Research Article
BibTex RIS Cite
Year 2022, Volume: 7 Issue: 1, 116 - 126, 13.01.2022
https://doi.org/10.53850/joltida.1007868

Abstract

References

  • Abbitt, J. T. (2011). An investigation of the relationship between self-efficacy beliefs about technology integration and Technological Pedagogical Content Knowledge (TPACK) among preservice teachers. Journal of Digital Learning in Teacher Education, 27(4), 134-143. doi:10.1080/21532974.2011.10784670
  • Akgün, Ö. E., & Topal, M. (2015). Information security awareness of the senior teacher students: Sakarya University sample. Sakarya University Journal of Education, 2(5), 98-121.
  • Alipio, M. (2020). Education during COVID-19 era: Are learners in a less-economically developed country ready for e-learning?. SSRN. http://hdl.handle.net/10419/216098 doi:10.2139/ssrn.3586311
  • Artino, A. R. (2009). Online learning: Are subjective perceptions of instructional context related to academic success?. The Internet and Higher Education, 12(3-4), 117-125. doi:10.1016/j.iheduc.2009.07.003
  • Atkinson, J. K., & Blankenship, R. (2009). Online learning readiness of undergraduate college students: A comparison between male and female learners. Learning in Higher Education, 5, 49-56.
  • Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W.H. Freeman and Company. 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. doi:10.1080/0158791042000212440
  • Bozkurt, A. (2020). Koronavirüs (Covid19) pandemi süreci ve pandemi sonrası dünyada eğitime yönelik değerlendirmeler: Yeni normal ve yeni eğitim paradigması. Açıköğretim Uygulamaları ve Araştırmaları Dergisi, 6(3), 112-142.
  • Bozkurt, A., & Sharma, R. C. (2020). Emergency remote teaching in a time of global crisis due to CoronaVirus pandemic. Asian Journal of Distance Education, 15(1), i-vi. doi:10.5281/zenodo.3778083
  • de Bruyn, L. L. (2004). Monitoring online communication: Can the development of convergence and social presence indicate an interactive learning environment?. Distance Education, 25(1), 67-81. doi: 10.1080/0158791042000212468
  • Chu, R. J. C. (2010). How family support and Internet self-efficacy influence the effects of e-learning among higher aged adults–Analyses of gender and age differences. Computers & Education, 55(1), 255-264. doi: 10.1016/j.compedu.2010.01.011
  • Chung, E., Subramaniam, G., & Dass, L. C. (2020). Online learning readiness among university students in Malaysia amidst COVID-19. Asian Journal of University Education, 16(2), 46-58. doi:10.24191/ajue.v16i2.10294
  • Cohen, J. (1997). Statistical power analysis for the behavioral sciences. NY, SF, London: Academic Press. Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches. Sage Publications.
  • Ćukušić, M., Alfirević, N., Granić, A., & Garača, Ž. (2010). E-learning process management and the e-learning performance: Results of a European empirical study. Computers & Education, 55(2), 554-565. doi: 10.1016/j.compedu.2010.02.017
  • Çokluk, Ö., Şekercioğlu, G., & Büyüköztürk, Ş. (2010). Sosyal bilimler için çok değişkenli istatistik: SPSS ve LISREL uygulamaları. Ankara: Pegem Akademi.
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
  • Decker, C. A. (2002). Computer preparedness: A study of computer use self-efficacy among DECA Students in Kentucky. In Hauppauge, S. S. (Eds.), Trends in cognitive psychology. NY: Nova Science Publishers, 2002.
  • Dehghanbanadaki, H., Seif, F., Vahidi, Y., Razi, F., Hashemi, E., Khoshmirsafa, M., & Aazami, H. (2020). Bibliometric analysis of global scientific research on Coronavirus (COVID-19). Medical Journal of the Islamic Republic of Iran, 34(1), 354-362. doi:10.34171/mjiri.34.51
  • 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. doi: 10.12738/estp.2013.3.1580
  • DeVellis, R. F. (2012). Scale development: Theory and applications. Sage Publications.
  • Dray, B. J., Lowenthal, P. R., Miszkiewicz, M. J., Ruiz‐Primo, M. A., & Marczynski, K. (2011). Developing an instrument to assess student readiness for online learning: A validation study. Distance Education, 32(1), 29-47. doi:10.1080/01587919.2011.565496
  • Firat, M., & Bozkurt, A. (2020). Variables affecting online learning readiness in an open and distance learning university. Educational Media International, 57(2), 112-127. doi:10.1080/09523987.2020.1786772
  • Galy, E., Downey, C., & Johnson, J. (2011). The effect of using e-learning tools in online and campus-based classrooms on student performance. Journal of Information Technology Education, 10(1), 209-230. George, D. (2011). SPSS for windows step by step: A simple study guide and reference, 17.0 update, 10/e. Pearson Education India.
  • González-Gómez, F., Guardiola, J., Rodríguez, Ó. M., & Alonso, M. Á. M. (2012). Gender differences in e-learning satisfaction. Computers & Education, 58(1), 283-290. doi:10.1016/j.compedu.2011.08.017
