The development of an online learning readiness scale for high school students

Year 2022, , 126 - 145, 29.11.2022

Mehmet Ramazanoğlu , Sungur Gürel , Ali Çetin

https://doi.org/10.21449/ijate.1125823

Cited By: 2

Abstract

Assessing students’ online learning readiness is important since numerous countries have started online learning at all education levels during the Covid-19 pandemic in the 21st century. By taking students’ online learning readiness level into account, it will be easier to establish on-target online learning environments. Although there are a number of online learning readiness scales available aiming at higher-education students in the Turkish setting, there is no scale available specifically for high-school students. This study, therefore, aims to develop a valid and reliable scale to identify the levels of online learning readiness for high school students in Türkiye. In order to develop an Online Learning Readiness Scale for high school students, a mixed-method exploratory sequential design was employed in this study. The first sample consisted of 916 students and the second sample consisted of 323 students who had previously experienced an online learning environment. The data were analyzed through exploratory factor analysis and confirmatory factor analysis. Validity and reliability evidences were also provided. The final version of the scale consisted of a total of 16 items in three dimensions; namely, computer self-efficacy, internet self-efficacy, and self-learning and explained 65.76% of the variance. The results of the study indicate that the Online Learning Readiness Scale (OLRS) developed in this particular study is a reliable and valid measurement tool in the assessment of online learning readiness levels of high school students in Türkiye and is expected to guide researchers and practitioners who focus on assessing high school students’ online learning readiness levels.

Keywords

Online learning readiness, Computer self-efficacy, Internet self-efficacy, Self-learning, High school students

Thanks

The authors would like to thank the assistance of Siirt Provincial Directorate of National Education personnel and high school principals who helped researchers to get in touch with high school students.

