한국인터넷방송통신학회논문지 (The Journal of the Institute of Internet, Broadcasting and Communication)

  • 제15권3호
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  • Pages.191-199
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  • 2015
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  • 2289-0238(pISSN)
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  • 2289-0246(eISSN)
한국인터넷방송통신학회 (The Institute of Internet, Broadcasting and Communication)
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협력학습에서 SNS 사용의도와 관련변인간의 예측력 규명

Identification of the Predictability of SNS Intention to Use and Related Variables in Collaborative Learning

  • 주영주 (이화여자대학교 교육공학과) ;
  • 정애경 (인천재능대학교 유아교육과) ;
  • 강정진 (동서울대학교 정보통신과) ;
  • 고경이 (이화여자대학교 교육공학과)
  • 투고 : 2015.05.26
  • 심사 : 2015.06.10
  • 발행 : 2015.06.30
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초록

본 연구는 협력과제 수행에서 학습자의 SNS에 대한 사용의도와 관련변인간의 관계를 규명함으로써 협력학습에서의 SNS 활용에 대한 새로운 시사점을 제공하고자 하는 것이다. 기술준비도와 수용모형을 토대로 학습자의 개인적 성향, 사회적 요인, 인지적 요인으로서 기술준비도, 주관적 규범, 지각된 유용성, 지각된 사용용이성이 SNS 사용의도를 예측할 것이라고 가정하였다. 이를 검증하기 위해 E대학교 '나눔리더십' 수강생 274명을 대상으로 설문조사를 실시하고 중다회귀분석을 통해 분석하였다. 연구 결과 첫째, 낙관성, 혁신성, 불편감, 주관적 규범이 지각된 사용용이성을 예측하였다. 둘째, 낙관성, 불안정성, 주관적 규범, 지각된 사용용이성이 지각된 유용성을 예측하였다. 마지막으로, 주관적 규범, 지각된 사용용이성, 지각된 유용성이 SNS 사용의도를 예측하였다. 긍정적 기술준비도가 부정적 기술준비도보다 인지적 요인을 더 크게 예측하고, 교수자와 또래 학습자의 역할이 중요하다는 것을 시사한다.

The purposes of this study are to examine the predictability of variables related to SNS intention to use in collaborative learning and provide some new implications. Based on Technology Readiness and Acceptance Model (TRAM), we hypothesized that optimism, innovativeness, discomfort, insecurity as personal disposition variables, subjective norm as a social variable, and perceived usefulness and perceived ease of use as cognitive variables would predict SNS intention to use. For this study, 274 'Share Leadership' students in E university completed surveys and it was analyzed by multiple regression analysis. The results of this study showed as follows. First, optimism, innovativeness, discomfort, and subjective norm predicted perceived ease of use. Second, optimism, insecurity, subjective norm and perceived ease of use predicted perceived usefulness. Third, subjective norm, perceived ease of use and perceived usefulness predicted SNS intention to use. From this, it is revealed that positive technology readiness predict much more than negative technology readiness do and the role of teacher and peers is very important.

