Development of Internet literacy self-efficacy scale for pre-service teachers

Year 2020, , 179 - 204, 30.04.2020

Nehir Yasan Ak

https://doi.org/10.19128/turje.664706

Cited By: 2

Abstract

This study aims to
develop the Internet Literacy Self-Efficacy Scale (ILSEF) that can be used to
examine pre-service teachers’ beliefs in their capabilities to perform recent
web functionalities. The data was collected from eight different departments
and all grade levels of the faculty of education at a state university in
Turkey. Two different samples were used to develop and validate the instrument.
The first and second samples consisted of 174 and 150 pre-service teachers,
respectively. In an effort to explore the factorial structure, exploratory and
confirmatory factor analyses were run. Construct validity was also checked by
convergent and discriminant validity. A four-factor structure with 16 items was
obtained: trustworthiness, creation, technical knowledge, and getting
information. This structure accounted for 65.40% of the total variance. The
reliability Cronbach alpha coefficients of the scale were calculated as ranging
from .90 to .71. The results provided some evidence that the scores obtained
from the Internet Literacy Self-Efficacy Scale are valid and reliable in
assessing pre-service teachers’ self-efficacy beliefs in terms of the Internet
use knowledge and skills.

Keywords

Educational technology, Instrument development, Internet literacy, Pre-service teachers, Self-efficacy

Thanks

I would like to thank Dr. Yeşim Çapa Aydın particularly for her valuable feedback in the statistical analyses of my study.

Öğretmen adayları için İnternet okuryazarlığı özyeterlik ölçeğinin geliştirilmesi

Abstract

Bu çalışma, öğretmen
adaylarının güncel web işlevlerini kullanabilme yetenekleriyle ilgili inançlarını
incelemek için kullanılabilecek İnternet Okuryazarlığı Özyeterlik Ölçeğini
(ILSEF) geliştirmeyi amaçlamaktadır. Veriler, Türkiye'deki bir devlet
üniversitesindeki eğitim fakültesinin 8 farklı bölümünden ve tüm sınıf
düzeylerinden toplanmıştır. Ölçeğin geliştirilmesi ve güvenirlik çalışmaları
için iki farklı örneklem kullanılmıştır. Birinci örneklem 174 ve ikinci
örneklem 150 öğretmen adayından oluşmaktadır. Faktöriyel yapıyı araştırmak
için, açımlayıcı ve doğrulayıcı faktör analizi yapılmıştır. Yapı geçerliği ayrıca
yakınsak ve ayırt edici geçerlik ile kontrol edilmiştir. 16 maddelik dört
faktörlü bir model elde edilmiştir: güvenilirlik, oluşturma, teknik bilgi ve
bilgi alma. Bu model toplam varyansın %65.40'ını açıklamıştır. Ölçeğe ilişkin Cronbach
alfa güvenirlik katsayıları .90 ile .71 arasında hesaplanmıştır. Sonuçlar, İnternet
Okuryazarlığı Özyeterlik Ölçeğinden elde edilen puanların, öğretmen adaylarının
İnternet kullanım bilgi ve becerilerine olan özyeterlik inançlarını değerlendirilmesinde
geçerli ve güvenilir bir yapıda olduğunu ortaya koymuştur.

