Skip to main content

# (Which) Mathematics Interest is Important for a Successful Transition to a University Study Program?

## Abstract

Students’ personal interest is hypothesized to be an important resource for learning, but only a few empirical studies have investigated the effect of interest on academic achievement and motivational outcomes of university studies. This lack of empirical studies is remarkable, because inadequate individual prerequisites are considered one reason for study drop-out. High drop-out rates in mathematics studies highlight students’ difficulties at the transition from school to university mathematics. The main aim of this contribution is to analyze the impact of cognitive learning prerequisites and mathematics interest on the outcomes in the first semester of a university mathematics program. In line with person–object theories of interest, we differentiate interest facets that reflect the changing nature of mathematics at the transition. We report results of a prediction study with 202 students enrolled in a university mathematics program. Correlation analyses show weak relations between interest and cognitive prerequisites. Regression analyses indicate that interest in proof and formal representations is a strong predictor for study satisfaction and motivation, whereas only cognitive prerequisites show an impact on achievement. Our results indicate how and to what extent the specified instruments measuring individual interests may inform study guidance before and student support during the first semester of a university mathematics program.

This is a preview of subscription content, access via your institution.

## Notes

1. The final school qualification grade is similar to the GPA and consists of grades in many courses in the last 2 years and performance in exams in the last year of schooling.

2. The sample size of each subsample (bachelor vs. teacher) provides sufficient statistical power to identify a medium effect for each predictor in the final model (α = .05, β = .80, f2 = .15).

3. The sample size provides sufficient statistical power to identify a small effect for each single predictor in the final model (α = .05, β = .80, f2 = .04).

## References

• Ainley, M., Hidi, S. & Berndorff, D. (2002). Interest, learning and the psychological processes that mediate their relationship. Journal of Educational Psychology, 94(3), 545–561.

• Assouline, M. & Meir, E. I. (1987). Meta-analysis of the relationship between congruence and well-being measures. Journal of Vocational Behaviour, 31(3), 319–332.

• Bengmark, S., Thunberg, H. & Winberg, T. M. (2017). Success-factors in transition to university mathematics. International Journal of Mathematical Education in Science and Technology, 48(7), 988–1001.

• Bergmann, C. (1992). Schulisch-berufliche Interessen als Determinanten der Studien- bzw. Berufswahl und -bewältigung [Educational-vocational interests as determinants of choice for major and career and coping with it]. In A. Krapp & M. Prenzel (Eds.), Interesse, Lernen, Leistung: Neuere Ansätze einer pädagogisch-psychologischen Interessenforschung [Interest, learning, achievement: New approaches of a pedagogical-psychological research on interest] (pp. 195–220). Münster, Germany: Aschendorff.

• Blömeke, S. (2009). Ausbildungs- und Berufserfolg im Lehramtsstudium im Vergleich zum Diplom-Studium [Vocational and career success in teacher education programs in comparison to diploma study programmes]. Zeitschrift für Erziehungswissenschaft, 12(1), 82–110.

• Blüthmann, I. (2012). Individuelle und studienbezogene Einflussfaktoren auf die Zufriedenheit von Bachelorstudierenden [Individual and study-related influences on bachelor students’ satisfaction]. Zeitschrift für Erziehungswissenschaften, 15(2), 273–303.

• Blüthmann, I., Lepa, S. & Thiel, F. (2008). Studienabbruch und -wechsel in den neuen Bachelorstudiengängen. Untersuchung und Analyse von Abbruchgründen [Drop-out and change of subject in the new bachelor study programs. Analysis of reasons for drop-out]. Zeitschrift für Erziehungswissenschaften, 11(3), 406–429.

• Brandstätter, H., Grillich, L. & Farthofer, A. (2006). Prognose des Studienabbruchs [Prediction of drop-out]. Zeitschrift für Entwicklungspsychologie und Pädagogische Psychologie, 38(3), 121–131.

• Clark, M. & Lovric, M. (2009). Understanding secondary–tertiary transition in mathematics. International Journal of Mathematical Education in Science and Technology, 40(6), 755–776.

