Development of Educational Data Literacy Competency Perception Scale for Early Childhood Teachers: Validity and Reliability Study
Year 2025,
Volume: 58 Issue: 2, 591 - 650, 16.08.2025
Fadime Biçici Uslu
,
Selda Aras
,
Arif Yılmaz
Abstract
Educational data literacy is defined as the competence to accurately observe, analyze, and respond to various types of data, with the aim of continuously improving teaching and learning processes at both classroom and school levels. This study aimed to develop a valid and reliable measurement tool to assess preschool teachers' perceptions of their competencies in educational data literacy. A quantitative research approach was adopted in the study. The study group consisted of 579 preschool teachers working in early childhood education institutions affiliated with the Ministry of National Education across 81 provinces of Türkiye during the 2022–2023 academic year. The data were analyzed using SPSS 22.0. and AMOS 24.0. software. The results of the exploratory factor analysis revealed that the scale comprises six dimensions and 39 items. The findings from the confirmatory factor analysis indicated that the model's fit indices were within acceptable limits. The internal consistency coefficient (Cronbach’s Alpha) of the scale was calculated as .97. Based on the findings, it can be concluded that the developed Educational Data Literacy Competency Perception Scale is a valid and reliable instrument for assessing preschool teachers’ perceptions of their educational data literacy competencies.
References
- Aras, S. (2019). Improving early childhood teachers’ formative assessment practices: Transformative role of collaborative action research. Uluslararası Eğitim Programları ve Öğretim Çalışmaları Dergisi, 9(2), 221–240. https://doi.org/10.31704/ijocis.2019.010
- Athanases, S., Wahleithner, J., & Bennett, L. (2012). Learning to attend to culturally and linguistically diverse learners through teacher inquiry in teacher education. Teachers College Record, 114(7), 1-50. DOI:10.1177/016146811211400703
- Bradbury, A. (2018). Datafied at four: The role of data in the ‘schoolification’ of early childhood education in England. Learning, Media and Technology,44(1),7-21. DOI: 10.1080/17439884.2018.1511577
- Bredekamp, S., & Copple, C. (1997). Developmentally appropriate practice in early childhood programs. National Association for the Education of Young Children.
- Büyüköztürk, Ş. (2002). Sosyal bilimler için veri analizi el kitabı, Pagem Yayıncılık.
- Büyüköztürk, Ş., Kılıç Çakmak, E., Akgün, Ö., Karadeniz, Ş., & Demirel, F. (2020). Eğitimde bilimsel araştırma yöntemleri. Ankara: Pegem Akademi.
- Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.).
Cooper, A., Klinger, D. A., & McAdie, P. (2017). What do teachers need? An exploration of evidence-informed practice for classroom assessment in Ontario. Educational Research, 59(2), 190–208. https://doi.org/10.1080/00131881.2017.1310392
- Data Quality Campaign. (2014). The Art of Making Data Work: A Framework for Building Capacity to Use Student Data.
- Datnow, A., & Park, V. (2019). Professional collaboration with purpose: Teacher learning for equitable and excellent schools. Routledge.
- DeVellis, R. F. (2021). Scale Development: Theory and Applications (5th ed.). Sage Publications.
Doğan, E. (2021). Okul yönetiminde veriye dayalı karar verme sürecinin yönetici görüşlerine göre değerlendirilmesi(Yayın No. 674382) (Doktora tezi, Gazi Üniversitesi). YÖK Ulusal Tez Merkezi. https://tez.yok.gov.tr
- Doğan, E. & Demirbolat, A.O.(2021). Data-driven Decision-Making in Schools Scale: A Study of Validity and Reliability. International Journal of Curriculum and Instruction,13(1), 507–523. https://files.eric.ed.gov/fulltext/EJ1285547.pdf
- Earl, L. M., & Katz, S. (2006). Leading schools in a data-rich world: Harnessing data for school improvement. Corwin Press.
