- Open Access
Metacognition and epistemic cognition in physics are related to physics identity through the mediation of physics self-efficacy
Phys. Rev. Phys. Educ. Res. 20, 010130 – Published 26 April, 2024
DOI: https://doi.org/10.1103/PhysRevPhysEducRes.20.010130
Abstract
This study aimed (i) to investigate how epistemic cognition in physics and metacognition, together with three dimensions of physics identity framework—recognition, physics self-efficacy, and interest—predicted the overall physics identity of Turkish high school students and also (ii) to investigate gender differences in study constructs. A sample of 1197 high school students participated in the study. The collected data were analyzed using structural equation modeling. The analysis results indicated that the model fitted the data well, further motivating intervention studies to test the causal relations proposed in the model. The results showed that recognition and interest directly predicted physics identity and mediated the relation of physics self-efficacy to it. Metacognition and epistemic cognition predicted physics identity through physics self-efficacy. The study also observed significant direct and indirect relations among metacognition, epistemic cognition, self-efficacy, recognition, and interest. Furthermore, gender differences were found in the current study. While no gender difference was observed in metacognition and epistemic cognition in physics, male students scored higher than female students in physics identity, self-efficacy, recognition, and interest. However, the mediation analysis further indicated that gender differences in physics self-efficacy might explain gender differences in physics identity, recognition, and interest. The results of this study could motivate future interventions testing the effect of metacognitive and epistemic activities on both physics self-efficacy and identity, and also, the interventions testing whether practices that reduce the gender gap in physics self-efficacy will help eliminate the gender gap in physics identity, recognition, and interest.
Physics Subject Headings (PhySH)
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References (150)
- 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).
- H. Cheng, G. Potvin, R. Khatri, L. H. Kramer, R. M. Lock, and Z. Hazari, Physics Education Research Conference on Examining physics identity development through two high school interventions, in Proceedings of the 2018 Physics Education Research Conference, Washington, DC (AIP, New York, 2018).
- A. C. Barton and E. Tan, We be burnin’! Agency, identity, and science learning, J. Learn. Sci. 19, 187 (2010).
- PISA 2024 Strategic Direction, and Vision for Science (OECD Publishing, Paris, 2020).
- P. J. Mulvey and S. Nicholson, Physics Bachelor’s Degrees: 2018. Results from the 2018 Survey of Enrollments and Degrees (AIP Statistical Research Center, College Park, MD, 2020).
- Physics Students in UK Universities (n.d.). Retrieved January 1, 2023, from https://www.iop.org/sites/default/files/2021-12/Physics-Students-in-UK-Universities-HESA-Data-Brief.pdf.
- The STEM need in Turkey for 2023, Turkish Industry & Business Association, Retrieved January 1, 2023, from https://tusiad.org/en/reports/item/9754-the-stem-need-in-turkey-for-2023.
- R. M. Lock, Z. Hazari, and G. Potvin, Impact of out-of-class science and engineering activities on physics identity and career intentions, Phys. Rev. Phys. Educ. Res. 15, 020137 (2019).
- Ö. Özkurt and I. Yakın, 2013–2019 yılları arasında Türkiye’deki üniversitelerin STEM alanlarında kayıtlı öğrenci sayılarının cinsiyet bağlamında karşılaştırılması, J. Soc. Sci. Hum 7, 68 (2020).
- Talent 2030 Dashboard 2018, National Centre for Universities and Business, 2018, http://www.ncub.co.uk/reports/talent-2030-dashboard-2018.
- J. P. Gee, Identity as an analytic lens for research in education, Rev. Res. Educ. 25, 99 (2000).
- 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).
- R. M. Lock, Z. Hazari, and G. Potvin, Physics career intentions: The effect of physics identity, math identity, and gender, AIP Conf. Proc. 1513, 262 (2013).
- A. Bandura, Self-Efficacy: The Exercise of Control (Freeman, New York, 1997).
- J. D. Cribbs, Z. Hazari, G. Sonnert, and P. M. Sadler, Establishing an explanatory model for mathematics identity, Child Dev. 86, 1048 (2015).
- 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).
- R. Dou and H. Cian, Constructing STEM identity: An expanded structural model for STEM identity research, J. Res. Sci. Teach. 59, 458 (2022).