• De Feyter, T., Caers, R., Vigna, C. & Berings, D. (2012). Unraveling the impact of the big five personality traits on academic performance: The moderating and mediating effects of self-efficacy and academic motivation. Learning and Individual Differences, 22(4), 439–448.

• Deci, E. L. & Ryan, R. M. (2002). Handbook of self-determination research. Rochester, NY: Univ. of Rochester Press.

• Di Martino, P. & Gregorio, F. (2018). The mathematical crisis in secondary–tertiary transition. International Journal of Science and Mathematics Education. https://doi.org/10.1007/s10763-018-9894-y.

• Di Martino, P. & Zan, R. (2015). The construct of attitude in mathematics education. In B. Pepin & B. Roesken-Winter (Eds.), From beliefs to dynamic affect systems in mathematics education (pp. 51–72). Cham, Switzerland: Springer.

• Dieter, M. (2012). Studienabbruch und Studienfachwechsel in der Mathematik [Drop-out and change of subject when studying mathematics] (Doctoral dissertation). Retrieved from http://duepublico.uni-duisburg-essen.de/servlets/DerivateServlet/Derivate-30759/Dieter_Miriam.pdf.

• Dinsmore, D. L. & Alexander, P. A. (2012). A critical discussion of deep and surface processing: What it means, how it is measured, the role of context, and model specification. Educational Psychology Review, 24(4), 499–567.

• Eccles, J. & Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual Review of Psychology, 53, 109–132.

• Engelbrecht, J. (2010). Adding structure to the transition process to advanced mathematical activity. International Journal of Mathematical Education in Science and Technology, 41(2), 143–154.

• Geiser, S. & Santelices, M. V. (2007). Validity of high-school grades in predicting student success beyond the freshman year: High-school record vs. standardized tests as indicators of four-year college outcomes. Center for Studies in Higher Education at the University of California, Berkeley CSHE 6.07.

• Gueudet, G. (2008). Investigating the secondary–tertiary transition. Educational Studies in Mathematics, 67(3), 237–254.

• Halverscheid, S. & Pustelnik, K. (2013). Studying math at the university: Is drop-out predictable? In A. M. Lindmeier & A. Heinze (Eds.), Proceedings of the 37th Conference of the International Group for the Psychology of Mathematics Education (Vol. 2, pp. 417–424). Kiel, Germany: PME.

• Hannula, M. S. (2011). The structure and dynamics of affect in mathematical thinking and learning. In M. Pytlak, T. Rowland & E. Swoboda (Eds.), Proceedings of the 7th Congress of the European Society for Research in Mathematics Education (pp. 34–60). Poland: University of Rzesów.

• Harackiewicz, J. M. & Hulleman, C. S. (2010). The importance of interest: The role of achievement goals and task values in promoting the development of interest. Social and Personality Psychology Compass, 4(1), 42–52.

• Häussler, P. & Hoffmann, L. (2000). A curricular frame for physics education: development, comparison with students’ interests, and impact on students’ achievement and self-concept. Science Education, 84, 689–705.

• Heinze, A., Reiss, K. & Rudolph, F. (2005). Mathematics achievement and interest in mathematics form a differential perspective. ZDM, 37(3), 212–220.

• Heublein, U., Richter, J., Schmelzer, R. & Sommer, D. (2014). Die Entwicklung der Studienabbruchquoten an den deutschen Hochschulen. [The development of drop-out rates at German universities]. Hannover, Germany: DZHW.

• Hidi, S. & Renninger, K. A. (2006). The four-phase model of interest development. Educational Psychologist, 41(2), 111–127.

• Holland, J. L. (1973). Making vocational choices: A theory of careers. Upper Saddle River, NJ: Prentice Hall.

• Hoyles, C., Newman, K. & Noss, R. (2001). Changing patterns of transition from school to university mathematics. International Journal of Mathematical Education in Science and Technology, 32(6), 829–845.

