- Physical Review Journals
All JournalsPhysics Magazine

Physical Review Physics Education Research

Reuse & Permissions

It is not necessary to obtain permission to reuse this article or its components as it is available under the terms of the Creative Commons Attribution 4.0 International license. This license permits unrestricted use, distribution, and reproduction in any medium, provided attribution to the author(s) and the published article's title, journal citation, and DOI are maintained. Please note that some figures may have been included with permission from other third parties. It is your responsibility to obtain the proper permission from the rights holder directly for these figures.

Export citation

Export citation

Choose format for download:

Download Citation
  • Open Access

Students’ types of interest in physics: A mixed Rasch model investigation

Sarah Zoechling*,†, Julia Woithe, and Sascha Schmeling

Martin Hopf

  • CERN, Teacher and Student Programmes Section, Geneva, Switzerland

  • *Contact author: sarah.zoechling@cern.ch
  • †Also at University of Vienna, Austrian Educational Competence Centre Physics, Vienna, Austria.
PDF

Phys. Rev. Phys. Educ. Res. 22, 020143 – Published 9 October, 2026

DOI: https://doi.org/10.1103/7t87-hcgv

Abstract

Promoting students’ interest in physics is a key goal of physics education. Describing students’ types of interest provides a great opportunity to offer practical and gender-independent recommendations to teachers for designing interesting learning activities. We investigated students’ types of interest in physics and their association with different student characteristics in a cross-cohort study involving German-speaking students aged 14–16 years (N=1219). We assessed the students’ interest in a classical and a modern physics content area, namely, mechanics and particle physics, as well as different student characteristics, such as physics-related self-concept. The collected data on students’ interest was analyzed using mixed Rasch models to unveil qualitative differences in the assessed constructs between different groups of students. The study showed that the vast majority of students (71%) can be categorized into one single type of interest in both content areas. Students of this first interest type were only interested in physics content set in certain contexts, for example, the context “one’s own body.” The second type of interest was specific to the different content areas. Students of the second interest type had relatively high physics-related self-concept and were interested in physics content, even when set in scientific or technical contexts. Whether students belong to one or the other type of interest was best described with a model comprising their degree of physics-related self-concept and their sex. Finally, we introduced the hierarchy of students’ levels of interest in physics (HOLIP) to describe the relative interestingness of different contexts for the first type of interest (i.e., the vast majority of students). We recommend using the HOLIP as a guideline for designing learning activities that promote interest in physics.

View figure in article

Physics Subject Headings (PhySH)

Article Text

References (132)