  • Gottman, J. M., McFall, R. M., & Barnett, J. T. (1969). Design and analysis of research using time series. Psychological Bulletin, 72(4), 299-306.
  • Gündüz, A. Y., & İşman, A. (2018). Pre-service teachers’ perception of distance education. TOJET: The Turkish Online Journal of Educational Technology, 17(1), 125-129.
  • Harvey, T. J., & Wilson, B. (1985). Gender differences in attitudes towards microcomputers shown by primary and secondary school pupils. British Journal of Educational Technology, 16(3), 183-187.
  • Haseski, H. İ. (2019). Information Technologies Course: An evaluation from the perspective of pre-service teachers. Trakya Journal of Education, 9(4), 666-679. doi:10.24315/tred.494705
  • Haseski, H. İ. (2020). Cyber security skills of pre-service teachers as a factor in computer-assisted education. International Journal of Research in Education and Science, 6(3), 484-500.
  • Higher Education Council (2021, October 8). Öğretmen Yetiştirme Lisans Programları. Retrieved from https://www.yok.gov.tr/Documents/Kurumsal/egitim_ogretim_dairesi/Yeni-Ogretmen-Yetistirme-Lisans-Programlari/Rehberlik_ve_Psikolojik_Danismanlik_Lisans_Programi.pdf
  • Horzum, M. B., Kaymak, Z. D., & Gungoren, O. C. (2015). Structural equation modeling towards online learning readiness, academic motivations, and perceived learning. Educational Sciences: Theory and Practice, 15(3), 759-770. doi:10.12738/estp.2015.3.2410
  • Horzum, M. B., Önder, İ., & Beşoluk, Ş. (2014). Chronotype and academic achievement among online learning students. Learning and Individual Differences, 30, 106-111. doi:10.1016/j.lindif.2013.10.017
  • Hossain, M. M. (2020). Current status of global research on novel Coronavirus disease (Covid-19): A bibliometric analysis and knowledge mapping. F1000Research, 9, 1-13. doi:10.12688/f1000research.23690.1 Hukle, D. R. L. (2009). An evaluation of readiness ractors for online education. (Unpublished doctoral dissertation). Mississippi State University, Mississippi.
  • Hung, M. L. (2016). Teacher readiness for online learning: Scale development and teacher perceptions. Computers & Education, 94, 120-133. doi: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. doi:10.1016/j.compedu.2010.05.004
  • Ilgaz, H., & Gülbahar, Y. (2015). A snapshot of online learners: E-readiness, e-satisfaction and expectations. International Review of Research in Open and Distributed Learning, 16(2), 171-187. doi:10.19173/irrodl.v16i2.2117
  • İlic, U. (2019). Instructional Technologies course from the perspective of faculty members. Paper presented at 1st Social and Human Sciences Congress, Malatya, Turkey.
  • İlic, U. (2021a). Online course satisfaction in a holistic flipped classroom approach. Journal of Educational Technology & Online Learning, 4(3), 432-447.
  • İlic, U. (2021b). Online learning readiness, phubbing and sofalizing levels of pre-service teachers amidst pandemic. Shanlax International Journal of Education, 9(4), 1–12. doi:10.34293/education.v9i4.4027
  • İlic, U. (2021c). The impact of Scratch-assisted instruction on Computational Thinking (CT) skills of pre-service teachers. International Journal of Research in Education and Science, 7(2), 426-444. doi:10.46328/ijres.1075
  • Joosten, T., & Cusatis, R. (2020). Online learning readiness. American Journal of Distance Education, 34(3), 180-193. doi:10.1080/08923647.2020.1726167
  • Kahveci, A., Sahin, N., & Genc, S. (2011). Computer perceptions of secondary school teachers and impacting demographics: A Turkish perspective. Turkish Online Journal of Educational Technology-TOJET, 10(1), 71-80
  • Keramati, A., Afshari-Mofrad, M., & Kamrani, A. (2011). The role of readiness factors in e-learning outcomes: An empirical study. Computers & Education, 57(3), 1919-1929. doi:10.1016/j.compedu.2011.04.005
  • Kerr, M. S., Rynearson, K., & Kerr, M. C. (2006). Student characteristics for online learning success. The Internet and Higher Education, 9(2), 91-105. doi:10.1016/j.iheduc.2006.03.002
  • Kharma, Q. (2019). Investigating students’ acceptance of online courses at Al-Ahliyya Amman University. Int. J. Adv. Comput. Sci. Appl, 10(7), 202-208.
  • Kline, P. (2000). The handbook of psychological testing. London: Routledge.
  • Kruger-Ross, M. J., & Waters, R. D. (2013). Predicting online learning success: Applying the situational theory of publics to the virtual classroom. Computers & Education, 61, 176-184. doi:10.1016/j.compedu.2012.09.015
  • Lawless, K. A., & Brown, S. W. (1997). Multimedia learning environments: Issues of learner control and navigation. Instructional science, 25(2), 117-131.
