Geri Bildirim Etkililik Algısı Ölçeği: Geçerlik ve Güvenirlik Çalışması

Yıl 2025, Cilt: 15 Sayı: 3, 909 - 930, 27.09.2025

Emrullah Esen , Oktay Cem Adıgüzel , Derya Atik Kara

https://doi.org/10.18039/ajesi.1633718

Öz

Bu çalışmanın amacı, geribildirimin etkililiğini değerlendirmek için geçerli ve güvenilir bir ölçme aracı geliştirmektir. Çalışmaya farklı sınıf düzeylerinden ve öğretmen eğitimi programlarından toplam 662 öğretmen adayı katılmıştır. Bu süreç, madde geliştirme, ölçek geliştirme ve ölçek değerlendirme olmak üzere birbirini takip eden üç aşamada yürütülmüştür. Ölçme aracının faktör yapısı açımlayıcı ve doğrulayıcı faktör analizi kullanılarak incelenmiştir. İlk olarak 334 lisans öğrencisinden toplanan veri setiyle açımlayıcı faktör analizi (AFA) yapılmış, ardından 328 lisans öğrencisinden oluşan ayrı bir veri setiyle doğrulayıcı faktör analizi (DFA) gerçekleştirilmiştir. AFA sonuçları, teorik çerçeveye karşılık gelen bilişsel, üst bilişsel ve duyuşsal boyutlardan oluşan üç faktörlü bir yapının varlığına işaret etmiştir. DFA sonuçları modelin uyum indekslerinin kabul edilebilir eşikleri önemli ölçüde aştığını ve böylece modelin yapı geçerliliğini doğruladığını göstermiştir. Ayrıca, ölçek boyutları için elde edilen Cronbach Alpha ve Omega katsayıları da ölçeğin güvenilir olduğunu göstermiştir. Faktör analizleri sonucunda, geribildirim etkinliğini değerlendirmek amacıyla 30 maddelik, üç boyutlu, geçerli ve güvenilir Likert tipi bir ölçme aracı geliştirilmiştir.

Anahtar Kelimeler

geri bildirim ölçeği , geri bildirime ilişkin algılar , ölçek geliştirme , geri bildirimin etkililiği

The Perceived Effectiveness of Feedback Scale: Validity and Reliability Study

Öz

The aim of this study was to develop a valid and reliable measurement tool for evaluating the perceived effectiveness of feedback. A total of 662 pre-service teachers from a variety of grade levels and teacher education programs participated in the study. This process was methodically executed in three sequential stages: item development, scale development, and scale evaluation. The factor structure of the assessment tool was examined using exploratory and confirmatory factor analysis. Initially, exploratory factor analysis (EFA) was conducted with a dataset collected from 334 undergraduate students, followed by a confirmatory factor analysis (CFA) with a separate set of 328 undergraduate students. The results of the EFA indicated the presence of a three-factor structure comprising cognitive, metacognitive, and affective dimensions that corresponds to the theoretical framework. The CFA further demonstrated that the model's fit indices significantly exceeded the acceptable thresholds, thus validating the model's construct validity. Furthermore, the reliability analyses yielded satisfactory results, as evidenced by the Cronbach's Alpha and Omega coefficients for the scale dimensions, which were found to be within the acceptable ranges. As a result of the factor analyses, a valid and reliable 30-item Likert-type measurement instrument with three dimensions has been established with the goal of assessing feedback effectiveness.