- Field, A. (2018). Discovering statistics using IBM SPSS statistics (5th ed.). SAGE Publications.
Fontichiaro, K., & Johnston, M. P. (2020). Rapid shifts in educators’ perceptions of data literacy priorities. Journal of Media Literacy Education, 12(3), 75-87. https://doi.org/10.23860/JMLE-2020- 12-3-7
- Gebre, E. H. (2022). Conceptions and perspectives of data literacy in secondary education. British Journal of Educational Technology, 53(5), 1080–1095. http://dx.doi.org/10.1111/bjet.13246
- George, D., & Mallery, M. (2010). SPSS for Windows Step by Step: A Simple Guide and Reference, 17.0 update (10a ed.). Pearson
- Gürbüz, S. (2019). AMOS ile yapısal eşitlik modellemesi. Seçkin Yayıncılık
- Hamilton, L., Halverson, R., Jackson, S., Mandinach, E., Supovitz, J., & Wayman, J. (2009). Using student achievement data to support instructional decision making (NCEE 2009-4067). Washington, DC: National Center for Education Evaluation and Regional Assistance, Institute of Education Sciences, US Department of Education
- Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 155. https://doi.org/10.1080/10705519909540118
- Ikemoto, G. S., & Marsh, J. A. (2007). Cutting through the “data-driven” mantra: Different conceptions of data-driven decision making. Teachers College Record, 109(13), 105-131. DOI:10.1177/016146810710901310
- Kartal, M., & Bardakçı, S. (2018). SPSS ve AMOS uygulamalı örneklerle güvenirlik ve geçerlik analizleri. Ankara: Akademisyen Kitabevi.
- Kline, P. (2015). A handbook of test construction: Introduction to psychometric design. Routledge.
- Lai M., Schildkamp K. (2013) Data-based Decision Making: An Overview. In: Schildkamp K., Lai M., Earl L. (eds) Data-based Decision Making in Education. Studies in Educational Leadership, vol 17. Springer, Dordrecht
- Love, N. (2012). Data literacy for teachers. Hawker Brownlow Education.
- Love, N., Stiles, K. E., Mundry, S., & DiRanna, K. (2008). A data coach's guide to improving learning for all students: Unleashing the power of collaborative inquiry. Corwin Press.
- Mandinach, E. B. (2012). A Perfect Time for Data Use: Using Data Driven Decision Making to Inform Practice. Educational Psychologist, 47(2), 71–85. http://doi.org/10.1080/00461520.2012.667064
- Mandinach, E. B., & Gummer, E. S. (2012). Navigating the landscape of data literacy: It IS complex. Washington, DC/Portland, OR: WestEd/Education Northwest.
Mandinach, E. B., & Gummer, E. S. (2013). A systemic view of implementing data literacy in educator preparation. Educational Researcher, 42(1), 30–37. https://doi.org/10.310 2/0013189X12459803
- Mandinach, E. B., & Gummer, E. S. (2016).Data Literacy for Educators: Making It Count in Teacher Preparation and Practice. Teachers College Press.
- Marsh, J. A. (2012). Interventions promoting educators’ use of data: Research insights and gaps. Teachers College Record, 114(11), 1–48. DOI:10.1177/016146811211401106
- McAfee, O. ve Leong, D. J. (2012). Erken çocukluk döneminde gelişim ve öğrenmenin değerlendirilmesi ve desteklenmesi (B. Ekinci, Çev.). Nobel Yayıncılık.
- McDowall, A., Mills, C., Cawte, K., & Miller, J. (2020). Data use as the heart of data literacy: An exploration of pre-service teachers’ data literacy practices in a teaching performance assessment. Asia-Pacific Journal of Teacher Education, 1–16. doi:10.1080/1359866x.2020.1777529
- McLachlan, C., Edwards, S., Margrain, V., & McLean, K. (2013). Children’s learning and development: Contemporary assessment in the early years. Palgrave Macmillan.
