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Üniversite Öğrencilerinin Çevrimiçi Sınavlara Yönelik Tutumlarına İlişkin Ölçek Geliştirme Çalışması

Yıl 2022, , 66 - 86, 27.03.2022
https://doi.org/10.32709/akusosbil.887141

Öz

Bu çalışma üniversite öğrencilerinin çevrimiçi sınavlara yönelik tutumlarını belirlemeye yönelik geçerli ve güvenilir bir ölçek geliştirmek amacıyla gerçekleştirilmiştir. Bu amaç doğrultusunda “Üniversite Öğrencileri İçin Çevrimiçi Sınavlara Yönelik Tutum Ölçeği (ÜÖÇSYTÖ)” şeklinde adlandırılan likert tipi bir ölçek sistematik bir süreçle geliştirilmiştir. Çalışma 2020-2021 eğitim öğretim yılında gerçekleştirilmiştir. Çalışmanın örneklemini farklı üniversitelerin farklı bölümlerinde öğrenim gören toplam 397 üniversite öğrencisi oluşturmaktadır. Faktör analizi öncesinde veri uygunluğu KMO (Kaiser-Meyer-Olkin) değeri ile belirlenmiştir. KMO değeri .831 olarak bulunmuştur. Cronbach-Alpha katsayısı .825 olarak belirlenmiştir. Ölçek Teknik Unsur, Önlem Alma, Bireysel Özellik ve Sınav Yapısı olarak adlandırılan dört boyuttan oluşmaktadır. Ölçeğin her bir alt boyutunun Cronbach Alpha değerleri ise sırasıyla; 0.74, 0.75, 0.70 ve 0.76 olarak bulunmuştur. Veri analizinde madde toplam analizi, t testi ve faktörler arası korelasyon analizi uygulanmış ve bu analizlerin sonuçlarının anlamlı olduğu bulunmuştur. Analizler sonucunda faktörler arası anlamlı pozitif bir ilişki olduğu belirlenmiştir. Ölçeğin toplam varyansın %52.940’ını açıkladığı belirlenmiştir. 21 maddeli 4 faktörlü ölçeğin doğrulayıcı faktör analizi ile yapı geçerliliği test edilmiştir. Çalışmada üniversite öğrencilerinin çevrimiçi sınavlara yönelik tutumlarını belirlemek amacıyla geçerli ve güvenilir bir ölçek geliştirilmiştir.