- D. Verdín, The power of interest: Minoritized women’s interest in engineering fosters persistence beliefs beyond belongingness and engineering identity, Int. J. STEM Educ. 8, 33 (2021).
- A. L. Brown, J. D. Bransford, R. Ferrara, and J. Campione, Learning, remembering and understanding, Handbook of Child Psychology: Vol. 3. Cognitive Development, 4th ed., edited by J. H. Flavell and E. M. Markman (Wiley, New York, 1983), pp. 77–166.
- A. L. Brown, Metacognition, executive control, self-regulation, and other more mysterious mechanisms, in Metacognition, Motivation, and Understanding, edited by F. E. Weinert and R. Kluwe (Lawrence Erlbaum Associates, Hillsdale, NJ, 1987).
- G. Schraw and R. S. Dennison, Assessing metacognitive awareness, Contemp. Educ. Psychol. 19, 460 (1994).
- B. K. Hofer and P. R. Pintrich, The development of epistemological theories: Beliefs about knowledge and knowing and their relation to learning, Rev. Educ. Res. 67, 88 (1997).
- A. Elby, Defining personal epistemology: A response to Hofer & Pintrich (1997) and Sandoval (2005), J. Learn. Sci. 18, 138 (2009).
- I. A. Halloun and D. Hestenes, Views about Sciences Survey: VASS, in Proceedings of the Sociology Paper presented at NARST, St. Louis, Missouri (1996), pp. 266–267.
- D. Hammer, Epistemological beliefs in introductory physics, Cognit. Instr. 12, 151 (1994).
- W. K. Adams, K. K. Perkins, N. S. Podolefsky, M. Dubson, N. D. Finkelstein, and C. E. Wieman, New instrument for measuring student beliefs about physics, and learning physics: The Colorado Learning Attitudes about Science Survey, Phys. Rev. ST Phys. Educ. Res. 2, 010101 (2006).
- K. Özmen and Ö. F. Özdemir, Conceptualisation, and development of the physics related personal epistemology questionnaire (PPEQ), Int. J. Sci. Educ. 41, 1207 (2019).
- M. Welsh and S. Schmitt-Wilson, Executive function, identity, and career decision-making in college students, SAGE Open 3, 2158244013505755 (2013).
- J. E. Marcia, Identity in adolescence, in Handbook of Adolescent Psychology (Wiley and Sons, New York, 1980), Vol. 9, p. 159.
- J. H. Flavell, Metacognition and cognitive monitoring: A new area of cognitive developmental inquiry, Am. Psychol. 34, 906 (1979).
- P. R. Pintrich, The role of metacognitive knowledge in learning, teaching, and assessing, Theory Pract. 41, 219 (2002).
- P. Irving and E. Sayre, Physics identity development: A snapshot of the stages of development of upper-level physics students, J. Scholarship Teach. Learn. 13, 68 (2013).
- S. Basu and S. Dixit, Role of metacognition in explaining decision-making styles: A study of knowledge about cognition and regulation of cognition, Pers. Individ. Diff. 185, 111318 (2022).
- K. Batha and M. Carroll, Metacognitive training aids decision making, Aust. J. Psychol. 59, 64 (2007).
- R. Griffith, M. Bauml, and S. Quebec-Fuentes, Promoting metacognitive decision-making in teacher education, Theory Pract. 55, 242 (2016).
- M. D. Berzonsky and K. Luyckx, Identity styles, self-reflective cognition, and identity processes: A study of adaptive and maladaptive dimensions of self-analysis, Identity 8, 205 (2008).
- K. Luyckx, B. Soenens, M. D. Berzonsky, I. Smits, L. Goossens, and M. Vansteenkiste, Information-oriented identity processing, identity consolidation, and well-being: The moderating role of autonomy, self-reflection, and self-rumination. Pers. Individ. Diff. 43, 1099 (2007).
- A. M. Grant, Rethinking psychological mindedness: Metacognition, self-reflection, and insight. Behav. Change 18, 8 (2001).
- A. Graham and R. Phelps, Being a teacher: Developing teacher identity and enhancing practice through metacognitive and reflective learning processes. Aust. J. Teach. Educ. 27, 11 (2003).
- L. McAlpine, C. Weston, J. Beauchamp, C. Wiseman, and C. Beauchamp, Building a metacognitive model of reflection. High. Educ. 37, 105 (1999).