  1. National Research Council. Next Generation Science Standards: For States, by States (The National Academies Press, Washington, DC, USA, 2013).
  2. PISA 2015 Assessment and Analytical Framework: Science, Reading, Mathematic, Financial Literacy and Collaborative Problem Solving (OECD Publishing, Paris, France, 2017).
  3. P. G. de Barba, G. E. Kennedy, and M. D. Ainley, The role of students’ motivation and participation in predicting performance in a MOOC: Motivation and participation in MOOCs, J. Comput. Assist. Learn. 32, 218 (2016).
  4. A. Kauertz and H. E. Fischer, Assessing students’ level of knowledge and analysing the reasons for learning difficulties in physics by Rasch analysis, in Applications of Rasch Measurement in Science Education, edited by X. Liu and W. J. Boone (JAM Press, Maple Grove, Minnesota, USA, 2006), pp. 212–246.
  5. K. Nuutila, A. Tapola, H. Tuominen, S. Kupiainen, A. Pásztor, and M. Niemivirta, Reciprocal predictions between interest, self-efficacy, and performance during a task, Front. Educ. 5, 36 (2020).
  6. R. Voss, P. Rudolf, F. Saunders, and D. Lee, The importance of physics to the economies of Europe (2019).
  7. M. V. Bøe, E. K. Henriksen, T. Lyons, and C. Schreiner, Participation in science and technology: Young people’s achievement-related choices in late-modern societies, Stud. Sci. Educ. 47, 37 (2011).
  8. Encouraging Student Interest in Science and Technology Studies (OECD Publishing, Paris, France, 2008).
  9. M. Ainley and J. Ainley, A cultural perspective on the structure of student interest in science, Int. J. Sci. Educ. 33, 51 (2011).
  10. A. V. Maltese and R. H. Tai, Pipeline persistence: Examining the association of educational experiences with earned degrees in stem among US students, Sci. Educ. 95, 877 (2011).
  11. W. Tyson, R. Lee, K. M. Borman, and M. A. Hanson, Science, technology, engineering, and mathematics (STEM) pathways: High school science and math coursework and postsecondary degree attainment, J. Educ. for Stud. Placed at Risk 12, 243 (2007).
  12. J. Osborne and S. Collins, Pupils’ views of the role and value of the science curriculum: A focus-group study, Int. J. Sci. Educ. 23, 441 (2001).
  13. R. Bybee and B. McCrae, Scientific literacy and student attitudes: Perspectives from PISA 2006 science, Int. J. Sci. Educ. 33, 7 (2011).
  14. Assessing Scientific, Reading and Mathematical Literacy: A Framework for PISA 2006 (OECD Publishing, Paris, France, 2006).
  15. M. Galton, Moving to secondary school: Initial encounters and their effects, Perspect. Educ. 2, 5 (2009).
  16. J. Osborne, S. Simon, and S. Collins, Attitudes towards science: A review of the literature and its implications, Int. J. Sci. Educ. 25, 1049 (2003).
  17. L. Hoffmann, P. Häußler, and M. Lehrke, Die IPN-Interessenstudie Physik (IPN Kiel, Kiel, Germany, 1998).
  18. D. Cheung, The key factors affecting students’ individual interest in school science lessons, Int. J. Sci. Educ. 40, 1 (2018).
  19. P. Häussler, L. Hoffman, R. Langeheine, J. Rost, and K. Sievers, A typology of students’ interest in physics and the distribution of gender and age within each type, Int. J. Sci. Educ. 20, 223 (1998).
  20. Z. Y. Kalender, E. Marshman, C. D. Schunn, T. J. Nokes-Malach, and C. Singh, Gendered patterns in the construction of physics identity from motivational factors, Phys. Rev. Phys. Educ. Res. 15 020119 (2019).
  21. J. Lavonen, B. Ávalos, K. Upadyaya, S. Araneda, K. Juuti, P. Cumsille, J. Inkinen, and K. Salmela-Aro, Upper secondary students’ situational interest in physics learning in Finland and Chile, Int. J. Sci. Educ. 43, 2577 (2021).
  22. PISA 2015 Results (Volume I): Excellence and Equity in Education (OECD Publishing, Paris, France, 2016).
  23. S. Sjøberg and C. Schreiner, Results and perspectives from the rose project: Attitudinal aspects of young people and science in a comparative perspective, in Science Education Research and Practice in Europe. Cultural Perspectives in Science Education (Sense Publishers, Rotterdam, The Netherlands, 2012), Vol. 5, pp. 203–236.