• Jordan, A., Krauss, S., Löwen, K., Blum, W., Neubrand, M., Brunner, M. & Baumert, J. (2008). Aufgaben im COACTIV-Projekt: Zeugnisse des kognitiven Aktivierungspotentials im deutschen Mathematikunterricht [Tasks in the COACTIV-project: Evidence of the potential for cognitive activation in German mathematics classes]. Journal für Mathematik-Didaktik, 29(2), 83–107.

• Kiemer, K., Gröschner, A., Pehmer, A.-K. & Seidel, T. (2015). Effects of a classroom discourse intervention on teachers’ practice and students’ motivation to learn mathematics and science. Learning and Instruction, 35, 94–103.

• KMK (2012). Bildungsstandards im Fach Mathematik für die Allgemeine Hochschulreife [Education standards in mathematics for the higher education entrance qualification]. Retrieved from http://www.kmk.org/fileadmin/Dateien/veroeffentlichungen_beschluesse/2012/2012_10_18-Bildungsstandards-Mathe-Abi.pdf.

• Köller, O., Baumert, J. & Schnabel, K. (2001). Does interest matter? The relationship between academic interest and achievement in mathematics. Journal for Research in Mathematics Education, 32(5), 448–470.

• Krapp, A. (2002). Structural and dynamic aspects of interest development: Theoretical considerations from an ontogenetic perspective. Learning and Instruction, 12(4), 383–409.

• Krapp, A. (2007). An educational-psychological conceptualisation of interest. International Journal for Educational and Vocational Guidance, 7(1), 5–21.

• Krapp, A. & Prenzel, M. (2011). Research on interest in science: Theories, methods, and findings. International Journal of Science Education, 33(1), 27–50.

• Krug, A. & Schukajlow, S. (2013). Problems with and without connection to reality and students’ task-specific interest. In A. M. Lindmeier & A. Heinze (Eds.), Proceedings of the 37th Conference of the International Group for the Psychology of Mathematics Education (Vol. 3, pp. 209–216). Kiel, Germany: PME.

• Kuncel, N. R., Hezlett, S. A. & Ones, D. S. (2001). A comprehensive meta-analysis of the predictive validity of the graduate record examinations: Implications for graduate student selection and performance. Psychological Bulletin, 127(1), 162–181.

• Lapan, R., Shaughnessy, P. & Boggs, K. (1996). Efficacy expectations and vocational interests as mediators between sex and choice of math/science college majors: A longitudinal study. Journal of Vocational Behavior, 49(3), 277–291.

• Lee, W., Lee, M.-J. & Bong, M. (2014). Testing interest and self-efficacy as predictors of academic self-regulation and achievement. Contemporary Educational Psychology, 39(2), 86–99.

• Liebendörfer, M. & Hochmuth, R. (2013). Interest in mathematics and the first steps at the university. In B. Ubuz, C. Haser & M. A. Mariotti (Eds.), Proceedings of the 8th Congress of the European Society for Research in Mathematics Education (pp. 2386–2395). Antalya, Turkey: ERME.

• Liston, M. & O’Donoghue, J. (2009). Factors influencing the transition to university service mathematics: Part I a quantitative study. Teaching Mathematics and Its Applications, 28(2), 77–87.

• Luk, H. S. (2005). The gap between secondary school and university mathematics. International Journal of Mathematical Education in Science and Technology, 36(2–3), 161–174.

• Marsh, H. W., Trautwein, U., Lüdtke, O., Köller, O. & Baumert, J. (2005). Academic self-concept, interest, grades, and standardized test scores: Reciprocal effects models of causal ordering. Child Development, 76(2), 397–416.

• Muthén, B. & Muthén, L. (1998–2015). Mplus (Version 7). LA: Muthén & Muthén.

• Nagy, G. (2006). Berufliche Interessen, kognitive und fachgebundene Kompetenzen: Ihre Bedeutung für die Studienfachwahl und die Bewährung im Studium [Vocational interests, cognitive and subject-related competences: Their significance for chosing a major and coping with the studies] (Doctoral dissertation). Retrieved from http://www.diss.fu-berlin.de/diss/receive/FUDISS_thesis_000000002714.

