Abstract
Despite numerous studies devoted to mathematics aptitude and achievement, research on how individuals experience math has remained relatively fragmented. Here, using a combined theoretical and data-driven approach, we sought to characterize self-reported math experiences, with a particular focus on negative math experiences. An examination of existing literature led to the identification of eight potential facets of math experiences: emotional, cognitive, physiological, behavioral, testing, classroom/social performance, self-efficacy, and attitudinal. We generated survey items intended to probe experiences within each of these facets and constructed a preliminary questionnaire of 107 candidate items, comprising positively and negatively framed statements about one’s math experiences, with data from a final analytic sample of N = 803 adult participants. Focusing on negative items, four key factors emerged from the data: negative attitudes and avoidance, physiological experiences, testing and educational experiences, and cognitive and emotional experiences. These results point to opportunities for contact between literatures (e.g., between negative attitudes and avoidance behaviors), and toward relatively unexplored topics, such as the importance of negative physiological experiences when facing math. On a practical level, we also provide short subscales with sound internal metrics for each of the four factors identified above. Taken together, this work may prove useful on both a theoretical and a methodological level for those looking to develop a unifying framework of negative math experiences.




Similar content being viewed by others
Data availability
Data is provided within the manuscript or supplementary information files. The data supporting this work will made available at the Open Science Framework at the following link: https://osf.io/2rhqz/files/osfstorage.
Notes
[(In – In+1) / In ≥ .15], where In is the eigenvalue for the factor in question and In+1 is the eigenvalue for the factor with the next lowest eigenvalue.
Items were recoded according to their rank order in Fig. 2 for the relevant subcomponent: AA01-AA22, PH01-PH21, TE01-TE15, CE01-CE19.
Recall that individual items were scored as 0–4.
Here we adopt the general guidelines that acceptable skew is between -1 and 1, and acceptable kurtosis is between -2 and 2 (Hair et al., 2021).
References
Aiken, L. R. (1974). Two scales of attitude toward mathematics. Journal for Research in Mathematics Education, 5(2), 67–71. https://doi.org/10.2307/748616
Alexander, L., & Martray, C. (1989). The development of an abbreviated version of the Mathematics Anxiety Rating Scale. Measurement and Evaluation in Counseling and Development, 22(3), 143–150.
Alpert, R., & Haber, R. N. (1960). Anxiety in academic achievement situations. The Journal of Abnormal and Social Psychology, 61(2), 207. https://doi.org/10.1037/h0045464
Ames, C. (1992). Classrooms: Goals, structures, and student motivation. Journal of Educational Psychology, 84(3), 261–271. https://doi.org/10.1037/0022-0663.84.3.261
Ashcraft, M. H. (2002). Math anxiety: Personal, educational, and cognitive consequences. Current Directions in Psychological Science, 11(5), 181–185. https://doi.org/10.1111/1467-8721.00196
Ashcraft, M. H., & Krause, J. A. (2007). Working memory, math performance, and math anxiety. Psychonomic Bulletin & Review, 14(2), 243–248. https://doi.org/10.3758/BF03194059
Ashcraft, M. H., & Moore, A. M. (2009). Mathematics anxiety and the affective drop in performance. Journal of Psychoeducational Assessment, 27(3), 197–205. https://doi.org/10.1177/0734282908330580
Aupperle, R. L., & Martin, M. P. (2010). Neural systems underlying approach and avoidance in anxiety disorders. Dialogues in Clinical Neuroscience, 12(4), 517–531. https://doi.org/10.31887/DCNS.2010.12.4/raupperle
Aupperle, R. L., Melrose, A. J., Francisco, A., Paulus, M. P., & Stein, M. B. (2015). Neural substrates of approach-avoidance conflict decision-making. Human Brain Mapping, 36(2), 449–462. https://doi.org/10.1002/hbm.22639
Avancini, C., & Szűcs, D. (2019). Psychophysiological correlates of mathematics anxiety. Mathematics Anxiety. https://doi.org/10.4324/9780429199981-3
Bandura, A. (1989). Regulation of cognitive processes through perceived self-efficacy. Developmental Psychology, 25(5), 729. https://doi.org/10.1037/0012-1649.25.5.729
Barroso, C., Ganley, C. M., McGraw, A. L., Geer, E. A., Hart, S. A., & Daucourt, M. C. (2021). A meta-analysis of the relation between math anxiety and math achievement. Psychological Bulletin, 147(2), 134. https://doi.org/10.1037/bul0000307
Baumeister, R. F., Vohs, K. D., Nathan DeWall, C., & Zhang, L. (2007). How emotion shapes behavior: Feedback, anticipation, and reflection, rather than direct causation. Personality and Social Psychology Review, 11(2), 167–203. https://doi.org/10.1177/1088868307301033
Beck, A. T., Epstein, N., Brown, G., & Steer, R. A. (1988). An inventory for measuring clinical anxiety: Psychometric properties. Journal of Consulting and Clinical Psychology, 56(6), 893.