  24. P. Häußler, Measuring students’ interest in physics - design and results of a cross-sectional study in the federal republic of Germany, Int. J. Sci. Educ. 9, 79 (1987).
  25. P. Häußler, L. Hoffman, R. Langeheine, J. Rost, and K. Sievers, Qualitative unterschiede im interesse an physik und konsequenzen für den unterricht [qualitative differences in interest in physics and consequences for teaching], Zeitschrift für Didaktik der Naturwissenschaften 2, 57 (1996).
  26. R. Langeheine, P. Häußler, L. Hoffmann, J. Rost, and K. Sievers, Strukturelle veränderungen des physikinteresses von der 7. zur 9. jahrgangsstufe, Zeitschrift für Entwicklungspsychologie und Pädagogische Psychologie 33, 20 (2001).
  27. J. Rost, K. Sievers, P. Häußler, L. Hoffmann, and R. Langeheine, Struktur und veränderung des interesses an physik bei schülern der 6. bis 10. klassenstufe [structure and change of interest in physics among grade 6 to grade 10 students], Zeitschrift für Entwicklungspsychologie und Pädagogische Psychologie 31, 18 (1999).
  28. K. Sievers. Struktur und Veränderung von Physikinteressen bei Jugendlichen, Ph.D. thesis, Universität Kiel, 1999.
  29. B. Drechsel, C. Carstensen, and M. Prenzel, The role of content and context in PISA interest scales: A study of the embedded interest items in the PISA 2006 science assessment, Int. J. Sci. Educ. 33, 73 (2011).
  30. O. Levrini, A. De Ambrosis, S. Hemmer, A. Laherto, M. Malgieri, O. Pantano, and G. Tasquier, Understanding first-year students’ curiosity and interest about physics—lessons learned from the hope project, Eur. J. Phys. 38, 025701 (2017).
  31. PISA 2006 Science Competencies for Tomorrow’s World. Volume 1. Analysis (OECD Publishing, Paris, France, 2007).
  32. S. Sjøberg and C. Schreiner, The rose project: An overview and key findings (2010).
  33. M. Ing and K. Nylund-Gibson, The importance of early attitudes toward mathematics and science, Teach. Coll. Rec. 119, 1 (2017).
  34. S. Zoechling, M. Hopf, J. Woithe, and S. Schmeling, Students’ interest in particle physics: Conceptualisation, instrument development, and evaluation using Rasch theory and analysis, Int. J. Sci. Educ. 44, 2353 (2022).
  35. A. Krapp, Entwicklung und förderung von interessen im unterricht, Psychologie in Erziehung und Unterricht 44, 185 (1998). accessed on 2025/07/04,
  36. A. Krapp and M. Prenzel, Interesse, Lernen, Leistung: Neuere Ansätze der Pädagogisch-Psychologischen Interessenforschung (Aschendorff, Münster, Germany, 1992).
  37. A. Krapp and M. Prenzel, Research on interest in science: Theories, methods, and findings, Int. J. Sci. Educ. 33, 27 (2011).
  38. S. Swarat, A. Ortony, and W. Revelle, Activity matters: Understanding student interest in school science, J. Res. Sci. Teach. 49, 515 (2012).
  39. P. O. Dierks, T. N. Höffler, and I. Parchmann, Profiling interest of students in science: Learning in school and beyond, Res. Sci. Technol. Educ. 32, 97 (2014).
  40. P. O. Dierks, T. N. Höffler, J. S. Blankenburg, H. Peters, and I. Parchmann, Interest in science: A RIASEC-based analysis of students’ interests, Int. J. Sci. Educ. 38, 238 (2016).
  41. A. Krapp, Structural and dynamic aspects of interest development: Theoretical considerations from an ontogenetic perspective, Learn. Instr. 12, 383 (2002).
  42. U. Schiefele, Situational and individual interest, in Handbook of Motivation at School, edited by K. R. Wentzel and A. Wigfield (Routledge, New York, 2009), pp. 197–222.
  43. S. Hidi and K. A. Renninger, The four-phase model of interest development, Educ. Psychol. 41, 111 (2006).
  44. M. Mitchell, Situational interest: Its multifaceted structure in the secondary school mathematics classroom, J. Educ. Psychol. 85, 424 (1993).
