The Prevalence and Determinants of Math Anxiety in a Non-Western Setting from the Lens of Self-Efficacy Theory & Attribution Theory

Manal Alyamni^1,

¹Department of Education, School of Psychology, Howard University, Washington DC, USA

Cite this paper:
Manal Alyamni. The Prevalence and Determinants of Math Anxiety in a Non-Western Setting from the Lens of Self-Efficacy Theory & Attribution Theory. American Journal of Educational Research. 2025; 13(7):372-382. doi: 10.12691/education-13-7-3

Abstract

The main aim of the current study is to identify the prevalence and determinants of math anxiety from the lens of self-efficacy theory & attribution theory. This study provides valuable data on the prevalence and causes of mathematics anxiety in a non-western setting – specifically, among 341 high school students (164 females/48.1% and 177 males/51.9%) in grade levels 10, 11, and 12 in Riyadh, Saudi Arabia. Using the Mathematics Self-Efficacy Scale (MSES), modified from Betz & Hackett's math anxiety adopted from Fennema-Sherman Mathematics Attitudes Scales and the Attrition Scale procedure implemented by Bar-Tal, this study focuses on the links among three interrelated constructs: math anxiety, perceived self-efficacy, and causal attribution. Results show that most of both male and female students are doubtful about their performance in math, but overall, female students show a higher degree of math anxiety than males. The data also showed a high positive correlation between external attributional and anxiety scores, based on a set of independent variables including confidence, value, enjoyment, motivation, teacher valuation, self-efficacy, internal beliefs, and external beliefs. The most significant independent variables were self-efficacy and enjoyment, while value and motivation were only marginally related to math anxiety. On average, the higher students’ self-efficacy, the lower their math anxiety.

Keywords:
Math Anxiety Self-Efficacy Theory Attribution Theory Non-Western Setting Determinants of Anxiety

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References:

