Volume 7, Issue 3 (September 2025)
IEEPJ 2025, 7(3): 1-21 |
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Yaghoobi A, Esmaeili Sedeh F, Karimi K, Afzali A, Kordnoghabi R. (2025). Developing a Structural Model for Predicting Students' Academic Performance: The Role of the Intelligence Trap Mediated by Grit and Self-Discipline. IEEPJ. 7(3), 1-21.
URL: http://ieepj.hormozgan.ac.ir/article-1-1036-en.html
URL: http://ieepj.hormozgan.ac.ir/article-1-1036-en.html
Abolghasem Yaghoobi *1 
, Fatemeh Esmaeili Sedeh2 , Kambiz Karimi3 , Afshin Afzali4 , Rasool Kordnoghabi5
, Fatemeh Esmaeili Sedeh2 , Kambiz Karimi3 , Afshin Afzali4 , Rasool Kordnoghabi5
1- Professor, Department of Psychology, Faculty of Economics and Social Sciences, Bu-Ali Sina University, Hamedan, Iran , yaghoobi@basu.ac.ir
2- Master of Educational Psychology, Department of Psychology, Faculty of Economics and Social Sciences, Bu-Ali Sina University, Hamedan, Iran
3- PhD in Educational Psychology, Department of Psychology, Faculty of Economics and Social Sciences, Bu-Ali Sina University, Hamedan, Iran
4- Associate Professor, Department of Psychology, Faculty of Economics and Social Sciences, Bu-Ali Sina University, Hamedan, Iran
5- Department of Psychology, Faculty of Economics and Social Sciences, Bu-Ali Sina University, Hamedan, Iran
2- Master of Educational Psychology, Department of Psychology, Faculty of Economics and Social Sciences, Bu-Ali Sina University, Hamedan, Iran
3- PhD in Educational Psychology, Department of Psychology, Faculty of Economics and Social Sciences, Bu-Ali Sina University, Hamedan, Iran
4- Associate Professor, Department of Psychology, Faculty of Economics and Social Sciences, Bu-Ali Sina University, Hamedan, Iran
5- Department of Psychology, Faculty of Economics and Social Sciences, Bu-Ali Sina University, Hamedan, Iran
Abstract: (2094 Views)
Objective: The present study sought to develop and test a structural equation model predicting students’ academic performance based on the intelligence trap, with grit and self-discipline as mediating variables.
Methods: This descriptive–correlational research was conducted using structural equation modeling. The statistical population comprised all students enrolled at Bu-Ali Sina University during the 2023–2024 academic year, from which a random cluster sample of 396 students was selected. Data were collected using the Intelligence Trap Questionnaire (2024), the Academic Performance Questionnaire by Pham and Taylor (1999), the Grit Scale by Duckworth and Quinn (2009), and the Self-Discipline Questionnaire by Zand Karimi et al. (2012). Data analysis was performed using Pearson correlation, regression, and path analysis in SPSS v.27 and LISREL v.8.8.
Results: The findings revealed a significant negative relationship between intelligence trap, academic performance, grit, and self-discipline (p < 0.01). The proposed structural model demonstrated acceptable fit indices, indicating that intelligence trap both directly and indirectly, through grit and self-discipline, predicts lower academic performance.
Conclusions: The results highlight that the intelligence trap can undermine students’ academic performance by weakening essential traits such as grit and self-discipline. These findings underscore the importance of identifying and addressing the intelligence trap within educational contexts to enhance students’ success.
Methods: This descriptive–correlational research was conducted using structural equation modeling. The statistical population comprised all students enrolled at Bu-Ali Sina University during the 2023–2024 academic year, from which a random cluster sample of 396 students was selected. Data were collected using the Intelligence Trap Questionnaire (2024), the Academic Performance Questionnaire by Pham and Taylor (1999), the Grit Scale by Duckworth and Quinn (2009), and the Self-Discipline Questionnaire by Zand Karimi et al. (2012). Data analysis was performed using Pearson correlation, regression, and path analysis in SPSS v.27 and LISREL v.8.8.