  45. P. Potvin and A. Hasni, Interest, motivation and attitude towards science and technology at k-12 levels: A systematic review of 12 years of educational research, Stud. Sci. Educ. 50, 85 (2014).
  46. E. L. Deci and R. M. Ryan, Die selbstbestimmungstheorie der motivation und ihre bedeutung für die pädagogik, Zeitschrift für Pädagogik 39, 223 (1993).
  47. E. L. Deci and R. M. Ryan, The “what” and “why” of goal pursuits: Human needs and the self-determination of behavior, Psychol. Inquiry 11, 227 (2000).
  48. H. E. Fischer and M. Horstendahl, Motivation and learning physics, Res. Sci. Educ. 27, 411 (1997).
  49. R. M. Ryan and E. L. Deci, Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being, Am. Psychol. 55, 68 (2000).
  50. A. Krapp, An educational-psychological theory of interest and its relation to SDT, in Handbook of Self-Determination Research, edited by E. L. Deci and R. M. Ryan (University of Rochester Press, Rochester, NY, 2002), pp. 405–427.
  51. I. Parchmann and J. Kuhn, Lernen im kontext, in Theorien in der Naturwissenschaftsdidaktischen Forschung, edited by D. Krüger, I. Parchmann, and H. Schecker (Springer Spektrum, Berlin, Germany, 2018), pp. 193–207.
  52. D. Nawrath, Kontextorientierung: Rekonstruktion Einer Fachdidaktischen Konzeption für Den Physikunterricht, Beiträge zur Didaktischen Rekonstruktion, Vol. 29 (Didaktisches Zentrum, Oldenburg, Germany, 2010), accessed on 2025/07/04.
  53. J. P. Mestre, Probing adults’ conceptual understanding and transfer of learning via problem posing, J. Appl. Dev. Psychol. 23, 9 (2002).
  54. P. Häußler, W. Bünder, R. Duit, W. Gräber, and J. Mayer, Naturwissenschaftsdidaktische Forschung: Perspektiven für Die Unterrichtspraxis (Institut für die Pädagogik der Naturwissenschaften, 1998).
  55. S. Fechner, Effects of Context Oriented Learning on Student Interest and Achievement in Chemistry Education (Logos, Berlin, Germany, 2009).
  56. S. Fechner, H. Van Vorst, E. Kölbach, and E. Sumfleth, It’s the situation that matters: Affective involvement in context-oriented learning tasks, in Affective Dimensions in Chemistry Education (Springer, New York, 2015), pp. 159–176.
  57. E. Kölbach, Kontexteinflüsse Beim Lernen Mit Lösungsbeispielen (Logos, Berlin, 2011).
  58. J. S. Blankenburg, T. N. Höffler, H. Peters, and I. Parchmann, The effectiveness of a project day to introduce sixth grade students to science competitions, Res. Sci. Technol. Educ. 34, 342 (2016).
  59. D. Elster, Student interests—the German and Austrian rose survey, J. Biol. Educ. 42, 5 (2007).
  60. C. Schreiner and S. Sjøberg, Sowing the seeds of rose: Background, rationale, questionnaire development and data collection for rose (the relevance of science education): A comparative study of students’ views of science and science education (2004), http://urn.nb.no/URN: NBN:no-14449.
  61. N. Holstermann and S. Bögeholz, Interesse von jungen und mädchen an naturwissenschaftlichen themen am ende der sekundarstufe i, Zeitschrift für Didaktik der Naturwissenschaften 13, 71 (2007).
  62. H. van Vorst, Kontextmerkmale und ihr Einfluss auf das Schülerinteresse im Fach Chemie [Context Characteristics and their Influences on Students’ Interests in Chemistry Education] (Logos, Berlin, 2013).
  63. Muckenfuß. Lernen im Sinnstiftenden Kontext: Entwurf Einer Zeitgemäßen Didaktik Des Physikunterrichts [Learning in Meaningful Contexts: Proposal of a Modern Physics Education] (Cornelsen, Berlin, 1995).
  64. A. Lindqvist, M. G. Sendén, and E. A. Renström, What is gender, anyway: A review of the options for operationalising gender, Psychol. Sexuality 12, 332 (2021).
  65. C. West and D. H. Zimmerman, Doing gender, Gender & Society 1, 125 (1987).
  66. Student questionnaire for PISA 2006 (2005).
  67. OECD, Pisa 2022 student questionnaire (2022). accessed: 2025-09-07.
  68. L. Archer, J. DeWitt, J. Osborne, J. Dillon, B. Willis, and B. Wong, ‘Not girly, not sexy, not glamorous’: Primary school girls’ and parents’ constructions of science aspirations, Pedagogy, Cult. Soc. 21, 171 (2013).