  • Lin, B., & Hsieh, C. T. (2001). Web-based teaching and learner control: A research review. Computers & Education, 37(3-4), 377-386. doi:10.1016/S0360-1315(01)00060-4
  • Masters, K., & Oberprieler, G. (2004). Encouraging equitable online participation through curriculum articulation. Computers & Education, 42(4), 319-332. doi:10.1016/j.compedu.2003.09.001
  • Pallant, J. (2001). "Survival manual." A step by step guide to data analysis using SPSS. Maidenhead, PA: Open University Press.
  • Pillay, H., Irving, K., & Tones, M. (2007). Validation of the diagnostic tool for assessing tertiary students’ readiness for online learning. High Education Research & Development, 26(2), 217-234. doi:10.1080/07294360701310821
  • Rahimi, M. (2011). The impact of computer-based activities on Iranian high-school students’ attitudes towards computer-assisted language learning. Procedia Computer Science, 3, 183-190.
  • Roussos, P. (2007). The Greek computer attitudes scale: Construction and assessment of psychometric properties. Computers in Human Behavior, 23(1), 578-590. doi:10.1016/j.chb.2004.10.027
  • Sánchez-Prieto, J. C., Olmos-Migueláñez, S., & García-Peñalvo, F. J. (2017). Mlearning and pre-service teachers: An assessment of the behavioral intention using an expanded TAM model. Computers in Human Behavior, 72, 644-654. doi:10.1016/j.chb.2016.09.061
  • Schrum, L., & Hong, S. (2002). From the field: Characteristics of successful tertiary online students and strategies of experienced online educators. Education and Information Technologies, 7(1), 5-16.
  • Selim, H. M. (2007). Critical success factors for e-learning acceptance: Confirmatory factor models. Computers & Education, 49(2), 396-413. doi:10.1016/j.compedu.2005.09.004
  • Selwyn, N. (1998). The effect of using a home computer on students' educational use of IT. Computers & Education, 31(2), 211-227. doi:10.1016/S0360-1315(98)00033-5
  • Smith, P. J. (2005). Learning preferences and readiness for online learning. Educational Psychology, 25(1), 3-12. doi:10.1080/0144341042000294868
  • 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. doi:10.1080/01587910303043
  • Tang, S. F., & Lim, C. L. (2013). Undergraduate students’ readiness in e-learning: A study at the business school in a Malaysian private university. International Journal of Management & Information Technology, 4(2), 198-204.
  • Teo, H. H., Wan, W., Chan, H., & Lim, C. Y. (2002). Bridging the digital divide: The effects of home computer ownership and school IT environment on self-directed learning. Paper presented at International Conference on Information Systems(ICIS).
  • Torkzadeh, G., & Koufteros, X. (1994). Factorial validity of a computer self-efficacy scale and the impact of computer training. Educational and Psychological Measurement, 54(3), 813-821. doi:10.1177/0013164494054003028
  • Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.
  • Vonderwell, S., & Savery, J. (2004). Online learning: Student role and readiness. Turkish Online Journal of Educational Technology-TOJET, 3(3), 38-42.
  • Wainer, H., & Thissen, D. (1996). How is reliability related to the quality of test scores? What is the effect of local dependence on reliability?. Educational Measurement: Issues and Practice, 15(1), 22-29.
  • Wang, C. H., Shannon, D. M., & Ross, M. E. (2013). Students’ characteristics, self-regulated learning, technology self-efficacy, and course outcomes in online learning. Distance Education, 34(3), 302-323. doi:10.1080/01587919.2013.835779
  • World Health Organization. (2021, October 9). Coronavirus disease (COVID-19) pandemic. Retrieved from https://www.who.int/emergencies/diseases/novel-coronavirus-2019.
  • Worldometer. (2021, December 15). COVID-19 Coronavirus pandemic. Retrieved from https://www.worldometers.info/coronavirus/.
  • Wynn, L. (2002). School readiness: Starting your child off right. Raleigh, NC: North Carolina Partnership for Children.
  • Xu, D., & Wang, H. (2006). Intelligent agent supported personalization for virtual learning environments. Decision Support Systems, 42(2), 825-843. doi:10.1016/j.dss.2005.05.033
  • Yeboah, A. K., & Smith, P. (2016). Relationships between minority students online learning experiences and academic performance. Online Learning, 20(4).
  • Yıldırım, A., & Şimşek, H. (2011). Qualitative research methods in social sciences. Ankara: Seçkin Publishing. Yu, T. (2018). Examining construct validity of the Student Online Learning Readiness (SOLR) instrument using confirmatory factor analysis. Online Learning, 22(4), 277-288.
  • 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. H. U. Journal of Education, 32(4), 896-915. doi:10.16986/huje.2016022763
  • Yurdugül, H., & Sarikaya, D. A. (2013). The scale of online learning readiness: A study of validity and reliability. Egitim ve Bilim, 38(169), 391-406.

