Journals / Çankırı Karatekin Üniversitesi Sosyal Bilimler Enstitüsü Dergisi / 2012 / Cilt: 3 - Sayı: 2

A Study on Identifying the Factors Affecting the Use of Social Software in Distance Education Environments

Uzaktan Eğitim Ortamlarında Sosyal Yazılım Kullanımının Kabulünü Etkileyen Faktörlerin Belirlenmesine Yönelik Bir Çalışma

Pages
45–68
Publication Date
2012-12-01
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

In order to examine distance learners' behavioral intention to use social software, their expectations and concerns were integrated with prior technology acceptance models, suggesting a hybrid acceptance model.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The popularity of social software -especially among younger generations-,has arisen the question of whether these technologies can be used for educational purposes.
📊
Key Findings & Data:Since there are little guiding instruments with respect to the acceptance of social software for distance learners, the grounded theory has been adopted in this study. 574 distance learners were asked two open ended questions that sought to gather the positive and negative expectations concerning the use of social networking software in their distance education programming.
💡
Conclusion & Impact:In order to examine distance learners' behavioral intention to use social software, their expectations and concerns were integrated with prior technology acceptance models, suggesting a hybrid acceptance model.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Distance Learning · Educational Social Software · Grounded Theory

Abstract

The popularity of social software -especially among younger generations-,has arisen the question of whether these technologies can be used for educational purposes. The purpose of this study is to identify the factors that influence the acceptance of social software for distance learning students. Since there are little guiding instruments with respect to the acceptance of social software for distance learners, the grounded theory has been adopted in this study. 574 distance learners were asked two open ended questions that sought to gather the positive and negative expectations concerning the use of social networking software in their distance education programming. The answers given to these questions were then coded and analyzed using QDA Miner. In order to examine distance learners' behavioral intention to use social software, their expectations and concerns were integrated with prior technology acceptance models, suggesting a hybrid acceptance model.

Özet

Sosyal yazılımların özellikle genç nesiller arasındaki popülaritesi son yıllarda bu teknolojilerin eğitsel amaçlı kullanılabilirliğinin sorgulanmasına neden olmaktadır Bu çalışmanın amacı, uzaktan eğitim programlarında sosyal yazılımlara karşı öğrencilerin kullanım niyetlerini belirleyen faktörlerin belirlenmesidir. Sosyal yazılımların uzaktan eğitimde kabulüne ilişkin enstrümanların az olması nedeniyle, bu çalışmada yerleşik kuram yaklaşımı benimsenmiştir. 574 uzaktan eğitim öğrencisine eğitimlerinde eğitsel sosyal yazılım kullanımı ile ilgili olumlu ve olumsuz beklentilerini içeren iki açık-uçlu soru yöneltilmiştir. Cevaplar QDA Miner programı ile kodlanmış ve analiz edilmiştir. Çalışma sonucunda uzaktan eğitim öğrencilerinin eğitsel sosyal yazılımları kullanma niyetlerini ortaya koymak adına, beklentileri ve endişeleri mevcut teknoloji kabul modelleri ile ilişkilendirilerek karma bir model önerisinde bulunulmuştur.

🔖

Cite This Article

AKBIYIK, A., COŞKUN, E. (2012). A Study on Identifying the Factors Affecting the Use of Social Software in Distance Education Environments. Çankırı Karatekin Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, Cilt: 3 - Sayı: 2, 45–68. https://ajindex.com/articles/128244

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (11)

  1. Adamson, J., Donovan, J.L. (2002). Research in Black and White. Qualitative Health Research, 12(6): 816-825.
  2. Ajzen, I. (1991). The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes, 50(2): 179-211.
  3. Alexander, B. (2006). Web 2.0: a new wave of innovation for teaching and learning? EDUCASE Review, 41(2): 32-44.
  4. Anderson, P. (2007). What is Web 2.0? Ideas, technologies and implications for education. JISC Technology & Standarts Watch. Anderson, T. (2005). Distance Learning: Social Software’s Killer App? http://auspace.athabascau.ca/bitstream/2149/2328/ l /distance_learnin g.pdf Bhattacherjee, A. (2001). Understanding Information Systems Continuance: An Expectation-ConŞrmation Model. MIS Quarterly, 25(3): 351- Birks, M., Mills, J. (2011). Grounded Theory: A Practical Guide. London: Sage. Brady, K.P., Holcomb, L.B., Smith, B.V. (2010). The Use of Alternative Social Networking Sites in Higher Educational Setting: A Case Study of the E-Learning BeneŞts of Ning in Education. Journal of Interactive Online Learning, 9(2): 151-170.
  5. Cadotte, E.R., Woodruff, R.B., Jenkins, R.L. (1987). Expectations and Norms in Models of Consumer Satisfaction. Journal of Marketing Research, 24(3): 305-314.
  6. Chung, J.E., Park, N., Wang, H., Fulk, J., McLaughlin, M. (2010). Age Differences in Perceptions of Online Community Participation Among Non-users: An Extension of The Technology Acceptance Model. Computers in Human Behavior, 26(6): 1674-1684.
  7. Creswell, J., Plano Clark, V. (2011). Designing and Conducting Mixed Methods Research (2. Sürüm b.). Thousand Oaks, CA: SAGE Publications. Davis, F.D. (1989).
  8. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3): 319- Davis, F.D., Bagozzi, R.P., Warshaw, P.R. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35(8): 982-1003.
  9. Fetscherin, M., Lattemann, C. (2008). User Acceptance of Virtual Worlds. Journal of Electronic Commerce Research, 9(3): 231-242.
  10. Fishbein, M., Ajzen, I. (1975).
  11. Belief Attitude, Intention, and Behavior. New York: Wiley. Garrett, N., Thoms, B., Soffer, M., Ryan, T. (2007). Extending the Elgg Social Networking System to Enhance the Campus Conversation. http://map.ipgkti.edu.my/resource/ppismptesl/refer-intemet_htm _tiles/Elgg-social network system to enhance campus conversation.pdf Glaser, B., Strauss, A. (1967). The Discovery of Grounded Theory: Strategies for Qualitative Resea