Skip to main content

Advertisement

Log in

The Impact of an Online Collaborative Program on Intrinsic Motivation, Satisfaction and Attitudes Towards Technology

  • Original research
  • Published:
Technology, Knowledge and Learning Aims and scope Submit manuscript

Abstract

This research examined the contribution of an online collaborative program involving students from two different teacher training colleges. It measured the impact of the program on attitudes towards technology with regard to technological anxiety, self-confidence and technological liking among students. The advanced online collaborative program at the training colleges was based on a model that used technology to increase trust between students from different cultures through online learning. The research was qualitative and was based on 58 graduate students who participated in the program. The questionnaires answered by participants dealt with the level of collaboration, intrinsic motivation, satisfaction, and attitudes towards technology. The results indicate that in an online collaborative program the student’s intrinsic motivation is affected by the level of his/her satisfaction, and this affects his/her attitudes towards technology when this is the only course for enhancing technology in education. The most significant contribution is to the liking of the use of advanced technologies, then to the self-confidence in using technology, and finally to decreasing the anxiety of technology.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Abedin, B. (2012). Sense of community and learning outcomes in computer supported collaborative learning environments. Proceedings of business and information: International Conference on Business and Information (BAI 2012), 9(1), D964–D969.

    Google Scholar 

  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes,50, 179–211.

    Google Scholar 

  • Ajzen, I. (2002). Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. Journal of Applied Social Psychology,32, 665–683.

    Google Scholar 

  • Amirault, R. J. (2012). Distance learning in the 21st century university. The Quarterly Review of Distance Education,13(4), 253–265.

    Google Scholar 

  • Arbuckle, J. L. (2013). AMOS 22.0 user’s guide. Chicago: SPSS Inc.

    Google Scholar 

  • Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin,88, 588–606.

    Google Scholar 

  • Blunch, N. J. (2008). Introduction to structural equation modelling using SPSS and AMOS. Thousand Oaks: SAGE Publications.

    Google Scholar 

  • Byrne, B. M. (2009). Structural equation modeling with AMOS. Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Callaghan, D. E., Graff, M. G., & Davies, J. (2013). Revealing all: Misleading self-disclosure rates in laboratory based on-line research. Cyberpsychology, Behavior, and Social Networking,16(9), 690–694.

    Google Scholar 

  • Cazan, A. M., Cocorada, E., & Maican, C. I. (2016). Computer anxiety and attitudes towards the computer and the internet with Romanian high-school and university students. Computers in Human Behavior,55, 258–267.

    Google Scholar 

  • Cheng, A.-C., Jordan, M. E., & Schallert, D. L. (2013). Reconsidering assessment in online/hybrid courses: Knowing versus learning. Computers & Education,68, 51–59.

    Google Scholar 

  • Choresh, N., & Magen-Nagar, N. (2017). Identifying the scale components of teacher trainers’ professional development in ICT. International Journal of Information and Education Technology,7(7), 518–524.

    Google Scholar 

  • Collins, A., Joseph, D., & Bielaczyc, K. (2004). Design research: Theoretical and methodological issues. Journal of the Learning Sciences,13(1), 15–42.

    Google Scholar 

  • Cunningham, C. A. (2009). Transforming schooling through technology: Twenty-first century approaches to participatory learning. Education and Culture,25(2), 46–61.

    Google Scholar 

  • Dayan, R., & Magen-Nagar, N. (2013). Teachers satisfaction following online courses in the ICT field. In Y. Yair & A. Shmueli (Eds.), MEITAL’s 11th national convention book: The world of open information—New technologies and the ways to evaluate them in online teaching and learning (pp. 136–140). Jerusalem: The Hebrew University (Hebrew).

    Google Scholar 

  • De Freitas, S., & Oliver, M. (2005). Does E-learning policy drive change in higher education? A case study relating models of organizational change to E-leaning implementation. Journal of Higher Education Policy and Management,27(1), 81–95.

    Google Scholar 

  • Demir, O., & Yurdugül, H. (2014). The adaptation of the scale of attitude towards computer into Turkish for middle and secondary school students. Education and Science,39(176), 247–256.

