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FACTORS MOTIVATING PRESERVICE TEACHERS FOR ONLINE LEARNING WITHIN THE CONTEXT OF ARCS MOTIVATION MODEL

Year 2015, Volume: 16 Issue: 2, 56 - 68, 03.04.2015
https://doi.org/10.17718/tojde.26620

Abstract

The purpose of this study was to determine the factors motivating pre-service teachers
for online learning within the context of ARCS motivation model. The study, in which the
phenomenology model was used, was carried out with 52 pre-service teachers attending
the department of Computer Education and Instructional Technologies at the Education
Faculty of Çanakkale Onsekiz Mart University in Turkey.
The participants were experienced in online learning. In the study, the data were
collected with an open-ended questionnaire within the framework of the ARCS motivation
model. The research data were analyzed with descriptive analysis and examined fewer
than four themes (attention, relevance, confidence and satisfaction).
Also, for each theme, sub-themes were obtained. The most frequent factor motivating for
online learning was “relevance to individual differences” found under the theme of
“confidence”. As for the least frequent motivating one, it was “flexibility” found under the
theme of “relevance”.

References

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  • March 24, 2013 from http://publicationshare.com/docs/corp_survey.pdf
  • Brophy, J. (2010). Motivating students to learn (3rd edition). New York, NY: Routledge.
  • Chen, K.-C., & Jang, S.-J. (2010). Motivation in online learning: Testing a model of self- determination theory. Computers in Human Behavior, 26(4), 741-752.
  • Chyung, S. Y. (2001). Systematic and systemic approaches to reducing attrition rates in online higher education. American Journal of Distance Education, 15(3), 36-49.
  • Clark, R. E. (2001). Mediaare “merevehicles”: Theopeningargument. In R.E.Clark (Ed.),
  • Learning from media: Arguments, analysis, and evidence (2nd edition) (pp. 1-12). Greenwich, CT: Information Age. Gabrielle, D. M. (2003). The effects of technology-mediated instructional strategies on motivation, performance, and self-directed learning. Unpublished Doctoral Dissertation,
  • The Florida State University, Florida. Hodges, C. B. (2004). Designing to motivate: Motivational techniques to incorporate in e- learning experiences. The Journal of Interactive Online Learning, 2(3), 1-7.
  • Keller, J. M. (1987a). Development and use of the ARCS model of instructional design.
  • Journal of Instructional Development, 10 (3), 2-10. Keller, J. M. (1987b). Strategies for stimulating the motivation to learn. Performance & Instruction, 26(8), 1-7.
  • Keller, J. M. (1997). Motivational design and multimedia: Beyond the novelty effect.
  • Strategic Human Resource Development Review, 1(1), 188–203. Keller, J. M. (1999). Motivation in cyber learning environments. International Journal of
  • Educational Technology, 1(1), 7–30. Keller, J. M., & Suzuki, K. (2004). Learning motivation and e-learning design: A multinationally validated process. Journal of Educational Media, 29(3), 229-239.