- McLachlan, C., McLaughlin, T., Cherrington, S., & Aspden, K. (2023). Using data systems to inform early childhood practice. In Assessment and data systems in early childhood settings: Theory and practice (pp. 3–25). Springer.
- Means, B., Chen, E., DeBarger, A., & Padilla, C. (2011). Teachers’ ability to use data to inform instruction: Challenges and supports. U.S. Department of Education, Office of Planning, Evaluation, and Policy Development.
- Mertler, C. A. (2007). Interpreting standardized test scores: Strategies for data-driven instructional decision making. Sage Publications.
- Naillioğlu Kaymak, M. & Doğan, E. (2023). Veri okuryazarlığı ölçeği’nin Türk kültürüne uyarlanması, Trakya Eğitim Dergisi, 13(2), 1282-1297.
- National Association for the Education of Young Children & National Association of Early Childhood Specialists in State Departments of Education. (1990). Guidelines for appropriate curriculum content and assessment in programs serving children ages 3 through 8. (Position statement). Washington, DC: NAEYC.
- North Carolina Department of Public Instruction. (2013). Data Literacy. Retrieved from http://ites.ncdpi.wikispaces.net/Data+Literacy
- Ocak, G., Olur, B., & Kutlu Çakın, A. (2022). Data literacy scale development for high school students. Research on Humanities and Social Sciences, 12(8), 1-11. https://doi.org/10.7176/RHSS/12-8-02
- Öz, S., & Özdemir, A. (2022). Validity And Reliability Study on The Development of Data Literacy Scale For Educators. International Journal of Contemporary Educational Research, 9(3), 649-661. https://doi.org/10.33200/ijcer.1079774
- Prado, C. J., & Marzal, A. M. (2013). Incorporating Data Literacy into Information Literacy Programs: Core Competencies and Contents. Libri, 63(2), 123–134. http://doi.org/10.1515/libri-2013-0010
- Reeves, P. L., & Burt, W. L. (2006). Challenges in data-based decisionmaking: Voices from principals. Educational Horizons, 85(1), 65-71. https://files.eric.ed.gov/fulltext/EJ750644.pdf
- Ridsdale, C., Rothwell, J., Smit, M., Ali-Hassan, H., Bliemel, M., Irvine, D., … Wuetherick, B. (2015). Strategies and Best Practices for Data Literacy Education. Dalhousie University.
- Schildkamp, K., & Lai, M. K. (2013). Data-based decision making: Conclusions and a data use framework. In K.
Schildkamp, M. K. Lai, & L. Earl (Eds.), Data-based decision making in education: Challenges and opportunities (pp. 177–191). Springer. http://dx.doi.org/10.1007/978-94-007-4816-3_10
- Tabachnick, B. G., & Fidell, L. S. (2019). Using multivariate statistics (7th ed.). Pearson.
