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Deneyimsel Öğrenme Ölçeğinin Türkçeye Uyarlanması: Geçerlik ve Güvenirlik Çalışması

Year 2025, Volume: 10 Issue: 2, 142 - 157, 25.12.2025

İbrahim Serdar Kızıltepe , Tezcan Kartal

https://doi.org/10.47479/ihead.1656910

Abstract

Deneyimsel öğrenme, bireylerin kendi yaşantılarından edindikleri deneyimleri öğrenme sürecine dâhil etmeyi hedeflemektedir. Öğrenme, yalnızca bilişsel bir yapı değil, aynı zamanda deneyime dayalı bir süreçtir. Bu süreçte a) somut deneyim, b) yansıtıcı gözlem, c) soyut kavramsallaştırma ve d) aktif deneyimleme gibi çeşitli aşamalar takip edilerek deneyime dayalı öğrenme gerçekleşmektedir. Bu çalışmada Kolb’un deneyimsel öğrenme çerçevesinde, Su ve Cheng (2019) tarafından geliştirilen deneyime dayalı ölçme aracının Fen Bilgisi öğretmen adayları için uyarlanma çalışması yürütülmüştür. Bu çerçevede, kültürel uyarlama adımları titizlikle takip edilmiş ve ölçme aracının pilot çalışmaları gerçekleştirilmiştir. Araştırmada, 3 ve 4. sınıfta öğrenim görmekte olan Fen Bilgisi öğretmen adayları arasından basit seçkisiz örnekleme yöntemi ile veriler elde edilmiştir. Ölçeğin faktör yapısını değerlendirmek amacıyla açımlayıcı faktör analizi, faktör yapısının doğrulanması için ise doğrulayıcı faktör analizi yapılmıştır. Elde edilen bulgular doğrultusunda, ölçme aracının faktör yapısının uygun olduğu belirlenmiştir. Ölçek alt faktörleri ve ölçeğin geneli için hesaplanan cronbach alfa güvenirlik katsayılarının .776 ile .953 arasında değiştiği, faktör yüklerinin ise .30’un üzerinde olduğu görülmüştür. Bu kapsamda, ölçeğin hem genelinde hem de alt faktör düzeyinde geçerli ve güvenilir olduğu sonucuna ulaşılmıştır.

Keywords

Fen bilgisi öğretmen adayı Deneyimsel öğrenme Sanal laboratuvar

Ethical Statement

Bu çalışmada bilimsel ve etik kurallara tam olarak uyulduğunu beyan ederim. Araştırma, Kırşehir Ahi Evran Üniversitesi Fen ve Mühendislik Bilimleri Bilimsel Araştırma ve Yayın Etiği Kurulu tarafından değerlendirilmiş ve 15/03/2024 tarihli, E-51062476-204.01.07-00000619668 numaralı etik kurul onayı alınmıştır.

Supporting Institution

Bu çalışma, Kırşehir Ahi Evran Üniversitesi Bilimsel Araştırma Projeleri Koordinasyon Birimi (BAP) tarafından desteklenmektedir.

Project Number

EGT.A3.24.001

Thanks

Bu çalışma, Kırşehir Ahi Evran Üniversitesi Bilimsel Araştırma Projeleri Koordinasyon Birimi (BAP) tarafından desteklenen EGT.A3.24.001 numaralı doktora tezi projesi kapsamında gerçekleştirilmiştir. Sağladıkları destek için teşekkür ederiz.