Results: The findings revealed a significant negative relationship between intelligence trap, academic performance, grit, and self-discipline (p < 0.01). The proposed structural model demonstrated acceptable fit indices, indicating that intelligence trap both directly and indirectly, through grit and self-discipline, predicts lower academic performance.
Conclusions: The results highlight that the intelligence trap can undermine students’ academic performance by weakening essential traits such as grit and self-discipline. These findings underscore the importance of identifying and addressing the intelligence trap within educational contexts to enhance students’ success.
Type of Study: Original |
Subject:
Educational Psychology
Received: 2025/05/5 | Accepted: 2025/07/26 | Published: 2025/09/1
Received: 2025/05/5 | Accepted: 2025/07/26 | Published: 2025/09/1
References
1. Al-Tameemi, R. A. N., Johnson, C., Gitay, R., Abdel-Salam, A.-S. G., Al Hazaa, K., BenSaid, A., & Romanowski, M. H. (2023). Determinants of poor academic performance among undergraduate students-A systematic literature review. International Journal of Educational Research Open, 4(4), 100232. [DOI:10.1016/j.ijedro.2023.100232]
2. Allom, V., Panetta, G., Mullan, B., & Hagger, M. S. (2016). Self-report and behavioural approaches to the measurement of self-control: Are we assessing the same construct? Personality and individual differences, 90, 137-142. [DOI:10.1016/j.paid.2015.10.051]
3. Arabzadeh, M., Kavossian, J., & Karimi, K. (2018). Investigate the relationship between self-efficacy and hope with academic achievement in students. 7(4), 137-150. [DOI:https://dor.isc.ac/dor/20.1001.1.2383353.1397.7.4.8.3]
4. Azam Rajabian, A., & Asghari Ebrahimabad, M. J. (2020). Correlation between Hardiness and Extroversion with Academic Performance. Educational and Scholastic studies, 8(2), 253-269. [DOI:https://dor.isc.ac/dor/20.1001.1.2423494.1398.8.2.12.5]
5. Bai, S. (2023). Motivated Reasoning and Its Applications to Life. Psychology, 14(12), 1827-1833. [DOI:10.4236/psych.2023.1412107]
6. Changbao, L., & Peishan, H. (2018). A Literature Review of the Consumer Cognitive Miserliness Behavior and Its Marketing Implications: Based on the Framework of the Cue Utilization Theory. Foreign Economics & Management, 40(08), 58-70. [DOI:https://doi.org/10.16538/j.cnki.fem.2018.08.005]
7. Clark, K. N., & Malecki, C. K. (2019). Academic Grit Scale: Psychometric properties and associations with achievement and life satisfaction. Journal of school psychology, 72, 49-66. [DOI:10.1016/j.jsp.2018.12.001]
8. Colom, R., & Flores-Mendoza, C. E. (2007). Intelligence predicts scholastic achievement irrespective of SES factors: Evidence from Brazil. Intelligence, 35(3), 243-251. [DOI:10.1016/j.intell.2006.07.008]
9. Dortaj, F., & Delavar, A. (2005). Effect of Process-Oriented and Outcome-Oriented Mental Simulation on Improving Students Academic Performance. Quarterly Journal of New Thought on Education, 1(2), 7 - 21. [DOI:https://doi.org/10.22051/jontoe.2005.267]
10. Duckworth, A. L., Peterson, C., Matthews, M. D., & Kelly, D. R. (2007). Grit: perseverance and passion for long-term goals. Journal of personality and social psychology, 92(6), 1087. [DOI:10.1037/0022-3514.92.6.1087]
11. Duckworth, A. L., & Quinn, P. D. (2009). Development and validation of the Short Grit Scale (GRIT-S). Journal of personality assessment, 91(2), 166-174. [DOI:10.1080/00223890802634290]