Kaynakça

  • Ağır, F. (2007). Uzaktan eğitime karşı tutum ölçeği geliştirmeye yönelik geçerlilik ve güvenirlik çalışması. Education Sciences, 3(2), 128-139.
  • Allen, M. (2017). The sage encyclopedia of communication research methods (Vols. 1-4). Thousand Oaks, CA: SAGE Publications. DOI: 10.4135/9781483381411.
  • Arend, B. D. (2007). Course assessment practices and student learning strategies in online courses. Journal of Asynchronous Learning Networks, 11(4), 3-17. DOI: http://dx.doi.org/10.24059/olj.v11i4.1712.
  • Axinn, W. G., Fricke, T. E., and Thornton, A. (1991). The microdemographic community-study approach: Improving survey data by integrating the ethnographic method. Sociological Methods & Research, 20(2), 187-217.
  • Baysak, E., Kaya, F. D., Dalgar, I., & Candansayar, S. (2016). Online game addiction in a sample from Turkey: Development and validation of the Turkish version of game addiction scale. Klinik Psikofarmakoloji Bülteni-Bulletin of Clinical Psychopharmacology, 26(1), 21-31.DOI: 10.5455/bcp.20150502073016.
  • Bearden, W. O., & Netemeyer, R. G. (1999). Handbook of marketing scales: Multi-item measures for marketing and consumer behavior research. Los Angles: Sage Publications.
  • Brown, J.D. (2001). Statistics Corner: Questions and answers about language testing statistics: What is an eigenvalue? JALT Testing & Evaluation SIG Newsletter, 5 (1), 15 – 19.
  • Brown, T.A. (2006). Confirmatory factor analysis for applied research. New York: Guilford Press.
  • Clyman, S.G. (1990). Orr NA. Status report on the NBME’s computer-based testing. Acad Med. (65), 235–41.
  • Creswell, J. W. (2014). A concise introduction to mixed methods research. SAGE Publications.
  • Çakmak, E. K., Çebi, A., and Kan, A. (2014). E-öğrenme ortamlarına yönelik sosyal bulunuşluk ölçeği geliştirme çalışması. Kuram ve Uygulamada Eğitim Bilimleri, 14(2), 755-768.
  • Çelen, F. K., Çelik, A. & Seferoglu, S. S. (2011). Yükseköğretimde çevrim-içi öğrenme: Sistemde yaşanan sorunlar ve çözüm önerileri. Journal of European Education, 1(1), 25-34.
  • Dirks, M. (1998). How is assessment being done in distance learning? Retrieved January, 3, 2021 from ERIC Database.
  • Fırat, M. (2016). Measuring the e-learning autonomy of distance education students. Open Praxis, 8(3), 191-201.
  • Forsyth, D. R., Archer, C. R. (1997). Technologically assisted instruction and student mastery, motivation, and matriculation. Teaching of Psychology, 24, 207–212.
  • Galante, D. J. (2002). Web-based mathematics: An examination of assessment strategies implemented in the online mathematics classroom (pp. 1-189). Illinois State University. Retrieved January, 3, 2021 from https://www.proquest.com/docview/305573922
  • Gatignon, H. (2010). Confirmatory factor analysis in statistical analysis of management data (pp. 59-122). New York, NY Springer
  • Ghozali, I & Fuad, (2014). Structural equation modeling: theory, concepts and applications with the LISREL program. Semarang: Badan Penerbit Universitas Diponegoro.
  • Guest, G., Bunce, A., & Johnson, L. (2006). How many interviews are enough? An experiment with data saturation and variability. Field Methods, 18(1), 59-82.
  • Hayton, J. C., Allen, D. G., and Scarpello, V. (2004). Factor retention decisions in exploratory factor analysis: A tutorial on parallel analysis. Organizational Research Methods, 7(2), 191-205.
  • Henseler, J., Ringle, C. M., and Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In New challenges to international marketing. Emerald Group Publishing Limited.