References

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  • Haznedar, Ö. & Baran, B. (2012). Eğitim fakültesi öğrencileri için e-öğrenmeye yönelik genel bir tutum ölçeği geliştirme çalışması. Eğitim Teknolojisi Kuram ve Uygulama, 2(2), 42-59. https://doi.org/10.17943/etku.84225
  • Horzum, M. B. & Çakır, O. (2009). The validity and reliability study of the Turkish version of the online technologies self-efficacy scale. Educational Sciences: Theory and Practice, 9(3), 1343-1356.
  • 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), 1-55. https://doi.org/10.1080/10705519909540118
  • Jarmon, L., Traphagan, T., Mayrath, M. & Trivedi, A. (2009). Virtual world teaching, experiential learning, and assessment: An interdisciplinary communication course in Second Life. Computers & Education, 53(1), 169-182. https://doi.org/10.1016/j.compedu.2009.01.010
  • Jolliffe, I. T. (1972). Discarding variables in a principal component analysis. I: Artificial data. Journal of the Royal Statistical Society Series C: Applied Statistics, 21(2), 160-173. https://doi.org/10.2307/2346488
  • Jöreskog, K. G. & Sörbom, D. (1993). Lisrel 8: Structural equation modeling with the SIMPLIS command language. Hillsdale, NJ: Lawrence Erlbaum Associates Publishers.
  • Kalaycı, S. (2010). SPSS uygulamalı çok değiskenli istatistik teknikleri. Ankara: Asil Yayın Dağıtım.
  • Karagöz, Y. (2021). SPSS-AMOS-META uygulamalı nicel-nitel-karma bilimsel araştırma yöntemleri ve yayın etiği. Nobel Yayıncılık.
  • Kartal, T. (2024). The influence of pedagogical and epistemological beliefs on preservice teachers’ technology acceptance in Turkey: A structural equation modeling. Croatian Journal of Education, 26(2), 607-650. https://doi.org/10.15516/cje.v26i2.5313
  • Kartal, T. & Taşdemir, A. (2023). Fizik kavramlarının öğretiminde sanal laboratuvar uygulamaları ve ideal öğrenme ortamı. B. Gülbahar (Ed.), Cumhuriyetin 100. yılında eğitimde idealler üzerine (ss. 199-236). Eğitim Yayın Evi.
  • Kartal, T., Kartal, B. & Uluay, G. (2016). Technological pedagogical content knowledge self-assessment scale (TPACK-SAS) for pre-service teachers: Development, validity and reliability. International Journal of Eurasia Social Sciences, 7(23), 1-36.
  • Kartal, T., Kızıltepe, İ. S. & Kartal, B. (2022). Extending technology acceptance model with scientific epistemological and science teaching efficacy beliefs: A study with preservice teachers. Journal of Education in Science Environment and Health, 8(1), 1-16. https://doi.org/10.21891/jeseh.1055590
  • Kavlak, E. E. & Birhanlı, A. (2023). Fen bilimleri öğretmenlerinin COVID-19 uzaktan eğitim sürecinde sanal laboratuvar uygulamaları hakkındaki görüşlerinin incelenmesi. International Anatolia Academic Online Journal Social Sciences Journal, 9(2), 26-36. https://doi.org/10.12738/estp.2013.4.1913
  • Kaya, Z., Kaya, O. N. & Emre, I. (2013). Adaptation of technological pedagogical content knowledge scale to Turkish. Educational Sciences: Theory and Practice, 13(4), 2367-2377. https://doi.org/10.12738/estp.2013.4.1913
  • Kline, R. B. (2023). Principles and Practice of Structural Equation Modeling. New York: The Guilford Press
  • Kolb, A. Y. & Kolb, D. A. (2005). Learning styles and learning spaces: Enhancing experiential learning in higher education. Academy of Management Learning & Education, 4(2), 193-212. https://doi.org/10.5465/amle.2005.17268566
  • Kolb, D. A. (1984). Experiential learning: Experience as the source of learning. Englewood Cliffs, NJ: Prentice Hall.
  • Le, Q. T., Pedro, A. & Park, C. S. (2015). A social virtual reality based construction safety education system for experiential learning. Journal of Intelligent & Robotic Systems, 79, 487-506. https://doi.org/10.1007/s10846-014-0112-z
  • Lindstrøm, C., Rajpaul, V., Brendehaug, M. & Engel, M. C. (2016). Perspectives on astronomy: probing Norwegian pre-service teachers and middle school students. arXiv preprint arXiv:1601.07445. https://doi.org/10.48550/arXiv.1601.07445
  • Menon, D., Chandrasekhar, M., Kosztin, D. & Steinhoff, D. C. (2020). Impact of mobile technology‐based physics curriculum on preservice elementary teachers' technology self‐efficacy. Science Education, 104(2), 252-289. https://doi.org/10.1002/sce.21554
  • McGowan, A. L. (2016). Impact of one-semester outdoor education programs on adolescent perceptions of self-authorship. Journal of Experiential Education, 39(4), 386-411.
  • Morris, T. H. (2020). Experiential learning–a systematic review and revision of Kolb’s model. Interactive Learning Environments, 28(8), 1064-1077. https://doi.org/10.1080/10494820.2019.1570279
  • Öztürk, N. B., Eroğlu, M. & Kelecioğlu, H. (2015). A review of articles concerning scale adaptation in the field of education. Education and Science, 40(178). https://doi.org/10.15390/EB.2015.4091
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Adaptation of the Experiential Learning Scale to Turkish: A Validity and Reliability Study

