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INTELLIGENCE AND ACADEMIC ACHIEVEMENT IN MATHEMATICS AT UNIVERSITY LEVEL: A STUDY OF STUDENTS’ BELIEFS
Corresponding Author(s) : Sadaf Naz
Humanities & Social Sciences Reviews,
Vol. 9 No. 2 (2021): March
Abstract
Purpose of the study: The current study explored a possible association between students’ beliefs about their intelligence and academic achievement and compared gender differences in terms of these two variables.
Methodology: The sample of the study comprised of four hundred and fifty (male and female) MSc mathematics students, randomly selected from seven public sector universities of Khyber Pakhtunkhwa, Pakistan. A scale developed by Dweck (1999) was adapted to collect data for this study. Academic achievement was measured through students’ previous examination scores.
Findings: Findings of the study showed that male students believed more in ‘incremental’ intelligence and had significantly higher academic achievement as compared to their female counterparts. A significant relationship was found between students’ beliefs in ‘incremental’ intelligence and their academic achievement.
Applications of the study: The study has important implications for teachers and academics in the subjects of science and mathematics. This study also has implications for policies planners and administration in terms of developing an understanding regarding the role of students’ beliefs about intelligence and academic achievement. The study could lead to new thinking about ways to work on the beliefs of students that could result in better academic achievement.
The novelty of this study: The study could also lead to further studies regarding the role of gender in affecting incremental beliefs and academic achievement.
Keywords
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- Ajzen, I. (2020). The theory of planned behavior: Frequently asked questions. Human Behavior and Emerging Technologies, 2(4), 314-324. https://doi.org/10.1002/hbe2.195 DOI: https://doi.org/10.1002/hbe2.195
- Alesi, M., Rappo, G., & Pepi, A. (2016). Investigating the improvement of decoding abilities and working memory in children with incremental or entity personal conceptions of intelligence: two case reports. Frontiers in psychology, 6, 1939. https://doi.org/10.3389/fpsyg.2015.01939 DOI: https://doi.org/10.3389/fpsyg.2015.01939
- Aydin, H., Ozfidan, B., & Carothers, D. (2017). Meeting the challenges of curriculum and instruction in school settings in the United States. Journal of Social Studies Education Research, 8(3), 76-92.
- Bandura, A. (1977). Social learning theory. Englewood Cliffs, NJ: Prentice-Hall.
- Barkley, E. F., & Major, C. H. (2020). Student engagement techniques: A handbook for college faculty. John Wiley & Sons.
- Bostwick, K., Collie, R., Martin, A., and Durksen, T. (2017). Students’ growth mindsets, goals, and academic outcomes in mathematics. Zeitschrift Psychol, 225, 107–116. https://doi.org/10.1027/2151-2604/a000287 DOI: https://doi.org/10.1027/2151-2604/a000287
- Boyle, G. J., Neumann, D. L., Furedy, J. J., & Westbury, H. R. (2010). Combining the methods of differential and experimental psychology to study sex differences in human cognitive psychological functions. Perceptual and Motor Skills, 110, 392–410. https://doi.org/10.2466/pms.110.2.396-410 DOI: https://doi.org/10.2466/pms.110.2.396-410
- Brandon, P. S., Lombardi, P., & Shen, G. Q. (Eds.). (2017). Future challenges in evaluating and managing sustainable development in the built environment. Wiley Blackwell. https://doi.org/10.1002/9781119190691 DOI: https://doi.org/10.1002/9781119190691
- Burkley, M., Parker, J., Stermer, S.P., &Burkley, E. (2010). Trait Beliefs that Make Women Vulnerable to Math Disengagement. Personality and Individual Differences, 48(2), 234-238. https://doi.org/10.1016/j.paid.2009.09.002 DOI: https://doi.org/10.1016/j.paid.2009.09.002
- Chen, J. A., and Tutwiler, M. S. (2017). Implicit theories of ability and self-efficacy: testing alternative social cognitive models to science motivation. Zeitschrift Psychol, 225, 127–136. https://doi.org/10.1027/2151-2604/a000289 DOI: https://doi.org/10.1027/2151-2604/a000289
- Chen, W. W., & Wong, Y. L. (2015). Chinese mindset: theories of intelligence, goal orientation and academic achievement in Hong Kong students. Educational Psychology, 35(6), 714-725. https://doi.org/10.1080/01443410 .2014.893559 DOI: https://doi.org/10.1080/01443410.2014.893559
- Claro, S & Loeb, S. (2017). New evidence that students’ beliefs about their brains drive learning. Evidence Speaks Reports, 2(29), 1-7.