- R. Yuan and P. Mak, Reflective learning and identity construction in practice, discourse and activity: Experiences of preservice language teachers in Hong Kong, Teach. Teach. Educ. 74, 205 (2018).
- E. W. Close, J. Conn, and H. G. Close, Becoming physics people: Development of integrated physics identity through the Learning Assistant experience, Phys. Rev. Phys. Educ. Res. 12, 010109 (2016).
- H. Huvard, R. M. Talbot, H. Mason, A. N. Thompson, M. Ferrara, and B. Wee, Science identity and metacognitive development in undergraduate mentor-teachers. Int. J. STEM Educ. 7, 31 (2020).
- D. Cañabate, T. Serra, R. Bubnys, and J. Colomer, Preservice teachers’ reflections on cooperative learning: Instructional approaches and identity construction. Sustainability 11, 5970 (2019).
- C. Beauchamp and L. Thomas, Understanding teacher identity: An overview of issues in the literature and implications for teacher education, Cambridge J. Educ. 39, 175 (2009).
- E. Wenger, Communities of Practice: Learning, Meaning, and Identity (Cambridge University Press, Cambridge, England, 1999).
- O. Levrini, M. Levin, and P. Fantini, Fostering appropriation through designing for multiple access points to a multidimensional understanding of physics, Phys. Rev. Phys. Educ. Res. 16, 020154 (2020).
- K. Silseth and H. C. Arnseth, Learning and identity construction across sites: A dialogical approach to analysing the construction of learning selves, Cult. Psychol. 17, 65 (2011).
- M. Varelas, D. B. Martin, and J. M. Kane, Content learning and identity construction: A framework to strengthen African American students’ mathematics and science learning in urban elementary school, Hum. Dev. 55, 319 (2013).
- I. Adler, M. Zion, and Z. R. Mevarech, The effect of explicit environmentally oriented metacognitive guidance and peer collaboration on students’ expressions of environmental literacy, J. Res. Sci. Teach. 53, 620 (2016).
- P. Georghiades, Making pupils’ conceptions of electricity more durable by means of situated metacognition, Int. J. Sci. Educ. 26, 85 (2004).
- S. Yerdelen-Damar and A. Eryılmaz, Promoting conceptual understanding with explicit epistemic intervention in metacognitive instruction: Interaction between the treatment and epistemic cognition, Res. Sci. Educ. 51, 547 (2021).
- N. Yuruk, M. E. Beeth, and C. Andersen, Analyzing the effect of metaconceptual teaching practices on students’ understanding of force and motion concepts, Res. Sci. Educ. 39, 449 (2009).
- L. D. Bendixen and D. C. Rule, An integrative approach to personal epistemology: A guiding model, Educ. Psychol. 39, 69 (2004).
- L. D. Bendixen and F. C. Feucht, Personal epistemology in the classroom: What does research and theory tell us and where do we need to go next? in Personal Epistemology in the Classroom: Theory, Research, and Implications for Practice, edited by L. D. Bendixen and F. C. Feucht (Cambridge University Press, Cambridge, England, 2010).
- A. Elby and D. Hammer, Epistemological resources and framing: A cognitive framework for helping teachers interpret and respond to their students’ epistemologies, in Personal Epistemology in the Classroom: Theory, Research, and Implications for Practice, edited by L. D. Bendixen and F. C. Feucht (Cambridge University Press, Cambridge, England, 2010), pp. 409–434.
- K. R. Muis, The role of epistemic beliefs in self-regulated learning, Educ. Psychol. 42, 173 (2007).
- D. C. Rule and L. D. Bendixen, The integrative model of personal epistemology development: Theoretical underpinnings and implications for education, in Personal Epistemology in the Classroom: Theory, Research, and Implications for Practice, edited by L. D. Bendixen and F. C. Feucht (Cambridge University Press, Cambridge, England, 2010), pp. 94–123.
- J. Brownlee, N. Purdie, and G. Boulton-Lewis, Changing epistemological beliefs in preservice teacher education students, Teach. High. Educ. 6, 247 (2001).
- C. S. Kalman, M. Sobhanzadeh, R. Thompson, A. Ibrahim, and X. Wang, Combination of interventions can change students? epistemological beliefs, Phys. Rev. ST Phys. Educ. Res. 11, 020136 (2015).