Anahtar Kelimeler

feedback scale , feedback perceptions , scale development , the effectiveness of feedback

Kaynakça

• Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423. Retrieved August 15, 2025, from https://doi.org/10.1037/0033-2909.103.3.411
• Agricola, B. T., Prins, F. J., & Sluijsmans, D. (2019). Impact of feedback request forms and verbal feedback on higher education students' feedback perception, self-effectiveness, and motivation. Assessment in Education: Principles, Policy & Practice, 27(1), 6-25. Retrieved November 15, 2023, from https://doi.org/10.1080/0969594x.2019.1688764
• Akkuzu, N., & Uyulgan, M. A. (2014). Toward making the invisible visible using a scale: Prospective teachers' thoughts and affective reactions to feedback. Irish Educational Studies, 33(3), 287-305. Retrieved December 3, 2023, from https://doi.org/10.1080/03323315.2014.923184
• Akolgo, D. R., Robiullah, A., & Ramirez, G. (2025). The emotional and motivational costs of poorly delivered academic feedback. Frontiers in Psychology, 16, Article 1585447. https://doi.org/10.3389/fpsyg.2025.1585447
• Baydas Onlu, O., Abdusselam, M. S., & Yilmaz, R. M. (2022). Students’ perception of instructional feedback scale: Validity and reliability study. Contemporary Educational Technology, 14(3), ep368. https://doi.org/10.30935/cedtech/11811
• Beydoğan, H. Ö. (2016). Öğretmen Adaylarına Yönelik Dönüt–Düzeltme Algı Ölçeği. Ahi Evran University Journal of Kırşehir Education Faculty, 17(2), 297-314. Retrieved January 18, 2024, from https://dergipark.org.tr/en/pub/kefad/issue/59426
• Bentler, P. M., & Chou, C.-P. (1987). Practical issues in structural modeling. Sociological Methods & Research, 16(1), 78–117. https://doi.org/10.1177/0049124187016001004
• Boateng, G. O., Neilands, T. B., Frongillo, E. A., Melgar-Quiñonez, H. R., & Young, S. L. (2018). Best practices for developing and validating scales for health, social, and behavioral research: A primer. Frontiers in Public Health, 6. https://www.frontiersin.org/articles/10.3389/fpubh.2018.00149
• Brookhart, S. (2008). How to give effective feedback to your students. Association for Supervision and Curriculum Development Byrne, B. M. (1994). Structural equation modeling with EQS and EQS/Windows. Sage.
• Callender, A. A., Franco‐Watkins, A. M., & Roberts, A. (2015). Improving metacognition in the classroom through instruction, training, and feedback. Metacognition and Learning, 11(2), 215-235. https://doi.org/10.1007/s11409-015-9142-6
• Carless, D., & Boud, D. (2018). The development of student feedback literacy: Enabling uptake of feedback. Assessment & Evaluation in Higher Education, 43(8), 1315-1325. Retrieved February 5, 2024, from https://doi.org/10.1080/02602938.2018.1463354
• Chang, G. C. (2014). Writing feedback as an exclusionary practice in higher education. Australian Review of Applied Linguistics, 37(3), 262-275. Retrieved November 30, 2023, from https://doi.org/10.1075/aral.37.3.05cha
• Charalampous, A., & Darra, M. (2024). The impact of teacher feedback on non-cognitive aspects of student's performance in higher education: A review of research. International Research in Education, 12(2), 1-15. Retrieved January 8, 2024, from https://doi.org/10.5296/ire.v12i2.22001
• Chen, F. F., West, S. G., & Sousa, K. H. (2006). A comparison of bifactor and second-order models of quality of life. Multivariate Behavioral Research, 41(2), 189–225. Retrieved August 15, 2025, from https://doi.org/10.1207/s15327906mbr4102_5
• Costello, A. B., & Osborne, J. W. (2005). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Practical Assessment, Research, and Evaluation, 10(1), 7-13. Retrieved March 1, 2024, from https://doi.org/10.7275/jyj1-4868