- Vahey, P., Rafanan, K., Patton, C., Swan, K., van’t Hooft, M., Kratcoski, A., & Stanford, T. (2012). A cross-disciplinary approach to teaching data literacy and proportionality. Educational Studies in Mathematics, 81, 179–205. https://doi.org/10.1007/s10649-012-9392-z
- Wolff, A., Gooch, D., Cavero Montaner, J. J., Rashid, U., & Kortuem, G. (2016). Creating an understanding of data literacy for a data-driven society. The Journal of Community Informatics, 12(3), 9–26. Retrieved from: https://openjournals.uwaterloo.ca/index.php/JoCI/article/view/3275/4298
Okul Öncesi Öğretmenleri İçin Eğitsel Veri Okuryazarlığı Yeterlik Algısı Ölçeği: Geçerlik ve Güvenirlik Çalışması
Year 2025,
Volume: 58 Issue: 2, 591 - 650, 16.08.2025
Fadime Biçici Uslu
,
Selda Aras
,
Arif Yılmaz
Abstract
Eğitsel veri okuryazarlığı, sınıf içi ve okul düzeyinde öğretme-öğrenme süreçlerini sürekli iyileştirmek amacıyla çeşitli veri türlerini doğru biçimde gözlemleme, analiz etme ve bu verilere uygun yanıtlar üretme yetkinliği olarak tanımlanmaktadır. Bu araştırmada, okul öncesi öğretmenlerinin eğitsel veri okuryazarlığına ilişkin yeterlik algılarını ölçmek amacıyla geçerli ve güvenilir bir ölçme aracı geliştirilmesi hedeflenmiştir. Araştırmada nicel araştırma yaklaşımı benimsenmiştir. Çalışma grubu, 2022–2023 eğitim-öğretim yılında Türkiye’nin 81 ilinde Millî Eğitim Bakanlığına bağlı okul öncesi eğitim kurumlarında görev yapan 579 öğretmenden oluşmaktadır. Veriler, SPSS 22.0 ve AMOS 24.0 programlarıyla analiz edilmiştir. Açıklayıcı faktör analizi sonucunda, ölçeğin altı boyut ve 39 maddeden oluştuğu belirlenmiştir. Doğrulayıcı faktör analizi bulguları, modelin uyum indekslerinin kabul edilebilir sınırlar içinde olduğunu göstermektedir. Ölçeğin iç tutarlılık katsayısı (Cronbach Alfa) .97 olarak hesaplanmıştır. Elde edilen bulgular doğrultusunda, geliştirilen Eğitsel Veri Okuryazarlığı Yeterlik Algısı Ölçeğinin (EVOYAÖ), okul öncesi öğretmenlerinin yeterlik algılarını değerlendirmek için geçerli ve güvenilir bir araç olarak kullanılabileceği sonucuna ulaşılmıştır.
References
- Aras, S. (2019). Improving early childhood teachers’ formative assessment practices: Transformative role of collaborative action research. Uluslararası Eğitim Programları ve Öğretim Çalışmaları Dergisi, 9(2), 221–240. https://doi.org/10.31704/ijocis.2019.010
- Athanases, S., Wahleithner, J., & Bennett, L. (2012). Learning to attend to culturally and linguistically diverse learners through teacher inquiry in teacher education. Teachers College Record, 114(7), 1-50. DOI:10.1177/016146811211400703
- Bradbury, A. (2018). Datafied at four: The role of data in the ‘schoolification’ of early childhood education in England. Learning, Media and Technology,44(1),7-21. DOI: 10.1080/17439884.2018.1511577
- Bredekamp, S., & Copple, C. (1997). Developmentally appropriate practice in early childhood programs. National Association for the Education of Young Children.
- Büyüköztürk, Ş. (2002). Sosyal bilimler için veri analizi el kitabı, Pagem Yayıncılık.
- Büyüköztürk, Ş., Kılıç Çakmak, E., Akgün, Ö., Karadeniz, Ş., & Demirel, F. (2020). Eğitimde bilimsel araştırma yöntemleri. Ankara: Pegem Akademi.
- Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.).
Cooper, A., Klinger, D. A., & McAdie, P. (2017). What do teachers need? An exploration of evidence-informed practice for classroom assessment in Ontario. Educational Research, 59(2), 190–208. https://doi.org/10.1080/00131881.2017.1310392
- Data Quality Campaign. (2014). The Art of Making Data Work: A Framework for Building Capacity to Use Student Data.
- Datnow, A., & Park, V. (2019). Professional collaboration with purpose: Teacher learning for equitable and excellent schools. Routledge.
- DeVellis, R. F. (2021). Scale Development: Theory and Applications (5th ed.). Sage Publications.
