller, J. (2011). Cognitive load theory. J. P. Mestre & B. H. Ross (Eds.), The psychology of learning and motivation: Cognition in education içinde (ss. 37–76). Elsevier Academic Press. https://doi.org/10.1016/B978-0-12-387691-1.00002-8
133. Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131. https://psycnet.apa.org/doi/10.1126/science.185.4157.1124
134. Vandewalle, D. (2012). A growth and fixed mindset exposition of the value of conceptual clarity. Industrial and Organizational Psychology, 5(3), 301-305. https://doi.org/10.1111/j.1754-9434.2012.01450.x
135. Wagner, B. M., & Phillips, D. A. (1992). Beyond beliefs: Parent and child behaviors and children's perceived academic competence. Child Development, 63(6), 1380–1391. https://doi.org/10.2307/1131563
136. Walton, J. (1992). Making the theoretical case. C. Ragin and H. Becker (Eds.). What is a case? Ex- ploring the foundations of social inquiry içinde. (ss. 121–138). Cambridge University Press.
137. Woolf, N. H., & Silver, C. (2018). Qualitative analysis using MAXQDA: The five-level QDATM method. Routledge.
138. World Bank. (2018). World development report 2018: Learning to realize education’s promise. World Bank. https://www.worldbank.org/en/publication/wdr2018 adresinden 05. 12. 2023 tarihinde erişilmiştir.
139. Xu, K. M., Koorn, P., de Koning, B., Skuballa, I. T., Lin, L., Henderikx, M., Marsh, H. W., Sweller, J., & Paas, F. (2021). A growth mindset lowers perceived cognitive load and improves learning: Integrating motivation to cognitive load. Journal of Educational Psychology, 113(6), 1177–1191. https://doi.org/10.1037/edu0000631
140. Xu, X., & Plaks, J. E. (2015). The neural correlates of implicit theory violation. Social neuroscience, 10(4), 431–447. https://doi.org/10.1080/17470919.2015.1008647
141. Yeager, D. S., & Dweck, C. S. (2012). Mindsets that promote resilience: When students believe that personal characteristics can be developed. Educational Psychologist, 47(4), 302–314. https://doi.org/10.1080/00461520.2012.722805
142. Yeager, D. S., & Walton, G. M. (2011). Social-psychological interventions in education: They’re not magic. Review of Educational Research, 81(2), 267–301. https://doi.org/10.3102/0034654311405999
143. Yeager, D.S., Hanselman, P., Walton, G.M. et al. (2019). A national experiment reveals where a growth mindset improves achievement. Nature 573, 364–369. https://doi.org/10.1038/s41586-019-1466-y
144. Yin, R. K. (2012). Applications of case study research (3rd ed). Sage
145. Yin, R.K. (1984) Case Study Research Design and Methods. Sage Publications.
146. Yıldırım, A. ve Şimşek, H. (2016). Sosyal bilimlerde nitel araştırma yöntemleri (Genişletilmiş 10. Baskı). Seçkin Yayıncılık.
147. Zhao, H., Zhang, M., Li, Y., & Wang, Z. (2023). The relationship between a growth mindset and junior high school students' meaning in life: A serial mediation model. Behavioral sciences (Basel, Switzerland), 13(2), 189. https://doi.org/10.3390/bs13020189