Year 2025, Volume: 10 Issue: 2, 142 - 157, 25.12.2025

İbrahim Serdar Kızıltepe , Tezcan Kartal

https://doi.org/10.47479/ihead.1656910

Abstract

Experiential learning aims to incorporate individuals’ personal experiences into the learning process. Learning is not solely a cognitive construct but also a process based on experience. In this process, experiential learning occurs through various stages: a) concrete experience, b) reflective observation, c) abstract conceptualization, and d) active experimentation. Within Kolb’s experiential learning framework, this study involved the adaptation of an experiential learning measurement tool developed by Su and Cheng (2019) for pre-service science teachers. The cultural adaptation procedures were meticulously followed, and pilot studies of the measurement tool were conducted. Data were collected using a simple random sampling method from third- and fourth-year pre-service science teachers. Exploratory factor analysis was conducted to examine the factor structure of the scale, and confirmatory factor analysis was performed to verify the structure. Based on these findings, the factor structure of the measurement tool was found to be appropriate. The Cronbach’s alpha reliability coefficients calculated for the sub-factors and the entire scale ranged from .776 to .953, and the fit indices were above .30. In this context, the scale was concluded to be valid and reliable, both overall and at the subfactor level.

Keywords

Preservice science teacher Experiential learning Virtual laboratory

Project Number

EGT.A3.24.001

References

  • Aiello, P., D'Elia, F., Di Tore, S., & Sibilio, M. (2012). A constructivist approach to virtual reality for experiential learning. E-learning and Digital Media, 9(3), 317-324. https://doi.org/10.2304/elea.2012.9.3.317
  • Altun, A. & Mazman, S. G. (2012). Programlamaya ilişkin öz yeterlilik algısı ölçeğinin Türkçe formumun geçerlilik ve güvenirlik çalışması. Journal of Measurement and Evaluation in Education and Psychology, 3(2), 297-308.
  • Asad, M. M., Naz, A., Churi, P. & Tahanzadeh, M. M. (2021). Virtual reality as pedagogical tool to enhance experiential learning: A systematic literature review. Education Research International, 2021(1), 1-17. https://doi.org/10.1155/2021/7061623
  • Bandalos, D. L. (2018). Measurement theory and applications for the social sciences. Guilford Publications.
  • Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191-215. https://doi.org/10.1037/0033-295X.84.2.191
  • Bennett, D., Sunderland, N., Bartleet, B. L., & Power, A. (2016). Implementing and sustaining higher education service-learning initiatives: Revisiting Young et al.’s organizational tactics. Journal of Experiential Education, 39, 145–163. doi:10.1177/1053825916629987
  • Borsa, J. C., Damásio, B. F. & Bandeira, D. R. (2012). Cross-cultural adaptation and validation of psychological instruments: Some considerations. Paidéia (Ribeirão Preto), 22, 423-432. https://doi.org/10.1590/S0103-863X2012000300014
  • Broadbent, J. & Poon, W. L. (2015). Self-regulated learning strategies & academic achievement in online higher education learning environments: A systematic review. The Internet and Higher Education, 27, 1-13. https://doi.org/10.1016/j.iheduc.2015.04.007
  • Breunig, M. (2017). Experientially learning and teaching in a student-directed classroom. Journal of Experiential Education, 40, 213–230. doi:10.1177/1053825917690870
  • Browne, M. W. & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136−162). Newbury Park, CA: Sage. https://doi.org/10.1177/0049124192021002
  • Candan, D. G. & Gencel, İ. E. (2015). Öğretme motivasyonu ölçeği’ni Türkçe’ye uyarlama çalışması. Mehmet Akif Ersoy Üniversitesi Eğitim Fakültesi Dergisi, 1(36), 72-89.
  • Clem, J. M., Mennicke, A. M. & Beasley, C. (2014). Development and validation of the experiential learning survey. Journal of Social Work Education, 50(3), 490-506. https://doi.org/10.1080/10437797.2014.917900
  • Dalgarno, B. & Lee, M. J. (2010). What are the learning affordances of 3‐D virtual environments?. British Journal of Educational Technology, 41(1), 10-32. https://doi.org/10.1111/j.1467-8535.2009.01038.x
  • DeVellis, R. F. & Thorpe, C. T. (2021). Scale development: Theory and applications. Sage publications.
  • Erkuş, A. (2007). Ölçek geliştirme ve uyarlama çalışmalarında karşılaşılan sorunlar. Türk Psikoloji Bülteni, 13(40), 17-25. https://doi.org/10.31828/tpb134004
  • Fidan, M., Debbag, M. & Cukurbasi, B. (2020). Technology proficiency self-assessments of teachers becoming professional in the 21st century: A scale adaptation study. Pegem Journal of Education and Instruction, 10(2), 465-492. http://dx.doi.org/10.14527/pegegog.2020.016
  • Field, A. (2009). Discovering statistics using SPSS (and sex and drugs and rock 'n' roll) (3rd Edition). Washington DC: SAGE Publication.
  • Fraenkel, J. R., Wallen, N. E. & Hyun, H. H. (2011). Validity and reliability, how to design and evaluate research in science education (8th Ed.). Mc Graw–Hill Companies.
  • Glazier, J., Bolick, C. & Stutts, C. (2017). Unstable ground: Unearthing the realities of experiential education in teacher education. Journal of Experiential Education, 40, 231–248. https://doi.org/10.1177/1053825917712734