Doğan, E. (2021). Okul yönetiminde veriye dayalı karar verme sürecinin yönetici görüşlerine göre değerlendirilmesi(Yayın No. 674382) (Doktora tezi, Gazi Üniversitesi). YÖK Ulusal Tez Merkezi. https://tez.yok.gov.tr
- Doğan, E. & Demirbolat, A.O.(2021). Data-driven Decision-Making in Schools Scale: A Study of Validity and Reliability. International Journal of Curriculum and Instruction,13(1), 507–523. https://files.eric.ed.gov/fulltext/EJ1285547.pdf
- Earl, L. M., & Katz, S. (2006). Leading schools in a data-rich world: Harnessing data for school improvement. Corwin Press.
- Field, A. (2018). Discovering statistics using IBM SPSS statistics (5th ed.). SAGE Publications.
Fontichiaro, K., & Johnston, M. P. (2020). Rapid shifts in educators’ perceptions of data literacy priorities. Journal of Media Literacy Education, 12(3), 75-87. https://doi.org/10.23860/JMLE-2020- 12-3-7
- Gebre, E. H. (2022). Conceptions and perspectives of data literacy in secondary education. British Journal of Educational Technology, 53(5), 1080–1095. http://dx.doi.org/10.1111/bjet.13246
- George, D., & Mallery, M. (2010). SPSS for Windows Step by Step: A Simple Guide and Reference, 17.0 update (10a ed.). Pearson
- Gürbüz, S. (2019). AMOS ile yapısal eşitlik modellemesi. Seçkin Yayıncılık
- Hamilton, L., Halverson, R., Jackson, S., Mandinach, E., Supovitz, J., & Wayman, J. (2009). Using student achievement data to support instructional decision making (NCEE 2009-4067). Washington, DC: National Center for Education Evaluation and Regional Assistance, Institute of Education Sciences, US Department of Education
- Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 155. https://doi.org/10.1080/10705519909540118
- Ikemoto, G. S., & Marsh, J. A. (2007). Cutting through the “data-driven” mantra: Different conceptions of data-driven decision making. Teachers College Record, 109(13), 105-131. DOI:10.1177/016146810710901310
- Kartal, M., & Bardakçı, S. (2018). SPSS ve AMOS uygulamalı örneklerle güvenirlik ve geçerlik analizleri. Ankara: Akademisyen Kitabevi.
- Kline, P. (2015). A handbook of test construction: Introduction to psychometric design. Routledge.
- Lai M., Schildkamp K. (2013) Data-based Decision Making: An Overview. In: Schildkamp K., Lai M., Earl L. (eds) Data-based Decision Making in Education. Studies in Educational Leadership, vol 17. Springer, Dordrecht
- Love, N. (2012). Data literacy for teachers. Hawker Brownlow Education.
- Love, N., Stiles, K. E., Mundry, S., & DiRanna, K. (2008). A data coach's guide to improving learning for all students: Unleashing the power of collaborative inquiry. Corwin Press.
- Mandinach, E. B. (2012). A Perfect Time for Data Use: Using Data Driven Decision Making to Inform Practice. Educational Psychologist, 47(2), 71–85. http://doi.org/10.1080/00461520.2012.667064
- Mandinach, E. B., & Gummer, E. S. (2012). Navigating the landscape of data literacy: It IS complex. Washington, DC/Portland, OR: WestEd/Education Northwest.
Mandinach, E. B., & Gummer, E. S. (2013). A systemic view of implementing data literacy in educator preparation. Educational Researcher, 42(1), 30–37. https://doi.org/10.310 2/0013189X12459803
- Mandinach, E. B., & Gummer, E. S. (2016).Data Literacy for Educators: Making It Count in Teacher Preparation and Practice. Teachers College Press.
- Marsh, J. A. (2012). Interventions promoting educators’ use of data: Research insights and gaps. Teachers College Record, 114(11), 1–48. DOI:10.1177/016146811211401106
- McAfee, O. ve Leong, D. J. (2012). Erken çocukluk döneminde gelişim ve öğrenmenin değerlendirilmesi ve desteklenmesi (B. Ekinci, Çev.). Nobel Yayıncılık.