The Impact of ICT Instruction on Online Learning Readiness of Pre-Service Teachers

Year 2022, Volume: 7 Issue: 1, 116 - 126, 13.01.2022
https://doi.org/10.53850/joltida.1007868

Abstract

The present study aimed to investigate the impact of a course that included ICT skills on the online learning readiness of pre-service teachers in a completely distance education environment. In the research, single group pre-test post-test model was adopted. The study was conducted with 123 pre-service teachers. The E-Learning Readiness Scale for College Students was used to collect the data. Furthermore, the course academic achievement final scores of the participants were employed. The data collection process continued during the 2020-2021 academic year fall term. The study findings demonstrated that total online learning readiness and sub-dimension scores increased after the Information Technologies Course. It was found that there was no difference across the scores based on gender. The academic achievements of female students were higher. At the beginning of the term, it was revealed that ease of use, online learning readiness and computer self-efficacy, internet self-efficacy and learner control variables varied based on personal computer ownership. At the end of the term, both these variables and academic achievement did not differ across personal computer ownership. There was a correlation between the ease of use variable and online learning readiness both at the beginning and the end of the term. On the other hand, there was no correlation between the academic achievement and ease of use or online learning readiness. It could be suggested that the present study findings could contribute to future studies in terms of online learning readiness.