[1]	C. F. Weems et al., “Test Anxiety Prevention and Intervention Programs in Schools: Program Development and Rationale,” School Ment. Health, vol. 2, no. 2, pp. 62–71, Jun. 2010.
[2]	F. C. Richardson and R. M. Suinn, “The mathematics anxiety rating scale: psychometric data.,” J. Couns. Psychol., vol. 19, no. 6, p. 551, 1972.
[3]	M. H. Ashcraft, “Math Anxiety: Personal, Educational, and Cognitive Consequences,” Curr. Dir. Psychol. Sci., vol. 11, no. 5, pp. 181–185, Oct. 2002.
[4]	N. E. Betz, “Prevalence, distribution, and correlates of math anxiety in college students.,” J. Couns. Psychol., vol. 25, no. 5, p. 441, 1978.
[5]	S. S. Stodolsky, “Telling Math: Origins of Math Aversion and Anxiety,” Educ. Psychol., vol. 20, no. 3, pp. 125–133, Jun. 1985.
[6]	R. P. Walsh, R. O. Engbretson, and B. A. O’Brien, “Anxiety and test-taking behavior.,” J. Couns. Psychol., vol. 15, no. 6, p. 572, 1968.
[7]	S. B. Sarason and G. Mandler, “Some correlates of test anxiety.,” J. Abnorm. Soc. Psychol., vol. 47, no. 4, p. 810, 1952.
[8]	E. Geist, “The anti-anxiety curriculum: Combating math anxiety in the classroom.,” J. Instr. Psychol., vol. 37, no. 1, 2010, Accessed: Jul. 08, 2025. [Online]. Available: https:// www.andrews.edu/ ceis/ gpc/ faculty-research/ montagano-research/the-anti-anxiety-cur.pdf.
[9]	A. Mattarella-Micke, J. Mateo, M. N. Kozak, K. Foster, and S. L. Beilock, “Choke or thrive?” The relation between salivary cortisol and math performance depends on individual differences in working memory and math-anxiety.,” Emotion, vol. 11, no. 4, p. 1000, 2011.
[10]	W. Wang et al., “Advancing Fine-Grained Visual Understanding with Multi-Scale Alignment in Multi-Modal Models,” Nov. 14, 2024, arXiv: arXiv: 2411 09691.
[11]	A. M. Legg and L. Locker Jr, “Math performance and its relationship to math anxiety and metacognition.,” North Am. J. Psychol., vol. 11, no. 3, 2009, Accessed: Jul. 08, 2025. [Online]. Available: https:// www.researchgate.net /profile/Angela-Legg/ publication/264622690_Math_ performance_and_its_relationship_to_ math_anxiety_and_ metacognition/ links/ 55194b500cf21b5da3b828e2/Math-performance-and-its-relationship-to-math- anxiety-and-metacognition. pdf.
[12]	K. Trezise and R. A. Reeve, “Cognition-emotion interactions: patterns of change and implications for math problem solving,” Front. Psychol., vol. 5, p. 840, 2014.
[13]	E. A. Maloney and S. L. Beilock, “Math anxiety: Who has it, why it develops, and how to guard against it,” Trends Cogn. Sci., vol. 16, no. 8, pp. 404–406, 2012.
[14]	G. Ramirez, E. A. Gunderson, S. C. Levine, and S. L. Beilock, “Math Anxiety, Working Memory, and Math Achievement in Early Elementary School,” J. Cogn. Dev., vol. 14, no. 2, pp. 187–202, Apr. 2013.
[15]	K. Gogol, M. Brunner, F. Preckel, T. Goetz, and R. Martin, “Developmental dynamics of general and school-subject-specific components of academic self-concept, academic interest, and academic anxiety,” Front. Psychol., vol. 7, p. 356, 2016.
[16]	C. Lobman, “‘I Feel Nervous . . . Very Nervous’ Addressing Test Anxiety in Inner City Schools Through Play and Performance,” Urban Educ., vol. 49, no. 3, pp. 329–359, Apr. 2014.
[17]	A. Bandura, “Social foundations of thought and action,” Englewood Cliffs NJ, vol. 1986, no. 23–28, p. 2, 1986.
[18]	F. Pajares and L. Graham, “Self-efficacy, motivation constructs, and mathematics performance of entering middle school students,” Contemp. Educ. Psychol., vol. 24, no. 2, pp. 124–139, 1999.
[19]	T. Williams and K. Williams, “Self-efficacy and performance in mathematics: Reciprocal determinism in 33 nations,” J. Educ. Psychol., vol. 102, no. 2, pp. 453–466, 2010.
[20]	T. D. Wilson, M. Damiani, and N. Shelton, “Chapter 5 - Improving the Academic Performance of College Students with Brief Attributional Interventions,” in Improving Academic Achievement, J. Aronson, Ed., in Educational Psychology., San Diego: Academic Press, 2002, pp. 89–108.
[21]	S. Graham, B. Weiner. Motivation, past, present and future. Available at: https:// www.academia.edu/ download/ 39592424/ Motivation_-_Past__ Present_and_Future.pdf.
[22]	R. E. Smith, J. C. Ascough, R. F. Ettinger, and D. A. Nelson, “Humor, anxiety, and task performance.,” J. Pers. Soc. Psychol., vol. 19, no. 2, p. 243, 1971.
[23]	A. J. Martin, J. Anderson, J. Bobis, J. Way, and R. Vellar, “Switching on and switching off in mathematics: An ecological study of future intent and disengagement among middle school students.,” J. Educ. Psychol., vol. 104, no. 1, p. 1, 2012.
[24]	S. J. Salend, “Addressing Test Anxiety,” Teach. Except. Child., vol. 44, no. 2, pp. 58–68, Nov. 2011.