  69. M. Prenzel, K. Schütte, and O. Walter, Interesse an den naturwissenschaften [interest in natural sciences], in Pisa 2006. Die Ergebnisse der Internationalen Vergleichsstudie [PISA 2006. The Results of the Third International Comparison Study], edited by PISA Konsortium Deutschland (Waxmann, Münster, Germany, 2007), pp. 107–124.
  70. T. Stern, P. Jelemenská, and F. Radits, Das interesse an naturwissenschaften: Eine analyse der österreichischen PISA-2006-ergebnisse, PISA 2006: Österreichischer Expertenbericht Zum Naturwissenschafts-Schwerpunkt, 2009.
  71. E. W. Jenkins and N. W. Nelson, Important but not for me: Students’ attitudes towards secondary school science in England, Res. Sci. Technol. Educ. 23, 41 (2005).
  72. R. J. Shavelson, J. J. Hubner, and G. C. Stanton, Self-concept: Validation of construct interpretations, Rev. Educ. Res. 46, 407 (1976).
  73. M. Bong and R. E. Clark, Comparison between self-concept and self-efficacy in academic motivation research, Educ. Psychol. 34, 139 (1999).
  74. H. W. Marsh, The structure of academic self-concept: The Marsh/Shavelson model, J. Educ. Psychol. 82, 623 (1990).
  75. Z. Hazari, G. Sonnert, P. M. Sadler, and M.-C. Shanahan, Connecting high school physics experiences, outcome expectations, physics identity, and physics career choice: A gender study, J. Res. Sci. Teach. 47, 978 (2010).
  76. D. Oyserman, K. Elmore, and G. Smith, Self, self-concept, and identity, in The Handbook of Self and Identity, edited by J. Tangney and M. Leary (Guilford Press, New York, NY, USA, 2012) 2nd ed., pp. 69–104.
  77. C. H. Cooley, Human Nature and the Social Order (Scribner’s Sons, New York, NY, USA, 1902).
  78. Z. Y. Kalender, E. Marshman, C. D. Schunn, T. J. Nokes-Malach, and C. Singh, Why female science, technology, engineering, and mathematics majors do not identify with physics: They do not think others see them that way, Phys. Rev. Phys. Educ. Res. 15, 020148 (2019).
  79. Z. Y. Kalender, E. Marshman, C. D. Schunn, T. J. Nokes-Malach, and C. Singh, Damage caused by women’s lower self-efficacy on physics learning, Phys. Rev. Phys. Educ. Res. 16, 010118 (2020).
  80. G. Buccheri, N. A. Gürber, and C. Brühwiler, The impact of gender on interest in science topics and the choice of scientific and technical vocations, Int. J. Sci. Educ. 33, 159 (2011).
  81. J. DeWitt and L. Archer, Who aspires to a science career? a comparison of survey responses from primary and secondary school students, Int. J. Sci. Educ. 37, 2170 (2015).
  82. A. Godwin, G. Potvin, Z. Hazari, and R. Lock, Identity, critical agency, and engineering: An affective model for predicting engineering as a career choice, J. Eng. Educ. 105, 312 (2016).
  83. P. R. Aschbacher, E. Li, and E. J. Roth, Is science me? high school students’ identities, participation and aspirations in science, engineering, and medicine, J. Res. Sci. Teach. 47, 564 (2010).
  84. H. B. Carlone and A. Johnson, Understanding the science experiences of successful women of color: Science identity as an analytic lens, J. Res. Sci. Teach. 44, 1187 (2007).
  85. A. L. Zeldin and F. Pajares, Against the odds: Self-efficacy beliefs of women in mathematical, scientific, and technological careers, Am. Educ. Res. J. 37, 215 (2000).
  86. J. Radišić, P. Selleri, F. Carugati, and A. Baucal, Are students in Italy really disinterested in science? a person-centred approach using the PISA 2015 data, Sci. Educ. 105, 438 (2021).
  87. D. J. Leiner, Sosci survey (2024). computer software.
  88. J. Mang, N. Ustjanzew, I. Leßke, A. Schiepe-Tiska, and K. Reiss, PISA 2015 skalenhandbuch. Dokumentation der erhebungsinstrumente, Waxmann, 2019.
  89. X. Liu, Using and Developing Measurement Instruments in Science Education: A Rasch Modeling Approach (Information Age Publishing, Charlotte, NC, USA, 2010).