  • Ilgaz, H., & Aşkar, P. (2009). Çevrimiçi uzaktan eğitim ortamında topluluk hissi ölçeği geliştirme çalışması. Turkish Journal of Computer and Mathematics Education, 1(1), 27-35.
  • James, R. (2016). Tertiary student attitudes to invigilated, online summative examinations. International Journal of Educational Technology in Higher Education, 13(1), 1-13.
  • Jegede, O. J., Fraser, B., and Curtin, D. F. (1995). The development and validation of a distance and open learning environment scale. Educational Technology Research and Development, 89-94.
  • Karal, H., & Kokoç, M. (2010). Üniversite öğrencilerinin sosyal ağ siteleri kullanım amaçlarını belirlemeye yönelik bir ölçek geliştirme çalışması. Türk Bilgisayar ve Matematik Eğitimi Dergisi, 1(3), 251-263.
  • Kınalıoğlu, İ. H., & Güven, Ş. (2011). Uzaktan eğitim sisteminde öğrenci başarısının ölçülmesinde karşılaşılan güçlükler ve çözüm önerileri. XIII. Akademik Bilişim Konferansı, 2 - 4 Şubat 2011 İnönü Üniversitesi, Malatya.
  • Kışla, T. (2005). Üniversite öğrencilerinin uzaktan eğitime yönelik tutumlarının incelenmesi. (Yayımlanmamış Yüksek Lisans Tezi). Ege Üniversitesi, Sosyal Bilimler Enstitüsü, İzmir
  • Latif, N. A. I. A., Abidin, I. M. Z., Azaman, N., Jamaludin, N., & Mokhtar, A. A. (2019, June). A Feature Extraction Technique Based on Factor Analysis for Pulsed Eddy Current Defects Categorization. In IOP Conference Series: Materials Science and Engineering (Vol. 554, No. 1, p. 012001). IOP Publishing.
  • Leavy, P. (2017). Research design: Quantitative, qualitative, mixed methods, arts‐based, and community‐based participatory research approaches. New York: The Guilford Press.
  • Ledesma, R. D., Valero-Mora, P., and Macbeth, G. (2015). The scree test and the number of factors: a dynamic graphics approach. The Spanish Journal of Psychology, 18. Article E11. https://doi.org/10.1017/sjp.2015.13
  • Liang, X., & Creasy, K. (2004). Classroom assessment in web-based instructional environment: Instructors’ experience. Practical Assessment, Research, and Evaluation, 9(1), 7. https://doi.org/10.7275/84mr-wp41
  • Luecht R.M., Hadadi A., Swanson D.B., and Case S.M. (1998). A comparative study of a comprehensive basic sciences test using paper-and-pencil and computerized formats. Acad Med.73(10),51–53.
  • Marsh, H. W., and Hocevar, D. (1988). A new, more powerful approach to multitrait-multimethod analyses: Application of second-order confirmatory factor analysis. Journal of Applied Psychology, 73(1), 107-117.
  • Martin, C. R., & Newell, R. J. (2004). Factor structure of the hospital anxiety and depression scale in individuals with facial disfigurement. Psychology, Health & Medicine, 9(3), 327-336.
  • Onwuegbuzie, A. J., and Collins, K. M. (2007). A typology of mixed methods sampling designs in social science research. Qualitative Report, 12(2), 281-316.
  • Parlak, Ö. (2007). İnternet temelli uzaktan eğitimde öğrenci doyumu ölçeği. Journal of Educational Sciences and Practices, 6(11), 53-72.
  • Patel, M. C., & Chauhan, N. B. (2012). Attitude towards application of distance education in agriculture and allied field-a scale development. Indian Research Journal on Extension Education, 12(1), 71-72
  • Perry, J. L., Nicholls, A. R., Clough, P. J., andCrust, L. (2015). Assessing model fit: Caveats and recommendations for confirmatory factor analysis and exploratory structural equation modeling. Measurement in Physical Education and Exercise Science, 19(1), 12-21.
  • Peterson, R. A. (2000). A meta-analysis of variance accounted for and factor loadings in exploratory factor analysis. Marketing Letters, 11(3), 261-275.