References

  • Abbitt, J. T. (2011). An investigation of the relationship between self-efficacy beliefs about technology integration and Technological Pedagogical Content Knowledge (TPACK) among preservice teachers. Journal of Digital Learning in Teacher Education, 27(4), 134-143. doi:10.1080/21532974.2011.10784670
  • Akgün, Ö. E., & Topal, M. (2015). Information security awareness of the senior teacher students: Sakarya University sample. Sakarya University Journal of Education, 2(5), 98-121.
  • Alipio, M. (2020). Education during COVID-19 era: Are learners in a less-economically developed country ready for e-learning?. SSRN. http://hdl.handle.net/10419/216098 doi:10.2139/ssrn.3586311
  • Artino, A. R. (2009). Online learning: Are subjective perceptions of instructional context related to academic success?. The Internet and Higher Education, 12(3-4), 117-125. doi:10.1016/j.iheduc.2009.07.003
  • Atkinson, J. K., & Blankenship, R. (2009). Online learning readiness of undergraduate college students: A comparison between male and female learners. Learning in Higher Education, 5, 49-56.
  • Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W.H. Freeman and Company. 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. doi:10.1080/0158791042000212440
  • Bozkurt, A. (2020). Koronavirüs (Covid19) pandemi süreci ve pandemi sonrası dünyada eğitime yönelik değerlendirmeler: Yeni normal ve yeni eğitim paradigması. Açıköğretim Uygulamaları ve Araştırmaları Dergisi, 6(3), 112-142.
  • Bozkurt, A., & Sharma, R. C. (2020). Emergency remote teaching in a time of global crisis due to CoronaVirus pandemic. Asian Journal of Distance Education, 15(1), i-vi. doi:10.5281/zenodo.3778083
  • de Bruyn, L. L. (2004). Monitoring online communication: Can the development of convergence and social presence indicate an interactive learning environment?. Distance Education, 25(1), 67-81. doi: 10.1080/0158791042000212468
  • Chu, R. J. C. (2010). How family support and Internet self-efficacy influence the effects of e-learning among higher aged adults–Analyses of gender and age differences. Computers & Education, 55(1), 255-264. doi: 10.1016/j.compedu.2010.01.011
  • Chung, E., Subramaniam, G., & Dass, L. C. (2020). Online learning readiness among university students in Malaysia amidst COVID-19. Asian Journal of University Education, 16(2), 46-58. doi:10.24191/ajue.v16i2.10294
  • Cohen, J. (1997). Statistical power analysis for the behavioral sciences. NY, SF, London: Academic Press. Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches. Sage Publications.
  • Ćukušić, M., Alfirević, N., Granić, A., & Garača, Ž. (2010). E-learning process management and the e-learning performance: Results of a European empirical study. Computers & Education, 55(2), 554-565. doi: 10.1016/j.compedu.2010.02.017
  • Çokluk, Ö., Şekercioğlu, G., & Büyüköztürk, Ş. (2010). Sosyal bilimler için çok değişkenli istatistik: SPSS ve LISREL uygulamaları. Ankara: Pegem Akademi.
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
  • Decker, C. A. (2002). Computer preparedness: A study of computer use self-efficacy among DECA Students in Kentucky. In Hauppauge, S. S. (Eds.), Trends in cognitive psychology. NY: Nova Science Publishers, 2002.
  • Dehghanbanadaki, H., Seif, F., Vahidi, Y., Razi, F., Hashemi, E., Khoshmirsafa, M., & Aazami, H. (2020). Bibliometric analysis of global scientific research on Coronavirus (COVID-19). Medical Journal of the Islamic Republic of Iran, 34(1), 354-362. doi:10.34171/mjiri.34.51
  • 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. doi: 10.12738/estp.2013.3.1580
  • DeVellis, R. F. (2012). Scale development: Theory and applications. Sage Publications.