• Deeley, S. J., Fischbacher‐Smith, M., Karadzhov, D., & Koristashevskaya, E. (2019). Exploring the ‘wicked’ problem of student dissatisfaction with assessment and feedback in higher education. Higher Education Pedagogies, 4(1), 385-405. Retrieved October 12, 2023, from https://doi.org/10.1080/23752696.2019.1644659
• Dowden, T., Pittaway, S., Yost, H., & McCarthy, R. (2013). Students’ perceptions of written feedback in teacher education: ideally feedback is a continuing two-way communication that encourages progress. Assessment & Evaluation in Higher Education, 38(3), 349-362. 632676 Retrieved December 21, 2023, from https://doi.org/10.1080/02602938.2011.632676
• Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272–299. Retrieved February 18, 2024, from https://doi.org/10.1037/1082-989X.4.3.272
• Flora, D. B., LaBrish, C., & Chalmers, R. P. (2012). Old and new ideas for data screening and assumption testing for exploratory and confirmatory factor analysis. Frontiers in Psychology, 3, 55-68. Retrieved March 7, 2024, from https://doi.org/10.3389/fpsyg.2012.00055
• Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. Retrieved December 8, 2023, from https://doi.org/10.1177/002224378101800104
• Glazzard, J., & Stones, S. (2019). Student perceptions of feedback in higher education. International Journal of Learning, Teaching and Educational Research, 18(11), 38-52. Retrieved October 25, 2023, from https://doi.org/10.26803/ijlter.18.11.3
• Hair, J. F., Black, W. C., & Babin, B. J. (2010). Multivariate Data Analysis: A Global Perspective. Pearson Education.
• Hair, J., Risher, J., Sarstedt, M., & Ringle, C. (2018). When to use and how to report the results of PLS-SEM. European Business Review, 31. Retrieved August 15, 2025, from https://doi.org/10.1108/EBR-11-2018-0203
• Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112. https://doi.org/10.3102/003465430298487
• Hayton, J. C., Allen, D. G., & Scarpello, V. (2004). Factor retention decisions in exploratory factor analysis: A tutorial on parallel analysis. Organizational Research Methods, 7(2), 191-205. Retrieved January 28, 2024, from https://doi.org/10.1177/1094428104263675
• Henderson, M., Phillips, M., Ryan, T., Boud, D., Dawson, P., Molloy, E., … & Mahoney, P. (2019). Conditions that enable effective feedback. Higher Education Research & Development, 38(7), 1401-1416.. Retrieved December 15, 2023, from https://doi.org/10.1080/07294360.2019.1657807
• Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135. Retrieved February 8, 2024, from https://doi.org/10.1007/s11747-014-0403-8
• Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
• Jöreskog, K. G., & Sörbom, D. (1984). LISREL VI user’s guide (3rd ed.). Scientific Software.
• Kara, F. M., Kazak, F. Z., & Aşçı, F. H. (2018). Perceived Teacher Feedback Scale: The validity and reliability study. Spor Bilimleri Dergisi, 29(2), 79-86. Retrieved March 12, 2024, from https://doi.org/10.17644/sbd.306544
• Kartol, A. & Arslan, N. (2021). Turkish version of the feedback orientation scale: Investigation of psychometric properties. International Journal of Turkish Literature Culture Education, 10(10/1), 321-329. Retrieved November 3, 2023, from https://doi.org/10.7884/teke.5129
• Kılıç, A. F. (2022). Deciding the number of dimensions in explanatory factor analysis: A brief overview of the methods. Pamukkale University Journal of Social Sciences Institute, 51, 305-318. Retrieved January 5, 2024, from https://doi.org/10.30794/pausbed.1095936 Kline, P. (1994). An easy guide to factor analysis. Routledge.
• Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). Guilford Press.
• Kline, R. B. (2016). Principles and practice of structural equation modeling (4th ed.). Guilford Press.
• Kluger, A. N., & DeNisi, A. (1996). The effects of feedback interventions on performance: a historical review, a meta-analysis, and a preliminary feedback intervention theory. Psychological Bulletin, 119(2), 254.