Beilock, S. L. (2008). Math performance in stressful situations. Current Directions in Psychological Science, 17(5), 339–343. https://doi.org/10.1111/j.1467-8721.2008.006
Beilock, S. L., & Carr, T. H. (2005). When high-powered people fail: Working memory and “choking under pressure” in math. Psychological Science, 16(2), 101–105. https://doi.org/10.1111/j.0956-7976.2005.00789.x
Benjamin, A. S., & Pashler, H. (2015). The value of standardized testing: A perspective from cognitive psychology. Policy Insights from the Behavioral and Brain Sciences, 2(1), 13–23. https://doi.org/10.1177/2372732215601116
Bessant, K. C. (1997). The development and validation of scores on the mathematics information processing scale (MIPS). Educational and Psychological Measurement, 57(5), 841–857.
Betz, N. E. (1978). Prevalence, distribution, and correlates of math anxiety in college students. Journal of Counseling Psychology, 25(5), 441–448. https://doi.org/10.1037/0022-0167.25.5.441
Betz, N. E., & Hackett, G. (1983). The relationship of mathematics self-efficacy expectations to the selection of science-based college majors. Journal of Vocational Behavior, 23(3), 329–345. https://doi.org/10.1016/0001-8791(83)90046-5
Boaler, J. (2014). Research suggests that timed tests cause math anxiety. Teaching Children Mathematics, 20(8), 469–474.
Buhrmester, M., Kwang, T., & Gosling, S. D. (2011). Amazon’s Mechanical Turk: A new source of inexpensive, yet high-quality data? Perspectives on Psychological Science, 6(1), 3–5. https://doi.org/10.1177/1745691610393980
Bull, R., & Lee, K. (2014). Executive functioning and mathematics achievement. Child Development Perspectives, 8(1), 36–41. https://doi.org/10.1111/cdep.12059
Cameron, J., & Nesse, R. (1986). The nature of emotion. Psychological Review, 93(1), 503–525.
Caviola, S., Carey, E., Mammarella, I. C., & Szucs, D. (2017). Stress, time pressure, strategy selection and math anxiety in mathematics: A review of the literature. Frontiers in Psychology, 8, 1488. https://doi.org/10.3389/fpsyg.2017.01488
Centerbar, D. B., & Clore, G. L. (2006). Do approach-avoidance actions create attitudes? Psychological Science, 17(1), 22–29. https://doi.org/10.1111/j.1467-9280.2005.01660.x
Chang, H., & Beilock, S. L. (2016). The math anxiety-math performance link and its relation to individual and environmental factors: A review of current behavioral and psychophysiological research. Current Opinion in Behavioral Sciences, 10, 33–38. https://doi.org/10.1016/j.cobeha.2016.04.011
Cragg, L., & Gilmore, C. (2014). Skills underlying mathematics: The role of executive function in the development of mathematics proficiency. Trends in Neuroscience and Education, 3(2), 63–68. https://doi.org/10.1016/j.tine.2013.12.001
D’Ailly, H., & Bergering, A. J. (1992). Mathematics anxiety and mathematics avoidance behavior: A validation study of two MARS factor-derived scales. Educational and Psychological Measurement, 52(2), 369–377. https://doi.org/10.1177/0013164492052002012
Daker, R. J., Gattas, S. U., Sokolowski, H. M., Green, A. E., & Lyons, I. M. (2021). First-year students’ math anxiety predicts STEM avoidance and underperformance throughout university, independently of math ability. npj Science of Learning, 6(1), 1–13. https://doi.org/10.1038/s41539-021-00095-7
Daker, R. J., Gattas, S. U., Necka, E. A., Green, A. E., & Lyons, I. M. (2023a). Does anxiety explain why math-anxious people underperform in math? Npj Science of Learning, 8(1), 6. https://doi.org/10.1038/s41539-023-00156-z
Daker, R. J., Slipenkyj, M. S., Green, A. E., & Lyons, I. M. (2023b). Evidence for avoidance tendencies linked to anxiety about specific types of thinking. Scientific Reports, 13(1), 3294. https://doi.org/10.1038/s41598-023-29834-z
DeCaro, D. A., Rittle-Johnson, B., & Beilock, S. L. (2010). The impact of performance pressure on mathematical problem solving in children. Developmental Psychology, 46(5), 1097–1108.