    Google Scholar 

  • Doll, J., & Ajzen, I. (1992). Accessibility and stability of predictors in the theory of planned behavior. Journal of Personality and Social Psychology,63, 754–765.

    Google Scholar 

  • Farrell, D., & Moffat, D. (2014). Applying the self-determination theory of motivation in games based learning. Paper presented at the, Vol. 1, pp. 118–127. Retrieved from https://search.proquest.com.hercules.macam.ac.il/docview/1674172762?accountid=41230.

  • Francisa, L., Katzb, Y., & Jones, H. (2000). The reliability and validity of the Hebrew version of the computer attitude scale. Computers & Education,35, 149–159.

    Google Scholar 

  • Fullan, M., & Langworthy, M. (2013). Towards a new end: New pedagogies for deep learning. http://www.newpedagogies.info/wp-content/uploads/2014/01/New_Pedagogies_for_Deep%20Learning_Whitepaper.pdf.

  • Halverson, R., & Smith, A. (2010). How new technologies have (and have not) changed teaching and learning in school. Journal of Computing in Teacher Education,26(2), 16–49.

    Google Scholar 

  • Hanze, M., & Berger, R. (2007). Cooperative learning, motivational effects and student characteristics: An experimental study comparing cooperative learning and direct instruction in 12th grand physics classes. Learning and Instruction,1(17), 29–41.

    Google Scholar 

  • Harasim, L. (2012). Learning theory and online technology: How new technologies are transforming learning opportunities. New York: Routledge Press.

    Google Scholar 

  • Horizon Report. (2014). Higher education edition. NMC. http://www.nmc.org/publications/2014-horizon-report-higher-ed.

  • Hoter, E., Shonfeld, M., & Ganayem, A. (2009). Information and communication technology (ICT) in the service of multiculturalism. IRRODL, 10(2). Retrieved from http://www.irrodl. org/index.php/irrodl/article/view/601/1207

  • Hue, L., & Ab Jalil, H. (2013). Attitudes towards ICT integration into curriculum and usage among university lecturers in Vietnam. International Journal of Instruction,6(2), 54–66.

    Google Scholar 

  • Johnson, D. W., & Johnson, F. (2013). Joining together: Group theory and group skills. Boston: Allyn & Bacon.

    Google Scholar 

  • Katz, Y. J., & Yablon, Y. B. (2009). Mobile learning: A major e-learning platform. In A. Szucs (Ed.), New technology platforms for learning revisited. LOGOS conference proceedings (pp. 121–126). Budapest: European Distance an E-learning Network.

    Google Scholar 

  • Kline, R. B. (2010). Principles and practice of structural equation modeling (3rd ed.). New York: Guilford Press.

    Google Scholar 

  • Koehler, M. J., Mishra, P., & Cain, W. (2013). What is technological pedagogical content knowledge (TPACK)? Journal of Education,193(3), 13–19.

    Google Scholar 

  • Kollias, V., Mamalougos, N., Vamvakoussi, X., Lakkala, M., & Vosniadou, S. (2005). Teachers’ attitudes to and beliefs about web-based collaborative learning environments in the context of an international implementation. Computers & Education,45(3), 295–315.

    Google Scholar 

  • Lambert, C., Erickson, L. Alhramelah, A. Rhoton, D. Lindbeck, R., & Sammons, D. (2014). Technology and adult students in higher education: A review of the literature. Issues and Trends in Educational Technology, 2(1).

  • Lee, M. K. O., Cheung, C. M. K., & Chen, Z. (2005). Acceptance of internet-based learning medium: The role of extrinsic and intrinsic motivation. Information & Management,42(8), 1095–1104.

    Google Scholar 

  • Loyd, B. H., & Gressard, C. P. (1984). Reliability and factorial validity of computer attitude scales. Educational and Psychological Measurement,44, 501–505.

    Google Scholar 

  • Magen-Nager, N. (2014). The influence of learning styles, learning strategies and intrinsic motivation on the success of special education pre-teachers in solving unconventional mathematical series. Dapim,58, 153–196 (Hebrew).

    Google Scholar 

  • Magen-Nagar, N., & Shamir-Inbal, T. (2014). National ICT program—A lever to change teachers’ work. American Journal of Educational Research,2(9), 727–734.