  • Law, K. M., Lee, V., & Yu, Y.T. (2010). Learning motivation in e-learning facilitated computer programming courses. Computers & Education, 55(1), 218-228.
  • Levy, Y. (2007). Comparing dropouts and persistence in e-learning courses. Computers & Education, 48, 185–204.
  • Mayer, R. E. (2009). Multimedia learning (2nd Eds). New York, USA: Cambridge University Press.
  • Mcgreal, R., & Elliott, M. (2008). Technologies of Online Learning (E-learning) In Terry
  • Anderson (Ed.), The Theory and Practice of Online Learning (2nd ed.) (pp. 143-165). Edmonton: AU Press, Athabasca University. Mclaren, A. C. (2010). The Effects of Instructor-Learner Interactions on Learner
  • Satisfaction in Online Masters Courses. Wayne State University Dissertations. Retrieved on February 20, 2013 from http://digitalcommons.wayne.edu/oa_dissertations/105
  • Mertens, D. M. (2009). Research and evaluation in education and Psychology integrating diversity with Quantitative, Qualitative, and Mixed methods (3th ed.). California: Sage Publications.
  • Miltiadou, M., & Savenye, W.C. (2003). Applying social cognitive constructs of motivation to enhance student success in online distance education. AACE Journal, 11 (1), 78-95.
  • Miles, B. M., & Huberman, A. M. (1994). Qualitative data analysis (2nd ed.). London: Sage Publications.
  • Patton, M. Q. (1990). Qualitative Evaluation and Research Methods (2nd ed.). Newbury Park, CA: Sage Pub.
  • Patton, M. Q. (2002). Qualitative research and evaluation methods. Thousand Oaks, CA: Sage.
  • Sawang, S., Newton, C., & Jamieson, K. (2013). Increasing learners’ satisfaction/intention to adopt more e-learning. Education + Training, 55(1).
  • Shank, P., & Sitze, A. (2004). Making sense of online learning: A guide for beginners and the truly skeptical. San Francisco: Pfeiffer.
  • Smith, R. (2008) Motivational Factors in E-Learning. Retrieved on June 15, 2013 from, http://www.ruthcsmith.com/GWU%20Papers/Motivation.pdf
  • Song, S. H., & Keller, J. M. (2001). Effectiveness of motivationally adaptive computer- assisted instruction on the dynamic aspects of motivation. Educational Technology
  • Research and Development, 49(2), 5-22. Sun, P. C., Tsai, R. J., Finger, G., Chen, Y.-Y., & Yeh, D. (2008). What drives a successful e- learning? An empirical investigation of the critical factors influencing learner satisfaction.
  • Computers & Education, 50(4), 1183–1202.
  • Wlodkowski, R. J. (1985). Enhancing adult motivation to learn: A comprehensive guide for teaching all adults (3rd edition). San Francisco: Jossey-Bass.
  • Yıldırım, A., & Simsek, H. (2008). Sosyal bilimlerde nitel araştırma yöntemleri [Qualitative
  • Research Methods in Social Sciences]. Ankara: Seçkin Yayıncılık. Yukselturk, E., & Bulut, S. (2007). Predictors for student success in an online course. Educational Technology & Society, 10(2), 71-83.
Year 2015, Volume: 16 Issue: 2, 56 - 68, 03.04.2015
https://doi.org/10.17718/tojde.26620