Deci, E. L., & Ryan, R. M. (1985). The general causality orientations scale: Self-determination in personality. Journal of Research in Personality, 19(2), 109–134. https://doi.org/10.1016/0092-6566(85)90023-6
Dew, K. H., Galassi, J. P., & Galassi, M. D. (1984). Math anxiety: Relation with situational test anxiety, performance, physiological arousal, and math avoidance behavior. Journal of counseling Psychology, 31(4), 580. https://doi.org/10.1037/0022-0167.31.4.580
Dowker, A., Sarkar, A., & Looi, C. Y. (2016). Mathematics anxiety: What have we learned in 60 years? Frontiers in Psychology, 7, 508. https://doi.org/10.3389/fpsyg.2016.00508
Dreger, R. M., & Aiken, L. R., Jr. (1957). The identification of number anxiety in a college population. Journal of educational psychology, 48(6), 344. https://doi.org/10.1037/h0045894
Eysenck, M. W., & Calvo, M. G. (1992). Anxiety and performance: The processing efficiency theory. Cognition & emotion, 6(6), 409–434. https://doi.org/10.1080/02699939208409696
Eysenck, M. W., & Derakshan, N. (2011). New perspectives in attentional control theory. Personality and Individual Differences, 50(7), 955–960. https://doi.org/10.1016/j.paid.2010.08.019
Felson, R. B. (1984). The effect of self-appraisals of ability on academic performance. Journal of personality and social psychology, 47(5), 944. https://doi.org/10.1037/0022-3514.47.5.944
Fennema, E., & Sherman, J. A. (1976). Fennema-Sherman mathematics attitudes scales: Instruments designed to measure attitudes toward the learning of mathematics by females and males. Journal for Research in Mathematics Education, 7(5), 324–326. https://doi.org/10.2307/748467
Foley, A. E., Herts, J. B., Borgonovi, F., Guerriero, S., Levine, S. C., & Beilock, S. L. (2017). The math anxiety-performance link: A global phenomenon. Current Directions in Psychological Science, 26(1), 52–58. https://doi.org/10.1177/0963721416672463
Freedman N. D. (2022). Math Anxiety Online Self-Test: http://www.mathpower.com/anxtest.htm.
Ganley, C. M., & McGraw, A. L. (2016). The development and validation of a revised version of the math anxiety scale for young children. Frontiers in Psychology, 7, 211252.
Good, C., Rattan, A., & Dweck, C. S. (2012). Why do women opt out? Sense of belonging and women’s representation in mathematics. Journal of personality and social psychology, 102(4), 700–717. https://doi.org/10.1037/a0026659
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
Hair Jr, J., Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling (PLS-SEM). Sage publications
Hannula, M. S., Pantziara, M., & Di Martino, P. (2018). Affect and mathematical thinking: Exploring developments, trends, and future directions. In T. Dreyfus, M. Artigue, D. Potari, S. Prediger, & K. Ruthven (Eds.), Developing Research in Mathematics Education Twenty Years of Communication, Cooperation and Collaboration in Europe (pp. 128–141). UK: Routledge.
Harari, R. R., Vukovic, R. K., & Bailey, S. P. (2013). Mathematics anxiety in young children: An exploratory study. The Journal of Experimental Education, 81(4), 538–555.