  90. Given that the IPN study included an introductory text, we wanted to investigate its potential influence on students’ interest. While a detailed discussion of the introductory text’s influence is beyond the scope of this paper, we can report that quantitatively there was no statistically significant difference in students’ interest associated with the use of different versions of the introductory text. However, the results provide some evidence for qualitative differences in interest, with some items being more or less interesting depending on the presented introductory text. For further details, readers are referred to the first author’s doctoral thesis (see Section 6.3.1 in Ref. [91]).

  91. S. Zoechling, Students’ Types of Interest in Physics Revisited, Ph.D. thesis, University of Vienna, 2023.
  92. A. Frey, P. Taskinen, and K. Schütte, PISA 2006 skalenhandbuch. Dokumentation der erhebungsinstrumente, Waxmann, 2009.
  93. S. Zoechling, M. Hopf, J. Woithe, and S. Schmeling, Study on the students’ types of interest in physics (oa edition) (2023), 10.11587/PHPAUN.
  94. OECD, PISA 2006 technical report, Tech rep., OECD Publishing, Paris, 2009.
  95. B. Wright and M. Stone, Best Test Design (MESA Press, Chicago, IL, USA, 1979).
  96. J. Rost and M. von Davier, Mixture distribution Rasch models, in Rasch Models: Foundations, Recent Developments, and Applications, edited by G. H. Fischer and I. W. Molenaar (Springer, New York, NY, 1995), pp. 257–268.
  97. P. F. Lazarsfeld and N. W. Henry, Latent Structure Analysis (Houghton Mifflin Co., Boston, 1968).
  98. M. von Davier, WINMIRA: A Program System for Analyses with the Rasch Model, with the Latent Class Analysis and with the Mixed-Rasch Model (IPN, Kiel, Germany, 1994).
  99. M. von Davier, Winmira program description and recent enhancements, Methods Psychol. Res. Online 2, 25 (1997).
  100. D. Preinerstorfer and A. K. Formann, Measure recovery and model selection in mixed Rasch models, Br. J. Math. Stat. Psychol. 65, 251 (2012).
  101. M. Quandt, Using the mixed Rasch model in the comparative analysis of attitudes, in Cross-Cultural Analysis: Methods and Applications, edited by E. Davidov, P. Schmidt, and J. Billiet (Routledge, New York, NY, USA, 2012), pp. 433–460.
  102. S. Sen, Spurious latent class problem in the mixed Rasch model: A comparison of three maximum likelihood estimation methods under different ability distributions, Int. J. Test. 18, 71 (2018).
  103. R. E. Kass and A. E. Raftery, Bayes factors, J. Am. Stat. Assoc. 90, 773 (1995).
  104. J. Rost and M. von Davier, A conditional item-fit index for Rasch models, Appl. Psychol. Meas. 18, 171 (1994).
  105. M. von Davier, WINMIRA 2001 user manual (2001).
  106. W. J. Boone, J. R. Staver, and M. S. Yale, Rasch Analysis in the Human Sciences (Springer, New York, 2014).
  107. P. C. Mahalanobis, On the generalised distance in statistics, in Proceedings of the National Institute of Science of India (1936), pp. 49–55.
  108. B. G. Tabachnick and L. S. Fidell, Using Multivariate Statistics, 6th ed. (Pearson, Boston, MA, USA, 2013).
  109. L. Niu, A review of the application of logistic regression in educational research: Common issues, implications, and suggestions, Educ. Rev. 72, 41 (2020).
  110. A. Field, Discovering Statistics Using SPSS: And Sex, and Drugs and Rock’n’roll (Sage, Los Angeles, CA, 2009).
  111. J. M. Linacre, A user’s guide to WINSTEPS, MINISTEP, Rasch model computer programs. Program manual 5.1.7 (2021).
  112. D. Muijs, Doing Quantitative Research in Education with SPSS (Sage, London, United Kingdom, 2004).
  113. E. Wetzel, J. R. Böhnke, C. H. Carstensen, M. Ziegler, and F. Ostendorf, Do individual response styles matter? assessing differential item functioning for men and women in the NEO-PI-R, J. Individ. Differ. 34, 69 (2013).