  • Riadi, E. (2018). SEM statistics: structural equation modeling with LISREL. Yogyakarta: Penerbit Andi.
  • Robles, M. and Braathen, S. (2002). Online assessment techniques. Delta Pi Epsilon Journal, 44(1), 39-49. Retrieved January 3, 2021 from https://www.learntechlib.org/p/93435/.
  • Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of Psychological Research Online, 8(2), 23-74.
  • Schumacker, R. E., and Lomax, R. G. (2010). A beginner’s guide to structural equation modeling (3rd ed.). New York, NY: Routledge.
  • Seçer, İ., Halmatov, S., ve Gençdoğan, B. (2013). Duygusal tepkisellik ölçeğinin Türkçeye uyarlanması: güvenirlik ve geçerlilik çalışması. Sakarya University Journal of Education, 3(1), 77-89.
  • Shraim, K. (2019). Online examination practices in higher education ınstitutions: learners’ perspectives. Turkish Online Journal of Distance Education, 20(4), 185-196. https://doi.org/10.17718/tojde.640588.
  • Sırakaya, M., Sırakaya, D. A., & Çakmak, E. K. (2015).Uzaktan eğitim öğrencilerinin çevrimiçi sınava yönelik tutum düzeylerinin incelenmesi. Kastamonu Eğitim Dergisi, 23(1), 87-104.
  • Sivo, S. A., Fan, X., Witta, E. L., & Willse, J. T. (2006). The search for “optimal” cutoff properties: Fit index criteria in structural equation modeling. The Journal of Experimental Education, 74(3), 267-288.
  • Sorensen, C. (2012). Learning online at the K-12 level: A parent/guardian perspective. International Journal of Instructional Media, 39(4), 297-308
  • Tabachnick, B. G., & Fidell, L. S. (1996). Using multivariate statistics (3rd Ed.). New York: Harper Collins.
  • Tanhan, F., & Çam, Z. (2011). Öğretmenlere yönelik yıldırma ölçeğinin geçerlik ve güvenirliğnin yeniden belirlenmesi. Cukurova University Faculty of Education Journal, 40(1), 87-90.
  • Tanyıldızı, M. ve Semerci, Ç. (2005). Çevrimiçi eğitim uygulamalarına ilişkin öğretim elemanı ve öğrenci görüşlerinin belirlenmesi. Türk Eğitim Bilimleri Dergisi, 3(2), 192-216.
  • Usta, İ., Uysal, Ö. and Okur, M. R. (2016). Çevrimiçi öğrenme tutum ölçeği: geliştirilmesi, geçerliği ve güvenirliği. &
  • Uzunboylu, H., & Özdamli, F. (2011). Teacher perception for m‐learning: scale development and teachers’ perceptions. Journal of Computer Assisted Learning, 27(6), 544-556.
  • Walker, S. L., and Fraser, B. J. (2005). Development and validation of an instrument for assessing distance education learning environments in higher education: The Distance Education Learning Environments Survey (DELES). Learning Environments Research, 8(3), 289-308.
  • Wang, Y. S., Wang, H. Y., and Shee, D. Y. (2007). Measuring e-learning systems success in an organizational context: Scale development and validation. Computers in Human Behavior, 23(4), 1792-1808.
  • White, R. J. and Hammer, C. A. (2000). Quiz-o-Matic: A free Web-based tool for construction of self-scoring on-line quizzes. Behavior Research Methods, Instruments, & Computers, 32(2), 250-253. DOI.10.3758/BF03207791.
  • Yee, N., Ducheneaut, N., and Nelson, L. (2012, May). Online gaming motivations scale: development and validation. In Proceedings of the SIGCHI Conference On Human Factors in Computing Systems (pp. 2803-2806).
  • Yong, A. G., and Pearce, S. (2013). A beginner’s guide to factor analysis: Focusing on exploratory factor analysis. Tutorials in Quantitative Methods for Psychology, 9(2), 79-94.
  • Yunkul, E., & Cankaya, S. (2017). Students’ attitudes towards Edmodo, a social learning network: A scale development study. Turkish Online Journal of Distance Education, 18(2), 16-29.