- Claro, S., Paunesku, D., & Dweck. C.S. (2016). Growth mindset tempers the effects of poverty on academic achievement, Proceedings of the National Academy of Sciences, 113, 8664-8. https://doi.org/10.1073/pna .1608207113 DOI: https://doi.org/10.1073/pnas.1608207113
- Costa, A., Faria, L., (2018). Implicit Theories of Intelligence and Academic Achievement: A Meta-Analytic Review. Frontiers in Psychology, 9. 1-16. https://doi.org/10.3389/fpsyg.2018.00829 DOI: https://doi.org/10.3389/fpsyg.2018.00829
- De Castella, K., & Byrne, D. (2015). My intelligence may be more malleable than yours: The revised implicit theories of intelligence (self-theory) scale is a better predictor of achievement, motivation, and student disengagement. European Journal of Psychology of Education, 30(3), 245-267. https://doi.org/10.1007/s10212-015-0244-y DOI: https://doi.org/10.1007/s10212-015-0244-y
- Dejonge, M. L., Omran, J., Faulkner, G. E., & Sabiston, C. M. (2020). University students' and clinicians’ beliefs and attitudes towards physical activity for mental health. Mental Health and Physical Activity, 18, 100316. https://doi.org/10.1016/j.mhpa.2019.100316 DOI: https://doi.org/10.1016/j.mhpa.2019.100316
- Devers, A. (2015). Thinking about Intelligence: How Student Mindsets Influence Academic Performance. Rising Tide, 7, 1-23.
- Diaconu-Gherasim, L. R., Tepordei, A. M., Mairean, C., & Rusu, A. (2019). Intelligence beliefs, goal orientations and children’s academic achievement: does the children’s gender matter? Educational Studies, 45(1), 95-112. https://doi.org/10.1080/03055698.2018.1443796 DOI: https://doi.org/10.1080/03055698.2018.1443796
- 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 DOI: https://doi.org/10.1037/0022-3514.54.1.5
- Dweck, C. (1999). Self-theories: their role in motivation, personality, and development. Philadelphia: Psychology Press.
- Eccles, J. S., & Wigfield, A. (2020). From expectancy-value theory to situated expectancy-value theory: A developmental, social cognitive, and sociocultural perspective on motivation. Contemporary Educational Psychology, 61, 101859. https://doi.org/10.1016/j.cedpsych.2020.101859 DOI: https://doi.org/10.1016/j.cedpsych.2020.101859
- Ferla, M., & Graham, A. (2019). Women slowly taking off: An investigation into female underrepresentation in commercial aviation. Research in Transportation Business & Management, 31, 100378. https://doi.org/10.1016/ j.rtbm.2019.100378 DOI: https://doi.org/10.1016/j.rtbm.2019.100378
- Fitri, S., Syahputra, E., & Syahputra, H. (2019). Blended learning rotation model of cognitive conflict strategy to improve mathematical resilience in high school students. International Journal of Scientific & Technology Research, 1(1), 80-87.
- Gay, L.R., Mills, G.E. and Airasian, P. (2011). Educational Research Competencies for Analysis and Applications. Pearson, Columbus.
- Gunderson, E. A., Park, D., Maloney, E. A., Beilock, S. L., & Levine, S. C. (2018). Reciprocal relations among motivational frameworks, math anxiety, and math achievement in early elementary school. Journal of Cognition and Development, 19(1), 21-46. https://doi.org/10.1080/15248372.2017.1421538 DOI: https://doi.org/10.1080/15248372.2017.1421538
- Haimovitz, K., & Dweck, C. S. (2017). The origins of children's growth and fixed mindsets: New research and a new proposal. Child development, 88(6), 1849-1859. https://doi.org/10.1111/cdev.12955 DOI: https://doi.org/10.1111/cdev.12955
- Hava, K., Guyer, T., & Cakir, H. (2020). Gifted students’ learning experiences in systematic game development process in after-school activities. Educational Technology Research and Development, 68(3), 1439-1459. https://doi.org/10.1007/s11423-020-09750-z DOI: https://doi.org/10.1007/s11423-020-09750-z
- Heyder, A., Weidinger, A. F., Cimpian, A., & Steinmayr, R. (2020). Teachers’ belief that math requires innate ability predicts lower intrinsic motivation among low-achieving students. Learning and Instruction, 65, 101220. https://doi.org/10.1016/j.learninstruc.2019.101220 DOI: https://doi.org/10.1016/j.learninstruc.2019.101220
- Hirsch, A., Bieleke, M., Schüler, J., & Wolff, W. (2020). Implicit theories about athletic ability modulate the effects of if-then planning on performance in a standardized endurance task. International journal of environmental research and public health, 17(7), 2576. https://doi.org/10.3390/ijerph17072576 DOI: https://doi.org/10.3390/ijerph17072576
- Hughes, J. S. (2015). Support for the domain specificity of implicit beliefs about persons, intelligence, and morality. Personality and Individual Differences, 86, 195-203. https://doi.org/10.1016/j.paid.2015.05.042 DOI: https://doi.org/10.1016/j.paid.2015.05.042
- Jones, B. D., Byrd, C. N., & Lusk, D. (2009). High school students' beliefs about intelligence. Research In The Schools, 16(2), 1-14.