- S. Yerdelen-Damar and A. Eryılmaz, The impact of the metacognitive 7E learning cycle on students’ epistemological understandings, Kastamonu Educ. J. 24, 603 (2016).
- T. T. Moores, J. C. J. Chang, and D. K. Smith, Clarifying the role of self-efficacy and metacognition as predictors of performance: Construct development and test, ACM SIGMIS Database: The DATABASE for Advances in Information, Systems 37, 125 (2006).
- A. M. Schmidt and J. K. Ford, Learning within a learner control training environment: The interactive effects of goal orientation and metacognitive instruction on learning outcomes, Pers. Psychol. 56, 405 (2003).
- K. J. Graham, C. M. Bohn-Gettler, and A. F. Raigoza, Metacognitive training in chemistry tutor sessions increases first year students’ self-efficacy, J. Chem. Educ. 96, 1539 (2019).
- S. Yerdelen-Damar and A. Eryılmaz, The impact of the metacognitive inquiry-based instruction on physics self-efficacy, in Proceedings of the Applied Education Congress (APPED), Ankara, Turkey (2012), https://fedu.metu.edu.tr/tr/system/files/ReportsAndDocuments/aped.pdf.
- J. L. Nietfeld, L. Cao, and J. W. Osborne, The effect of distributed monitoring exercises and feedback on performance, monitoring accuracy, and self-efficacy, Metacogn. Learn. 1, 159 (2006).
- A. Taghani and M. R. Razavi, The effect of metacognitive skills training of study strategies on academic self-efficacy and academic engagement and performance of female students in Taybad, Curr. Psychol. 41, 8784 (2022).
- S. A. Coutinho and G. Neuman, A model of metacognition, achievement goal orientation, learning style and self-efficacy, Learn. Environ. Res. 11, 131 (2008).
- R. Cera, M. Mancini, and A. Antonietti, Relationships between metacognition, self-efficacy and self-regulation in learning. J. Educ. Cult. Psychol. 7, 115 (2013).
- S. Yerdelen-Damar and H. Peşman, Relations of gender and socioeconomic status to physics through metacognition and self-efficacy. J. Educ. Res. 106, 280 (2013).
- M. C. Boyes and M. Chandler, Cognitive development, epistemic doubt, and identity formation in adolescence, J. Youth Adolesc. 21, 277 (1992).
- T. Krettenauer, The role of epistemic cognition in adolescent identity formation: Further evidence, J. Youth Adolesc. 34, 185 (2005).
- O. Levrini, P. Fantini, G. Tasquier, B. Pecori, and M. Levin, Defining and operationalizing appropriation for science learning, J. Learn. Sci. 24, 93 (2015).
- P. W. Irving and E. C. Sayre, Identity statuses in upper-division physics students, Cult. Stud. Sci. Educ. 11, 1155 (2016).
- C. J. Faber, R. L. Kajfez, D. M. Lee, L. C. Benson, M. S. Kennedy, and E. G. Creamer, A grounded theory model of the dynamics of undergraduate engineering students’ researcher identity and epistemic thinking, J. Res. Sci. Teach. 59, 529 (2022).
- X. Guo, X. Hao, W. Deng, X. Ji, S. Xiang, and W. Hu, The relationship between epistemological beliefs, reflective thinking, and science identity: A structural equation modeling analysis, Int. J. STEM Educ. 9, 40 (2022).
- S. Kapucu and E. Bahçivan, High school students’ scientific epistemological beliefs, self-efficacy in learning physics and attitudes toward physics: A structural equation model, Res. Sci. Technol. Educ. 33, 252 (2015).
- J. A. Chen and F. Pajares, Implicit theories of ability of Grade 6 science students: Relation to epistemological beliefs and academic motivation and achievement in science, Contemp. Educ. Psychol. 35, 75 (2010).
- D. Hammer, Epistemological beliefs in introductory physics, Cognit. Instr. 12, 151 (1994).
- K. Hogan, Relating students’ personal frameworks for science learning to their cognition in collaborative contexts, Sci. Educ. 83, 1 (1999).
- M. H. Lee, R. E. Johanson, and C. C. Tsai, Exploring Taiwanese high school students’ conceptions of and approaches to learning science through a structural equation modeling analysis, Sci. Educ. 92, 191 (2008).
- S. A. Rosenberg, D. Hammer, and J. Phelan, Multiple epistemological coherences in an eighth-grade discussion of the rock cycle, J. Learn. Sci. 15, 261 (2006).