References

• Achukwu, C.B., Nwosu, K.C., Uzoekwe, H.E., & Juliana, A. (2015). Computer self-efficacy, computer-related technology dependence and on-line learning readiness of undergraduate students. International Journal of Higher Education Management, 1(2), 60-71.
• Arbaugh, J.B. (2000). Virtual classroom characteristics and student satisfaction with internet based MBA courses. Journal of Management Education, 24(1), 32 54. https://doi.org/10.1177/105256290002400104
• Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman/Times Books/ Henry Holt & Co.
• Bandura, A., Adams, N.E., & Beyer, J. (1977). Cognitive processes mediating behavioral change. Journal of Personality and Social Psychology, 35(3), 125 139. https://doi.org/10.1037//0022-3514.35.3.125
• Barker, P. (2002). On being an online tutor. Innovations in Education and Teaching International, 39(1), 3 13. https://doi.org/10.1080/13558000110097082
• Bentler, P.M., & Chou, C.P. (1987). Practical issues in structural modeling. Sociological Methods & Research, 16(1), 78-117. https://doi.org/10.1177/0049124187016001004
• Bernard, R.M., Brauer, A., Abrami, P.C., & Surkes, M. (2004). The development of a questionnaire for predicting online learning achievement. Distance Education, 25(1), 31 47. https://doi.org/10.1080/0158791042000212440 Borotis, S., & Poulymenakou, A. (2004). E learning readiness components: Key issues to consider before adopting e learning interventions. In E learn: World conference on e learning in corporate, government, healthcare, and higher education (pp. 1622 1629).
• Browne, M.W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K.A. Bollen and J.S. Long (Eds.), Testing structural equation models (pp. 136-162). Sage.
• Byrne, B.M. (1998). Structural equation modeling with Lisrel, Prelis, and Simplis: Basic concepts, applications, and programming (1st ed.). Psychology Press. https://doi.org/10.4324/9780203774762
• Cattell, R.B. (1966). The scree test for the number of factors. Multivariate Behavioral Research, 1(2), 245-276. https://doi.org/10.1207/s15327906mbr0102_10
• Chang, S.C., & Tung, F.C. (2008). An empirical investigation of students’ behavioral intentions to use the online learning course website. British Journal of Educational Technology, 39(1), 71-83. https://doi.org/10.1111/j.1467-8535.2007.00742.x
• Chizmar, J.F., & Walbert, M.S. (1999). Web-based learning environments guided by principles of good teaching practice. The Journal of Economic Education, 30(3), 248 259. https://doi.org/10.1080/00220489909595985
• Choucri, N., Maugis, V., Madnick, S., Siegel, M., Gillet, S., O’Donnel, S., Best, M., Zhu, H., & Haghseta F. (2003). Global e readiness for what. In N. Choucri, V. Maugis, S. Madnick, & M. Siegel (Eds.), Global e-readiness-for what (pp. 1–47). Center for eBusiness at MIT: Massachusetts Institute of Technology Cambridge, MA.
• Compeau, D.R., & Higgins, C.A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189-211. https://doi.org/10.2307/249688 Comrey, A.L., & Lee, H.B. (1992). A first course in factor analysis. Lawrence Eribaum Associates.
• Creswell, J. (2012). Educational research: planning, conducting, and evaluating quantitative and qualitative research. (4th Ed.). Pearson.
• Creswell, J.W., & Plano Clark, V.L. (2006). Designing and conducting mixed methods research. SAGE.
• Cronbach, L.J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16, 297–334. https://doi.org/10.1007/BF02310555
• Daniels, H.L., & Moore, D.M. (2000). Interaction of cognitive style and learner control in a hypermedia environment. International Journal of Instructional Media, 27(4), 369-382.
• Demir Kaymak, Z., & Horzum, M.B. (2013). Relationship between online learning readiness and structure and interaction of online learning students. Educational Sciences: Theory and Practice, 13(3), 1792-1797. https://doi.org/10.12738/estp.2013.3.1580
• DeTure, M. (2004). Cognitive Style and Self-Efficacy: Predicting student success in online distance education. American Journal of Distance Education, 18(1), 21 38. https://doi.org/10.1207/s15389286ajde1801 _3
• DeVellis, R.F. (2017). Scale development: Theory and applications (4th ed.). Sage.
• Durak, H. (2017). Turkish adaptation of the flipped learning readiness scale for middle school students. Bartın University Journal of Faculty of Education, 6(3), 1056 1068. https://doi.org/10.14686/buefad.328826
• Forero, G.C., Maydeu-Olivares, A., & Gallardo-Pujol, D. (2009). Factor analysis with ordinal indicators: A Monte Carlo study comparing DWLS and ULS estimation. Structural Equation Modeling, 16(4), 625–641. https://doi.org/10.1080/10705510903203573