Keywords

Eğitim teknolojisi, Internet okur-yazarlığı, Öğretmen eğitimi, Öz yeterlik

References

• Anderson, L., Bourke, S. (2000). Assessing affective characteristics in the schools. New York: Routledge. https://doi.org/10.4324/9781410605443
• Angela, T. (2011). A constructivist approach to new media: An opportunity to improve social studies didactics. Procedia-Social and Behavioral Sciences, 11(11), 185–189. doi:10.1016/j.sbspro.2011.01.058
• Arbuckle, J. L., & Wothke, W. (1999). Amos 4.0 user's guide. Chicago, IL: SmallWaters Corporation.
• Aypay, A., Celik, H. C., Aypay, A., & Sever, M. (2012). Technology acceptance in education: A study of pre-service teachers in Turkey. TOJET: The Turkish Online Journal of Educational Technology, 11(4), 264-272. https://eric.ed.gov/?id=EJ989276
• Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioural change. Psychological Review, 84(2), 191-215. https://psycnet.apa.org/doi/10.1037/0033-295X.84.2.191
• Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall. https://doi.org/10.1111/1467-839X.00024
• Bandura, A. (1998). Self-efficacy. In V. S. Ramachaudran (Ed.), Encyclopedia of human behavior (Vol. 4, pp. 71-81). New York: Academic Press. (Reprinted in H. Friedman [Ed.], Encyclopedia of mental health. San Diego: Academic Press.
• Bandura, A. (2006). Guide for constructing self-efficacy scales. In Urdan, T., Pajares, F. (Eds.), Self-efficacy beliefs of adolescents (Vol. 5, pp. 307-337). Greenwich, CT: Information Age.
• Bong, M., & Skaalvik, E. M. (2003). Academic self-concept and self-efficacy: How different are they really?. Educational psychology review, 15(1), 1-40. https://doi.org/10.1023/A:1021302408382
• Bong, M., & Clark, R. E. (1999). Comparison between self-concept and self-efficacy in academic motivation research. Educational psychologist, 34(3), 139-153. https://doi.org/10.1207/s15326985ep3403_1
• Bornstein, M. H., Jager, J., & Putnick, D. L. (2013). Sampling in developmental science: Situations, shortcomings, solutions, and standards. Developmental Review, 33(4), 357-370. https://doi.org/10.1016/j.dr.2013.08.003
• 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.
• Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189-211. DOI: 10.2307/249688
• Cortina J. M. (1993). What is coefficient alpha? An examination of theory and applications. Journal of Applied Psychology, 78(1), 98-104. https://doi.org/10.1037/0021-9010.78.1.98
• Eachus, P., & Cassidy, S. (2006). Development of the web users self-efficacy scale (WUSE). Issues in Informing Science and Information Technology Journal, 3, 199-209. http://usir.salford.ac.uk/id/eprint/1172
• Eastin, M. S., & LaRose, R. (2000). Internet self-efficacy and the psychology of the digital divide. Journal of computer-mediated communication, 6(1), JCMC611. https://doi.org/10.1111/j.1083-6101.2000.tb00110.x
• 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. https://psycnet.apa.org/doi/10.1037/1082-989X.4.3.272
• Ferrari, A. (2012). Digital competence in practice: An analysis of frameworks (Report EUR 25351 EN). Luxembourg: Publications Office of the European Union. http://ftp.jrc.es/EURdoc/JRC68116.pdf
• Field. A. (2009). Discovering statistics using by SPSS (3rd ed.). London: Sage Publication.
• Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177%2F002224378101800104
• Gouveia, V. V., & Soares, A. K. S. (2015). Calculadoras de validade de construto (CVC). João Pessoa, PB: BNCS/Universidade Federal da Paraíba. Recuperado de http://akssoares.com/psicometria/calculadora-vme-e-cc.
• Joo, Y. J., Bong, M., & Choi, H. J. (2000). Self-efficacy for self-regulated learning, academic self-efficacy, and Internet self-efficacy in web-based instruction. Educational Technology and Development, 48(2), 5-17 https://doi.org/10.1007/BF02313398
• Jöreskog, K. G., & Sörbom, D. (1993). LISREL 8: Structural equation modeling with the SIMPLIS command language. Chicago: Scientific Software International. Google Scholar
• Hair, J. F., Anderson, R. E., Tatham, R. L. & Black, W. C. (2010). Multivariate Data Analysis (7th ed.). Upper Saddle River, NJ: Prentice Hall, Inc. Google Scholar
