Cited by 45Student Assessment and FeedbackEvaluation of Teaching PracticesHigher Education Practises and Engagement

Students’ feedback literacy in higher education: an initial scale validation study

Open access
Woitt, Svenja, Weidlich, Joshua, Jivet, Ioana, Orhan Göksün, Derya, Drachsler, Hendrik, Kalz, Marco·2025·Teaching in Higher Education

Abstract

Given the crucial role of feedback in supporting learning in higher education, understanding the factors influencing feedback effectiveness is imperative.Student feedback literacy, that is, the set of attitudes and abilities to make sense of and utilize feedback is therefore considered a key concept.Rigorous investigations of feedback literacy require psychometrically sound measurement.To this end, the present paper reports on the development and initial validation (N = 221) of a self-report instrument.Grounded in the conceptual literature and building on previous scale validation efforts, an initial overinclusive item pool is generated.Exploratory factor analysis and the Rasch measurement model yield adequate psychometric properties of an initial scale measuring two dimensions: feedback attitudes and feedback practices with a total of 21 items.We further provide evidence for criterion-related validity.Findings are discussed in light of the emerging feedback literacy literature and avenues for further improvement of the scale are reported.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1080/13562517.2023.2263838

Cites

10 of 10 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 24

  1. Anseel, F., A.S. Beatty, W. Shen, F. Lievens, and P.R. Sackett. (2015). How are we doing after 30 years? A meta-analytic review of the antecedents and outcomes of feedback-seeking behavior. Journal of Management 41, no. 1, 318-48.
  2. Biggs, J., D. Kember, and D.Y. Leung. 2001. The revised two-factor study process questionnaire: R- SPQ-2F. British Journal of Educational Psychology 71, no. 1: 133-49.
  3. Bond, T.G., and C.M. Fox. 2015. Applying the Rasch model: Fundamental measurement in the human sciences. 3rd ed. New York: Routledge.
  4. Brown, G.T., and A. Zhao. 2023. In defence of psychometric measurement: A systematic review of contemporary self-report feedback inventories. Educational Psychologist, 1-15.
  5. Butler, D.L., and P.H. Winne. 1995. Feedback and self-regulated learning: A theoretical synthesis. Review of Educational Research 65, no. 3: 245-81.
  6. Chen, D. 2023. Toward an understanding of 21st-century skills: From a systematic review. International Journal of and Vocational Guidance 23: 275-94. doi:10.1007/s10775-021-09511-1. · DOI
  7. Costello, A.B., and J. Osborne. 2005. Best practices in exploratory factor analysis: Four recommen- dations for getting the most from your analysis. University of Massachusetts Amherst. doi:10. 7275/jyj1-4868 · DOI · Paper page
  8. Cronbach, L.J., and P.E. Meehl. 1955. Construct validity in psychological tests. Psychological Bulletin 52, no. 4: 281.
  9. De Winter, J.C., and D. Dodou. 2012. Factor recovery by principal axis factoring and maximum likelihood factor analysis as a function of factor pattern and sample size. Journal of Applied Statistics 39, no. 4: 695-710.
  10. Garino, A. 2020. Ready, willing and able: A model to explain successful use of feedback. Advances in Health Sciences Education 25, no. 2: 337-61. doi:10.1007/s10459-019-09924-2. · DOI
  11. Joughin, G., D. Boud, P. Dawson, and J. Tai. 2021. What can higher education learn from feedback seeking behaviour in organisations? Implications for feedback literacy Assessment & Evaluation in Higher Education 46, no. 1: 80-91. doi:10.1080/02602938.2020.1733491. · DOI
  12. Kim, Y., J. Dykema, J. Stevenson, P. Black, and D.P. Moberg. 2019. Straightlining: Overview of measurement, comparison of indicators, and effects in mail-web mixed-mode surveys. Social Science Computer Review 37, no. 2: 214-33. doi:10.1177/0894439317752406. · DOI
  13. Linacre, J.M. 1994. Sample size and item calibration stability. Rasch Measurement Transactions 7, no. 4: 328.
  14. Linacre, J.M., and B.D. Wright. 1993. Constructing linear measures from counts of qualitative obser- vations. Paper presented at the fourth international conference on biometrics, Informetrics and Scientometrics, Berlin, Germany. https://files.eric.ed.gov/fulltext/ED364574.pdf.
  15. Linderbaum, B.A., and P.E. Levy. 2010. The development and validation of the Feedback Orientation Scale (FOS). Journal of Management 36, no. 6: 1372-405.
  16. Little, T., P. Dawson, D. Boud, and J. Tai. 2023. Can students' feed-back literacy be improved? A scoping review of interventions. Assessment & Evaluation in Higher Education, 1-14. doi:10. 1080/02602938.2023.2177613. · DOI
  17. Mahmood, K. 2016. Do people overestimate their information literacy skills? A systematic review of empirical evidence on the Dunning-Kruger effect. Communications in Information Literacy 10, no. 2: 3.
  18. Malecka, B., D. Boud, and D. Carless. 2022. Eliciting, processing and enacting feedback: Mechanisms for embedding student feedback literacy within the curriculum. Teaching in Higher Education 27, no. 7: 908-22. doi:10.1080/13562517.2020.1754784. · DOI
  19. Nieminen, J. H., and D. Carless. 2023. Feedback literacy: A critical review of an emerging concept. Higher Education 85, no. 6: 1381-400.
  20. Van der Kleij, F.M., L.E. Adie, and J.J. Cumming. 2019. A meta-review of the student role in feed- back. International Journal of Educational Research 98: 303-23.
  21. Winstone, N., and D. Carless, eds. 2019. Designing effective feedback processes in higher education: A learning-focused approach. Routledge.
  22. Wright, B.D. 1996. Reliability and separation. Rasch Measurement Transactions 1996 9, no. 4: 472.
  23. Yildiz, H., E. Bozpolat, and E. Hazar. 2022. Feedback literacy scale: A study of validation and reliability. International Journal of Eurasian Education and Culture 7, no. 19, 2214-49.
  24. Zwick, R., D.T. Thayer, and C. Lewis. 1999. An empirical Bayes approach to Mantel-Haenszel DIF analysis. Journal of Educational Measurement 36, no. 1: 1-28.