- Karlen, Y., Suter, F., Hirt, C., & Merki, K. M. (2019). The role of implicit theories in students' grit, achievement goals, intrinsic and extrinsic motivation, and achievement in the context of a long-term challenging task. Learning and Individual Differences, 74, 101757. https://doi.org/10.1016/j.lindif.2019.101757 DOI: https://doi.org/10.1016/j.lindif.2019.101757
- Kassaee, A. M. (2016). Examining the role of motivation and mindset in the performance of college students majoring in STEM fields (Doctoral dissertation, Middle Tennessee State University).
- Kim, Y. C., & Jung, J. H. (2019). Conceptualizing shadow curriculum: definition, features and the changing landscapes of learning cultures. Journal of Curriculum Studies, 51(2), 141-161. https://doi.org/10.1080/00220 272.2019.1568583 DOI: https://doi.org/10.1080/00220272.2019.1568583
- Lee, J. J. (2020). Frame failures and reframing dialogues in the public sector design projects. International Journal of Design, 14(1), 81-94.
- Lou, N. M., & Noels, K. A. (2019). Promoting growth in foreign and second language education: A research agenda for mindsets in language learning and teaching. System, 86, 102126. https://doi.org/10.1016/j.system.2019.102126 DOI: https://doi.org/10.1016/j.system.2019.102126
- Macnamara, B. N., & Rupani, N. S. (2017). The relationship between intelligence and mindset. Intelligence, 64, 52-59. https://doi.org/10.1016/j.intell.2017.07.003 DOI: https://doi.org/10.1016/j.intell.2017.07.003
- Mak, K. K., & Pichika, M. R. (2019). Artificial intelligence in drug development: present status and future prospects. Drug discovery today, 24(3), 773-780. https://doi.org/10.1016/j.drudis.2018.11.014 DOI: https://doi.org/10.1016/j.drudis.2018.11.014
- Mascret, N., Roussel, P., & Cury, F. (2015). Using implicit measures to highlight science teachers’ implicit theories of intelligence. European journal of psychology of education, 30(3), 269-280. https://doi.org/10.1007/s10212-015-0249-6 DOI: https://doi.org/10.1007/s10212-015-0249-6
- Moe, A., Hausmann, M., & Hirnstein, M. (2021). Gender stereotypes and incremental beliefs in STEM and non-STEM students in three countries: Relationships with performance in cognitive tasks. Psychological research, 85(2), 554-567. https://doi.org/10.1007/s00426-019-01285-0 DOI: https://doi.org/10.1007/s00426-019-01285-0
- Mofield, E. L., & Parker Peters, M. (2018). Mindset misconception? Comparing mindsets, perfectionism, and attitudes of achievement in gifted, advanced, and typical students. Gifted Child Quarterly, 62(4), 327-349. https://doi.org/10.1177/0016986218758440 DOI: https://doi.org/10.1177/0016986218758440
- Mullensiefen, D., Harrison, P., Caprini, F., & Fancourt, A. (2015). Investigating the importance of self-theories of intelligence and musicality for students' academic and musical achievement. Frontiers in psychology, 6, 1702. https://doi.org/10.3389/fpsyg.2015.01702 DOI: https://doi.org/10.3389/fpsyg.2015.01702
- Mundy, L. (2012). The richer sex. Time, 179(12), 28-34.
- OKeefe, P. A., Dweck, C. S., & Walton, G. M. (2018). Implicit theories of interest: Finding your passion or developing it?. Psychological Science, 29(10), 1653-1664. https://doi.org/10.1177/0956797618780643 DOI: https://doi.org/10.1177/0956797618780643
- Ortiz Alvarado, N. B., Rodriguez Ontiveros, M., & Ayala Gaytán, E. A. (2019). Do mindsets shape students’ well-being and performance?. The Journal of psychology, 153(8), 843-859. https://doi.org/10.1080/00223980 .2019.1631141 DOI: https://doi.org/10.1080/00223980.2019.1631141
- Paul, R., & Elder, L. (2019). The miniature guide to critical thinking concepts and tools. Rowman & Littlefield.
- Peng, M. Y. P., & Chen, C. C. (2019). The effect of instructor’s learning modes on deep approach to student learning and learning outcomes. Educational Sciences: Theory & Practice, 19(3),65-85.