12. Duckworth, A. L., & Seligman, M. E. (2005). Self-discipline outdoes IQ in predicting academic performance of adolescents. Psychological science, 16(12), 939-944. [DOI:10.1111/j.1467-9280.2005.01641.x]
13. Esmaeili Sedeh, F. (2024). Development and Validation of the Intelligence Trap Questionnaire and Examination of Its Relationship with Students' Academic Performance Mediated by Grit and Self-Discipline Bu-Ali Sina]. Iran https://research.basu.ac.ir/_Pages/Research.aspx?Id=1080538
14. Francis, B. K., & Babu, S. S. (2019). Predicting academic performance of students using a hybrid data mining approach. Journal of medical systems, 43(6), 162. [DOI:10.1007/s10916-019-1295-4]
15. Gelles, L. A., Lord, S. M., Hoople, G. D., Chen, D. A., & Mejia, J. A. (2020). Compassionate flexibility and self-discipline: Student adaptation to emergency remote teaching in an integrated engineering energy course during COVID-19. Education Sciences, 10(11), 304. [DOI:10.3390/educsci10110304]
16. Hagger, M. S., & Hamilton, K. (2019). Grit and self‐discipline as predictors of effort and academic attainment. British Journal of Educational Psychology, 89(2), 324-342. [DOI:10.1111/bjep.12241]
17. He, X., Wang, H., Chang, F., Dill, S.-E., Liu, H., Tang, B., & Shi, Y. (2021). IQ, grit, and academic achievement: Evidence from rural China. International Journal of Educational Development, 80, 102306. [DOI:10.1016/j.ijedudev.2020.102306]
18. Higgins, L. T., & Xiang, G. (2009). The development and use of intelligence tests in China. Psychology and Developing Societies, 21(2), 257-275. [DOI:10.1177/097133360902100205]
19. Hosseni, M., Zoghi Paidar, M. R., & Rashid, K. (2018). The roles of grit and intelligence in predicting students' academic Achievement. Biquarterly Journal of Cognitive Strategies in Learning, 6(11), 233-248. [DOI:https://doi.org/10.22084/j.psychogy.2018.16198.1753]
20. Kagoiya, P., & Kagema, N. (2018). Examining factors contributing to indiscipline in primary schools in Nyeri Central Sub-County, Kenya. Pedagogical Research, 3(2), 1-8. [DOI:10.20897/pr/91650]
21. Kahan, D. M., Peters, E., Dawson, E. C., & Slovic, P. (2017). Motivated numeracy and enlightened self-government. Behavioural public policy, 1(1), 54-86. [DOI:10.2139/ssrn.2319992]
22. Karbach, J., Gottschling, J., Spengler, M., Hegewald, K., & Spinath, F. M. (2013). Parental involvement and general cognitive ability as predictors of domain-specific academic achievement in early adolescence. Learning and Instruction, 23, 43-51. [DOI:10.1016/j.learninstruc.2012.09.004]
23. Kriegbaum, K., Becker, N., & Spinath, B. (2018). The relative importance of intelligence and motivation as predictors of school achievement: A meta-analysis. Educational Research Review, 25, 120-148. [DOI:10.1016/j.edurev.2018.10.001]
24. Laidra, K., Pullmann, H., & Allik, J. (2007). Personality and intelligence as predictors of academic achievement: A cross-sectional study from elementary to secondary school. Personality and individual differences, 42(3), 441-451. [DOI:10.1016/j.paid.2006.08.001]
25. 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, 1-19. [DOI:10.1186/s40594-020-00227-2]
26. Lynn, R., & Vanhanen, T. (2012). National IQs: A review of their educational, cognitive, economic, political, demographic, sociological, epidemiological, geographic and climatic correlates. Intelligence, 40(2), 226-234. [DOI:10.1016/j.intell.2011.11.004]
27. McMahon, S. D., Peist, E., Davis, J. O., Bare, K., Martinez, A., Reddy, L. A., Espelage, D. L., & Anderman, E. M. (2020). Physical aggression toward teachers: Antecedents, behaviors, and consequences. Aggressive behavior, 46(1), 116-126. [DOI:10.1002/ab.21870]