[25]	B. Capili, “Cross-sectional studies,” AJN Am. J. Nurs., vol. 121, no. 10, pp. 59–62, 2021.
[26]	K. A. Levin, “Study design III: Cross-sectional studies,” Evid. Based Dent., vol. 7, no. 1, pp. 24–25, 2006.
[27]	L. Cohen, L. Manion, and K. Morrison, “Surveys, longitudinal, cross-sectional and trend studies,” in Research methods in education, Routledge, 2017, pp. 334–360. Accessed: Jul. 08, 2025. [Online]. Available: https:// www.taylorfrancis.com/ chapters/ edit/10.4324/9781315456539-17/surveys-longitudinal -cross-sectional-trend-studies- louis-cohen-lawrence-manion -keith-morrison.
[28]	D. Bar-Tal, A. Raviv, A. Raviv, and Y. Bar-Tal, “Consistency of pupils’ attributions regarding success and failure.,” J. Educ. Psychol., vol. 74, no. 1, p. 104, 1982.
[29]	F. Pajares and J. Kranzler, “Self-efficacy beliefs and general mental ability in mathematical problem-solving,” Contemp. Educ. Psychol., vol. 20, no. 4, pp. 426–443, 1995.
[30]	E. Fennema and J. A. Sherman, “Fennema-Sherman mathematics attitudes scales: Instruments designed to measure attitudes toward the learning of mathematics by females and males,” J. Res. Math. Educ., vol. 7, no. 5, pp. 324–326, 1976.
[31]	M. Takunyacı, E. Masal, M. Masal, Ö. Ergene, and K. Erden, “Fennema-Sherman Mathematics Attitude Scales: Adaptaition to Turkish Culture,” Sak. Univ. J. Educ., vol. 9, no. 1, pp. 208–223, 2019.
[32]	B. Weiner, “An attributional theory of achievement motivation and emotion.,” Psychol. Rev., vol. 92, no. 4, p. 548, 1985.
[33]	G. Hackett, “Role of mathematics self-efficacy in the choice of math-related majors of college women and men: A path analysis.,” J. Couns. Psychol., vol. 32, no. 1, p. 47, 1985.
[34]	E. L. Usher and F. Pajares, “Sources of self-efficacy in mathematics: A validation study,” Contemp. Educ. Psychol., vol. 34, no. 1, pp. 89–101, 2009.
[35]	N. M. Else-Quest, J. S. Hyde, and M. C. Linn, “Cross-national patterns of gender differences in mathematics: a meta-analysis.,” Psychol. Bull., vol. 136, no. 1, p. 103, 2010.
[36]	A. D. Liem, S. Lau, and Y. Nie, “The role of self-efficacy, task value, and achievement goals in predicting learning strategies, task disengagement, peer relationship, and achievement outcome,” Contemp. Educ. Psychol., vol. 33, no. 4, pp. 486–512, 2008.
[37]	A. F. Hayes, “Mediation, moderation, and conditional process analysis,” Introd. Mediat. Moderat. Cond. Process Anal. Regres. -Based Approach, vol. 1, no. 6, pp. 12–20, 2013.
[38]	R. Pekrun, “The Control-Value Theory of Achievement Emotions: Assumptions, Corollaries, and Implications for Educational Research and Practice,” Educ. Psychol. Rev., vol. 18, no. 4, pp. 315–341, Nov. 2006.
[39]	J. W. Creswell and J. D. Creswell, Research design: Qualitative, quantitative, and mixed methods approach. Sage publications, 2017.
[40]	F. Faul, E. Erdfelder, A.-G. Lang, and A. Buchner, “G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences,” Behav. Res. Methods, vol. 39, no. 2, pp. 175–191, May 2007.
[41]	A. Field, Discovering statistics using IBM SPSS statistics. Sage publications limited, 2024. Accessed: Jul. 08, 2025. [Online]. Available: https:// books.google.com/ books? hl=en& lr=&id= 83L2EAAAQBAJ&oi=fnd&pg= PT8&dq=Field,+A.+(2024).+Discovering+ statistics+using+IBM+ SPSS+statistics.+Sage+publications+ limited.&ots=UbNSxrHPAO&sig=ejILh_DF_Jv6YZ1dybBA5r234Qg.
[42]	R. M. O’brien, “A Caution Regarding Rules of Thumb for Variance Inflation Factors,” Qual. Quant., vol. 41, no. 5, pp. 673–690, Sep. 2007.
[43]	A. Devine, K. Fawcett, D. Szűcs, and A. Dowker, “Gender differences in mathematics anxiety and the relation to mathematics performance while controlling for test anxiety,” Behav. Brain Funct., vol. 8, no. 1, Dec. 2012.
[44]	S. J. Spencer, C. M. Steele, and D. M. Quinn, “Stereotype threat and women’s math performance,” J. Exp. Soc. Psychol., vol. 35, no. 1, pp. 4–28, 1999.
[45]	A. Wigfield and J. S. Eccles, “Expectancy–Value Theory of Achievement Motivation,” Contemp. Educ. Psychol., vol. 25, no. 1, pp. 68–81, Jan. 2000.
[46]	B. K. Hamre and R. C. Pianta, “Student-teacher relationships.,” 2006, Accessed: Jul. 08, 2025. [Online]. Available: https:// psycnet.apa.org/ record/ 2006-03571-005.
[47]	A. Bandura, Self-efficacy: The exercise of control, vol. 11. Freeman, 1997.
[48]	R. Trigueros Ramos, J. M. Aguilar Parra, I. M. Mercader Rubio, J. M. Fernández Campoy, and J. J. Carrión Martínez, “Set the Controls for the Heart of the Maths. The Protective Factor of Resilience in the Face of Mathematical Anxiety, 2020, Accessed: Jul. 08, 2025. [Online]. Available: https:// repositorio.ual.es/ handle/ 10835/8474.