- Price, R. B. E. (2021). Nietzsche, Heidegger and Colonialism: Occupying South East Asia (Vol. 85). Routledge. https://doi.org/10.4324/9781003090618 DOI: https://doi.org/10.4324/9781003090618
- Priess-Groben, H., and Hyde, J. (2017). Implicit theories, expectancies, and values predict mathematics motivation and behavior across high school and college. J. Youth. Adolescence. 46, 1318–1332. https://doi.org/10.1007 /s10964-016-0579-y DOI: https://doi.org/10.1007/s10964-016-0579-y
- Redding, C. (2019). A teacher like me: A review of the effect of student–teacher racial/ethnic matching on teacher perceptions of students and student academic and behavioral outcomes. Review of Educational Research, 89(4), 499-535. https://doi.org/10.3102/0034654319853545 DOI: https://doi.org/10.3102/0034654319853545
- Renaud-Dubé, A., Guay, F., Talbot, D., Taylor, G., & Koestner, R. (2015). The relations between implicit intelligence beliefs, autonomous academic motivation, and school persistence intentions: A mediation model, Social Psychology of Education, 18, 255-72. https://doi.org/10.1007/s11218-014-9288-0 DOI: https://doi.org/10.1007/s11218-014-9288-0
- Rissanen, I., Kuusisto, E., Hanhimäki, E., & Tirri, K. (2018). The implications of teachers’ implicit theories for moral education: A case study from Finland. Journal of Moral Education, 47(1), 63-77. https://doi.org/10.1080 /03057240.2017.1374244 DOI: https://doi.org/10.1080/03057240.2017.1374244
- Savage, G. C., & Lewis, S. (2018). The phantom national? Assembling national teaching standards in Australia’s federal system. Journal of Education Policy, 33(1), 118-142. https://doi.org/10.1080/02680939.2017.1325518 DOI: https://doi.org/10.1080/02680939.2017.1325518
- Savage, J. E., Jansen, P. R., Stringer, S., Watanabe, K., Bryois, J., De Leeuw, C. A., ... & Posthuma, D. (2018). Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence. Nature genetics, 50(7), 912-919. https://doi.org/10.1038/s41588-018-0152-6 DOI: https://doi.org/10.1038/s41588-018-0152-6
- Sisk, V. F., Burgoyne, A. P., Sun, J., Butler, J. L., & Macnamara, B. N. (2018). To what extent and under which circumstances are growth mind-sets important to academic achievement? Two meta-analyses. Psychological science, 29(4), 549-571. https://doi.org/10.1177/0956797617739704 DOI: https://doi.org/10.1177/0956797617739704
- Stump, G., Husman, J., Chung, W. T., & Done, A. (2009, October). Student beliefs about intelligence: Relationship to learning. In 2009 39th IEEE Frontiers in Education Conference (pp. 1-6). IEEE. https://doi.org/10.1109/FIE.2009.5350426 DOI: https://doi.org/10.1109/FIE.2009.5350426
- Tambe, P., Cappelli, P., & Yakubovich, V. (2019). Artificial intelligence in human resources management: Challenges and a path forward. California Management Review, 61(4), 15-42. https://doi.org/10.1177/0 008125619867910 DOI: https://doi.org/10.1177/0008125619867910
- Tarbetsky, A. L., Collie, R. J., & Martin, A. J. (2016). The role of implicit theories of intelligence and ability in predicting achievement for Indigenous (Aboriginal) Australian students. Contemporary Educational Psychology, 47, 61-71. https://doi.org/10.1016/j.cedpsych.2016.01.002 DOI: https://doi.org/10.1016/j.cedpsych.2016.01.002
- Thippana, J., Elliott, L., Gehman, S., Libertus, K., & Libertus, M. E. (2020). Parents’ use of number talk with young children: Comparing methods, family factors, activity contexts, and relations to math skills. Early Childhood Research Quarterly, 53, 249-259. https://doi.org/10.1016/j.ecresq.2020.05.002 DOI: https://doi.org/10.1016/j.ecresq.2020.05.002
- Thomas, A.J., & Sarnecka, B.W. (2015). Exploring the relation between people’s theories of intelligence and beliefs about brain development, Frontiers in Psychology, 6, 1-12. https://doi.org/10.3389/fpsyg.2015.00921 DOI: https://doi.org/10.3389/fpsyg.2015.00921
- Todor, I. (2014). Investigating “the old stereotype†about boys/girls and mathematics: Gender differences in implicit theory of intelligence and mathematics self-efficacy beliefs. Procedia-Social and Behavioral Sciences, 159, 319-323. https://doi.org/10.1016/j.sbspro.2014.12.380 DOI: https://doi.org/10.1016/j.sbspro.2014.12.380
- Tondeur, J., Van Braak, J., Ertmer, P. A., & Ottenbreit-Leftwich, A. (2017). Understanding the relationship between teachers’ pedagogical beliefs and technology use in education: a systematic review of qualitative evidence. Educational technology research and development, 65(3), 555-575. https://doi.org/10.1007/s11423-016-9481-2 DOI: https://doi.org/10.1007/s11423-016-9481-2
- VahalÃková, E. (2013). The Relationship between Mind Sets and the Motivation of secondary School Students of English as a second Language (Doctoral dissertation, Dissertation). Masaryk University. Retrieved from https://is. muni. cz/th/270621/ff_m).