• Gökçearslan, Ş., Solmaz, E., & Kukul, V. (2017). Mobile learning readiness scale: an adaptation study. Eğitim Teknolojisi Kuram ve Uygulama, 7(1), 143 157. https://doi.org/10.17943/etku.288492
• Guttman, L. (1954). Some necessary conditions for common-factor analysis. Psychometrika, 19(2), 149 161. https://doi.org/10.1007/BF02289162
• Hill, J.R. (2000). Web-based instruction: Prospects and challenges. Educational media and technology yearbook, 25, 141 55.
• Horzum, M., Bektaş, M., Ayvaz Can, A., Üngören, Y., & Sellüm, F. (2019). Authentic learning readiness scale for teachers: The validity and reliability study. Uluslararası Alan Eğitimi Dergisi, 5(2), 94-106. https://doi.org/10.32570/ijofe.645859
• Hu, L.T., & Bentler, P.M. (1999). Cut off 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
• Hung, M.L. (2016). Teacher readiness for online learning: scale development and teacher perceptions. Computers & Education, 94, 120 133. https://doi.org/10.1016/j.compedu.2015.11.012
• Hung, M.L., Chou, C., Chen, C.H., & Own, Z.Y. (2010). Learner readiness for online learning: Scale development and student perceptions. Computers & Education, 55(3), 1080-1090. https://doi.org/10.1016/j.compedu.2010.05.004
• International Society for Technology in Education (ISTE). (2016). ISTE Standards for Students (ebook): A Practical Guide for Learning with Technology. Susan Brooks-Young.
• İlhan, M., & Çetin, B. (2013). The validity and reliability study of the Turkish version of an online learning readiness scale. Eğitim Teknolojisi Kuram ve Uygulama, 3(2), 72-101.
• Kaiser, H.F. (1960). The application of electronic computers to factor analysis. Educational and Psychological Measurement, 20(1), 141 151. https://doi.org/10.1177/001316446002000116
• Katz, Y.J. (2000). The comparative suitability of three ICT distance learning methodologies for college level instruction. Educational Media International, 7(1), 25 30. https://doi.org/10.1080/095239800361482
• Katz, Y.J. (2002). Attitudes affecting college students’ preferences for distance learning. Journal of Computer Assisted Learning, 18(1), 2 9. https://doi.org/10.1046/j.0266 4909.2001.00202.x
• Khan, I.M. (2009). An analysis of the motivational factors in online learning (Doctoral dissertation, University of Phoenix). https://www.learntechlib.org/p/127822/
• Kim, Y., & Glassman, M. (2013). Beyond search and communication: development and validation of the internet self-efficacy scale (ISS). Computers in Human Behavior, 29 (4), 1421-1429. https://doi.org/10.1016/j.chb.2013.01.018
• Kline, B.R. (2011). Principles and practice of structural equation modeling. (3rd ed.). Guilford
• Kuo, Y.C., Walker, A., Schroder, K.E.E., & Belland, B.R. (2014). Interaction, internet self-efficacy, and self-regulated learning as predictors of student satisfaction in online education courses. The Internet and Higher Education, 20, 35 50. https://doi.org/10.1016/j.iheduc.2013.10.001
• Lajoie, S.P., & Naismith, L. (2012). Computer-based learning environments. In: Seel, N. M. (eds) Encyclopedia of the sciences of learning. Springer. https://doi.org/10.1007/978-1-4419-1428-6_512
• Lenahan Bernard, J.M. (2014). Relationship of computer self efficacy and self directed learning readiness to civilian employees’ completion of online courses (Doctoral dissertation, Nova Southeastern University). https://www.proquest.com/docview/1727477573?pqorigsite=gscholar&fromopenview=true
• Li, C.H. (2016). Confirmatory factor analysis with ordinal data: Comparing robust maximum likelihood and diagonally weighted least squares. Behavioral Researcher, 48, 936 949. https://doi.org/10.3758/s13428-015-0619-7
• Liang, J.C., & Wu, S.H. (2010). Nurses' motivations for web-based learning and the role of internet self-efficacy. Innovations in Education and Teaching International, 47(1), 25-37. https://doi.org/10.1080/14703290903525820
• Lim, C. K. (2001). Computer self-efficacy, academic self-concept, and other predictors of satisfaction and future participation of adult distance learners. American Journal of Distance Education, 15(2), 41 51. https://doi.org/10.1080/08923640109527083
• Lin, B., & Hsieh, C.T. (2001). Web-based teaching and learner control: A research review. Computers & Education, 37(4), 377 386. https://doi.org/10.1016/S0360 1315(01)00060 4
• Lin, H.H., Lin, S., Yeh, C.H., & Wang, Y.S. (2016). Measuring mobile learning readiness: Scale development and validation. Internet Research, 26(1), 265 287. https://doi.org/10.1108/IntR-10-2014-0241