A Scale Development Research for Undergraduate Students’ Attitudes towards Online Exams

Yıl 2022, , 66 - 86, 27.03.2022
https://doi.org/10.32709/akusosbil.887141

Öz

This study aims to develop a scale to determine undergraduate students’ attitudes towards online exams. Depending on this framework, the scale was developed through a systematic scale development process. The study was conducted in 2020-2021 academic year. The sample of this study consists of 397 undergraduate students of different universities from different departments. The Cronbach-Alpha was found as .825. The scale consists of four dimensions named Technical Element, Taking Precautions, Individual Feature and Exam Structure. Cronbach Alpha values of sub-dimensions are respectively; 0.74, 0.75, 0.70 and 0.76. T test, based on the lower-upper group mean difference, item-total analysis and correlation analysis between factors were applied and the results of these analyzes were found to be significant. Correlation analysis indicated that there is a positive meaningful relationship among factors. For the appropriateness of data to factor analysis the value of Kaiser-Meyer-Olkin. (KMO) was found .831. Total variance of 52.940 % was explained. Explanatory factor analysis indicated that the scale has four dimensions with 21 items. For construct validity confirmatory factor analysis was used. Results indicate that scale was valid and reliable to determine undergraduate students’ attitude towards online exams. 

Kaynakça

  • Ağır, F. (2007). Uzaktan eğitime karşı tutum ölçeği geliştirmeye yönelik geçerlilik ve güvenirlik çalışması. Education Sciences, 3(2), 128-139.
  • Allen, M. (2017). The sage encyclopedia of communication research methods (Vols. 1-4). Thousand Oaks, CA: SAGE Publications. DOI: 10.4135/9781483381411.
  • Arend, B. D. (2007). Course assessment practices and student learning strategies in online courses. Journal of Asynchronous Learning Networks, 11(4), 3-17. DOI: http://dx.doi.org/10.24059/olj.v11i4.1712.
  • Axinn, W. G., Fricke, T. E., and Thornton, A. (1991). The microdemographic community-study approach: Improving survey data by integrating the ethnographic method. Sociological Methods & Research, 20(2), 187-217.
  • Baysak, E., Kaya, F. D., Dalgar, I., & Candansayar, S. (2016). Online game addiction in a sample from Turkey: Development and validation of the Turkish version of game addiction scale. Klinik Psikofarmakoloji Bülteni-Bulletin of Clinical Psychopharmacology, 26(1), 21-31.DOI: 10.5455/bcp.20150502073016.
  • Bearden, W. O., & Netemeyer, R. G. (1999). Handbook of marketing scales: Multi-item measures for marketing and consumer behavior research. Los Angles: Sage Publications.
  • Brown, J.D. (2001). Statistics Corner: Questions and answers about language testing statistics: What is an eigenvalue? JALT Testing & Evaluation SIG Newsletter, 5 (1), 15 – 19.
  • Brown, T.A. (2006). Confirmatory factor analysis for applied research. New York: Guilford Press.
  • Clyman, S.G. (1990). Orr NA. Status report on the NBME’s computer-based testing. Acad Med. (65), 235–41.
  • Creswell, J. W. (2014). A concise introduction to mixed methods research. SAGE Publications.
  • Çakmak, E. K., Çebi, A., and Kan, A. (2014). E-öğrenme ortamlarına yönelik sosyal bulunuşluk ölçeği geliştirme çalışması. Kuram ve Uygulamada Eğitim Bilimleri, 14(2), 755-768.
  • Çelen, F. K., Çelik, A. & Seferoglu, S. S. (2011). Yükseköğretimde çevrim-içi öğrenme: Sistemde yaşanan sorunlar ve çözüm önerileri. Journal of European Education, 1(1), 25-34.
  • Dirks, M. (1998). How is assessment being done in distance learning? Retrieved January, 3, 2021 from ERIC Database.
  • Fırat, M. (2016). Measuring the e-learning autonomy of distance education students. Open Praxis, 8(3), 191-201.
  • Forsyth, D. R., Archer, C. R. (1997). Technologically assisted instruction and student mastery, motivation, and matriculation. Teaching of Psychology, 24, 207–212.
  • Galante, D. J. (2002). Web-based mathematics: An examination of assessment strategies implemented in the online mathematics classroom (pp. 1-189). Illinois State University. Retrieved January, 3, 2021 from https://www.proquest.com/docview/305573922