- van Aalderen-Smeets, S. I., & van der Molen, J. H. W. (2018). Modeling the relation between students’ implicit beliefs about their abilities and their educational STEM choices. International journal of technology and design education, 28(1), 1-27. https://doi.org/10.1007/s10798-016-9387-7 DOI: https://doi.org/10.1007/s10798-016-9387-7
- Vincentâ€Ruz, P., & Schunn, C. D. (2017). The increasingly important role of science competency beliefs for science learning in girls. Journal of Research in Science Teaching, 54(6), 790-822. https://doi.org/10.1002/tea.21387 DOI: https://doi.org/10.1002/tea.21387
- Wren, D. A., & Bedeian, A. G. (2020). The evolution of management thought. John Wiley & Sons.
- Yeager, D. S., Hanselman, P., Walton, G. M., Murray, J. S., Crosnoe, R., Muller, C., ... & Dweck, C. S. (2019). A national experiment reveals where a growth mindset improves achievement. Nature, 573(7774), 364-369. https://doi.org/10.1038/s41586-019-1466-y DOI: https://doi.org/10.1038/s41586-019-1466-y
References
Ajzen, I. (2020). The theory of planned behavior: Frequently asked questions. Human Behavior and Emerging Technologies, 2(4), 314-324. https://doi.org/10.1002/hbe2.195 DOI: https://doi.org/10.1002/hbe2.195
Alesi, M., Rappo, G., & Pepi, A. (2016). Investigating the improvement of decoding abilities and working memory in children with incremental or entity personal conceptions of intelligence: two case reports. Frontiers in psychology, 6, 1939. https://doi.org/10.3389/fpsyg.2015.01939 DOI: https://doi.org/10.3389/fpsyg.2015.01939
Aydin, H., Ozfidan, B., & Carothers, D. (2017). Meeting the challenges of curriculum and instruction in school settings in the United States. Journal of Social Studies Education Research, 8(3), 76-92.
Bandura, A. (1977). Social learning theory. Englewood Cliffs, NJ: Prentice-Hall.
Barkley, E. F., & Major, C. H. (2020). Student engagement techniques: A handbook for college faculty. John Wiley & Sons.
Bostwick, K., Collie, R., Martin, A., and Durksen, T. (2017). Students’ growth mindsets, goals, and academic outcomes in mathematics. Zeitschrift Psychol, 225, 107–116. https://doi.org/10.1027/2151-2604/a000287 DOI: https://doi.org/10.1027/2151-2604/a000287
Boyle, G. J., Neumann, D. L., Furedy, J. J., & Westbury, H. R. (2010). Combining the methods of differential and experimental psychology to study sex differences in human cognitive psychological functions. Perceptual and Motor Skills, 110, 392–410. https://doi.org/10.2466/pms.110.2.396-410 DOI: https://doi.org/10.2466/pms.110.2.396-410
Brandon, P. S., Lombardi, P., & Shen, G. Q. (Eds.). (2017). Future challenges in evaluating and managing sustainable development in the built environment. Wiley Blackwell. https://doi.org/10.1002/9781119190691 DOI: https://doi.org/10.1002/9781119190691
Burkley, M., Parker, J., Stermer, S.P., &Burkley, E. (2010). Trait Beliefs that Make Women Vulnerable to Math Disengagement. Personality and Individual Differences, 48(2), 234-238. https://doi.org/10.1016/j.paid.2009.09.002 DOI: https://doi.org/10.1016/j.paid.2009.09.002
Chen, J. A., and Tutwiler, M. S. (2017). Implicit theories of ability and self-efficacy: testing alternative social cognitive models to science motivation. Zeitschrift Psychol, 225, 127–136. https://doi.org/10.1027/2151-2604/a000289 DOI: https://doi.org/10.1027/2151-2604/a000289
Chen, W. W., & Wong, Y. L. (2015). Chinese mindset: theories of intelligence, goal orientation and academic achievement in Hong Kong students. Educational Psychology, 35(6), 714-725. https://doi.org/10.1080/01443410 .2014.893559 DOI: https://doi.org/10.1080/01443410.2014.893559
Claro, S & Loeb, S. (2017). New evidence that students’ beliefs about their brains drive learning. Evidence Speaks Reports, 2(29), 1-7.
Claro, S., Paunesku, D., & Dweck. C.S. (2016). Growth mindset tempers the effects of poverty on academic achievement, Proceedings of the National Academy of Sciences, 113, 8664-8. https://doi.org/10.1073/pna .1608207113 DOI: https://doi.org/10.1073/pnas.1608207113
Costa, A., Faria, L., (2018). Implicit Theories of Intelligence and Academic Achievement: A Meta-Analytic Review. Frontiers in Psychology, 9. 1-16. https://doi.org/10.3389/fpsyg.2018.00829 DOI: https://doi.org/10.3389/fpsyg.2018.00829
De Castella, K., & Byrne, D. (2015). My intelligence may be more malleable than yours: The revised implicit theories of intelligence (self-theory) scale is a better predictor of achievement, motivation, and student disengagement. European Journal of Psychology of Education, 30(3), 245-267. https://doi.org/10.1007/s10212-015-0244-y DOI: https://doi.org/10.1007/s10212-015-0244-y
Dejonge, M. L., Omran, J., Faulkner, G. E., & Sabiston, C. M. (2020). University students' and clinicians’ beliefs and attitudes towards physical activity for mental health. Mental Health and Physical Activity, 18, 100316. https://doi.org/10.1016/j.mhpa.2019.100316 DOI: https://doi.org/10.1016/j.mhpa.2019.100316
Devers, A. (2015). Thinking about Intelligence: How Student Mindsets Influence Academic Performance. Rising Tide, 7, 1-23.