Hart, R., Casserly, M., Uzzell, R., Palacios, M., Corcoran, A., & Spurgeon, L. (2015). Student Testing in America's Great City Schools: An Inventory and Preliminary Analysis. Council of the Great City Schools
Hembree, R. (1990). The nature, effects, and relief of mathematics anxiety. Journal for Research in Mathematics Education, 21(1), 33–46. https://doi.org/10.2307/749455
Hendy, H. M., Schorschinsky, N., & Wade, B. (2014). Measurement of math beliefs and their associations with math behaviors in college students. Psychological Assessment, 26(4), 1225.
Henschel, S., & Roick, T. (2018). The multidimensional structure of math anxiety revisited. European Journal of Psychological Assessment. https://doi.org/10.1027/1015-5759/a000477
Hollenbeck, K. (2002). Determining when test alterations are valid accommodations or modifications for large-scale assessment. Large-scale assessment programs for all students: Validity, technical adequacy, and implementation, 395–425. Lawrence Erlbaum Associates Publishers
Hulleman, C. S., Godes, O., Hendricks, B. L., & Harackiewicz, J. M. (2010). Enhancing interest and performance with a utility value intervention. Journal of Educational Psychology, 102(4), 880–895. https://doi.org/10.1037/a0019506
Ito, R., & Lee, A. C. (2016). The role of the hippocampus in approach-avoidance conflict decision-making: Evidence from rodent and human studies. Behavioural Brain Research, 313, 345–357. https://doi.org/10.1016/j.bbr.2016.07.039
Jackson, C. D., & Leffingwell, R. J. (1999). The role of instructors in creating math anxiety in students from kindergarten through college. The Mathematics Teacher, 92(7), 583–586.
Jansen, M., Lüdtke, O., & Schroeders, U. (2016). Evidence for a positive relation between interest and achievement: Examining between-person and within-person variation in five domains. Contemporary Educational Psychology, 46, 116–127. https://doi.org/10.1016/j.cedpsych.2016.05.004
Leary, M. R. (1983). A brief version of the fear of negative evaluation scale. Personality and social psychology bulletin, 9(3), 371–375. https://doi.org/10.1177/0146167283093007
Lee, J. (2009). Mathematics self-concept, self-efficacy and anxiety scale [Database record]. Retrieved from PsycTESTS. https://doi.org/10.1037/t31473-000
Lee, J., Cho, S., Kim, B., & Bong, M. (2014). Math interest, anxiety, and self-efficacy: Examining reciprocal relations. Learning and Individual Differences, 35, 99–108. https://doi.org/10.1016/j.lindif.2021.102060
Lee, J., & Stankov, L. (2018). Non-cognitive predictors of academic achievement: Evidence from TIMSS and PISA. Learning and individual Differences, 65, 50–64. https://doi.org/10.1016/j.lindif.2018.05.009
Lerner, J. S., Li, Y., Valdesolo, P., & Kassam, K. S. (2015). Emotion and decision making. Annual review of psychology, 66, 799–823. https://doi.org/10.1146/annurev-psych-010213-115043
Liebert, R. M., & Morris, L. W. (1967). Cognitive and emotional components of test anxiety: A distinction and some initial data. Psychological Reports, 20(3), 975–978.
Lim, S. Y., & Chapman, E. (2015). Effects of using history as a tool to teach mathematics on students’ attitudes, anxiety, motivation and achievement in grade 11 classrooms. EDucational Studies in Mathematics, 90, 189–212.
Lovett, B. J. (2010). Extended time testing accommodations for students with disabilities: Answers to five fundamental questions. Review of Educational Research, 80(4), 611–638. https://doi.org/10.3102/0034654310364063
Luttrell, V. R., Callen, B. W., Allen, C. S., Wood, M. D., Deeds, D. G., & Richard, D. C. (2010). The mathematics value inventory for general education students: Development and initial validation. Educational and Psychological Measurement, 70(1), 142–160. https://doi.org/10.1177/0013164409344526
Lyons, I. M., & Beilock, S. L. (2012). Mathematics anxiety: Separating the math from the anxiety. Cerebral Cortex, 22(9), 2102–2110. https://doi.org/10.1093/cercor/bhr289
Malinsky, M., Ross, A., Pannells, T., & McJunkin, M. (2006). Math anxiety in pre-service elementary school teachers. Education, 127(2), 274–280.
