Öğretim Elemanlarinin Teknoloji Entegrasyonu Yeterliğine Yönelik Öğrenci Algisi Ölçeği: Geçerlik ve Güvenirlik Çalişmasi

Abstract

Bu çalışmanın amacı, öğretmen adaylarının derslerine giren öğretim elemanlarının teknoloji entegrasyonu yeterliklerine yönelik algılarının belirlenmesidir. Çalışmada nicel yöntem kullanılmıştır. Çalışmanın verileri farklı bölümlerde öğrenim gören 505 öğretmen adayından elde edilmiştir. Bu örneklem grubunda yer alan öğretmen adaylarından toplamda 408 sağlıklı veri elde edilmiştir. 215 öğretmen adayı ile açımlayıcı faktör analizi (AFA), 193 öğretmen adayı ile de doğrulayıcı faktör analizi (DFA) yapılmıştır. Ölçek “hiçbir zaman”, “nadiren”, “bazen”, “çoğu zaman” ve “her zaman” şeklinde ifade edilen 5 kategorili derecelendirmeden oluşmaktadır. Algı ölçeğinin faktör yapısı AFA ile belirlenmiş, ardından DFA ile test edilmiştir. Ölçeğin Cronbach Alfa iç tutarlılık katsayısı .940 olarak hesaplanmıştır. Ölçeğe ait her bir alt faktörden elde edilen güvenirlik katsayısı; 12 maddelik birinci faktör için α=.909 ve 13 maddelik ikinci faktör için α=.904 olarak hesaplanmıştır. Ölçekte yer alan birinci faktörün “Teknolojiden Faydalanma” ve ikinci faktörün ise “Teknoloji Kullanımı” olarak adlandırılması kararlaştırılmıştır. Sonuç olarak, 25 maddeden oluşan iki faktörlü geçerli ve güvenilir bir ölçek geliştirilmiştir. Ölçeğe ilişkin alınan yüksek puan; öğretmen adaylarının, dersine giren öğretim elemanının/elemanlarının teknoloji entegrasyonu yeterliğini yüksek düzeyde algıladığına işaret etmektedir.

Keywords

• Teknoloji Entegrasyonu, Algı, Ölçek Geliştirme, Geçerlik, Öğretim Elemanı, Öğretmen Adayı

Student’s Perception Scale About Instructors’ Technology Integration Competence: Validity And Reliability Study

Abstract

The aim of this study is to define preservice teachers’ perceptions about their instructors’ technology integration competence in their lessons. Quantitative method was used in the study. Data of the study wasgathered from 505 preservice teachers from different departments. 408 reliable data were gathered in total from the preservise teachers of this sample group. Explanatory factor analysis (EFA) was conducted with 215 preservice teachers and confirmatory factor analysis (CFA) was conducted with 193 preservice teachers. The scale iscomposed of 5 rating categorizations defined as “never”, “rarely”, “sometimes”, “frequently” and “always”. Factor structure of perception scale was defined with EFA and then was tested with confirmatory factor analysis (CFA). Cronbach Alpha Internal consistency of the scale was calculated as .940. Reliability coefficient obtained from each sub-factor belonging to scale was calculated for the first factor including 12 items as α=.909 and α=.904 for 13 items. The first and the second factors in the scale were decided to be named as “Making use of technology” and “Using technology” respectively. As a result, a valid and reliable scale composed of 25 items and 2 factors wasdeveloped. The high point taken related with scale shows that preservice teachers perceived that teaching staff/staffs’ technology integration competence at high level

Keywords

• Technology Integration, Perception, Scale Development, Validity, Instructor, Preservice Teacher

References

1. Barron, A. E., Orwig, G. W., Ivers, K.S. & Lilavois, N. (2001). Technologies for education (4th). Greenwood Village, CO: Libraries Unlimited-Greenwood Publishing Groups, Inc.
2. Bauer, J. & Kenton, J. (2005). Toward technology integration in the schools: Why it isn’t happening. Journal of Technology and Teacher Education, 13(4), 519-546.
3. Brown, T. A. (2006). Confirmatory Factor Analysis for Applied Research. New York, NY: Guilford Press.
4. Büyüköztürk, Ş. (2010). Sosyal bilimler için çok değişkenli istatistik. Pegem A Yayıncılık, Ankara.
5. Chen, C. H. (2008). Why do teachers not practice what they believe regarding technology integration? Journal of Educational Research, 102(1), 65–75.
6. Chen, W., Lim, C. & Tan, A. (2010). Pre-service teachers‘ ICT experiences and competencies: New generation of teachers in digital age. Society, 58(3), 631-638.
7. Çokluk, Ö., Şekercioğlu, G. ve Büyüköztürk, Ş. (2012). Sosyal bilimler için çok değişkenli SPSS ve LİSREL uygulamaları. PegemA Yayıncılık, Ankara,
8. DeVellis, R. F. (2003). Scale development: Theory and applications (2nd ed.). Applied Social Research Methods Series Volume 26, Thousand Oaks, CA: SAGE.