- J. Biggs, Individual differences in study processes and the quality of learning outcomes, Higher Educ. 8, 381 (1979).
- C. Chin and D. E. Brown, Learning in science: A comparison of deep and surface approaches, J. Res. Sci. Teach. 37, 109 (2000).
- J. M. Case and R. F. Gunstone, Approaches to learning in a second year chemical engineering course, Int. J. Sci. Educ. 25, 801 (2003).
- E. Hazel, M. Prosser, and K. Trigwell, Variation in learning orchestration in university biology courses, Int. J. Sci. Educ. 24, 737 (2002).
- K. R. Muis and M. C. Duffy, Epistemic climate and epistemic change: Instruction designed to change students’ beliefs and learning strategies and improve achievement, J. Educ. Psychol. 105, 213 (2013).
- M. S. Khine, B. J. Fraser, and E. Afari, Structural relationships between learning environments and students’ non-cognitive outcomes: Secondary analysis of PISA data, Learn. Environ. Res. 23, 395 (2020).
- Y. H. Lee and H. Y. Hong, Preservice teachers’ intention for constructivist ICT integration: Implications from their Internet epistemic beliefs and internet-based learning self-efficacy, Interact. Learn. Environ. 32, 102 (2023).
- H. I. Strømsø and I. Bråten, Beliefs about knowledge and knowing and multiple-text comprehension among upper secondary students, Educ. Psychol. 29, 425 (2009).
- M. M. Williams and C. George-Jackson, Using and doing science: Gender, self-efficacy, and science identity of undergraduate students in STEM, J. Women Minorities Sci. Eng. 20, 99 (2014).
- P. Vincent-Ruz and C. D. Schunn, The nature of science identity and its role as the driver of student choices, Int. J. STEM Educ. 5, 48 (2018).
- Z. Hazari, P. M. Sadler, and G. Sonnert, The science identity of college students: Exploring the intersection of gender, race, and ethnicity, J. Coll. Sci. Teach. 42, 82 (2013).
- C. Monsalve, Z. Hazari, D. McPadden, G. Sonnert, and P. Sadler, presented at PER Conf. 2016, Sacramento, CA, https://www.compadre.org/Repository/document/ServeFile.cfm?ID=14235&DocID=4589.
- V. Seyranian, A. Madva, N. Duong, N. Abramzon, Y. Tibbetts, and J. M. Harackiewicz, The longitudinal effects of stem identity and gender on flourishing and achievement in college physics, Int. J. STEM Educ. 5, 40 (2018).
- S. Cwik and C. Singh, Not feeling recognized as a physics person by instructors and teaching assistants is correlated with female students’ lower grades, Phys. Rev. Phys. Educ. Res. 18, 010138 (2022).
- S. Yerdelen-Damar and A. Eryılmaz, Questions about physics: The case of a Turkish ‘Ask a Scientist’website, Res. Sci. Educ. 40, 223 (2010).
- R. Trumper, Factors affecting junior high school students’ interest in physics, J. Sci. Educ. Technol. 15, 47 (2006).
- J. M. Nissen, Gender differences in self-efficacy states in high school physics, Phys. Rev. Phys. Educ. Res. 15, 013102 (2019).
- S. Cwik and C. Singh, Damage caused by societal stereotypes: Women have lower physics self-efficacy controlling for grade even in courses in which they outnumber men, Phys. Rev. Phys. Educ. Res. 17, 020138 (2021).
- M. S. Topçu and Ö. Yılmaz Tüzün, Elementary students’ metacognition and epistemological beliefs considering science achievement, gender and socioeconomic status, Elementary Educ. Online 8, 676, 2009.
- F. Kurt, Investigating students’ epistemological beliefs through gender, grade level, and fields of study, Master’s thesis, Middle East Technical University, 2009.
- K. Ozkal, C. Tekkaya, S. Sungur, J. Cakiroglu, and E. Cakiroglu, Elementary students’ scientific epistemological beliefs in relation to socioeconomic status and gender, J. Sci. Teach. Educ. 21, 873 (2010).
- S. Ozkan and C. Tekkaya, How do epistemological beliefs differ by gender and socioeconomic status, Hacettepe Univ. J. Educ 41, 339 (2011).