  • Dray, B. J., Lowenthal, P. R., Miszkiewicz, M. J., Ruiz‐Primo, M. A., & Marczynski, K. (2011). Developing an instrument to assess student readiness for online learning: A validation study. Distance Education, 32(1), 29-47. doi:10.1080/01587919.2011.565496
  • Firat, M., & Bozkurt, A. (2020). Variables affecting online learning readiness in an open and distance learning university. Educational Media International, 57(2), 112-127. doi:10.1080/09523987.2020.1786772
  • Galy, E., Downey, C., & Johnson, J. (2011). The effect of using e-learning tools in online and campus-based classrooms on student performance. Journal of Information Technology Education, 10(1), 209-230. George, D. (2011). SPSS for windows step by step: A simple study guide and reference, 17.0 update, 10/e. Pearson Education India.
  • González-Gómez, F., Guardiola, J., Rodríguez, Ó. M., & Alonso, M. Á. M. (2012). Gender differences in e-learning satisfaction. Computers & Education, 58(1), 283-290. doi:10.1016/j.compedu.2011.08.017
  • Gottman, J. M., McFall, R. M., & Barnett, J. T. (1969). Design and analysis of research using time series. Psychological Bulletin, 72(4), 299-306.
  • Gündüz, A. Y., & İşman, A. (2018). Pre-service teachers’ perception of distance education. TOJET: The Turkish Online Journal of Educational Technology, 17(1), 125-129.
  • Harvey, T. J., & Wilson, B. (1985). Gender differences in attitudes towards microcomputers shown by primary and secondary school pupils. British Journal of Educational Technology, 16(3), 183-187.
  • Haseski, H. İ. (2019). Information Technologies Course: An evaluation from the perspective of pre-service teachers. Trakya Journal of Education, 9(4), 666-679. doi:10.24315/tred.494705
  • Haseski, H. İ. (2020). Cyber security skills of pre-service teachers as a factor in computer-assisted education. International Journal of Research in Education and Science, 6(3), 484-500.
  • Higher Education Council (2021, October 8). Öğretmen Yetiştirme Lisans Programları. Retrieved from https://www.yok.gov.tr/Documents/Kurumsal/egitim_ogretim_dairesi/Yeni-Ogretmen-Yetistirme-Lisans-Programlari/Rehberlik_ve_Psikolojik_Danismanlik_Lisans_Programi.pdf
  • Horzum, M. B., Kaymak, Z. D., & Gungoren, O. C. (2015). Structural equation modeling towards online learning readiness, academic motivations, and perceived learning. Educational Sciences: Theory and Practice, 15(3), 759-770. doi:10.12738/estp.2015.3.2410
  • Horzum, M. B., Önder, İ., & Beşoluk, Ş. (2014). Chronotype and academic achievement among online learning students. Learning and Individual Differences, 30, 106-111. doi:10.1016/j.lindif.2013.10.017
  • Hossain, M. M. (2020). Current status of global research on novel Coronavirus disease (Covid-19): A bibliometric analysis and knowledge mapping. F1000Research, 9, 1-13. doi:10.12688/f1000research.23690.1 Hukle, D. R. L. (2009). An evaluation of readiness ractors for online education. (Unpublished doctoral dissertation). Mississippi State University, Mississippi.
  • Hung, M. L. (2016). Teacher readiness for online learning: Scale development and teacher perceptions. Computers & Education, 94, 120-133. doi: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. doi:10.1016/j.compedu.2010.05.004
  • Ilgaz, H., & Gülbahar, Y. (2015). A snapshot of online learners: E-readiness, e-satisfaction and expectations. International Review of Research in Open and Distributed Learning, 16(2), 171-187. doi:10.19173/irrodl.v16i2.2117
  • İlic, U. (2019). Instructional Technologies course from the perspective of faculty members. Paper presented at 1st Social and Human Sciences Congress, Malatya, Turkey.
  • İlic, U. (2021a). Online course satisfaction in a holistic flipped classroom approach. Journal of Educational Technology & Online Learning, 4(3), 432-447.