  114. D. Andrich, A rating formulation for ordered response categories, Psychometrika 43, 561 (1978).
  115. D. Andrich, The Rasch model explained, in Applied Rasch Measurement: A Book of Exemplars, edited by S. Alagumalai, D. D. Curtis, and N. Hungi (Springer-Kluwer, Berlin, Germany, 2005), pp. 308–328.
  116. R. J. Adams, M. L. Wu, and M. Wilson, The Rasch rating model and the disordered threshold controversy, Educ. Psychol. Meas. 72, 547 (2012).
  117. J. M. Linacre, Step disordering and thurstone thresholds, Rasch Meas. Trans. 5, 171 (1991).
  118. G. N. Masters, A Rasch model for partial credit scoring, Psychometrika 47, 149 (1982).
  119. R. V. Olsen and S. Lie, Profiles of students’ interest in science issues around the world: Analysis of data from PISA 2006, Int. J. Sci. Educ. 33, 97 (2011).
  120. S. Habig, J. S. Blankenburg, H. van Vorst, S. Fechner, I. Parchmann, and E. Sumfleth, Context characteristics and their effects on students’ situational interest in chemistry, Int. J. Sci. Educ. 40, 1154 (2018).
  121. M. Rösler, N. Wellnitz, and J. Mayer, Motivationale einflüsse auf schriftliche testleistungen im fach biologie [motivational influences on achievements in written tests in biology], Erkenntnisweg Biologiedidaktik 13, 179 (2014).
  122. M. Rösler, N. Wellnitz, and J. Mayer, The role of interesting and motivating contexts in the assessment of content knowledge and decision-making, Challenges Biol. Educ. Res. 135 (2018).
  123. Y. Van Vaerenbergh and T. D. Thomas, Response styles in survey research: A literature review of antecedents, consequences, and remedies, Int. J. Public Opin. Res. 25, 195 (2013).
  124. B. Weijters, E. Cabooter, and N. Schillewaert, The effect of rating scale format on response styles: The number of response categories and response category labels, Int. J. Res. Mark. 27, 236 (2010).
  125. K. J. Dockendorff and C. Geist, Beyond the binary: Gender image and experiences of marginalization on campus, J. Crit. Scholarship on Higher Educ. Stud. Aff. 6 (2022), https://ecommons.luc.edu/jcshesa/vol6/iss1/3 (accessed on 8 March 2023).
  126. C. M. Lechner, N. Bhaktha, K. Groskurth, and M. Bluemke, Why ability point estimates can be pointless: A primer on using skill measures from large-scale assessments in secondary analyses, Meas. Instrum. Soc. Sci. 3, 2 (2021).
  127. K. B. Christensen, From Rasch scores to regression, J. Appl. Meas. 7, 184 (2006).
  128. L. Höft and S. Bernholt, Longitudinal couplings between interest and conceptual understanding in secondary school chemistry: An activity-based perspective, Int. J. Sci. Educ. 41, 607 (2019).
  129. A. L. Zeldin, S. L. Britner, and F. Pajares, A comparative study of the self-efficacy beliefs of successful men and women in mathematics, science, and technology careers, J. Res. Sci. Teach. 45, 1036 (2008).
  130. U. Zoller and F. G. Watson, Teacher training for the “second generation” of science curricula: The curriculum-proof teacher, Sci. Educ. 58, 93 (1974).
  131. G. S. Aikenhead, Science in Social Issues: Implications for Teaching (Publications Office, Science Council of Canada, Ottawa, Ontario, Canada, 1980).
  132. K.-S. Tang, G. Cooper, and W. Nielsen, Philosophical, legal, ethical, and practical considerations in the emerging use of generative AI in academic journals: Guidelines for research in science education (RISE), Res. Sci. Educ. 1, 797 (2024).

Outline

Information

Phys. Rev. Phys. Educ. Res. 22, 020143– Published 9 October, 2026
  • Received 27 November 2025
  • Accepted 1 July 2026
Crossmark - Check for updates button
Creative Commons Logo

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.

Published by the American Physical Society

Sign In to Your Journals Account

Filter

Filter

Article Lookup

Enter a citation