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참고문헌

  1. M. Alavi, "Computer-mediated collaborative learning: An empirical evaluation," MIS quarterly, Vol.18, No.2, pp.159-174, 1994. https://doi.org/10.2307/249763
  2. A. L. Veerman, J. E. Andriessen, and G. Kanselaar, "Learning through synchronous electronic discussion," Computers & Education, Vol.34, No.3, pp.269-290, 1994. https://doi.org/10.1016/S0360-1315(99)00050-0
  3. P. Dillenbourg, "What do you mean by collaborative learning? Collaborative-learning: Cognitive and Computational Approaches," Oxford: Elsevier, pp.1-19, 1999.
  4. Korea Internet & Security Agency., "2013 Mobile Internet Use", Seoul: Korea Internet & Security Agency, 2013.
  5. E. Kim, J. Kim, and Y. Choi., "Effects of reflective activity on learning flow, academic self-efficacy, and academic achievement toward the use of Social Network Services(SNS) on cooperative learning," The Korean Association for Educational Methodology, Vol. 23, No. 4, pp. 665-686, 2013.
  6. S. Chang and C. Nam, "The Effects of Students' Perception of Mobile Device Use and Online Communication Tool Use, and Their Collective Self-esteem on Their Attitude toward Collaborative Learning in Mobile Learning Environments," The Journal of Educational Information and Media, Vol. 19, No. 4, pp. 811-835, 2013.
  7. H. Lee, M. Choi, and M. Park, "The Effects of Self-Efficacy and User's Cognitive Factors on Reuse Intention of SNS," Korea Society for Information Management, Vol. 29, no. 3, pp. 145-167, 2012. https://doi.org/10.3743/KOSIM.2012.29.3.145
  8. A. Parasuraman, "Technology Readiness Index (TRI): A multiple-item scale to measure readiness to embrace new technologies," Journal of Service Research, Vol. 2, No. 4, pp.307-320, 2000. https://doi.org/10.1177/109467050024001
  9. D. G. Mick and S. Fournier, "Paradoxes of technology: consumer cognizance, emotions, and coping strategies," Journal of Consumer Research, Vol. 25, No. 2, pp.123-143, 1998. https://doi.org/10.1086/209531
  10. C. Lin, H. Shih, and P. J. Sher, "Integrating technology readiness into technology acceptance: The TRAM model," Psychology and Marketing, Vol.24, No.7, pp.641-657, 2007. https://doi.org/10.1002/mar.20177
  11. M. L. Meuter, A. L. Ostrom, M. J. Bitner, and R. Roundtree, "The influence of technology anxiety on consumer use and experiences with self-service technologies," Journal of Business Research, Vol.56, No.11, pp.899-906, 2003. https://doi.org/10.1016/S0148-2963(01)00276-4
  12. F. D. Davis, "Perceived usefulness, perceived ease of use, and user acceptance of information technology," MIS Quaterly, Vol. 13, No. 3, pp.319-340, 1989. https://doi.org/10.2307/249008
  13. R. Walczuch, J. Lemmink, and S. Streukens, "The effect of service employees' technology readiness on technology acceptance," Information & Management, Vol. 44, No. 2, pp. 206-215, 2007. https://doi.org/10.1016/j.im.2006.12.005
  14. A. H. Yuen and W. W. Ma, "Exploring teacher acceptance of e-learning technology," Asia Pacific Journal of Teacher Education, Vol. 36, No. 3, pp.229-243, 2008. https://doi.org/10.1080/13598660802232779
  15. J. S. C. Lin, and H. C. Chang, "The role of technology readiness in self-service technology acceptance," Managing Service Quality, Vol. 21, No. 4, pp.424-444, 2011. https://doi.org/10.1108/09604521111146289
  16. V. Venkatesh and F. D. Davis, "A theoretical extension of the technology acceptance model: four longitudinal field studies," Management Science, Vol.46, No.2, pp.186-204, 2000. https://doi.org/10.1287/mnsc.46.2.186.11926
  17. E. M. Van Raaij and J. J. Schepers, "The acceptance and use of a virtual learning environment in China," Computers & Education, Vol. 50, No. 3, pp.838-852, 2008. https://doi.org/10.1016/j.compedu.2006.09.001
  18. J. Lee, and M. Shin., "Factors for the Adoption of Smartphone-based Mobile Banking: On User's Technology Readiness and Expertise", The Journal of Society for e-Business Studies, Vol. 16, No. 4, pp. 155-172, 2011. https://doi.org/10.7838/jsebs.2011.16.4.155
  19. D. Lee, S. Lee, and J. Lee, "The Effects of Subjective Norm and Social Interactivity on Usage Intention in WBC Learning Systems," Korea Society of IT Services, Vol. 7, no. 4, pp. 21-43, 2008.
  20. S. Taylor and P. A. Todd, "Understanding information on technology usage: A test of competing models", Information Systems Research, Vol. 6, No. 2, pp.144-176, 1995. https://doi.org/10.1287/isre.6.2.144
  21. J. C. Nunnally and I. R. Bernstein, Psychometric theory, NY: McGraw-Hill, 1994.
  22. Y. Wang, H. Wang and D. Y. Shee, "Measuring e-learning systems success in an organizational context: Scale development and validation", Computers in Human Behavior, Vol. 23, No. 4, pp.1792-1808, 2007. https://doi.org/10.1016/j.chb.2005.10.006
  23. R. B. Kline, Principles and practice of structural equation modeling, Guilford Press, 2010.
  24. S. B. Moon, "Basic concepts and applications of structural equation modeling : with AMOS17.0. ", Seoul: Hakjisa, 2009.
  25. S. A. Sivo and P. Cheng-Chang, "Undergraduate Engineering and Psychology Students' Use of a Course Management System: A Factorial Invariance Study of User Characteristics and Attitudes", Journal of Technology Studies, Vol.31, No.2, pp.94-103, 2005.
  26. B. H. Cho, "Design of Social Learning Platform for Collaborative Study", The Journal of The Institute of Internet, Broadcasting and Communication (JIIBC), Vol. 13, No. 5, pp.189-194, 2013. https://doi.org/10.7236/JIIBC.2013.13.5.189