  • Gatignon, H. (2010). Confirmatory factor analysis in statistical analysis of management data (pp. 59-122). New York, NY Springer
  • Ghozali, I & Fuad, (2014). Structural equation modeling: theory, concepts and applications with the LISREL program. Semarang: Badan Penerbit Universitas Diponegoro.
  • Guest, G., Bunce, A., & Johnson, L. (2006). How many interviews are enough? An experiment with data saturation and variability. Field Methods, 18(1), 59-82.
  • Hayton, J. C., Allen, D. G., and Scarpello, V. (2004). Factor retention decisions in exploratory factor analysis: A tutorial on parallel analysis. Organizational Research Methods, 7(2), 191-205.
  • Henseler, J., Ringle, C. M., and Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In New challenges to international marketing. Emerald Group Publishing Limited.
  • Ilgaz, H., & Aşkar, P. (2009). Çevrimiçi uzaktan eğitim ortamında topluluk hissi ölçeği geliştirme çalışması. Turkish Journal of Computer and Mathematics Education, 1(1), 27-35.
  • James, R. (2016). Tertiary student attitudes to invigilated, online summative examinations. International Journal of Educational Technology in Higher Education, 13(1), 1-13.
  • Jegede, O. J., Fraser, B., and Curtin, D. F. (1995). The development and validation of a distance and open learning environment scale. Educational Technology Research and Development, 89-94.
  • Karal, H., & Kokoç, M. (2010). Üniversite öğrencilerinin sosyal ağ siteleri kullanım amaçlarını belirlemeye yönelik bir ölçek geliştirme çalışması. Türk Bilgisayar ve Matematik Eğitimi Dergisi, 1(3), 251-263.
  • Kınalıoğlu, İ. H., & Güven, Ş. (2011). Uzaktan eğitim sisteminde öğrenci başarısının ölçülmesinde karşılaşılan güçlükler ve çözüm önerileri. XIII. Akademik Bilişim Konferansı, 2 - 4 Şubat 2011 İnönü Üniversitesi, Malatya.
  • Kışla, T. (2005). Üniversite öğrencilerinin uzaktan eğitime yönelik tutumlarının incelenmesi. (Yayımlanmamış Yüksek Lisans Tezi). Ege Üniversitesi, Sosyal Bilimler Enstitüsü, İzmir
  • Latif, N. A. I. A., Abidin, I. M. Z., Azaman, N., Jamaludin, N., & Mokhtar, A. A. (2019, June). A Feature Extraction Technique Based on Factor Analysis for Pulsed Eddy Current Defects Categorization. In IOP Conference Series: Materials Science and Engineering (Vol. 554, No. 1, p. 012001). IOP Publishing.
  • Leavy, P. (2017). Research design: Quantitative, qualitative, mixed methods, arts‐based, and community‐based participatory research approaches. New York: The Guilford Press.
  • Ledesma, R. D., Valero-Mora, P., and Macbeth, G. (2015). The scree test and the number of factors: a dynamic graphics approach. The Spanish Journal of Psychology, 18. Article E11. https://doi.org/10.1017/sjp.2015.13
  • Liang, X., & Creasy, K. (2004). Classroom assessment in web-based instructional environment: Instructors’ experience. Practical Assessment, Research, and Evaluation, 9(1), 7. https://doi.org/10.7275/84mr-wp41
  • Luecht R.M., Hadadi A., Swanson D.B., and Case S.M. (1998). A comparative study of a comprehensive basic sciences test using paper-and-pencil and computerized formats. Acad Med.73(10),51–53.
  • Marsh, H. W., and Hocevar, D. (1988). A new, more powerful approach to multitrait-multimethod analyses: Application of second-order confirmatory factor analysis. Journal of Applied Psychology, 73(1), 107-117.
  • Martin, C. R., & Newell, R. J. (2004). Factor structure of the hospital anxiety and depression scale in individuals with facial disfigurement. Psychology, Health & Medicine, 9(3), 327-336.
  • Onwuegbuzie, A. J., and Collins, K. M. (2007). A typology of mixed methods sampling designs in social science research. Qualitative Report, 12(2), 281-316.
  • Parlak, Ö. (2007). İnternet temelli uzaktan eğitimde öğrenci doyumu ölçeği. Journal of Educational Sciences and Practices, 6(11), 53-72.
  • Patel, M. C., & Chauhan, N. B. (2012). Attitude towards application of distance education in agriculture and allied field-a scale development. Indian Research Journal on Extension Education, 12(1), 71-72
  • Perry, J. L., Nicholls, A. R., Clough, P. J., andCrust, L. (2015). Assessing model fit: Caveats and recommendations for confirmatory factor analysis and exploratory structural equation modeling. Measurement in Physical Education and Exercise Science, 19(1), 12-21.