Cited by

Authors
Woitt, S., Weidlich, J., Jivet, I., Orhan Göksün, D., Drachsler, H., & Kalz, M.
Affiliations
  • Heidelberg University of Education (DE)
  • DIPF | Leibniz Institute for Research and Information in Education (DE)
  • Goethe University Frankfurt (DE)
  • Faculty of Education, Adiyaman University, Adiyaman, Turkey
Corresponding author
Weidlich, Joshua
Venue
Teaching in Higher Education
Published
2023-10-17
Volume
30
Issue
1
Pages
257-276
ISSN
  • 1356-2517 (ISSN-L)
  • 1470-1294
OpenAlex
W4387697902
Cited by
45
References
10
Citations by year
2026: 26 · 2025: 15 · 2024: 4
FWCI
20.13
Type
journal article
Language
en
Open access
Locations
  • Teaching in Higher Education (publishedVersion, cc-by-nc-nd)
  • DSpace (Open University in the Netherlands) (submittedVersion, cc-by-nc-nd)
  • Zurich Open Repository and Archive (University of Zurich) (submittedVersion, cc-by-nc-nd)
  • Zurich Open Repository and Archive (University of Zurich)
Topics
  • Social Sciences › Education › Student Assessment and Feedback
  • Social Sciences › Education › Evaluation of Teaching Practices
  • Social Sciences › Education › Higher Education Practises and Engagement
Keywords
feedback literacy, student feedback, feedback effectiveness, feedback practices, scale development, psychometric validation, Rasch model, university students, self-report measures

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review