• Hooper, D., Coughlan, J., & Mullen, M. R. (2008). Structural equation modelling: Guidelines for determining model fit. Electronic Journal of Business Research Methods, 6(1), 53-60. http://mural.maynoothuniversity.ie/6596/
• Hu, L. H. & 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), 1-15. https://doi.org/10.1080/10705519909540118
• Kaya, S., & Durmuş, A. (2010). Pre-service teachers’ perceived internet self-efficacy and levels of internet use for research. Procedia-Social and Behavioral Sciences, 2(2), 4370-4376. https://doi.org/10.1016/j.sbspro.2010.03.695
• Kao, C. P., & Tsai, C. C. (2009). Teachers’ attitudes toward web-based professional development, with relation to Internet self-efficacy and beliefs about web-based learning. Computers & Education, 53(1), 66-73. https://doi.org/10.1016/j.compedu.2008.12.019
• Kao, C. P., Wu, Y. T., & Tsai, C. C. (2011). Elementary school teachers’ motivation toward web-based professional development, and the relationship with Internet self-efficacy and belief about web-based learning. Teaching and Teacher Education, 27(2), 406-415. https://doi.org/10.1016/j.tate.2010.09.010
• Kıyıcı, F. B. (2010). The definitions and preferences of science teacher candidates concerning web 2.0 tools: A phenomenological research study. The Turkish Online Journal of Educational Technology, 9(2), 185–195. http://www.tojet.net/articles/v9i2/9219.pdf
• Kim, Y., Glassman, M., Bartholomew, M., & Hur, E. H. (2013). Creating an educational context for Open Source Intelligence: The development of Internet self-efficacy through a blog-centric course. Computers & Education, 69, 332-342. https://doi.org/10.1016/j.compedu.2013.07.034
• Kline, P. (1999). A Handbook of Psychological Testing, 2nd ed. London: Routledge. https://doi.org/10.4324/9781315812274
• Kline, R. B. (2011). Principles and practice of structural equation modeling (Second ed.). New York: The Guilford Press. https://psycnet.apa.org/doi/undefined
• Kurbanoglu, S. S. (2003). Self-efficacy: A concept closely linked to information literacy and lifelong learning. Journal of Documentation, 59(6), 635–646. https://doi.org/10.1108/00220410310506295
• Laver, K., George, S., Ratcliffe, J., & Crotty, M. (2012). Measuring technology self efficacy: reliability and construct validity of a modified computer self efficacy scale in a clinical rehabilitation setting. Disability and rehabilitation, 34(3), 220-227. https://doi.org/10.3109/09638288.2011.593682
• Lee, L., Chen, D. T., Li, J. Y., & Lin, T. B. (2015). Understanding new media literacy: The development of a measuring instrument. Computers & Education, 85, 84–93. https://doi.org/10.1016/j.compedu.2015.02.006
• Liaw, S. S., Huang, H. M., & Chen, G. D. (2007). Surveying instructor and learner attitudes toward e-learning. Computers & Education, 49(4), 1066-1080. https://doi.org/10.1016/j.compedu.2006.01.001
• Livingstone, S., M. Bober and E.J. Helsper (2005) Internet Literacy Among Children and Young People: Findings from the UK Children Go Online Project. London: London School of Economics and Political Science. URL: www.children-go-online.net
• McCoach, D. B., Gable, R. K., & Madura, J. P. (2013). Affective characteristics in school and corporate environments: Their conceptual definitions. In D. B. McCoach, R. K. Gable & J. P. Madura (Eds.), Instrument Development in the Affective Domain. New York: Springer. https://doi.org/10.1007/978-1-4614-7135-6_1
• Miltiadou, M., & Yu, C. H. (2000). Validation of the Online Technologies Self-Efficacy Scale (OTSES). Educational Technology Review, 11(1). https://eric.ed.gov/?id=ED445672
• Moran, M., Hawkes, M., & Gayar, O. E. (2010). Tablet personal computer integration in higher education: Applying the unified theory of acceptance and use technology model to understand supporting factors. Journal of Educational Computing Research, 42(1), 79-101. https://doi.org/10.2190%2FEC.42.1.d
• Nunnally, J. C. (1967). McGraw-Hill series in psychology. Psychometric theory. New York, NY, US: McGraw-Hill.
• Nunnally, Jum C. (1978). Psychometric Theory, 2nd ed. New York: McGraw-Hill.