9. Erkuş, A. (2012). Psikolojide ölçme ve ölçek geliştirme. Pegem Akademi Yayınları, Ankara.
10. Ertmer, P. A., Conklin, D., Lewandowski, J., Osika, E., Selo, M. & Wignall, E. (2003). Increasing preservice teachers’ capacity for technology integration through the use of electronic models. Teacher Education Quarterly, 30(1), 95-112.
11. Eyyam, R., Meneviş, İ. ve Doğruer, N. (2011). Perceptions of teacher candidates towards Web 2.0 technologies. Procedia Social and Behavioral Sciences, 15, 2663–2666.
12. Field, A. P. (2009). Discovering Statistics using SPSS: And Sex and Drugs and Rock ‘N’ Roll. 3rd ed. London: Sage.
13. Franklin, T. (1999). Teacher computer access, student computer access, years of teaching experience, and professional development as predictors of competency of K-4 Ohio public school students on the National Educational Technology Standards. Unpublished Doctoral Dissertation, Ohio University, Athens OH .
14. Gorder, L. M. (2008). A study of teacher perceptions of instructional technology integration in the classroom. Delta Pi Epsilon Journal, 50(2), 63-76.
15. Günüç, S. (2016). Üniversitelerde Öğrenci Bağlılığı. Nobel Yayıncılık, İstanbul.
16. Hew, K. F. & Brush, T. (2007). Integrating technology into K-12 teaching and learning: Current knowledge gaps and recommendations for future research. Educational Technology Research and Development, 55, 223-252.
17. Hohlfeld, T. N., Ritzhaupt, A. D., Barron, A. E. & Kemker, K. (2008). Examining the digital divide in K-12 public schools: Four-year rrends for supporting ICT literacy in Florida. Computers & Education, 51(4), 1648–1663.
18. Hooper, D., Coughlan, J. & Mullen, M. (2008). “Structural Equation Modelling: Guidelines for Determining Model Fit.” Electronic Journal of Business Research Methods. 6(1), 53–60.
19. Hsu, S. (2010). The Relationship between Teacher's technology integration ability and usage. Journal of Educational Computing Research, 43(3), 309-325.
20. 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.
21. Hutcheson, G. D. & Sofroniou, N. (1999). The Multivariate Social Scientist: An Introduction to Generalized Linear Models. Thousand Oaks, CA: Sage.
22. Inan, F. A. & Lowther, D. L. (2010). Factors affecting technology integration in K-12 classrooms: A path model. Education Tech Research Dev, 58, 137-154.
23. Jimoyiannisa, A. & Komisb, V. (2007). Examining teachers’ beliefs about ICT in education: Implications of a teacher preparation programme. Teacher Development, 11(2), 149- 173.
24. Jöreskog, K. & Sörbom, D. (2001). Lisrel 8: User’s reference guide. Chicago, USA: Scientific Software International Inc.
25. Kajuna, L. W. (2009). Implementation of Technology Integration in Higher Education: A Case Study of the University of Dar-es-Salaam in Tanzania. Unpublished Doctoral Dissertation, Ohio Universitesi.
26. Karaca, F. (2011a). Teacher and Student Perceptions about Technology Use in an Elementary School in Ankara. Journal of Social Studies Education Research, 2(2), 43-59.
27. Karaca, F. (2011b). Factors Associated with Technology Integration to Elementary School Settings: A Path Model. Unpublished Doctoral Dissertation, Middle East Technical University, Ankara, Turkey.
28. Kline, R. B. (2011). Principles and Practice of Structural Equation Modeling. 3rd ed. New York: Guilford.
29. Lei, J. (2009). Digital natives as preservice teachers: What technology preparation is needed?. Journal of Computing in Teacher Education, 25(3), 87-97.
30. Lim, C. P. & Chai, C. S. (2008). Teachers’ pedagogical beliefs and their planning and conduct of computer-mediated classroom lesson. British Journal of Educational Technology, 39(5), 807-828.
31. Mama, M. & Hennessy, S. (2010). Level of technology integration by primary teachers in Cyprus and student engagement. Technology, Pedagogy and Education, 19(2), 269-275.
32. Mertler, C. A. & Vannatta, R. A. (2005). Advanced and multivariate statistical methods: Pratical application and interpretation (3. bs.). CA: Pyrczak Publishing.
33. Norris, C., Sullivan, T., Poirot, J. & Soloway, E. (2003). No access, no use, no impact: Snapshot surveys of educational technology in K-12. Journal of Research on Technology in Education, 36(1), 15–27.
34. Pallant, J. (2007). SPSS Survival Manual: A Step by Step Guide to Data Analysis using SPSS for Windows. Maidenhead: Open University Press.
35. Raykov, T. & G. A. Marcoulides. (2006). A First Course in Structural Equation Modeling. 2nd ed. Mahwah, NJ: Lawrence Erlbaum.
36. Shuldman, M. (2004). Superintendent Conceptions of Institutional Conditions That Impact Teacher Technology Integration. Journal of Research on Technology in Education, 36(4), 319-343.
37. Sümer, N. (2000). Yapısal eşitlik modelleri: Temel kavramlar ve örnek uygulamalar. Turkish Psychological Articles, 3(6), 49–74.
38. Tabachnick, G. G. & L. S. Fidell. (2007). Experimental Designs using ANOVA. Belmont, CA: Duxbury.
39. Teo, T. (2009). Modelling technology acceptance in education: A study of pre - service teachers. Computers & Education, 52(2), 302- 312.
40. Tezbaşaran, A. A. (1997). Likert tipi ölçek geliştirme kılavuzu (2. bs.). Ankara: Türk Psikologlar Derneği Yayınları.
41. Thompson, B. (2008). Exploratory and Confirmatory Factor Analysis: Understanding Concepts and Applications. 3rd ed. Washington, DC: American Psychological Association.
42. Van Braak, J., Tondeur, J. & Valcke, M. (2004). Explaining different types of computer use among primary school teachers. European Journal of Psychology of Education, 19(4), 407–422.
43. Vannatta, R. A. & Fordham, N. (2004). Teacher dispositions as predictors of classroom technology use. Journal of Research on Technology in Education, 36(3), 253–271.
44. Velazquez, C. M. (2008). Testing predictive models of technology ıntegration in Mexico and the United States. Computers in the Schools, 24(3-4), 153-173.