• Kumral, O., & Saracaloglu, A. S. (2011). An evaluation of elementary school teachers' teaching profession courses programme via educational criticism model. Education Sciences, 6(1), 1-15.
• Kutasi, R. (2023). Feedback: unveiling its impact and enhancing its effectiveness in education. Journal of Pedagogy - Revista de Pedagogie, 2, 7-32. https://doi.org/10.26755/revped/2023.2/7.
• Labuhn, A. S., Zimmerman, B. J., & Hasselhorn, M. (2010). Enhancing students’ self-regulation and mathematics performance: the influence of feedback and self-evaluative standards. Metacognition and Learning, 5(2), 173-194. https://doi.org/10.1007/s11409-010-9056-2 Lawshe, C. H. (1975). A quantitative approach to content validity. Personnel Psychology, 28(4), 563–575. https://doi.org/10.1111/j.1744-6570.1975.tb01393.x
• MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1, 130-149. https://doi.org/10.1037/1082-989X.1.2.130
• Molin, F., Haelermans, C., Cabus, S., & Groot, W. (2020). The effect of feedback on metacognition-a randomized experiment using polling technology. Computers & Education, 152, 103885. https://doi.org/10.1016/j.compedu.2020.103885
• Narciss, S. & Huth, K. (2004). How to design informative feedback for multimedia learning. In Niegemann, R. Brünken, & D. Leutner (Eds.), Instructional design for multimedia learning. Münster: Waxmann.
• Narciss, S. (2008). Feedback strategies for interactive learning tasks. In Handbook of research on educational communications and technology (pp. 125-143). Routledge.
• Nicol, D. and Macfarlane‐Dick, D. (2006). Formative assessment and self‐regulated learning: A model and seven principles of good feedback practice. Studies in Higher Education, 31(2), 199-218. https://doi.org/10.1080/03075070600572090
• Nugraheny, E., Claramita, M., Rahayu, G., & Kumara, A. (2016). Feedback in the nonshifting context of the midwifery clinical education in indonesia: A mixed methods study. Iranian Journal of Nursing and Midwifery Research, 21(6), 628. Retrieved December 7, 2023, from https://doi.org/10.4103/1735-9066.197671
• Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
• Ocak, G., & Karafil, B. (2020). Development of Teacher Feedback Use Evaluation Scale. International Journal of Progressive Education, 16(1), 287-299. Retrieved February 20, 2024, from https://doi.org/10.29329/ijpe.2020.228.20
• Ostaeyen, S. V., Embo, M., Rotsaert, T., Clercq, O. D., Schellens, T., & Valcke, M. (2023). A qualitative textual analysis of feedback comments in eportfolios: Quality and alignment with the CanMeds roles. Perspectives on Medical Education, 12(1). Retrieved March 5, 2024, from https://doi.org/10.5334/pme.1050
• Öntaş, T., & Kaya, B. (2019). Investigation of the opinions of pre-service primary school teachers to give feedback in preparation of teaching materials. National Education, 48(224), 59-73. Retrieved October 22, 2023, from https://dergipark.org.tr/tr/pub/milliegitim/issue/50252
• Păduraru, M. (2023). Students' perceptions of feedback in higher education. Proceedings of the 9th International Conference Education Facing Contemporary World Issues, 125-138. Retrieved November 30, 2023, from https://doi.org/10.15405/epes.23045.36
• Pallant, J. (2020). SPSS survival manual: A step by step guide to data analysis using IBM SPSS (7th. ed.). Routledge.
• Pekrun, R. (2006). The control-value theory of achievement emotions: Assumptions, corollaries, and implications for educational research and practice. Educational Psychology Review, 18(4), 315–341. https://doi.org/10.1007/s10648-006-9029-9
• Satorra, A., & Bentler, P. M. (2001). A scaled difference chi-square test statistic for moment structure analysis. Psychometrika, 66(4), 507-514. Retrieved November 25, 2023, from https://doi.org/10.1007/BF02296192
• Schunk, D. H., & Zimmerman, B. J. (2007). Influencing children’s self-efficacy and self-regulation of reading and writing through modeling. Reading & Writing Quarterly, 23(1), 7–25. https://doi.org/10.1080/10573560600837578