  • Peterson, R. A. (2000). A meta-analysis of variance accounted for and factor loadings in exploratory factor analysis. Marketing Letters, 11(3), 261-275.
  • Riadi, E. (2018). SEM statistics: structural equation modeling with LISREL. Yogyakarta: Penerbit Andi.
  • Robles, M. and Braathen, S. (2002). Online assessment techniques. Delta Pi Epsilon Journal, 44(1), 39-49. Retrieved January 3, 2021 from https://www.learntechlib.org/p/93435/.
  • Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of Psychological Research Online, 8(2), 23-74.
  • Schumacker, R. E., and Lomax, R. G. (2010). A beginner’s guide to structural equation modeling (3rd ed.). New York, NY: Routledge.
  • Seçer, İ., Halmatov, S., ve Gençdoğan, B. (2013). Duygusal tepkisellik ölçeğinin Türkçeye uyarlanması: güvenirlik ve geçerlilik çalışması. Sakarya University Journal of Education, 3(1), 77-89.
  • Shraim, K. (2019). Online examination practices in higher education ınstitutions: learners’ perspectives. Turkish Online Journal of Distance Education, 20(4), 185-196. https://doi.org/10.17718/tojde.640588.
  • Sırakaya, M., Sırakaya, D. A., & Çakmak, E. K. (2015).Uzaktan eğitim öğrencilerinin çevrimiçi sınava yönelik tutum düzeylerinin incelenmesi. Kastamonu Eğitim Dergisi, 23(1), 87-104.
  • Sivo, S. A., Fan, X., Witta, E. L., & Willse, J. T. (2006). The search for “optimal” cutoff properties: Fit index criteria in structural equation modeling. The Journal of Experimental Education, 74(3), 267-288.
  • Sorensen, C. (2012). Learning online at the K-12 level: A parent/guardian perspective. International Journal of Instructional Media, 39(4), 297-308
  • Tabachnick, B. G., & Fidell, L. S. (1996). Using multivariate statistics (3rd Ed.). New York: Harper Collins.
  • Tanhan, F., & Çam, Z. (2011). Öğretmenlere yönelik yıldırma ölçeğinin geçerlik ve güvenirliğnin yeniden belirlenmesi. Cukurova University Faculty of Education Journal, 40(1), 87-90.
  • Tanyıldızı, M. ve Semerci, Ç. (2005). Çevrimiçi eğitim uygulamalarına ilişkin öğretim elemanı ve öğrenci görüşlerinin belirlenmesi. Türk Eğitim Bilimleri Dergisi, 3(2), 192-216.
  • Usta, İ., Uysal, Ö. and Okur, M. R. (2016). Çevrimiçi öğrenme tutum ölçeği: geliştirilmesi, geçerliği ve güvenirliği. &
  • Uzunboylu, H., & Özdamli, F. (2011). Teacher perception for m‐learning: scale development and teachers’ perceptions. Journal of Computer Assisted Learning, 27(6), 544-556.
  • Walker, S. L., and Fraser, B. J. (2005). Development and validation of an instrument for assessing distance education learning environments in higher education: The Distance Education Learning Environments Survey (DELES). Learning Environments Research, 8(3), 289-308.
  • Wang, Y. S., Wang, H. Y., and Shee, D. Y. (2007). Measuring e-learning systems success in an organizational context: Scale development and validation. Computers in Human Behavior, 23(4), 1792-1808.
  • White, R. J. and Hammer, C. A. (2000). Quiz-o-Matic: A free Web-based tool for construction of self-scoring on-line quizzes. Behavior Research Methods, Instruments, & Computers, 32(2), 250-253. DOI.10.3758/BF03207791.
  • Yee, N., Ducheneaut, N., and Nelson, L. (2012, May). Online gaming motivations scale: development and validation. In Proceedings of the SIGCHI Conference On Human Factors in Computing Systems (pp. 2803-2806).
  • Yong, A. G., and Pearce, S. (2013). A beginner’s guide to factor analysis: Focusing on exploratory factor analysis. Tutorials in Quantitative Methods for Psychology, 9(2), 79-94.
  • Yunkul, E., & Cankaya, S. (2017). Students’ attitudes towards Edmodo, a social learning network: A scale development study. Turkish Online Journal of Distance Education, 18(2), 16-29.
Toplam 59 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Eğitim
Yazarlar

Gürbüz Ocak 0000-0001-8568-0364

Gülçin Karakuş 0000-0002-0587-4079

Yayımlanma Tarihi 27 Mart 2022
Gönderilme Tarihi 26 Şubat 2021
Yayımlandığı Sayı Yıl 2022

Kaynak Göster

APA Ocak, G., & Karakuş, G. (2022). Üniversite Öğrencilerinin Çevrimiçi Sınavlara Yönelik Tutumlarına İlişkin Ölçek Geliştirme Çalışması. Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi, 24(1), 66-86. https://doi.org/10.32709/akusosbil.887141