Meece, J. L., Wigfield, A., & Eccles, J. S. (1990). Predictors of math anxiety and its influence on young adolescents' course enrollment intentions and performance in mathematics. Journal of Educational Psychology, 82(1), 60–70. https://doi.org/10.1037/0022-0663.82.1.60
Melnikoff, D. E., Lambert, R., & Bargh, J. A. (2020). Attitudes as prepared reflexes. Journal of Experimental Social Psychology, 88, 103950. https://doi.org/10.1016/j.jesp.2019.103950
Mulhern, F., & Rae, G. (1998). Development of a shortened form of the Fennema-Sherman Mathematics Attitudes Scales. Educational and Psychological Measurement, 58(2), 295–306. https://doi.org/10.1177/0013164498058002012
National Assessment of Educational Progress [NAEP]. (2019). 2019 National Assessment of Educational Progress (NAEP) Mathematics Report Card. U.S. Department of Education, National Center for Education Statistics.
Necka, E. A., Cacioppo, J. T., Norman, G. J., & Cacioppo, S. (2016). Data quality and generalizability of Amazon Mechanical Turk (MTurk) samples. Behavior Research Methods, 48(4), 1403–1414.
Necka, E. A., Sokolowski, H. M., & Lyons, I. M. (2015). The role of self-math overlap in understanding math anxiety and the relation between math anxiety and performance. Frontiers in Psychology, 6, 1543. https://doi.org/10.3389/fpsyg.2015.01543
Ochsner, K. N., & Phelps, E. (2007). Emerging perspectives on emotion–cognition interactions. Trends in Cognitive Sciences, 11(8), 317–318. https://doi.org/10.1016/j.tics.2007.06.008
Olivier, E., Archambault, I., De Clercq, M., & Galand, B. (2019). Student self-efficacy, classroom engagement, and academic achievement: Comparing three theoretical frameworks. Journal of Youth and Adolescence, 48, 326–340. https://doi.org/10.1007/s10964-018-0952-0
Paige, L., & Mansell, W. (2013). To attend or not attend? A critical review of the factors impacting on initial appointment attendance from an approach–avoidance perspective. Journal of Mental Health, 22(1), 72–82. https://doi.org/10.3109/09638237.2012.705924
Pajares, F., & Graham, L. (1999). Self-efficacy, motivation constructs, and mathematics performance of entering middle school students. Contemporary Educational Psychology, 24(2), 124–139. https://doi.org/10.1006/ceps.1998.0991
Paolacci, G., Chandler, J., & Ipeirotis, P. G. (2010). Running experiments on Amazon Mechanical Turk. Judgment and Decision Making, 5(5), 411–419. https://doi.org/10.1017/S1930297500002205
Pekrun, R. (2006). The control-value theory of achievement emotions: Assumptions, corollaries, and implications for educational research and practice. Educational Psychology Review, 18, 315–341. https://doi.org/10.1007/s10648-006-9029-9
Pekrun, R., Goetz, T., Titz, W., & Perry, R. P. (2002). Academic emotions in students’ self-regulated learning and achievement: A program of qualitative and quantitative research. Educational Psychologist, 37(2), 91–105. https://doi.org/10.1207/S15326985EP3702_4
Perry, A. B. (2004). Decreasing math anxiety in college students. College student journal, 38(2)
Ramirez, G., Shaw, S. T., & Maloney, E. A. (2018). Math anxiety: Past research, promising interventions, and a new interpretation framework. Educational Psychologist, 53(3), 145–164. https://doi.org/10.1080/00461520.2018.1447384
Reyes, M. R., Brackett, M. A., Rivers, S. E., White, M., & Salovey, P. (2012). Classroom emotional climate, student engagement, and academic achievement. Journal of Educational Psychology, 104(3), 700–712. https://doi.org/10.1037/a0027268
Richardson, F. C., & Suinn, R. M. (1972). The mathematics anxiety rating scale: Psychometric data. Journal of Counseling Psychology, 19(6), 551. https://doi.org/10.1037/h0033456
Roos, A. L., Goetz, T., Voracek, M., Krannich, M., Bieg, M., Jarrell, A., & Pekrun, R. (2021). Test anxiety and physiological arousal: A systematic review and meta-analysis. Educational Psychology Review, 33, 579–618. https://doi.org/10.1007/s10648-020-09543-z
Scherer, K. R. (2009). The dynamic architecture of emotion: Evidence for the component process model. Cognition and Emotion, 23(7), 1307–1351. https://doi.org/10.1080/02699930902928969
Schiefele, U., & Csikszentmihalyi, M. (1995). Motivation and ability as factors in mathematics experience and achievement. Journal for Research in Mathematics Education, 26(2), 163–181.