28. Minnigh, T. L., Sanders, J. M., Witherell, S. M., & Coyle, T. R. (2024). Grit as a predictor of academic performance: Not much more than conscientiousness. Personality and individual differences, 221, 112542. [DOI:10.1016/j.paid.2024.112542]
29. Ostovar, N., Hosseininasab, D., & Livarjani, S. (2020). Discrimination of disciplined and indiscipline students based on early maladaptive schemas and family functioning components. Biquarterly Journal of Cognitive Strategies in Learning, 7(13), 173-190. [DOI:https://doi.org/10.22084/j.psychogy.2019.18454.1921]
30. Ottati, V., Price, E. D., Wilson, C., & Sumaktoyo, N. (2015). When self-perceptions of expertise increase closed-minded cognition: The earned dogmatism effect. Journal of Experimental Social Psychology, 61, 131-138. [DOI:10.1016/j.jesp.2015.08.003]
31. Pham, L. B., & Taylor, S. E. (1999). From thought to action: Effects of process-versus outcome-based mental simulations on performance. Personality and Social Psychology Bulletin, 25(2), 250-260. [DOI:10.1177/0146167299025002010]
32. Ritchie, S. J., & Tucker-Drob, E. M. (2018). How much does education improve intelligence? A meta-analysis. Psychological science, 29(8), 1358-1369. [DOI:10.1177/0956797618774253]
33. Robson, D. (2019). The Intelligence Trap: Revolutionise Your Thinking and Make Wiser Decisions. Hachette UK. [DOI:https://davidrobson.me/books/the-intelligence-trap/]
34. Sadler, P. M., Sonnert, G., Coyle, H. P., Cook-Smith, N., & Miller, J. L. (2013). The influence of teachers' knowledge on student learning in middle school physical science classrooms. American Educational Research Journal, 50(5), 1020-1049. [DOI:10.3102/0002831213477680]
35. Sánchez-Álvarez, N., Berrios Martos, M. P., & Extremera, N. (2020). A meta-analysis of the relationship between emotional intelligence and academic performance in secondary education: A multi-stream comparison. Frontiers in psychology, 11, 1517. [DOI:10.3389/fpsyg.2020.01517]
36. Stigler, J. W., & Hiebert, J. (2017). The culture of teaching: A global perspective. In International handbook of teacher quality and policy (pp. 52-65). Routledge. [DOI:10.4324/9781315710068-4]
37. Suleiman, I. B., Okunade, O. A., Dada, E. G., & Ezeanya, U. C. (2024). Key factors influencing students' academic performance. Journal of Electrical Systems and Information Technology, 11(1), 41. [DOI:10.1186/s43067-024-00166-w]
38. Swaab, R. I., Schaerer, M., Anicich, E. M., Ronay, R., & Galinsky, A. D. (2014). The too-much-talent effect: Team interdependence determines when more talent is too much or not enough. Psychological science, 25(8), 1581-1591. [DOI:10.1177/0956797614537280]
39. Tullis, J. G., & Feder, B. (2023). The "curse of knowledge" when predicting others' knowledge. Memory & Cognition, 51(5), 1214-1234. [DOI:10.3758/s13421-022-01382-3]
40. Weber, H. S., Lu, L., Shi, J., & Spinath, F. M. (2013). The roles of cognitive and motivational predictors in explaining school achievement in elementary school. Learning and individual differences, 25, 85-92. [DOI:10.1016/j.lindif.2013.03.008]
41. Wieman, C. (2007). New formula for science education. Physics World, 20(1), 10. [DOI:10.1088/2058-7058/20/1/15]
42. Zand Karimi, G., Yazdi, S. M., & Banijamali, S. S. (2012). Self-discipline and productivity among automotive workers. Journal of Psychological Studies, 8(2), 9 - 26. [DOI:https://doi.org/10.22051/psy.2012.1714]
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