  • İlic, U. (2021b). Online learning readiness, phubbing and sofalizing levels of pre-service teachers amidst pandemic. Shanlax International Journal of Education, 9(4), 1–12. doi:10.34293/education.v9i4.4027
  • İlic, U. (2021c). The impact of Scratch-assisted instruction on Computational Thinking (CT) skills of pre-service teachers. International Journal of Research in Education and Science, 7(2), 426-444. doi:10.46328/ijres.1075
  • Joosten, T., & Cusatis, R. (2020). Online learning readiness. American Journal of Distance Education, 34(3), 180-193. doi:10.1080/08923647.2020.1726167
  • Kahveci, A., Sahin, N., & Genc, S. (2011). Computer perceptions of secondary school teachers and impacting demographics: A Turkish perspective. Turkish Online Journal of Educational Technology-TOJET, 10(1), 71-80
  • Keramati, A., Afshari-Mofrad, M., & Kamrani, A. (2011). The role of readiness factors in e-learning outcomes: An empirical study. Computers & Education, 57(3), 1919-1929. doi:10.1016/j.compedu.2011.04.005
  • Kerr, M. S., Rynearson, K., & Kerr, M. C. (2006). Student characteristics for online learning success. The Internet and Higher Education, 9(2), 91-105. doi:10.1016/j.iheduc.2006.03.002
  • Kharma, Q. (2019). Investigating students’ acceptance of online courses at Al-Ahliyya Amman University. Int. J. Adv. Comput. Sci. Appl, 10(7), 202-208.
  • Kline, P. (2000). The handbook of psychological testing. London: Routledge.
  • Kruger-Ross, M. J., & Waters, R. D. (2013). Predicting online learning success: Applying the situational theory of publics to the virtual classroom. Computers & Education, 61, 176-184. doi:10.1016/j.compedu.2012.09.015
  • Lawless, K. A., & Brown, S. W. (1997). Multimedia learning environments: Issues of learner control and navigation. Instructional science, 25(2), 117-131.
  • Lin, B., & Hsieh, C. T. (2001). Web-based teaching and learner control: A research review. Computers & Education, 37(3-4), 377-386. doi:10.1016/S0360-1315(01)00060-4
  • Masters, K., & Oberprieler, G. (2004). Encouraging equitable online participation through curriculum articulation. Computers & Education, 42(4), 319-332. doi:10.1016/j.compedu.2003.09.001
  • Pallant, J. (2001). "Survival manual." A step by step guide to data analysis using SPSS. Maidenhead, PA: Open University Press.
  • Pillay, H., Irving, K., & Tones, M. (2007). Validation of the diagnostic tool for assessing tertiary students’ readiness for online learning. High Education Research & Development, 26(2), 217-234. doi:10.1080/07294360701310821
  • Rahimi, M. (2011). The impact of computer-based activities on Iranian high-school students’ attitudes towards computer-assisted language learning. Procedia Computer Science, 3, 183-190.
  • Roussos, P. (2007). The Greek computer attitudes scale: Construction and assessment of psychometric properties. Computers in Human Behavior, 23(1), 578-590. doi:10.1016/j.chb.2004.10.027
  • Sánchez-Prieto, J. C., Olmos-Migueláñez, S., & García-Peñalvo, F. J. (2017). Mlearning and pre-service teachers: An assessment of the behavioral intention using an expanded TAM model. Computers in Human Behavior, 72, 644-654. doi:10.1016/j.chb.2016.09.061
  • Schrum, L., & Hong, S. (2002). From the field: Characteristics of successful tertiary online students and strategies of experienced online educators. Education and Information Technologies, 7(1), 5-16.
  • Selim, H. M. (2007). Critical success factors for e-learning acceptance: Confirmatory factor models. Computers & Education, 49(2), 396-413. doi:10.1016/j.compedu.2005.09.004
  • Selwyn, N. (1998). The effect of using a home computer on students' educational use of IT. Computers & Education, 31(2), 211-227. doi:10.1016/S0360-1315(98)00033-5
  • Smith, P. J. (2005). Learning preferences and readiness for online learning. Educational Psychology, 25(1), 3-12. doi:10.1080/0144341042000294868
  • 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. doi:10.1080/01587910303043
  • Tang, S. F., & Lim, C. L. (2013). Undergraduate students’ readiness in e-learning: A study at the business school in a Malaysian private university. International Journal of Management & Information Technology, 4(2), 198-204.
  • Teo, H. H., Wan, W., Chan, H., & Lim, C. Y. (2002). Bridging the digital divide: The effects of home computer ownership and school IT environment on self-directed learning. Paper presented at International Conference on Information Systems(ICIS).
  • Torkzadeh, G., & Koufteros, X. (1994). Factorial validity of a computer self-efficacy scale and the impact of computer training. Educational and Psychological Measurement, 54(3), 813-821. doi:10.1177/0013164494054003028
  • Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.
  • Vonderwell, S., & Savery, J. (2004). Online learning: Student role and readiness. Turkish Online Journal of Educational Technology-TOJET, 3(3), 38-42.
  • Wainer, H., & Thissen, D. (1996). How is reliability related to the quality of test scores? What is the effect of local dependence on reliability?. Educational Measurement: Issues and Practice, 15(1), 22-29.
  • Wang, C. H., Shannon, D. M., & Ross, M. E. (2013). Students’ characteristics, self-regulated learning, technology self-efficacy, and course outcomes in online learning. Distance Education, 34(3), 302-323. doi:10.1080/01587919.2013.835779
  • World Health Organization. (2021, October 9). Coronavirus disease (COVID-19) pandemic. Retrieved from https://www.who.int/emergencies/diseases/novel-coronavirus-2019.
  • Worldometer. (2021, December 15). COVID-19 Coronavirus pandemic. Retrieved from https://www.worldometers.info/coronavirus/.
  • Wynn, L. (2002). School readiness: Starting your child off right. Raleigh, NC: North Carolina Partnership for Children.
  • Xu, D., & Wang, H. (2006). Intelligent agent supported personalization for virtual learning environments. Decision Support Systems, 42(2), 825-843. doi:10.1016/j.dss.2005.05.033
  • Yeboah, A. K., & Smith, P. (2016). Relationships between minority students online learning experiences and academic performance. Online Learning, 20(4).
  • Yıldırım, A., & Şimşek, H. (2011). Qualitative research methods in social sciences. Ankara: Seçkin Publishing. Yu, T. (2018). Examining construct validity of the Student Online Learning Readiness (SOLR) instrument using confirmatory factor analysis. Online Learning, 22(4), 277-288.
  • 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. H. U. Journal of Education, 32(4), 896-915. doi:10.16986/huje.2016022763
  • Yurdugül, H., & Sarikaya, D. A. (2013). The scale of online learning readiness: A study of validity and reliability. Egitim ve Bilim, 38(169), 391-406.
There are 74 citations in total.

Details

Primary Language English
Subjects Other Fields of Education
Journal Section Research Article
Authors

Ulaş İlic 0000-0003-4213-8713

Publication Date January 13, 2022
Submission Date October 12, 2021
Published in Issue Year 2022 Volume: 7 Issue: 1

Cite

APA İlic, U. (2022). The Impact of ICT Instruction on Online Learning Readiness of Pre-Service Teachers. Journal of Learning and Teaching in Digital Age, 7(1), 116-126. https://doi.org/10.53850/joltida.1007868

Journal of Learning and Teaching in Digital Age 2023. © 2023. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. 19195

Journal of Learning and Teaching in Digital Age. All rights reserved, 2023. ISSN:2458-8350