  • Gürsoy, G. & Göksun, D. O. (2019). The experiences of pre-service science teachers in educational content development using Web 2.0 Tools. Contemporary Educational Technology, 10(4), 338-357. https://doi.org/10.30935/cet.000000
  • Haznedar, Ö. & Baran, B. (2012). Eğitim fakültesi öğrencileri için e-öğrenmeye yönelik genel bir tutum ölçeği geliştirme çalışması. Eğitim Teknolojisi Kuram ve Uygulama, 2(2), 42-59. https://doi.org/10.17943/etku.84225
  • Horzum, M. B. & Çakır, O. (2009). The validity and reliability study of the Turkish version of the online technologies self-efficacy scale. Educational Sciences: Theory and Practice, 9(3), 1343-1356.
  • 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), 1-55. https://doi.org/10.1080/10705519909540118
  • Jarmon, L., Traphagan, T., Mayrath, M. & Trivedi, A. (2009). Virtual world teaching, experiential learning, and assessment: An interdisciplinary communication course in Second Life. Computers & Education, 53(1), 169-182. https://doi.org/10.1016/j.compedu.2009.01.010
  • Jolliffe, I. T. (1972). Discarding variables in a principal component analysis. I: Artificial data. Journal of the Royal Statistical Society Series C: Applied Statistics, 21(2), 160-173. https://doi.org/10.2307/2346488
  • Jöreskog, K. G. & Sörbom, D. (1993). Lisrel 8: Structural equation modeling with the SIMPLIS command language. Hillsdale, NJ: Lawrence Erlbaum Associates Publishers.
  • Kalaycı, S. (2010). SPSS uygulamalı çok değiskenli istatistik teknikleri. Ankara: Asil Yayın Dağıtım.
  • Karagöz, Y. (2021). SPSS-AMOS-META uygulamalı nicel-nitel-karma bilimsel araştırma yöntemleri ve yayın etiği. Nobel Yayıncılık.
  • Kartal, T. (2024). The influence of pedagogical and epistemological beliefs on preservice teachers’ technology acceptance in Turkey: A structural equation modeling. Croatian Journal of Education, 26(2), 607-650. https://doi.org/10.15516/cje.v26i2.5313
  • Kartal, T. & Taşdemir, A. (2023). Fizik kavramlarının öğretiminde sanal laboratuvar uygulamaları ve ideal öğrenme ortamı. B. Gülbahar (Ed.), Cumhuriyetin 100. yılında eğitimde idealler üzerine (ss. 199-236). Eğitim Yayın Evi.
  • Kartal, T., Kartal, B. & Uluay, G. (2016). Technological pedagogical content knowledge self-assessment scale (TPACK-SAS) for pre-service teachers: Development, validity and reliability. International Journal of Eurasia Social Sciences, 7(23), 1-36.
  • Kartal, T., Kızıltepe, İ. S. & Kartal, B. (2022). Extending technology acceptance model with scientific epistemological and science teaching efficacy beliefs: A study with preservice teachers. Journal of Education in Science Environment and Health, 8(1), 1-16. https://doi.org/10.21891/jeseh.1055590
  • Kavlak, E. E. & Birhanlı, A. (2023). Fen bilimleri öğretmenlerinin COVID-19 uzaktan eğitim sürecinde sanal laboratuvar uygulamaları hakkındaki görüşlerinin incelenmesi. International Anatolia Academic Online Journal Social Sciences Journal, 9(2), 26-36. https://doi.org/10.12738/estp.2013.4.1913
  • Kaya, Z., Kaya, O. N. & Emre, I. (2013). Adaptation of technological pedagogical content knowledge scale to Turkish. Educational Sciences: Theory and Practice, 13(4), 2367-2377. https://doi.org/10.12738/estp.2013.4.1913
  • Kline, R. B. (2023). Principles and Practice of Structural Equation Modeling. New York: The Guilford Press
  • Kolb, A. Y. & Kolb, D. A. (2005). Learning styles and learning spaces: Enhancing experiential learning in higher education. Academy of Management Learning & Education, 4(2), 193-212. https://doi.org/10.5465/amle.2005.17268566
  • Kolb, D. A. (1984). Experiential learning: Experience as the source of learning. Englewood Cliffs, NJ: Prentice Hall.
  • Le, Q. T., Pedro, A. & Park, C. S. (2015). A social virtual reality based construction safety education system for experiential learning. Journal of Intelligent & Robotic Systems, 79, 487-506. https://doi.org/10.1007/s10846-014-0112-z
  • Lindstrøm, C., Rajpaul, V., Brendehaug, M. & Engel, M. C. (2016). Perspectives on astronomy: probing Norwegian pre-service teachers and middle school students. arXiv preprint arXiv:1601.07445. https://doi.org/10.48550/arXiv.1601.07445
  • Menon, D., Chandrasekhar, M., Kosztin, D. & Steinhoff, D. C. (2020). Impact of mobile technology‐based physics curriculum on preservice elementary teachers' technology self‐efficacy. Science Education, 104(2), 252-289. https://doi.org/10.1002/sce.21554
  • McGowan, A. L. (2016). Impact of one-semester outdoor education programs on adolescent perceptions of self-authorship. Journal of Experiential Education, 39(4), 386-411.
  • Morris, T. H. (2020). Experiential learning–a systematic review and revision of Kolb’s model. Interactive Learning Environments, 28(8), 1064-1077. https://doi.org/10.1080/10494820.2019.1570279
  • Öztürk, N. B., Eroğlu, M. & Kelecioğlu, H. (2015). A review of articles concerning scale adaptation in the field of education. Education and Science, 40(178). https://doi.org/10.15390/EB.2015.4091
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There are 51 citations in total.