- McDowall, A., Mills, C., Cawte, K., & Miller, J. (2020). Data use as the heart of data literacy: An exploration of pre-service teachers’ data literacy practices in a teaching performance assessment. Asia-Pacific Journal of Teacher Education, 1–16. doi:10.1080/1359866x.2020.1777529
- McLachlan, C., Edwards, S., Margrain, V., & McLean, K. (2013). Children’s learning and development: Contemporary assessment in the early years. Palgrave Macmillan.
- McLachlan, C., McLaughlin, T., Cherrington, S., & Aspden, K. (2023). Using data systems to inform early childhood practice. In Assessment and data systems in early childhood settings: Theory and practice (pp. 3–25). Springer.
- Means, B., Chen, E., DeBarger, A., & Padilla, C. (2011). Teachers’ ability to use data to inform instruction: Challenges and supports. U.S. Department of Education, Office of Planning, Evaluation, and Policy Development.
- Mertler, C. A. (2007). Interpreting standardized test scores: Strategies for data-driven instructional decision making. Sage Publications.
- Naillioğlu Kaymak, M. & Doğan, E. (2023). Veri okuryazarlığı ölçeği’nin Türk kültürüne uyarlanması, Trakya Eğitim Dergisi, 13(2), 1282-1297.
- National Association for the Education of Young Children & National Association of Early Childhood Specialists in State Departments of Education. (1990). Guidelines for appropriate curriculum content and assessment in programs serving children ages 3 through 8. (Position statement). Washington, DC: NAEYC.
- North Carolina Department of Public Instruction. (2013). Data Literacy. Retrieved from http://ites.ncdpi.wikispaces.net/Data+Literacy
- Ocak, G., Olur, B., & Kutlu Çakın, A. (2022). Data literacy scale development for high school students. Research on Humanities and Social Sciences, 12(8), 1-11. https://doi.org/10.7176/RHSS/12-8-02
- Öz, S., & Özdemir, A. (2022). Validity And Reliability Study on The Development of Data Literacy Scale For Educators. International Journal of Contemporary Educational Research, 9(3), 649-661. https://doi.org/10.33200/ijcer.1079774
- Prado, C. J., & Marzal, A. M. (2013). Incorporating Data Literacy into Information Literacy Programs: Core Competencies and Contents. Libri, 63(2), 123–134. http://doi.org/10.1515/libri-2013-0010
- Reeves, P. L., & Burt, W. L. (2006). Challenges in data-based decisionmaking: Voices from principals. Educational Horizons, 85(1), 65-71. https://files.eric.ed.gov/fulltext/EJ750644.pdf
- Ridsdale, C., Rothwell, J., Smit, M., Ali-Hassan, H., Bliemel, M., Irvine, D., … Wuetherick, B. (2015). Strategies and Best Practices for Data Literacy Education. Dalhousie University.
- Schildkamp, K., & Lai, M. K. (2013). Data-based decision making: Conclusions and a data use framework. In K.
Schildkamp, M. K. Lai, & L. Earl (Eds.), Data-based decision making in education: Challenges and opportunities (pp. 177–191). Springer. http://dx.doi.org/10.1007/978-94-007-4816-3_10
- Tabachnick, B. G., & Fidell, L. S. (2019). Using multivariate statistics (7th ed.). Pearson.
- Vahey, P., Rafanan, K., Patton, C., Swan, K., van’t Hooft, M., Kratcoski, A., & Stanford, T. (2012). A cross-disciplinary approach to teaching data literacy and proportionality. Educational Studies in Mathematics, 81, 179–205. https://doi.org/10.1007/s10649-012-9392-z
- Wolff, A., Gooch, D., Cavero Montaner, J. J., Rashid, U., & Kortuem, G. (2016). Creating an understanding of data literacy for a data-driven society. The Journal of Community Informatics, 12(3), 9–26. Retrieved from: https://openjournals.uwaterloo.ca/index.php/JoCI/article/view/3275/4298