• Oskay, Ö.Ö. (2011). Internet self-effıcacy preferences of internet based environments and achievement of prospective teachers. Hacettepe University Journal of Education, 40, 291-299.
 https://www.learntechlib.org/p/51226/
• Peterson, R. A. (1994). A meta-analysis of Cronbach’s coefficient alpha. Journal of Consumer Research, 21(2), 381–391. https://doi.org/10.1086/209405
• Preacher, K. J., & MacCallum, R. C. (2003). Repairing Tom Swift's electric factor analysis machine. Understanding statistics: Statistical issues in psychology, education, and the social sciences, 2(1), 13-43. https://doi.org/10.1207/S15328031US0201_02
• Rosenberg, M. (1965). The rosenberg self esteem scale: From society and the adolescent self image. Princeton, NJ:Princeton University Press.
• Sang, G., Valcke, M., van Braak, J., & Tondeur, J. (2010). Student Teachers' Thinking Processes and ICT Integration: Predictors of Prospective Teaching Behaviors with Educational Technology. Computers & Education, 54(1), 103-112. https://doi.org/10.1016/j.compedu.2009.07.010
• Stevens, J. P. (2002). Applied multivariate statistics for the social sciences (4. ed.). Hillsdale, NJ: Erlbaum.
• Sun, J. C. Y., & Rueda, R. (2012). Situational interest, computer self‐efficacy and self‐regulation: Their impact on student engagement in distance education. British Journal of Educational Technology, 43(2), 191-204. https://doi.org/10.1111/j.1467-8535.2010.01157.x
• Şad, S. N., & Demir, O. (2015). Computer and Internet Use Self-Efficacy Scale for Elementary School Teachers: Validity and Reliability Studies. Elementary Education Online, 14(2), 489-510. http://dx.doi.org/10.17051/io.2015.00172
• Şahin, İ. (2009). Validity and reliability of educational Internet use self-efficacy beliefs scale. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 21, 459-471. Available at: http://dergisosyalbil.selcuk.edu.tr/susbed/article/view/338
• Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics. Needham Heights, MA: Allyn and Bacon.
• Tella, A. (2011). An assessment of mathematics teachers' Internet self-efficacy: implications on teachers' delivery of mathematics instruction. International Journal of Mathematical Education in Science and Technology, 42(2), 155-174. https://doi.org/10.1080/0020739X.2010.519798
• Teo, T. (2009). Modelling technology acceptance in education: A study of pre-service teachers. Computers & Education, 52(2), 302-312. https://doi.org/10.1016/j.compedu.2008.08.006
• Teo, T., & Koh, J. H. L. (2010). Assessing the dimensionality of computer self-efficacy among pre-service teachers in Singapore: A structural equation modeling approach. International Journal of Education and Development using Information and Communication Technology, 6(3), 7. https://www.learntechlib.org/p/42385/
• Terzis, V., & Economides, A. A. (2011). The acceptance and use of computer based assessment. Computers & Education, 56(4), 1032-1044. https://doi.org/10.1016/j.compedu.2010.11.017
• Timothy, T. E. O. (2009). Examining the relationship between student teachers' self-efficacy beliefs and their intended uses of technology for teaching: A structural equation modelling approach. TOJET: The Turkish Online Journal of Educational Technology, 8(4), 7-15. https://eric.ed.gov/?id=EJ859493
• Thompson, B. 2008. Exploratory and Confirmatory Factor Analysis: Understanding Concepts and Applications. 3rd ed. Washington, DC: American Psychological Association.
• Tsai, M.-J., &Tsai, C.-C. (2003) Information searching strategies in web-based science learning: the role of Internet self-efficacy. Innovations in Education and Teaching International, 40(1), 43–50. https://doi.org/10.1080/1355800032000038822
• Wang, L., Ertmer, P. A., & Newby, T. J. (2004). Increasing preservice teachers’ self-efficacy beliefs for technology integration. Journal of Research on Technology in Education, 36(3), 231-250. https://doi.org/10.1080/15391523.2004.10782414
• Willis, G.B. ( 2005). Cognitive interviewing: A tool for improving questionnaire design. Thousand Oaks, CA: SAGE. Google Scholar
• Wong, K. T., Teo, T., & Russo, S. (2012). Influence of gender and computer teaching efficacy on computer acceptance among Malaysian student teachers: An extended technology acceptance model. Australasian Journal of Educational Technology, 28(7), 1190-1207. https://doi.org/10.14742/ajet.796
• Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision sciences, 27(3), 451-481. https://doi.org/10.1111/j.1540-5915.1996.tb00860.x
• Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. DOI: 10.2307/30036540
• Young, J. A. (2015). Assessing new media literacies in social work education: The development and validation of a comprehensive assessment instrument. Journal of Technology in Human Services, 33(1), 72–86. https://doi.org/10.1080/15228835.2014.998577
• Yurdugül, H., & Sırakaya, D. A. (2013). Çevrimiçi öğrenme hazır bulunuşluluk ölçeği: Geçerlik ve güvenirlik çalışması. Eğitim ve Bilim, 38(169). http://egitimvebilim.ted.org.tr/index.php/EB/article/view/2420
• Zimmerman, B. J. (2000). Self-efficacy: An essential motive to learn. Contemporary Educational Psychology, 25(1), 82-91. https://doi.org/10.1080/15228835.2014.998577