• Organization for Economic Co-operation and Development (2016). “PISA 2015 mathematics framework”. PISA 2015 assessment and analytical framework: Science, reading, mathematics and financial literacy. Paris, France: Author.

• Pekrun, R., Goetz, T., Titz, W. & Perry, R. P. (2002). Positive emotions in education. In E. Frydenberg (Ed.), Beyond coping. Meeting goals, visions, and challenges (pp. 149–173). Oxford, England: Oxford University Press.

• Pyzdrowski, L. J., Sun, Y., Curtis, R., Miller, D., Winn, G. & Hensel, R. A. M. (2013). Readiness and attitudes as indicators for success in college calculus. International Journal of Science and Mathematics Education, 11(3), 529–554.

• Rach, S., Heinze, A. & Ufer, S. (2014). Welche mathematischen Anforderungen erwarten Studierende im ersten Semester des Mathematikstudiums? [Which mathematical requirements do students expect in the first semester of studying mathematics?]. Journal für Mathematik-Didaktik, 35(2), 205–228.

• Rach, S., Kosiol, T. & Ufer, S. (2017). Interest and self-concept concerning two characters of mathematics: All the same, or different effects? In R. Göller, R. Biehler, R. Hochmuth & H.-G. Rück (Eds.), Didactics of Mathematics in Higher Education as a Scientific Discipline – Conference Proceedings (khdm-report 17-05, pp. 294–298). Kassel, Germany: khdm.

• Radford, L. (2015). Of love, frustration, and mathematics: A cultural-historical approach to emotions in mathematics teaching and learning. In B. Pepin & B. Roesken-Winter (Eds.), From beliefs to dynamic affect systems in mathematics education (pp. 25–49). Cham, Switzerland: Springer.

• Richardson, M., Abraham, C. & Bond, R. (2012). Psychological correlates of university students’ academic performance: A systematic review and meta-analysis. Psychological Bulletin, 138(2), 353–387.

• Robbins, S. B., Lauver, K., Le, H., Davis, D., Langley, R. & Carlstrom, A. (2004). Do psychosocial and study skill factors predict college outcomes? A meta-analysis. Psychological Bulletin, 130(2), 261–288.

• Schiefele, U. (2009). Situational and individual interest. In K. R. Wentzel & A. Wigfield (Eds.), Handbook of motivation at school. Educational psychology handbook series (pp. 197–222). New York, NY: Routledge.

• Schiefele, U. & Jacob-Ebbinghaus, L. (2006). Lernmerkmale und Lehrqualität als Bedingungsfaktoren der Studienzufriedenheit [Features of learning and teaching as conditional factors of satisfaction with the study program]. Zeitschrift für Pädagogische Psychologie, 20(3), 199–212.

• Schiefele, U., Krapp, A. & Wild, K.-P. (1995). Course-specific interest and extrinsic motivation as predictors of specific learning strategies and course grades. Paper prepared for presentation at the 6th EARLI Conference at Nijmegen.

• Schiefele, U., Krapp, A. & Winteler, A. (1992). Interest as a predictor of academic achievement: A meta-analyisis of research. In K. A. Renninger, S. Hidi & A. Krapp (Eds.), The role of interest in learning and development (pp. 183–211). Hillsdale, MI: Erlbaum.

• Schiefele, U., Moschner, B. & Husstegge, R. (2002). Skalenhandbuch SMILE-Projekt [Guide of scales from the SMILE project]. Bielefeld, Germany: Universität Bielefeld.

• Schiefele, U., Streblow, L. & Brinkmann, J. (2007). Aussteigen oder Durchhalten. Was unterscheidet Studienabbrecher von anderen Studierenden? [drop-out or persist. What differentiates students that drop-out from other students]. Zeitschrift für Entwicklungspsychologie und Pädagogische Psychologie, 39(3), 127–140.