Diaconu-Gherasim, L. R., Tepordei, A. M., Mairean, C., & Rusu, A. (2019). Intelligence beliefs, goal orientations and children’s academic achievement: does the children’s gender matter? Educational Studies, 45(1), 95-112. https://doi.org/10.1080/03055698.2018.1443796 DOI: https://doi.org/10.1080/03055698.2018.1443796
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 DOI: https://doi.org/10.1037/0022-3514.54.1.5
Dweck, C. (1999). Self-theories: their role in motivation, personality, and development. Philadelphia: Psychology Press.
Eccles, J. S., & Wigfield, A. (2020). From expectancy-value theory to situated expectancy-value theory: A developmental, social cognitive, and sociocultural perspective on motivation. Contemporary Educational Psychology, 61, 101859. https://doi.org/10.1016/j.cedpsych.2020.101859 DOI: https://doi.org/10.1016/j.cedpsych.2020.101859
Ferla, M., & Graham, A. (2019). Women slowly taking off: An investigation into female underrepresentation in commercial aviation. Research in Transportation Business & Management, 31, 100378. https://doi.org/10.1016/ j.rtbm.2019.100378 DOI: https://doi.org/10.1016/j.rtbm.2019.100378
Fitri, S., Syahputra, E., & Syahputra, H. (2019). Blended learning rotation model of cognitive conflict strategy to improve mathematical resilience in high school students. International Journal of Scientific & Technology Research, 1(1), 80-87.
Gay, L.R., Mills, G.E. and Airasian, P. (2011). Educational Research Competencies for Analysis and Applications. Pearson, Columbus.
Gunderson, E. A., Park, D., Maloney, E. A., Beilock, S. L., & Levine, S. C. (2018). Reciprocal relations among motivational frameworks, math anxiety, and math achievement in early elementary school. Journal of Cognition and Development, 19(1), 21-46. https://doi.org/10.1080/15248372.2017.1421538 DOI: https://doi.org/10.1080/15248372.2017.1421538
Haimovitz, K., & Dweck, C. S. (2017). The origins of children's growth and fixed mindsets: New research and a new proposal. Child development, 88(6), 1849-1859. https://doi.org/10.1111/cdev.12955 DOI: https://doi.org/10.1111/cdev.12955
Hava, K., Guyer, T., & Cakir, H. (2020). Gifted students’ learning experiences in systematic game development process in after-school activities. Educational Technology Research and Development, 68(3), 1439-1459. https://doi.org/10.1007/s11423-020-09750-z DOI: https://doi.org/10.1007/s11423-020-09750-z
Heyder, A., Weidinger, A. F., Cimpian, A., & Steinmayr, R. (2020). Teachers’ belief that math requires innate ability predicts lower intrinsic motivation among low-achieving students. Learning and Instruction, 65, 101220. https://doi.org/10.1016/j.learninstruc.2019.101220 DOI: https://doi.org/10.1016/j.learninstruc.2019.101220
Hirsch, A., Bieleke, M., Schüler, J., & Wolff, W. (2020). Implicit theories about athletic ability modulate the effects of if-then planning on performance in a standardized endurance task. International journal of environmental research and public health, 17(7), 2576. https://doi.org/10.3390/ijerph17072576 DOI: https://doi.org/10.3390/ijerph17072576
Hughes, J. S. (2015). Support for the domain specificity of implicit beliefs about persons, intelligence, and morality. Personality and Individual Differences, 86, 195-203. https://doi.org/10.1016/j.paid.2015.05.042 DOI: https://doi.org/10.1016/j.paid.2015.05.042
Jones, B. D., Byrd, C. N., & Lusk, D. (2009). High school students' beliefs about intelligence. Research In The Schools, 16(2), 1-14.
Karlen, Y., Suter, F., Hirt, C., & Merki, K. M. (2019). The role of implicit theories in students' grit, achievement goals, intrinsic and extrinsic motivation, and achievement in the context of a long-term challenging task. Learning and Individual Differences, 74, 101757. https://doi.org/10.1016/j.lindif.2019.101757 DOI: https://doi.org/10.1016/j.lindif.2019.101757
Kassaee, A. M. (2016). Examining the role of motivation and mindset in the performance of college students majoring in STEM fields (Doctoral dissertation, Middle Tennessee State University).
