Predicting Math Performance of Middle Eastern Students: The Role of Dispositions
Abstract
:1. Introduction
2. Self-Efficacy and Academic Success
3. Morning and Evening Typology and Academic Success
4. The Present Study
5. Method
5.1. Participants
5.2. Materials and Procedure
6. Results of Analyses
6.1. Descriptors of the Sample
6.2. Assessment of Contributions to Performance
7. Discussion of Results
8. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Huang, H.B. What is good action research? Action Res. 2010, 8, 93–109. [Google Scholar] [CrossRef]
- Mertler, C.A. The Wiley Handbook of Action Research in Education; John Wiley & Sons: Hoboken, NJ, USA, 2019. [Google Scholar]
- Francis, B.; Craig, N.; Hodgen, J.; Taylor, B.; Tereshchenko, A.; Connolly, P.; Archer, L. The impact of tracking by attainment on pupil self-confidence over time: Demonstrating the accumulative impact of self-fulfilling prophecy. Br. J. Sociol. Educ. 2020, 41, 626–642. [Google Scholar] [CrossRef]
- Hart, S.A.; Ganley, C.M. The nature of math anxiety in adults: Prevalence and correlates. J. Numer. Cogn. 2019, 5, 122–139. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Biwer, F.; Wiradhany, W.; Oude Egbrink, M.; Hospers, H.; Wasenitz, S.; Jansen, W.; De Bruin, A. Changes and adaptations: How university students self-regulate their online learning during the COVID-19 pandemic. Front. Psychol. 2021, 12, 642593. [Google Scholar] [CrossRef] [PubMed]
- Broadbent, J.; Fuller-Tyszkiewicz, M. Profiles in self-regulated learning and their correlates for online and blended learning students. Educ. Technol. Res. Dev. 2018, 66, 1435–1455. [Google Scholar] [CrossRef]
- Hyde, J.S.; Mertz, J.E. Gender, culture, and mathematics performance. Proc. Natl. Acad. Sci. USA 2009, 106, 8801–8807. [Google Scholar] [CrossRef] [Green Version]
- De las Cuevas, P.; García-Arenas, M.; Rico, N. Why Not STEM? A Study Case on the Influence of Gender Factors on Students’ Higher Education Choice. Mathematics 2022, 10, 239. [Google Scholar] [CrossRef]
- Euchi, J.; Omri, A.; Al-Tit, A. The pillars of economic diversification in Saudi Arabia. World Rev. Sci. Technol. Sustain. Dev. 2018, 14, 330–343. [Google Scholar] [CrossRef]
- Hamdan, A.; Sarea, A.; Khamis, R.; Anasweh, M. A causality analysis of the link between higher education and economic development: Empirical evidence. Heliyon 2020, 6, e04046. [Google Scholar] [CrossRef]
- Jamjoom, F.B.; Kelly, P. Higher education for women in the Kingdom of Saudi Arabia. In Higher Education in Saudi Arabia; Smith, L., Abouammoh, A., Eds.; Springer: New York, NY, USA, 2013; pp. 117–125. [Google Scholar]
- Al Alhareth, Y.; Al Alhareth, Y.; Al Dighrir, I. Review of women and society in Saudi Arabia. Am. J. Educ. Res. 2015, 3, 121–125. [Google Scholar] [CrossRef]
- Pilotti, M.A.E.; Abdulhadi, E.J.; Algouhi, T.A.; Salameh, M.H. The new and the old: Responses to change in the Kingdom of Saudi Arabia. J. Int. Women’s Stud. 2021, 22, 341–358. [Google Scholar]
- El-Moussa, O.J.; Alghazo, R.; Pilotti, M.A.E. Data-driven predictions of academic success among college students in Saudi Arabia. Crit. Stud. Teach. Learn. 2021, 9, 115–134. [Google Scholar]