• Livingstone, S., & Helsper, E. (2010). Balancing opportunities and risks in teenagers' use of the Internet: The role of online skills and internet self-efficacy. New Media & Society, 12(2), 309-329. https://doi.org/10.1177/1461444809342697
• Maccallum, R.C., Browne, M.W., & Sugawara, H.M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1(2), 130-149.
• Matsunaga, M. (2010). How to factor-analyze your data right: Do’s, don’ts, and how to’s. International Journal of Psychological Research, 3(1), 97 110. http://www.redalyc.org/articulo.oa?id=299023509007
• McVay, M. (2001). How to be a successful distance learning student: Learning on the internet. Pearson Custom Pub.
• Meade, A.W., & Craig, S.B. (2012). Identifying careless responses in survey data. Psychological Methods, 17(3), 437–455. https://doi.org/10.1037/a0028085
• Muthén, L.K., & Muthén, B.O. (1998-2017). Mplus user’s guide (8th ed.)
• Nunnally, J.C., & Bernstein, I.H. (1967). Psychometric theory (Vol. 226). McGraw-Hill.
• Oladoke, A.O. (2006). Measurement of self-directed learning in online learners. Ph.D. Thesis, Capella University. https://www.learntechlib.org/p/118702/
• Oliver, R.G. (2001). Assuring the quality of online learning in australian higher education. Proceedings of 2000 Moving Online Conference. (pp. 222-231). Gold Coast, QLD. Norsearch Reprographics. https://ro.ecu.edu.au/ecuworks/4792
• Pillay, H., Irving, K., & Tones, M. (2007). Validation of the diagnostic tool for assessing tertiary students’ readiness for online learning. Higher Education Research & Development, 26(2), 217-234. https://doi.org/10.1080/07294360701310821
• Poole, D.M. (2000). Student participation in a discussion-oriented online course: A case study. Journal of Research on Computing in Education, 33(2), 162 177. https://doi.org/10.1080/08886504.2000.10782307
• Raykov, T. (1997). Estimation of composite reliability for congeneric measures. Applied Psychological Measurement, 21, 173-184. https://doi.org/10.1177/01466216970212006
• Richardson, C.J., & Swan, K. (2003). Examining social presence in online courses in relation to students’ perceived learning and satisfaction. Journal of Asynchronous Learning Networks, 7(1), 68-88. http://dx.doi.org/10.24059/olj.v7i1.1864
• Senemoğlu, N. (2011). Gelişim, öğrenme ve öğretim: Kuramdan uygulamaya (19. ed.). Pegem Akademi.
• Shyu, H.Y., & Brown, S.W. (1992). Learner control versus program control in interactive videodisc instruction: What are the effects in procedural learning? International Journal of Instructional Media, 19(2), 85 95.
• Simmering, M.J., Posey, C., & Piccoli, G. (2009). Computer self-efficacy and motivation to learn in a self-directed online course. Decision Sciences Journal of Innovative Education, 7(1), 99-121. https://doi.org/10.1111/j.1540-4609.2008.00207.x
• Sivo, S.A., Pan, C.C. & Hahs-Vaughn, D.L. (2007). Combined longitudinal effects of attitude and subjective norms on student outcomes in a web-enhanced course: A structural equation modeling approach. British Journal of Educational Technology, 38(5), 861-875. https://doi.org/10.1111/j.1467-8535.2006.00672.x
• Smith, P.J., Murphy, K.L., & Mahoney, S.E. (2003). Towards identifying factors underlying readiness for online learning: An exploratory study. Distance Education, 24(1), 57 67. https://doi.org/10.1080/01587910303043
• Tabachnick, B., & Fidell, L. (2013). Using multivariate statistics. Boston, MA: Pearson Education Inc.
• Thorndike, R. M. (2005). Measurement and evaluation in psychology and education. Upper Pearson Prentice Hall.
• 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
• Tucker, L.R., & Lewis, C. (1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38(1), 1-10. https://doi.org/10.1007/BF02291170
• Vrasidas, C., & McIsaac, M.C. (2000). Principles of pedagogy and evaluation for web-based learning. Education Media International, 37(2), 105 111. https://doi.org/10.1080/095239800410405
• Watkins, R., Leigh, D., & Triner, D. (2004). Assessing readiness for e-learning. Performance Improvement Quarterly, 17(4), 66 79. https://doi.org/10.1111/j.1937 8327.2004.tb00321.x
• Yurdugül, H., & Demir, Ö. (2017). An investigation of pre-service teachers' readiness for e-learning at undergraduate level teacher training programs: The case of Hacettepe University. Hacettepe Üniversitesi Eğitim Fakültesi Dergisi (H. U. Journal of Education), 32(4), 896-915. https://doi.org/10.16986/HUJE.2016022763
• Yurdugül, H., & Sırakaya, D.A. (2013). The scale of online learning readiness: a study of validity and reliability. Eğitim ve Bilim, 38(169), 391 406. http://eb.ted.org.tr/index.php/EB/article/view/2420