Schunk, D. H. (1991). Self-efficacy and academic motivation. Educational Psychologist, 26(3–4), 207–231.
Spielberger, C. C., Gorsuch, R. L., & Lushene, R. (1970). State-Trait Anxiety Inventory. Consulting Psychology Press.
Suárez-Pellicioni, M., Demir-Lira, Ö. E., & Booth, J. R. (2021). Neurocognitive mechanisms explaining the role of math attitudes in predicting children’s improvement in multiplication skill. Cognitive, Affective, & Behavioral Neuroscience, 21, 917–935. https://doi.org/10.3758/s13415-021-00906-9
Tapia, M. (1996). The Attitudes toward Mathematics Instrument
Tindal, G., & Fuchs, L. (1999). A summary of research on test changes: An empirical basis for defining accommodations. University of Kentucky, Mid-South Regional Resource Center.
Tobias, S., & Weissbrod, C. (1980). Anxiety and mathematics: An update. Harvard Educational Review, 50(1), 63–70. https://doi.org/10.17763/haer.50.1.xw483257j6035084
Valiente, C., Swanson, J., & Eisenberg, N. (2012). Linking students’ emotions and academic achievement: When and why emotions matter. Child Development Perspectives, 6(2), 129–135. https://doi.org/10.1111/j.1750-8606.2011.00192.x
Wang, Z., Lukowski, S. L., Hart, S. A., Lyons, I. M., Thompson, L. A., Kovas, Y., & Petrill, S. A. (2015). Is math anxiety always bad for math learning? The role of math motivation. Psychological science, 26(12), 1863–1876. https://doi.org/10.1177/0956797615602471
Watt, H. M., Shapka, J. D., Morris, Z. A., Durik, A. M., Keating, D. P., & Eccles, J. S. Math Motivational Beliefs Scales. Developmental Psychology
Werner, L. (2001). Changing student attitudes toward math: Using dance to teach math. center for applied research and educational improvement. Retrieved from the University of Minnesota Digital Conservancy, https://hdl.handle.net/11299/143714
Wigfield, A., & Meece, J. L. (1988). Math anxiety in elementary and secondary school students. Journal of Educational Psychology, 80(2), 210. https://doi.org/10.1037/0022-0663.80
Won, H. W., Lee, J. H., & Park, M. K. (2018). Academic procrastination in mathematics learning: A mediating role of mathematics anxiety. Educational Psychology in Practice, 34(4), 377–391.
Yang, B. W., Razo, J., & Persky, A. M. (2019). Using testing as a learning tool. American journal of pharmaceutical education. https://doi.org/10.5688/ajpe7324
Zan, R., Brown, L., Evans, J., & Hannula, M. S. (2006). Affect in mathematics education: An introduction. Educational studies in mathematics. https://doi.org/10.1007/s10649-006-9028-2
Acknowledgements
We would like to thank two anonymous reviewers for helpful and highly constructive feedback.
Funding
This work was supported by research start-up funds (Georgetown University) to Ian Lyons.
Author information
Authors and Affiliations
Contributions
A.A.G.: study conceptualization, literature review, theoretical framework development, study design, data collection, analysis plan development, data analysis, writing, revision. R.J.D.: study design, analysis plan development, revision. K.H.: literature review, revision. I.M.L.: funding, theoretical framework development, study design, analysis plan development,writing, revision, supervision.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare no conflict of interests.
Ethical approval
All participants provided informed consent and all procedures were approved by the Georgetown University Institutional Review Board (Approval #2017–1293).
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendix A
Appendix A
Appendix A provides full item text and source information for all initial items in each facet. See Tables 6, 7, 8, 9, 10, 11, 12, 13.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Grabowska, A.A., Daker, R.J., Ho, K. et al. An integrated approach to understanding negative math experiences. Psychological Research 89, 84 (2025). https://doi.org/10.1007/s00426-025-02096-2
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s00426-025-02096-2