Abstract

References

  • Bonk, C. J. (2002). Online training in an online world. CourseShare.com. Retrieved on
  • March 24, 2013 from http://publicationshare.com/docs/corp_survey.pdf
  • Brophy, J. (2010). Motivating students to learn (3rd edition). New York, NY: Routledge.
  • Chen, K.-C., & Jang, S.-J. (2010). Motivation in online learning: Testing a model of self- determination theory. Computers in Human Behavior, 26(4), 741-752.
  • Chyung, S. Y. (2001). Systematic and systemic approaches to reducing attrition rates in online higher education. American Journal of Distance Education, 15(3), 36-49.
  • Clark, R. E. (2001). Mediaare “merevehicles”: Theopeningargument. In R.E.Clark (Ed.),
  • Learning from media: Arguments, analysis, and evidence (2nd edition) (pp. 1-12). Greenwich, CT: Information Age. Gabrielle, D. M. (2003). The effects of technology-mediated instructional strategies on motivation, performance, and self-directed learning. Unpublished Doctoral Dissertation,
  • The Florida State University, Florida. Hodges, C. B. (2004). Designing to motivate: Motivational techniques to incorporate in e- learning experiences. The Journal of Interactive Online Learning, 2(3), 1-7.
  • Keller, J. M. (1987a). Development and use of the ARCS model of instructional design.
  • Journal of Instructional Development, 10 (3), 2-10. Keller, J. M. (1987b). Strategies for stimulating the motivation to learn. Performance & Instruction, 26(8), 1-7.
  • Keller, J. M. (1997). Motivational design and multimedia: Beyond the novelty effect.
  • Strategic Human Resource Development Review, 1(1), 188–203. Keller, J. M. (1999). Motivation in cyber learning environments. International Journal of
  • Educational Technology, 1(1), 7–30. Keller, J. M., & Suzuki, K. (2004). Learning motivation and e-learning design: A multinationally validated process. Journal of Educational Media, 29(3), 229-239.
  • Law, K. M., Lee, V., & Yu, Y.T. (2010). Learning motivation in e-learning facilitated computer programming courses. Computers & Education, 55(1), 218-228.
  • Levy, Y. (2007). Comparing dropouts and persistence in e-learning courses. Computers & Education, 48, 185–204.
  • Mayer, R. E. (2009). Multimedia learning (2nd Eds). New York, USA: Cambridge University Press.
  • Mcgreal, R., & Elliott, M. (2008). Technologies of Online Learning (E-learning) In Terry
  • Anderson (Ed.), The Theory and Practice of Online Learning (2nd ed.) (pp. 143-165). Edmonton: AU Press, Athabasca University. Mclaren, A. C. (2010). The Effects of Instructor-Learner Interactions on Learner
  • Satisfaction in Online Masters Courses. Wayne State University Dissertations. Retrieved on February 20, 2013 from http://digitalcommons.wayne.edu/oa_dissertations/105
  • Mertens, D. M. (2009). Research and evaluation in education and Psychology integrating diversity with Quantitative, Qualitative, and Mixed methods (3th ed.). California: Sage Publications.
  • Miltiadou, M., & Savenye, W.C. (2003). Applying social cognitive constructs of motivation to enhance student success in online distance education. AACE Journal, 11 (1), 78-95.
  • Miles, B. M., & Huberman, A. M. (1994). Qualitative data analysis (2nd ed.). London: Sage Publications.
  • Patton, M. Q. (1990). Qualitative Evaluation and Research Methods (2nd ed.). Newbury Park, CA: Sage Pub.
  • Patton, M. Q. (2002). Qualitative research and evaluation methods. Thousand Oaks, CA: Sage.
  • Sawang, S., Newton, C., & Jamieson, K. (2013). Increasing learners’ satisfaction/intention to adopt more e-learning. Education + Training, 55(1).
  • Shank, P., & Sitze, A. (2004). Making sense of online learning: A guide for beginners and the truly skeptical. San Francisco: Pfeiffer.
  • Smith, R. (2008) Motivational Factors in E-Learning. Retrieved on June 15, 2013 from, http://www.ruthcsmith.com/GWU%20Papers/Motivation.pdf
  • Song, S. H., & Keller, J. M. (2001). Effectiveness of motivationally adaptive computer- assisted instruction on the dynamic aspects of motivation. Educational Technology
  • Research and Development, 49(2), 5-22. Sun, P. C., Tsai, R. J., Finger, G., Chen, Y.-Y., & Yeh, D. (2008). What drives a successful e- learning? An empirical investigation of the critical factors influencing learner satisfaction.
  • Computers & Education, 50(4), 1183–1202.
  • Wlodkowski, R. J. (1985). Enhancing adult motivation to learn: A comprehensive guide for teaching all adults (3rd edition). San Francisco: Jossey-Bass.
  • Yıldırım, A., & Simsek, H. (2008). Sosyal bilimlerde nitel araştırma yöntemleri [Qualitative
  • Research Methods in Social Sciences]. Ankara: Seçkin Yayıncılık. Yukselturk, E., & Bulut, S. (2007). Predictors for student success in an online course. Educational Technology & Society, 10(2), 71-83.
There are 33 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Serkan Izmırlı

Ozden Sahin Izmırlı

Publication Date April 3, 2015
Submission Date April 3, 2015
Published in Issue Year 2015 Volume: 16 Issue: 2

Cite

APA Izmırlı, S., & Izmırlı, O. S. (2015). FACTORS MOTIVATING PRESERVICE TEACHERS FOR ONLINE LEARNING WITHIN THE CONTEXT OF ARCS MOTIVATION MODEL. Turkish Online Journal of Distance Education, 16(2), 56-68. https://doi.org/10.17718/tojde.26620