- X. Guo, W. Deng, K. Hu, W. Lei, S. Xiang, and W. Hu, The effect of metacognition on students’ chemistry identity: The chain mediating role of chemistry learning burnout and chemistry learning flow, Chem. Educ. Res. Pract. 23, 408 (2022).
- D. Hammer and A. Elby, On the form of a personal epistemology, in Personal Epistemology: The Psychology of Beliefs about Knowledge and Knowing, edited by B. K. Hofer and P. R. Pintrich (Lawrence Erlbaum Associates Publishers, Hillsdale, NJ, 2002), pp. 169–190.
- B. K. Hofer, Dimensionality and disciplinary differences in personal epistemology. Contemp. Educ. Psychol. 25, 378 (2000).
- S. Chen, B. Wei, and H. Zhang, Exploring high school students’ disciplinary science identities and their differences, Int. J. Sci. Math. Educ. 21, 377 (2022).
- Y. Ulu and S. Yerdelen-Damar, Fizik Benlik Ölçeğinin Türkçeye Uyarlama Çalışması, V. Ulusal Fizik Eğitimi Kongresi, 2022, Istanbul, Online (2022).
- A. Akın, R. Abacı ve, and B. Çetin, Bilişötesi farkındalık envanteri’nin türkçe formunun geçerlik ve güvenirlik çalışması, Kuram Uygul. Egit. Bil. 7, 655 (2007).
- T. Kline, Psychological Testing: A Practical Approach to Design and Evaluation (Sage Publications, Inc., Thousand Oaks, CA, 2005).
- K. A Bollen, Total, direct, and indirect effects in structural equation models, Sociol. Methodol. 17, 37 (1987).
- J. Pearl, Direct and indirect effects, in Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence (Morgan Kaufmann, San Francisco, CA, 2001), p. 411.
- K. A. Pituch and J. P. Stevens, Applied Multivariate Statistics for the Social Sciences: Analyses with SAS and IBM’s SPSS, 6th ed. (Routledge, New York, NY, 2016).
- J. Cohen and P. Cohen, Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences (Erlbaum, Hillsdale, NJ, 1983).
- S. J. Finney and C. DiStefano, Nonnormal and categorical data in structural equation modeling, Structural Equation Modeling: A Second Course, 2nd ed., edited by G. R. Hancock and R. O. Mueller (Information Age Publishing, Charlotte, NC, 2013), pp. 439–492.
- L. K. Muthén and B. Muthén, Mplus User’s Guide (Muthén & Muthén, Los Angeles, CA, 2017).
- L. T. Hu and P. M. Bentler, Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives, Struct. Equ. Model. 6, 1 (1999).
- H. W. Marsh, K. T. Hau, and Z. Wen, In search of golden rules: Comment on hypothesis-testing approaches to setting cutoff values for fit indexes and dangers in overgeneralizing Hu and Bentler’s (1999) findings, Struct. Equ. Model. 11, 320 (2004).
- K Schermelleh-Engel, H. Moosbrugger, and H. Müller, Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures, Methods Psychol. Res. Online 8, 23 (2003).
- J. Pallant, SPSS Survival Manual: A Step by Step Guide to Data Analysis Using the SPSS Program, 4th ed. (Allen & Unwin, Berkshire, 2011).
- S. R. Briggs and J. M. Cheek, The role of factor analysis in the development and evaluation of personality scales, J. Pers. 54, 106 (1986).
- C. K. Enders, Applied Missing Data Analysis (Guilford Press, New York, 2010).
- J. C. Anderson and D. W. Gerbing, Structural equation modeling in practice: A review and recommended two-step approach, Psychol. Bull. 103, 411 (1988).
- W. A. Sandoval and K. Morrison, High school students’ ideas about theories and theory change after a biological inquiry unit, J. Res. Sci. Teach. 40, 369 (2003).
- N. D. Finkelstein and S. J. Pollock, Replicating, and understanding successful innovations: Implementing tutorials in introductory physics, Phys. Rev. ST Phys. Educ. Res. 1, 010101 (2005).
- R. F. Moll and M. Milner-Bolotin, The effect of interactive lecture experiments on student academic achievement and attitudes towards physics, Can. J. Phys. 87, 917 (2009).
- V. L. Akerson and M. L. Volrich, Teaching nature of science explicitly in a first-grade internship setting, J. Res. Sci. Teach. 43, 377 (2006).