• Schukajlow, S. & Krug, A. (2014). Are interest and enjoyment important for students’ performance? In P. Liljedahl, C. Nicol, S. Oesterle & D. Allan (Eds.), Proceedings of the 38th Conference of the International Group for the Psychology of Mathematics Education and the 36th Conference of the North American Chapter of the Psychology of Mathematics Education (Vol. 5, pp. 129–136). Vancouver: PME.

• Schunk, D. H. (1991). Self-efficacy and academic motivation. Educational Psychologist, 26(3,4), 207–231.

• Senko, C., Hama, H. & Belmonte, K. (2013). Achievement goals, study strategies, and achievement: A test of the “learning agenda” framework. Learning and Individual Differences, 24, 1–10.

• Sonnert, G. & Sadler, P. (2015). The impact of instructor and institutional factors on students’ attitudes. In D. Bressoud, V. Mesa & C. Rasmussen (Eds.), Insights and recommendations from the MAA National Study of College Calculus (pp. 17–30). Washington, DC: Mathematical Association of America Press.

• Sorge, S., Petersen, S. & Neumann, K. (2016). Die Bedeutung der Studierfähigkeit für den Studienerfolg im 1. Semester in Physik [The significance of the ability to study for the study success in the first semester in physics]. Zeitschrift für Didaktik der Naturwissenschaften, 22(1), 165–180.

• Stroet, K., Opdenakker, M. C. & Minnaert, A. (2015). What motivates early adolescents for school? A longitudinal analysis of associations between observed teaching and motivation. Contemporary Educational Psychology, 42, 129–140.

• Tall, D. (2008). The transition to formal thinking in mathematics. Mathematics Education Research Journal, 20(2), 5–24.

• Trapmann, S., Hell, B., Weigand, S. & Schuler, H. (2007). Die Validität von Schulnoten zur Vorhersage des Studienerfolgs — Eine Metaanalyse [Validity of school grades predicting study success — A meta-analysis]. Zeitschrift für Pädagogische Psychologie, 21(1), 11–27.

• Ufer, S. (2015). The role of study motives and learning activities for success in first semester mathematics studies. In K. Beswick, T. Muir & J. Wells (Eds.), Proceedings of the 39th Conference of the International Group for the Psychology of Mathematics Education (Vol. 4, pp. 265–272). Hobart, Australia: PME.

• Ufer, S., Rach, S. & Kosiol, T. (2017). Interest in mathematics= interest in mathematics? What general measures of interest reflect when the object of interest changes. ZDM The International Journal on Mathematics Education, 49(3), 397–409.

• Ulriksen, L., Møller Madsen, L. & Holmegaard, H. T. (2010). What do we know about explanations for drop-out/opt out among young people from STM higher education programmes? Studies in Science Education, 46(2), 209–244.

• Vollstedt, M., Heinze, A., Gojdka, K. & Rach, S. (2014). Framework for examining the transformation of mathematics and mathematics learning in the transition from school to university. In S. Rezat, M. Hattermann & A. Peter-Koop (Eds.), Transformation - a fundamental idea of mathematics education (pp. 29–50). New York, NY: Springer.

• Zan, R., Brown, L., Evans, J. & Hannula, M. S. (2006). Affect in mathematics education: An introduction. Educational Studies in Mathematics, 63(2), 113–121.

Download references

## Author information

Authors

### Corresponding author

Correspondence to Timo Kosiol.

## Rights and permissions

Reprints and Permissions

## About this article

### Cite this article

Kosiol, T., Rach, S. & Ufer, S. (Which) Mathematics Interest is Important for a Successful Transition to a University Study Program?. Int J of Sci and Math Educ 17, 1359–1380 (2019). https://doi.org/10.1007/s10763-018-9925-8

Download citation

• Received:

• Accepted:

• Published:

• Issue Date:

• DOI: https://doi.org/10.1007/s10763-018-9925-8

### Keywords

• Interest and learning
• Interest in mathematics
• Study satisfaction
• Study success
• Transition from school to university mathematics