Details

Primary Language Turkish
Subjects Science Education
Journal Section Research Article
Authors

İbrahim Serdar Kızıltepe 0000-0002-6210-5372

Tezcan Kartal 0000-0001-7609-3555

Project Number EGT.A3.24.001
Submission Date March 13, 2025
Acceptance Date June 21, 2025
Publication Date December 25, 2025
Published in Issue Year 2025 Volume: 10 Issue: 2

Cite

APA Kızıltepe, İ. S., & Kartal, T. (2025). Deneyimsel Öğrenme Ölçeğinin Türkçeye Uyarlanması: Geçerlik ve Güvenirlik Çalışması. Ihlara Eğitim Araştırmaları Dergisi, 10(2), 142-157. https://doi.org/10.47479/ihead.1656910

Dear Colleagues,
We are very pleased to announce that the latest issue of IHEAD (Vol. 10- Iss. 2) has been released. We kindly want to express our speacial thanks to the editorial board members, reviewers, and authors for their invaluable contribution to this issue. Also, we are delighted to announce that the next issue (Vol. 11- Iss. 1) of the IHEAD will be available online in June, 2026. As of January, 2024, IHEAD has been accepting submissions in English along with Turkish. Handling your papers within the scope education for the next issue will be a great pleasure for us. Many thanks in advance for your contributions.
Editorial Board

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