- Qureshi, R. Human resources development and the status of women labor force in Saudi Arabia: A critical analysis. Int. J. Curr. Res. Acad. Rev. 2014, 2, 144–155. [Google Scholar]
- Pilotti, M.A.E. What lies beneath sustainable education? Predicting and tackling gender differences in STEM academic success. Sustainability 2021, 13, 1671. [Google Scholar] [CrossRef]
- Spencer, S.J.; Logel, C.; Davies, P.G. Stereotype threat. Annu. Rev. Psychol. 2016, 67, 415–437. [Google Scholar] [CrossRef] [Green Version]
- Papadakis, S. Gender stereotypes in Greek computer science school textbooks. Int. J. Teach. Case Stud. 2018, 9, 48–71. [Google Scholar] [CrossRef]
- Papadakis, S.; Tousia, C.; Polychronaki, K. Women in computer science. The case study of the Computer Science Department of the University of Crete, Greece. Int. J. Teach. Case Stud. 2018, 9, 142–151. [Google Scholar] [CrossRef]
- Passolunghi, M.C.; Ferreira, T.I.R.; Tomasetto, C. Math–gender stereotypes and math-related beliefs in childhood and early adolescence. Learn. Individ. Differ. 2014, 34, 70–76. [Google Scholar] [CrossRef]
- Collins, K.H.; Price, E.F.; Hanson, L.; Neaves, D. Consequences of stereotype threat and imposter syndrome: The personal journey from stem-practitioner to stem-educator for four women of color. Taboo J. Cult. Educ. 2020, 19, 10. [Google Scholar]
- Bandura, A. Self-efficacy: Toward a unifying theory of behavioral change. Psychol. Rev. 1977, 84, 191–215. [Google Scholar] [CrossRef]
- Bartimote-Aufflick, K.; Bridgeman, A.; Walker, R.; Sharma, M.; Smith, L. The study, evaluation, and improvement of university student self-efficacy. Stud. High. Educ. 2016, 41, 1918–1942. [Google Scholar] [CrossRef]
- Roick, J.; Ringeisen, T. Self-efficacy, test anxiety, and academic success: A longitudinal validation. Int. J. Educ. Res. 2017, 83, 84–93. [Google Scholar] [CrossRef]
- Gecas, V. The social psychology of self-efficacy. Group Organ. Manag. 1989, 15, 291–316. [Google Scholar] [CrossRef]
- Shelton, S.H. Developing the construct of general self-efficacy. Psychol. Rep. 1990, 66, 987–994. [Google Scholar] [CrossRef]
- Pulakos, E.D.; Arad, S.; Donovan, M.A.; Plamondon, K.E. Adaptability in the workplace: Development of a taxonomy of adaptive performance. J. Appl. Psychol. 2000, 85, 612–624. [Google Scholar] [CrossRef] [Green Version]
- Schueler, K.; Fritz, J.; Dorfschmidt, L.; Van Harmelen, A.L.; Stroemer, E.; Wessa, M. Psychological network analysis of general self-efficacy in high vs. low resilient functioning healthy adults. Front. Psychiatry 2021, 12, 736147. [Google Scholar] [CrossRef]
- Bouih, A.; Nadif, B.; Benattabou, D. Assessing the effect of general self-efficacy on academic achievement using path analysis: A preliminary study. J. Engl. Lang. Teach. Appl. Linguist. 2021, 3, 18–24. [Google Scholar] [CrossRef]
- Lane, J.; Lane, A.M.; Kyprianou, A. Self-efficacy, self-esteem and their impact on academic performance. Soc. Behav. Personal. 2004, 32, 247–256. [Google Scholar] [CrossRef]
- Choi, N. Self-efficacy and self-concept as predictors of college students’ academic performance. Psychol. Sch. 2005, 42, 197–205. [Google Scholar] [CrossRef]