    Google Scholar 

  • Melamed, U., Peled, R., Mor, N., Shonfeld, M., Harel, S., & Ben Shimon, I. (2011). A program for adjusting teacher education colleges to the 21st century. Israel: Ministry of Education (Hebrew).

    Google Scholar 

  • Monteiro, V., Mata, L., & Peixoto, F. (2015). Intrinsic motivation inventory: Psychometric properties in the context of first language and mathematics learning. Psicologia: Reflexão e Crítica,28(3), 434–443.

    Google Scholar 

  • OECD. (2013). Draft collaborative problem solving framework. http://www.oecd.org/pisa/pisaproducts/Draft%20PISA%202015%20Collaborative%20Problem%20Solving%20Framework%20.pdf.

  • Palloff, R. M., & Pratt, K. (2005). Online learning communities revisited. In Presentation to the 21st annual conference on distance teaching and learning. http://www.uwex.edu/disted/conference/Resource_library/proceedings/05_1801.pdf.

  • Resta, P., & Carroll, T. (2010). Redefining teacher education for digital age learners. Summit report. Austin, TX: University of Texas Press.

    Google Scholar 

  • Resta, P., & Shonfeld, M. (2013). A study of trans-national learning teams in a virtual world. In R. McBride & M. Searson (Eds.), Proceedings of society for information technology and teacher education international conference (pp. 2932–2940). Chesapeake, VA: AACE.

  • Ryan, R. M., Koestner, R., & Deci, E. L. (1991). Ego-involved persistence: When free-choice behavior is not intrinsically motivated. Motivation and Emotion,15, 185–205.

    Google Scholar 

  • Schifter, D. E., & Ajzen, I. (1985). Intentions, perceived control, and weight loss: An application of the theory of planned behavior. Journal of Personality and Social Psychology,49, 843–851.

    Google Scholar 

  • Selwyn, N. (2010). Looking beyond learning: Notes towards the critical study of educational technology. Journal of Computer Assisted learning,26(1), 65–73.

    Google Scholar 

  • Shonfeld, M., & Goldstein, O. (2014). ICT integration in teaching and teachers training by faculty members in israeli colleges of education, 2013. In M. Searson & M. Ochoa (Eds.), Proceedings of society for information technology and teacher education international conference 2014 (pp. 2655–2660). Chesapeake, VA: Association for the Advancement of Computing in Education (AACE).

    Google Scholar 

  • Shonfeld, M., Hoter, E., & Ganayem, A. (2013). Israel: Connecting cultures in conflict. In R. Austin & B. Hunter (Eds.), Online learning and community cohesion: Linking schools (pp. 41–58). NY: New York.

    Google Scholar 

  • Shonfeld, M., & Weinberger, Y. (2017). What influences teacher educators’ use of collaborative learning? In M. Shonfeld & D. Gibson (Eds.), Collaborative learning in a global world. IAP: New York.

    Google Scholar 

  • Sivakumaran, T., & Lux, A. (2011). Overcoming computer anxiety: A three-step process for adult learners. US-China Education Review,8(5), 155–161.

    Google Scholar 

  • So, H. J., & Brush, T. A. (2008). Student perceptions of collaborative learning, social presence and satisfaction in a blended learning environment: Relationships and critical factors. Computers & Education,51, 318–336.

    Google Scholar 

  • Stake, R. E. (2000). Case studies. In N. K. Denzin & Y. S. Lincoln (Eds.), Handbook of qualitative research (pp. 105–117). Thousand Oaks, CA: Sage Publications.

    Google Scholar 

  • Yalman, M., & Tunga, M. A. (2014). Examining the attitudes of students from state and foundation universities in Turkey towards the computer and www (world wide web). Education and Science,39(137), 222–233.

    Google Scholar 

  • Zimmerman, T. D. (2012). Exploring learner to content interaction as a success factor in online courses. International Review of Research in Open and Distance Learning,13(4), 152–165.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Noga Magen-Nagar.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shonfeld, M., Magen-Nagar, N. The Impact of an Online Collaborative Program on Intrinsic Motivation, