THE ROLE OF ONLINE EDUCATION PREFERENCES ON STUDENT’S ACHIEVEMENT

Year 2015, Volume: 16 Issue: 3, 3 - 12, 06.07.2015

Meltem Baturay , Erman Yukselturk

https://doi.org/10.17718/tojde.47810

Cited By: 17

Abstract

Online education has expanded and is expected to continue growing rapidly in time along with technological innovations. It is obvious that there is a movement toward online learning which necessitates the need of more empirical evidence on effective learning and learners’ achievement. This study investigated effect of the variables: demographics (age, gender, being employed/unemployed, and computer efficacy); Internet self-efficacy; satisfaction (student-student, student-instructor, student-content interaction); and the reasons for online education preferences of students’ on their achievement. Differing from previous studies the current study particularly investigates the effect of students’ reasons for their preferences of distance education on their success besides all other variables. The results indicated that there is a positive correlation between students’ reasons for their preferences of distance education and their achievement scores which was measured by their final test scores. Besides, according to results of the regression analyses, preferences related to achievement was the only variable to affect regression equation in the online course regression analyses. That was accounted for about 5.1 % of the variance in students’ final grades.

Keywords

Online learning; distance education; preference; achievement; satisfaction; demographics; Internet self-efficacy

Assoc. Prof. Dr. Meltem Huri BATURAY Distance Learning Research & Implementation Center

Abstract

References

• Baturay, M. H. (2010). Relationships among Sense of Classroom Community, Perceived
• Cognitive Learning and Satisfaction of Students at an E-learning Course. Interactive Learning Environments, 19(5), 563-575. Baturay, M. H. & Bay, O. F. (2010). The Effects of Problem-Based Learning on the Classroom Community Perceptions and Achievement of Web-based Education Students.
• Computers & Education, 55, 43-52. Blocher, J. M., Montes, L. S., Willis, E.M. & Tucker, G. (2002). Online learning: Examining the successful student profile. The Journal of Interactive Online Learning, 1(2): 1-12.
• Bouhnik, D., & Marcus, T. (2006). Interaction in distance-learning courses. Journal of the American Society for Information Science and Technology, 57 (3), 299-305.
• Broadley, T., & Trinidad, S. (2008). Teachers working in an online world. InN.Yelland, G.
• Neal & E. Dakich (Eds.)., Rethinking education with ICT: New directions for effective practices, (pp.149-164). Rotterdam, The Netherlands: Sense Publishers. Chyung, S. (2001). Systematic and systemic approaches to reducing attrition rates in online higher education. The American Journal of Distance Education 15 (3): 36–49.
• Ergul, H. (2004). Relationship between student characteristics and academic achievement in distance education and application on students of Anadolu University.
• Turkish Online Journal of Distance Education 5(2). Grabinger, R.S. & Dunlap, J.C. (2000). Rich environments for active learning: A definition.
• In Squires, D., Conole, G. & Jacobs, G. (Eds.). The changing face of learning technology (pp.8-38). Cardiff, Wales, UK, University of Wales. Gratton-Lavoie, C. & Stanley, D. (2009). Teaching and Learning Principles of Micro economics Online: An Empirical Assessment. Journal of Economic Education, 40(1), 3-25.
• Güngör, C. & A kar, P. (2004). E-ö renmenin ve bili sel stilin ba arı ve internet özyeterlik algızı üzerindeki etkisi. H.Ü. E itim Fakültesi Dergisi, 27, 116-125.
• Joo, Y., J., Bong, M., & Choi, H. J. (2000). Self-efficacy for self-regulated learning, academic selfefficacy, and Internet self-efficacy in Web-based instruction. Educational
• Technology Research and Development, 48(2), 5-17. King, B. F., Harner, M., & Brown, W. C. (2000). Self-regulatory behavior influences in distance learning. International Journal of Instructional Media, 27 (2), 147–156.
• Lim, C. K. (2001). Computer self-efficacy, academic self-concept, and other predictor of satisfaction and future participation of adult distance learners. The American Journal of
• Distance Education. 15(2), 41-51. Lim, D. H., & Kim, H. J. (2003). Motivation and learner characteristics affecting online learning and learning application. Journal of Educational Technology Systems, 31 (4), 423–439.
• Lim, D. H., & Morris, M. L. (2009). Learner and Instructional Factors Influencing Learning
• Outcomes within a Blended Learning Environment. Educational Technology & Society, 12 (4), 282–293. Lim, D. H., Morris, M. L. & Yoon, S. W., (2006). Combined effect of instructional and learner variables on course outcomes within an online learning environment. Journal of
• Interactive Online Learning, 5(3), 255-269. Lucas, J. W. (2007). Personality Type (MBTI) Relationship to performance and satisfaction in web-based instruction (WBI). A dissertation, Graduate Faculty of North
• Carolina State University, US. Mandernach, B. J., Donnelli, E. & Hebert-Dailey, A. (2006). Learner attribute research juxtaposed with classroom practice: Predictors of success in the accelerated, online classroom. Journal of Educators Online, 3 (2).
• Moore, M.G. (2001). Surviving as a distance teacher. American Journal of Distance Education, 15(2), 1-5.
• Murray D., Casey, D., & Fraser, J. (2007). Talkabout Walkabout: Evaluation of a Flexible
• Learning Initiative. In P. Tsang., R. Kwan., & R. Fox (Eds.), Enhancing Learning through Technology. World Scientific Publishing Co: Singapore. Qureshi, E., Morton, L. L. & Antosz, E. (2002). An interesting profile-university students who take distance education courses show weaker motivation than on-campus students.
• Online Journal of Distance Learning Administration, 5(4). Roblyer, M. D., Davis, L., Mills, S., Marshall, J., & Pape, L. (2008). Toward practical procedures for predicting and promoting success in virtual school students. The American
• Journal of Distance Education, 22(2), 90-109. Sankaran, S., & Bui, T. (2001). Impact of learning strategies and motivation on performance: A study in Web-based instruction. Journal of Instructional Psychology, 28(3), 191-198.
• 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.
• Shih, C. C. & Gamon, J. (2001). Web-based learning: Relationships among student motivation, attitude, learning styles, and achievement. Journal of Agricultural Education, 2(4), 12-20.
• Song, L., Singleton, E. S., Hill, J. R., & Koh, M. H. (2004). Improving online learning:
• Student perceptions of useful and challenging characteristics. Internet and Higher Education, 7, 59-70. Wojciechowski, A. & Palmer, L.B (2005) Individual student characteristics: can any be predictors of success in online classes? Online Journal of Distance Learning Education, 8(2).
• Wang, A. Y. & Newlin, M. H. (2002). Predictors of web student performance: the role of self-efficacy and reasons for taking an on-line class. Computers in Human Behavior, 18(2), 151-163.
• Yukselturk, E. & Bulut S. (2007) Predictors for Student Success in an Online Course,
• Educational Technology & Society,10(2), 71-83. Zimmerman, B. J. (2000). Attaining self-regulation: A social cognitive perspective. In M.
• Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 13-39). New York: Academic Press.