- Fenning, B.E.; May, L.N. “Where there is a will, there is an A”: Examining the roles of self-efficacy and self-concept in college students’ current educational attainment and career planning. Soc. Psychol. Educ. 2013, 16, 635–650. [Google Scholar] [CrossRef]
- Heslin, P.A.; Klehe, U.C. Self-efficacy. In Encyclopedia of Industrial/Organizational Psychology; Rogelberg, S.G., Ed.; Sage: New York, NY, USA, 2006; pp. 705–708. [Google Scholar]
- Lane, J.; Lane, A.M. Self-efficacy and academic performance. Soc. Behav. Personal. 2001, 29, 687–694. [Google Scholar] [CrossRef]
- Lent, R.W.; Hackett, G. Career self-efficacy: Empirical status and future directions. J. Vocat. Behav. 1987, 30, 347–382. [Google Scholar] [CrossRef]
- Wilson, D.; Bates, R.; Scott, E.P.; Painter, S.M.; Shaffer, J. Differences in self-efficacy among women and minorities in STEM. J. Women Minorities Sci. Eng. 2015, 21, 27–45. [Google Scholar] [CrossRef]
- Whitcomb, K.M.; Kalender, Z.Y.; Nokes-Malach, T.J.; Schunn, C.D.; Singh, C. A mismatch between self-efficacy and performance: Undergraduate women in engineering tend to have lower self-efficacy despite earning higher grades than men. Int. J. Eng. Educ. 2020, 36, 1–36. [Google Scholar]
- Williams, M.M.; George-Jackson, C. Using and doing science: Gender, self-efficacy, and science identity of undergraduate students in STEM. J. Women Minorities Sci. Eng. 2014, 20, 99–126. [Google Scholar] [CrossRef]
- Rittmayer, M.A.; Beier, M.E. Self-efficacy in STEM. In Applying Research to Practice (ARP) Resources; Bogue, B., Cady, E., Eds.; SWE-AWE: Chicago, IL, USA; NAE CASEE: Washington, DC, USA, 2009; pp. 1–12. Available online: http://www.engr.psu.edu/AWE/ARPresources.aspx (accessed on 30 December 2021).
- Seymour, E. The loss of women from science, mathematics, and engineering undergraduate majors: An explanatory account. Sci. Educ. 1995, 79, 437–473. [Google Scholar] [CrossRef]
- Zarafshani, K.; Knobloch, N.A.; Aghahi, H. General perceived self-efficacy of Iranian College of Agriculture students. J. Int. Agric. Ext. Educ. 2008, 15, 69–84. [Google Scholar] [CrossRef]
- Rezaei, A. Can self-efficacy and self-confidence explain Iranian female students’ academic achievement? Gend. Educ. 2012, 24, 393–409. [Google Scholar] [CrossRef]
- Kerkhof, G.A. Inter-individual differences in the human circadian system: A review. Biol. Psychol. 1985, 20, 83–112. [Google Scholar] [CrossRef]
- Kerkhof, G.A.; Van Dongen, H.P.A. Morning-type and evening-type individuals differ in the phase position of their endogenous circadian oscillator. Neurosci. Lett. 1996, 21, 153–156. [Google Scholar] [CrossRef]
- Taillard, J.; Philip, P.; Bioulac, B. Morningness/eveningness and the need for sleep. J. Sleep Res. 1999, 8, 291–295. [Google Scholar] [CrossRef] [PubMed]
- Carrier, J.; Monk, T.H.; Buysse, D.J.; Kupfer, D.J. Sleep and morningness-eveningness in the ‘middle’ years of life (20–59 y). J. Sleep Res. 1997, 6, 230–237. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- De Almeida-Filho, D.G.; Koike, B.D.V.; Billwiller, F.; Farias, K.S.; de Sales, I.R.P.; Luppi, P.H.; Ribeiro, S.; Queiroz, C.M. Hippocampus-retrosplenial cortex interaction is increased during phasic REM and contributes to memory consolidation. Sci. Rep. 2021, 11, 13078. [Google Scholar] [CrossRef] [PubMed]
- Vollmer, C.; Jankowski, K.S.; Díaz-Morales, J.F.; Itzek-Greulich, H.; Wüst-Ackermann, P.; Randler, C. Morningness–eveningness correlates with sleep time, quality, and hygiene in secondary school students: A multilevel analysis. Sleep Med. 2017, 30, 151–159. [Google Scholar] [CrossRef]
- Preckel, F.; Fischbach, A.; Scherrer, V.; Brunner, M.; Ugen, S.; Lipnevich, A.A.; Roberts, R.D. Circadian preference as a typology: Latent-class analysis of adolescents’ morningness/eveningness, relation with sleep behavior, and with academic outcomes. Learn. Individ. Differ. 2020, 78, 101725. [Google Scholar] [CrossRef]
- Önder, İ. Association of happiness with morningness-eveningness preference, sleep-related variables and academic performance in university students. Biol. Rhythm Res. 2020, 53, 950–965. [Google Scholar] [CrossRef]
- Gomes, A.A.; Tavares, J.; de Azevedo, M.H.P. Sleep and academic performance in undergraduates: A multi-measure, multi-predictor approach. Chronobiol. Int. 2011, 28, 786–801. [Google Scholar] [CrossRef]
- Mirghani, H.O. The effect of chronotype (morningness/eveningness) on medical students’ academic achievement in Sudan. J. Taibah Univ. Med. Sci. 2017, 12, 512–516. [Google Scholar] [CrossRef]
- Piffer, D.; Ponzi, D.; Sapienza, P.; Zingales, L.; Maestripieri, D. Morningness–eveningness and intelligence among high-achieving US students: Night owls have higher GMAT scores than early morning types in a top-ranked MBA program. Intelligence 2014, 47, 107–112. [Google Scholar] [CrossRef]
- Akram, N.; Khan, N.; Ameen, M.; Mahmood, S.; Shamim, K.; Amin, M.; Rana, Q.U.A. Morningness-eveningness preferences, learning approach, and academic achievement of undergraduate medical students. Chronobiol. Int. 2018, 35, 1262–1268. [Google Scholar] [CrossRef]
- Hamm, S.; Robertson, I. Preferences for deep-surface learning: A vocational education case study using a multimedia assessment activity. Australas. J. Educ. Technol. 2010, 26, 951–965. [Google Scholar] [CrossRef]
- Adan, A.; Natale, V. Gender differences in morningness-eveningness preference. Chronobiol. Int. 2002, 19, 709–720. [Google Scholar] [CrossRef] [PubMed]
- Roenneberg, T.; Wirz-Justice, A.; Merrow, M. Life between clocks: Daily temporal patterns of human chronotypes. J. Biol. Rhythm. 2003, 18, 80–90. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Mirghani, H.O.; Albalawi, K.S.; Alali, O.Y.; Albalawi, W.M.; Albalawi, K.M.; Aljohani, T.R.; Albalawi, W.S. Breakfast skipping, late dinner intake, and chronotype (eveningness-morningness) among medical students in Tabuk City, Saudi Arabia. Pan Afr. Med. J. 2019, 34, 178–183. [Google Scholar] [CrossRef] [PubMed]
- Preckel, F.; Lipnevich, A.A.; Boehme, K.; Brandner, L.; Georgi, K.; Könen, T.; Mursin, K.; Roberts, R.D. Morningness-eveningness and educational outcomes: The lark has an advantage over the owl at high school. Br. J. Educ. Psychol. 2013, 83, 114–134. [Google Scholar] [CrossRef]
- Montaruli, A.; Castelli, L.; Galasso, L.; Mulè, A.; Bruno, E.; Esposito, F.; Caumo, A.; Roveda, E. Effect of chronotype on academic achievement in a sample of Italian University students. Chronobiol. Int. 2019, 36, 1482–1495. [Google Scholar] [CrossRef]
- Mirghani, H.O.; Alnomsi, S.J.; Albalawi, K.S.; Alali, O.Y.; Albalawi, W.M.; Albalawi, K.M.; Albalawi, W.S. The chronotype (eveningness-morningness) effects on academic achievement among medical students in Tabuk City, Saudi Arabia. Egypt. J. Hosp. Med. 2018, 71, 3504–3507. [Google Scholar] [CrossRef]
- Carruthers, S.A.; Young, A.L. Preference of condition concerning time in learning environments of rural versus city eighth-grade students. In Proceedings of the First Annual Conference on Teaching Students through Their Individual Learning Styles, New York, NY, USA, 24–29 July 1979. [Google Scholar]
- Goldin, A.P.; Sigman, M.; Braier, G.; Golombek, D.A.; Leone, M.J. Interplay of chronotype and school timing predicts school performance. Nat. Hum. Behav. 2020, 4, 387–396. [Google Scholar] [CrossRef]
- Allmnakrah, A.; Evers, C. The need for a fundamental shift in the Saudi education system: Implementing the Saudi Arabian economic vision 2030. Res. Educ. 2020, 106, 22–40. [Google Scholar] [CrossRef]
- Tayan, B.M. The Saudi Tatweer education reforms: Implications of neoliberal thought to Saudi education policy. Int. Educ. Stud. 2017, 10, 61–71. [Google Scholar] [CrossRef] [Green Version]
- Algarni, F.; Male, T. Leadership in Saudi Arabian public schools: Time for devolution? Int. Stud. Educ. Adm. 2014, 42, 45–59. [Google Scholar] [CrossRef]
- Barry, A. Equal opportunity in education and employment in Saudi Arabia: Heading in the right direction but challenges remain. Educ. Plan. 2021, 28, 7–21. [Google Scholar]
- X, M. By any Means Necessary; Pathfinder Press: London, UK, 1971; p. 43. [Google Scholar]
- Labib, W.; Abdelsattar, A.; Ibrahim, Y.; Abdelhadi, A. What motivates students to study Engineering? A comparative study between males and females in Saudi Arabia. Educ. Sci. 2021, 11, 147. [Google Scholar] [CrossRef]
- Smith, C.S.; Reilly, C.; Midkiff, K. Evaluation of three circadian rhythm questionnaires with suggestions for an improved measure of morningness. J. Appl. Psychol. 1989, 74, 728. [Google Scholar] [CrossRef]
- Chen, G.; Gully, S.M.; Eden, D. Validation of a new general self-efficacy scale. Organ. Res. Methods 2001, 4, 62–83. [Google Scholar] [CrossRef] [Green Version]
- Field, A. Discovering Statistics Using SPSS; Sage: New York, NY, USA, 2009. [Google Scholar]
- BaHammam, A.S.; Almestehi, W.; Albatli, A.; AlShaya, S. Distribution of chronotypes in a large sample of young adult Saudis. Ann. Saudi Med. 2011, 31, 183–186. [Google Scholar] [CrossRef] [Green Version]
- Adan, A.; Archer, S.N.; Hidalgo, M.P.; Di Milia, L.; Natale, V.; Randler, C. Circadian typology: A comprehensive review. Chronobiol. Int. 2012, 29, 1153–1175. [Google Scholar] [CrossRef] [Green Version]
- Núñez, P.; Perillan, C.; Arguelles, J.; Diaz, E. Comparison of sleep and chronotype between senior and undergraduate university students. Chronobiol. Int. 2019, 36, 1626–1637. [Google Scholar] [CrossRef]
- O’Dea, R.E.; Lagisz, M.; Jennions, M.D.; Nakagawa, S. Gender differences in individual variation in academic grades fail to fit expected patterns for STEM. Nat. Commun. 2018, 9, 3777. [Google Scholar] [CrossRef]
- Pilotti, M.A.E.; Al Ghazo, R.; Al Shamsi, S.J. Academic entitlement amid social change in the Kingdom of Saudi Arabia. J. Appl. Res. High. Educ. 2021. [Google Scholar] [CrossRef]
- Fernández-Cézar, R.; Solano-Pinto, N.; Garrido, D. Can mathematics achievement be predicted? The role of cognitive–behavioral–emotional variables. Mathematics 2021, 9, 1591. [Google Scholar] [CrossRef]
- Shapka, J.D. Trajectories of math achievement and perceived math competence over high school and postsecondary education: Effects of an all-girl curriculum in high school. Educ. Res. Eval. 2009, 15, 527–541. [Google Scholar] [CrossRef]
- Maley, B.; Rafferty, M. Can math competency predict success in nursing school? Teach. Learn. Nurs. 2019, 14, 198–202. [Google Scholar] [CrossRef]
- Williams, K.L.; Burt, B.A.; Hilton, A.A. Math achievement: A role strain and adaptation approach. J. Multicult. Educ. 2016, 10, 368–383. [Google Scholar] [CrossRef]
- Pilotti, M.A.; El-Moussa, O.J.; Abdelsalam, H.M. Measuring the impact of the pandemic on female and male students’ learning in a society in transition: A must for sustainable education. Sustainability 2022, 14, 3148. [Google Scholar] [CrossRef]
- Sexton, T.L.; Tuckman, B.W. Self-beliefs and behavior: The role of self-efficacy and outcome expectation over time. Personal. Individ. Differ. 1991, 12, 725–736. [Google Scholar] [CrossRef]
- Moussa-Inaty, J.; Causapin, M.; Groombridge, T. Does language really matter when solving mathematical word problems in a second language? A cognitive load perspective. Educ. Stud. 2020, 46, 18–38. [Google Scholar] [CrossRef]
- Ferguson, A.M.; Fairburn, J. Language experience for problem-solving in Mathematics. Read. Teach. 1985, 38, 504–507. Available online: https://www.jstor.org/stable/20198837 (accessed on 30 December 2021).
- Beal, C.R.; Adams, N.M.; Cohen, P.R. Reading proficiency and Mathematics problem solving by high school English language learners. Urban Educ. 2010, 45, 58–74. [Google Scholar] [CrossRef] [Green Version]
- Kazima, M. Malawian students’ meanings for probability vocabulary. Educ. Stud. Math. 2007, 64, 169–189. [Google Scholar] [CrossRef]
- Oviedo, G.C. Comprehending algebra word problems in the first and second languages. In Proceedings of the 4th International Symposium on Bilingualism, Temple, AZ, USA, 30 April–3 May 2003; Cohen, J., McAlister, K.T., Rolstad, K., MacSwan, J., Eds.; Cascadilla Press: Somerville, MA, USA, 2005; pp. 267–295. [Google Scholar]
- Davis, E.K.; Bishop, A.J.; Seah, W.T. We don’t understand English that is why we prefer English: Primary school students’ preference for the language of instruction in Mathematics. Int. J. Sci. Math. Educ. 2013, 13, 583–604. [Google Scholar] [CrossRef]
Major | Morningness | Self-Efficacy | ||
---|---|---|---|---|
Male | Female | Male | Female | |
No-STEM Majors | 29.05 (0.89) | 32.46 (0.45) | 4.00 (0.12) | 3.82 (0.08) |
STEM Majors | 33.30 (0.63) | 32.50 (0.38) | 3.85 (0.10) | 3.78 (0.06) |
Course Grades | Final Test Grades | |||
---|---|---|---|---|
No-STEM Majors | Male | Female | Male | Female |
Pass (≥66%) | 44.06% | 72.35% | 57.41% | 38.82% |
Fail (<66%) | 47.46% | 17.06% | 42.59% | 61.18% |
Mean | 61.52 (3.46) | 70.03 (2.18) | 58.05 (4.14) | 52.36 (2.22) |
Withdrawal | 8.48% | 10.59% | ||
STEM Majors | ||||
Pass (≥66%) | 50.00% | 68.97% | 44.79% | 37.30% |
Fail (<66%) | 38.89% | 17.93% | 55.21% | 62.70% |
Mean | 60.48 (2.54) | 67.34 (1.77) | 53.39 (2.82) | 50.01 (1.81) |
Withdrawal | 11.11% | 13.10% |
Predictor Variables | B | SE | Beta | t | Sign. |
---|---|---|---|---|---|
No-STEM Male Students | |||||
Constant | 77.705 | 20.109 | |||
Morningness | −0.366 | 0.470 | −0.095 | −0.780 | ns |
Self-Efficacy | 2.433 | 3.370 | 0.087 | 0.722 | ns |
Timing of Course | −23.709 | 6.657 | −0.430 | −3.561 | 0.001 |
No-STEM Female Students | |||||
Constant | 64.525 | 16.294 | |||
Morningness | −0.162 | 0.383 | −0.033 | −0.422 | ns |
Self-Efficacy | 2.480 | 2.100 | 0.092 | 1.181 | ns |
Timing of Course | 2.653 | 4.417 | 0.047 | 0.601 | ns |
STEM Male Students | |||||
Constant | 20.933 | 17.079 | |||
Morningness | 1.095 | 0.376 | 0.271 | 2.908 | 0.004 |
Self-Efficacy | 2.696 | 2.442 | 0.103 | 1.104 | ns |
Timing of Course | −11.086 | 5.119 | −0.200 | −2.166 | 0.033 |
STEM Female Students | |||||
Constant | 47.179 | 10.987 | |||
Morningness | 0.125 | 0.276 | 0.027 | 0.453 | ns |
Self-Efficacy | 3.875 | 1.755 | 0.130 | 2.208 | 0.028 |
Timing of Course | 2.685 | 3.551 | 0.044 | 0.756 | ns |
Predictor Variables | B | SE | Beta | t | Sign. |
---|---|---|---|---|---|
No-STEM Male Students | |||||
Constant | 67.888 | 24.249 | |||
Morningness | −0.624 | 0.567 | −0.134 | −1.101 | ns |
Self-Efficacy | 5.964 | 4.063 | 0.178 | 1.468 | ns |
Timing of Course | −24.169 | 8.028 | −0.367 | −3.011 | 0.004 |
No-STEM Female Students | |||||
Constant | 44.102 | 16.609 | |||
Morningness | −0.013 | 0.390 | −0.003 | −0.034 | ns |
Self-Efficacy | 2.531 | 2.141 | 0.093 | 1.182 | ns |
Timing of Course | −2.032 | 4.503 | −0.035 | −0.451 | ns |
STEM Male Students | |||||
Constant | −13.509 | 18.632 | |||
Morningness | 1.536 | 0.411 | 0.341 | 3.739 | 0.000 |
Self-Efficacy | 5.326 | 2.664 | 0.183 | 1.999 | 0.048 |
Timing of Course | −7.219 | 5.584 | −0.117 | −1.293 | ns |
STEM Female Students | |||||
Constant | 33.289 | 11.164 | |||
Morningness | 0.259 | 0.280 | 0.054 | 0.923 | ns |
Self-Efficacy | 3.464 | 1.783 | 0.113 | 1.943 | ns |
Timing of Course | −8.764 | 3.608 | −0.142 | −2.429 | 0.016 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Pilotti, M.A.E.; Abdelsalam, H.M.; Anjum, F.; Daqqa, I.; Muhi, I.; Latif, R.M.; Nasir, S.; Al-Ameen, T.A. Predicting Math Performance of Middle Eastern Students: The Role of Dispositions. Educ. Sci. 2022, 12, 314. https://doi.org/10.3390/educsci12050314
Pilotti MAE, Abdelsalam HM, Anjum F, Daqqa I, Muhi I, Latif RM, Nasir S, Al-Ameen TA. Predicting Math Performance of Middle Eastern Students: The Role of Dispositions. Education Sciences. 2022; 12(5):314. https://doi.org/10.3390/educsci12050314
Chicago/Turabian StylePilotti, Maura A. E., Hanadi M. Abdelsalam, Farheen Anjum, Ibtisam Daqqa, Imad Muhi, Raja M. Latif, Sumiya Nasir, and Talal A. Al-Ameen. 2022. "Predicting Math Performance of Middle Eastern Students: The Role of Dispositions" Education Sciences 12, no. 5: 314. https://doi.org/10.3390/educsci12050314
APA StylePilotti, M. A. E., Abdelsalam, H. M., Anjum, F., Daqqa, I., Muhi, I., Latif, R. M., Nasir, S., & Al-Ameen, T. A. (2022). Predicting Math Performance of Middle Eastern Students: The Role of Dispositions. Education Sciences, 12(5), 314. https://doi.org/10.3390/educsci12050314