- W. A. Sandoval and B. J. Reiser, Explanation-driven inquiry: Integrating conceptual and epistemic scaffolds for scientific inquiry, Sci. Educ. 88, 345 (2004).
- R. S. Schwartz, N. G. Lederman, and B. A. Crawford, Developing views of nature of science in an authentic context: An explicit approach to bridging the gap between nature of science and scientific inquiry, Sci. Educ. 88, 610 (2004).
- E. F. Redish and D. Hammer, Reinventing college physics for biologists: Explicating an epistemological curriculum, Am. J. Phys. 77, 629 (2009).
- D. Cheung, The combined effects of classroom teaching and learning strategy use on students’ chemistry self-efficacy, Res. Sci. Educ. 45, 101 (2015).
- X. Huang, R. E. Mayer, and E. L. Usher, Better together: Effects of four self-efficacy-building strategies on online statistical learning, Contemp. Educ. Psychol. 63, 101924 (2020).
- F. Ogan-Bekiroglu and M. Aydeniz, Enhancing preservice physics teachers’ perceived self-efficacy of argumentation-based pedagogy through modelling and mastery experiences, Eurasia J. Math. Sci. Technol. Educ. 9, 233 (2013).
- V. Sawtelle, E. Brewe, and L. Kramer, Positive impacts of Modeling Instruction on self-efficacy, AIP Conf. Proc. 1289, 289 (2010).
- M. Yough, Tapping the sources of self-efficacy: Promoting preservice teachers’ sense of efficacy for instructing English language learners, Teach. Teach. Educ. 54, 206 (2019).
- J. C. Y. Sun and K. Y. C. Hsu, A smart eye-tracking feedback scaffolding approach to improving students’ learning self-efficacy and performance in a C programming course, Comput. Hum. Behav. 95, 66 (2019).
- N. Valencia-Vallejo, O. López-Vargas, and L. Sanabria-Rodríguez, Effect of a metacognitive scaffolding on self-efficacy, metacognition, and achievement in E-Learning environments, Knowl. Manage. E-Learn. 11, 1 (2019).
- J. H. Zhang, B. Meng, L. C. Zou, Y. Zhu, and G. J. Hwang, Progressive flowchart development scaffolding to improve university students’ computational thinking and programming self-efficacy, Interact. Learn. Environ. 31, 3792 (2021).
- R. Henderson, V. Sawtelle, and J. M. Nissen, Gender & self-efficacy: A call to physics educator, Phys. Teach. 58, 345 (2020).
- T. Espinosa, K. Miller, I. Araujo, and E. Mazur, Reducing the gender gap in students’ physics self-efficacy in a team- and project-based introductory physics class, Phys. Rev. Phys. Educ. Res. 15, 010132 (2019).
- Z. Hazari, D. Chari, G. Potvin, and E. Brewe, The context dependence of physics identity: Examining the role of performance/competence, recognition, interest, and sense of belonging for lower and upper female physics undergraduates, J. Res. Sci. Teach. 57, 1583 (2020).
- Z. Y. Kalender, E. Marshman, C. Schunn, T. N. 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, 020146 (2019).
- Y. Li and C. Singh, Statistically equivalent models with different causal structures: An example from physics identity, Phys. Rev. Phys. Educ. Res. 20, 010101 (2024).
- V. Adlakha and E. Kuo, Critical issues in statistical causal inference for observational physics education research, Phys. Rev. Phys. Educ. Res. 19, 020160 (2023).
- J. R. Fraenkel, N. E. Wallen, and H. H. Hyun, Internal Validity. How to Design and Evaluate Research in Education (McGraw-Hill, New York, 2012), pp. 166–183.
- A. Traxler, X. Cid, J. Blue, and R. Barthelemy, Enriching gender in physics education research: A binary past and a complex future, Phys. Rev. Phys. Educ. Res. 12, 020114 (2016).
- B. M. Byrne, Structural Equation Modeling with Mplus: Basic Concepts, Applications, and Programming (Routledge, New York, 2012).
- F. F. Chen, Sensitivity of goodness of fit indexes to lack of measurement invariance, Struct. Equ. Model. 14, 464 (2007).
- G. W. Cheung and R. B. Rensvold, Evaluating goodness-of-fit indexes for testing measurement invariance, Struct. Equ. Model. 9, 233 (2002).