Kim, Y. C., & Jung, J. H. (2019). Conceptualizing shadow curriculum: definition, features and the changing landscapes of learning cultures. Journal of Curriculum Studies, 51(2), 141-161. https://doi.org/10.1080/00220 272.2019.1568583 DOI: https://doi.org/10.1080/00220272.2019.1568583
Lee, J. J. (2020). Frame failures and reframing dialogues in the public sector design projects. International Journal of Design, 14(1), 81-94.
Lou, N. M., & Noels, K. A. (2019). Promoting growth in foreign and second language education: A research agenda for mindsets in language learning and teaching. System, 86, 102126. https://doi.org/10.1016/j.system.2019.102126 DOI: https://doi.org/10.1016/j.system.2019.102126
Macnamara, B. N., & Rupani, N. S. (2017). The relationship between intelligence and mindset. Intelligence, 64, 52-59. https://doi.org/10.1016/j.intell.2017.07.003 DOI: https://doi.org/10.1016/j.intell.2017.07.003
Mak, K. K., & Pichika, M. R. (2019). Artificial intelligence in drug development: present status and future prospects. Drug discovery today, 24(3), 773-780. https://doi.org/10.1016/j.drudis.2018.11.014 DOI: https://doi.org/10.1016/j.drudis.2018.11.014
Mascret, N., Roussel, P., & Cury, F. (2015). Using implicit measures to highlight science teachers’ implicit theories of intelligence. European journal of psychology of education, 30(3), 269-280. https://doi.org/10.1007/s10212-015-0249-6 DOI: https://doi.org/10.1007/s10212-015-0249-6
Moe, A., Hausmann, M., & Hirnstein, M. (2021). Gender stereotypes and incremental beliefs in STEM and non-STEM students in three countries: Relationships with performance in cognitive tasks. Psychological research, 85(2), 554-567. https://doi.org/10.1007/s00426-019-01285-0 DOI: https://doi.org/10.1007/s00426-019-01285-0
Mofield, E. L., & Parker Peters, M. (2018). Mindset misconception? Comparing mindsets, perfectionism, and attitudes of achievement in gifted, advanced, and typical students. Gifted Child Quarterly, 62(4), 327-349. https://doi.org/10.1177/0016986218758440 DOI: https://doi.org/10.1177/0016986218758440
Mullensiefen, D., Harrison, P., Caprini, F., & Fancourt, A. (2015). Investigating the importance of self-theories of intelligence and musicality for students' academic and musical achievement. Frontiers in psychology, 6, 1702. https://doi.org/10.3389/fpsyg.2015.01702 DOI: https://doi.org/10.3389/fpsyg.2015.01702
Mundy, L. (2012). The richer sex. Time, 179(12), 28-34.
OKeefe, P. A., Dweck, C. S., & Walton, G. M. (2018). Implicit theories of interest: Finding your passion or developing it?. Psychological Science, 29(10), 1653-1664. https://doi.org/10.1177/0956797618780643 DOI: https://doi.org/10.1177/0956797618780643
Ortiz Alvarado, N. B., Rodriguez Ontiveros, M., & Ayala Gaytán, E. A. (2019). Do mindsets shape students’ well-being and performance?. The Journal of psychology, 153(8), 843-859. https://doi.org/10.1080/00223980 .2019.1631141 DOI: https://doi.org/10.1080/00223980.2019.1631141
Paul, R., & Elder, L. (2019). The miniature guide to critical thinking concepts and tools. Rowman & Littlefield.
Peng, M. Y. P., & Chen, C. C. (2019). The effect of instructor’s learning modes on deep approach to student learning and learning outcomes. Educational Sciences: Theory & Practice, 19(3),65-85.
Price, R. B. E. (2021). Nietzsche, Heidegger and Colonialism: Occupying South East Asia (Vol. 85). Routledge. https://doi.org/10.4324/9781003090618 DOI: https://doi.org/10.4324/9781003090618
Priess-Groben, H., and Hyde, J. (2017). Implicit theories, expectancies, and values predict mathematics motivation and behavior across high school and college. J. Youth. Adolescence. 46, 1318–1332. https://doi.org/10.1007 /s10964-016-0579-y DOI: https://doi.org/10.1007/s10964-016-0579-y
Redding, C. (2019). A teacher like me: A review of the effect of student–teacher racial/ethnic matching on teacher perceptions of students and student academic and behavioral outcomes. Review of Educational Research, 89(4), 499-535. https://doi.org/10.3102/0034654319853545 DOI: https://doi.org/10.3102/0034654319853545
Renaud-Dubé, A., Guay, F., Talbot, D., Taylor, G., & Koestner, R. (2015). The relations between implicit intelligence beliefs, autonomous academic motivation, and school persistence intentions: A mediation model, Social Psychology of Education, 18, 255-72. https://doi.org/10.1007/s11218-014-9288-0 DOI: https://doi.org/10.1007/s11218-014-9288-0
Rissanen, I., Kuusisto, E., Hanhimäki, E., & Tirri, K. (2018). The implications of teachers’ implicit theories for moral education: A case study from Finland. Journal of Moral Education, 47(1), 63-77. https://doi.org/10.1080 /03057240.2017.1374244 DOI: https://doi.org/10.1080/03057240.2017.1374244
Savage, G. C., & Lewis, S. (2018). The phantom national? Assembling national teaching standards in Australia’s federal system. Journal of Education Policy, 33(1), 118-142. https://doi.org/10.1080/02680939.2017.1325518 DOI: https://doi.org/10.1080/02680939.2017.1325518
Savage, J. E., Jansen, P. R., Stringer, S., Watanabe, K., Bryois, J., De Leeuw, C. A., ... & Posthuma, D. (2018). Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence. Nature genetics, 50(7), 912-919. https://doi.org/10.1038/s41588-018-0152-6 DOI: https://doi.org/10.1038/s41588-018-0152-6
Sisk, V. F., Burgoyne, A. P., Sun, J., Butler, J. L., & Macnamara, B. N. (2018). To what extent and under which circumstances are growth mind-sets important to academic achievement? Two meta-analyses. Psychological science, 29(4), 549-571. https://doi.org/10.1177/0956797617739704 DOI: https://doi.org/10.1177/0956797617739704
Stump, G., Husman, J., Chung, W. T., & Done, A. (2009, October). Student beliefs about intelligence: Relationship to learning. In 2009 39th IEEE Frontiers in Education Conference (pp. 1-6). IEEE. https://doi.org/10.1109/FIE.2009.5350426 DOI: https://doi.org/10.1109/FIE.2009.5350426
Tambe, P., Cappelli, P., & Yakubovich, V. (2019). Artificial intelligence in human resources management: Challenges and a path forward. California Management Review, 61(4), 15-42. https://doi.org/10.1177/0 008125619867910 DOI: https://doi.org/10.1177/0008125619867910
Tarbetsky, A. L., Collie, R. J., & Martin, A. J. (2016). The role of implicit theories of intelligence and ability in predicting achievement for Indigenous (Aboriginal) Australian students. Contemporary Educational Psychology, 47, 61-71. https://doi.org/10.1016/j.cedpsych.2016.01.002 DOI: https://doi.org/10.1016/j.cedpsych.2016.01.002
Thippana, J., Elliott, L., Gehman, S., Libertus, K., & Libertus, M. E. (2020). Parents’ use of number talk with young children: Comparing methods, family factors, activity contexts, and relations to math skills. Early Childhood Research Quarterly, 53, 249-259. https://doi.org/10.1016/j.ecresq.2020.05.002 DOI: https://doi.org/10.1016/j.ecresq.2020.05.002
Thomas, A.J., & Sarnecka, B.W. (2015). Exploring the relation between people’s theories of intelligence and beliefs about brain development, Frontiers in Psychology, 6, 1-12. https://doi.org/10.3389/fpsyg.2015.00921 DOI: https://doi.org/10.3389/fpsyg.2015.00921
Todor, I. (2014). Investigating “the old stereotype†about boys/girls and mathematics: Gender differences in implicit theory of intelligence and mathematics self-efficacy beliefs. Procedia-Social and Behavioral Sciences, 159, 319-323. https://doi.org/10.1016/j.sbspro.2014.12.380 DOI: https://doi.org/10.1016/j.sbspro.2014.12.380
Tondeur, J., Van Braak, J., Ertmer, P. A., & Ottenbreit-Leftwich, A. (2017). Understanding the relationship between teachers’ pedagogical beliefs and technology use in education: a systematic review of qualitative evidence. Educational technology research and development, 65(3), 555-575. https://doi.org/10.1007/s11423-016-9481-2 DOI: https://doi.org/10.1007/s11423-016-9481-2
VahalÃková, E. (2013). The Relationship between Mind Sets and the Motivation of secondary School Students of English as a second Language (Doctoral dissertation, Dissertation). Masaryk University. Retrieved from https://is. muni. cz/th/270621/ff_m).
van Aalderen-Smeets, S. I., & van der Molen, J. H. W. (2018). Modeling the relation between students’ implicit beliefs about their abilities and their educational STEM choices. International journal of technology and design education, 28(1), 1-27. https://doi.org/10.1007/s10798-016-9387-7 DOI: https://doi.org/10.1007/s10798-016-9387-7
Vincentâ€Ruz, P., & Schunn, C. D. (2017). The increasingly important role of science competency beliefs for science learning in girls. Journal of Research in Science Teaching, 54(6), 790-822. https://doi.org/10.1002/tea.21387 DOI: https://doi.org/10.1002/tea.21387
Wren, D. A., & Bedeian, A. G. (2020). The evolution of management thought. John Wiley & Sons.
Yeager, D. S., Hanselman, P., Walton, G. M., Murray, J. S., Crosnoe, R., Muller, C., ... & Dweck, C. S. (2019). A national experiment reveals where a growth mindset improves achievement. Nature, 573(7774), 364-369. https://doi.org/10.1038/s41586-019-1466-y DOI: https://doi.org/10.1038/s41586-019-1466-y