• Shute, V. J. (2008). Focus on formative feedback. Review of Educational Research, 78(1), 153-189. https://doi.org/10.3102/0034654307313795
• Schumacker, R. E. and Lomax, R. G. (2004). A beginner's guide to structural equation modeling (2nd Ed.) Psychology Press. https://doi.org/10.4324/9781410610904
• Sinclair, H. K., & Cleland, J. A. (2007). Undergraduate medical students: Who seeks formative feedback? Medical Education, 41(6), 580-582. Retrieved January 20, 2024, from https://doi.org/10.1111/j.1365-2923.2007.02768.x
• Şahin, M. (2015). Investigation of prospective teachers' opinions about the feedback activity used in teaching and learning process. Bolu Abant Izzet Baysal University Journal of Faculty of Education, 15(Special Issue I), 247-264.
• Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (5th ed.). Allyn & Bacon/Pearson Education.
• Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Pearson.
• Tärning, B., Lee, J. Y., Andersson, R., Månsson, K., Gulz, A., & Haake, M. (2020). Assessing the black box of feedback neglect in a digital educational game for elementary school. Journal of the Learning Sciences, 29(4-5), 511-549. Retrieved November 12, 2023, from https://doi.org/10.1080/10508406.2020.1770092
• Voerman, L., Meijer, P. C., Korthagen, F. A. J., & Simons, R. J. (2012). Types and frequencies of feedback interventions in classroom interaction in secondary education. Teaching and Teacher Education, 28(8), 1107–1115. https://doi.org/10.1016/j.tate.2012.06.006
• Wang, Z., Gong, S., Xu, S., & Hu, X. (2019). Elaborated feedback and learning: Examining cognitive and motivational influences. Computers & Education, 136, 130-140. https://doi.org/10.1016/j.compedu.2019.04.003
• Winstone, N., Nash, R. A., Rowntree, J., & Parker, M. (2017). ‘It'd be useful, but I wouldn't use it’: barriers to university students’ feedback seeking and recipience. Studies in Higher Education, 42(11), 2026-2041. Retrieved December 5, 2023, from https://doi.org/10.1080/03075079.2015.1130032
• Wisniewski, B., Zierer, K., & Hattie, J. (2020). The power of feedback revisited: A meta-analysis of educational feedback research. Frontiers in Psychology, 10, 3087. Retrieved January 15, 2024, from https://doi.org/10.3389/fpsyg.2019.03087
• Worthington, R. L., & Whittaker, T. A. (2006). Scale development research: A content analysis and recommendations for best practices. The Counseling Psychologist, 34(6), 806–838. Retrieved August 15, 2025, from https://doi.org/10.1177/0011000006288127
• Yang, L., Chiu, M., & Yan, Z. (2021). The power of teacher feedback in affecting student learning and achievement: insights from students’ perspective. Educational Psychology, 41, 821-824. https://doi.org/10.1080/01443410.2021.1964855.
• Yuan, K.-H., & Bentler, P. M. (1998). Robust mean and covariance structure analysis. British Journal of Mathematical and Statistical Psychology, 51(1), 63-88. Retrieved February 22, 2024, from https://doi.org/10.1111/j.2044-8317.1998.tb00667.x
• Yuan, K.-H., & Bentler, P. M. (2000). Three likelihood-based methods for mean and covariance structure analysis with nonnormal missing data. Sociological Methodology, 30(1), 165-200. Retrieved March 10, 2024, from https://doi.org/10.1111/0081-1750.00078
• Yüksel, S. (2007). Effect of hidden curriculum on prospective teachers' thoughts about teacher training courses. Educational Administration: Theory and Practice, 50, 321-345. Retrieved November 30, 2023, from https://dergipark.org.tr/en/pub/kuey/issue/10347
• Zinbarg, R. E., Revelle, W., Yovel, I., & Li, W. (2005). Cronbach’s α, Revelle’s β, and McDonald’s ωh: their relations with each other and two alternative conceptualizations of reliability. Psychometrika, 70(1), 123-133. Retrieved January 8, 2024, from https://doi.org/10.1007/s11336-003-0974-7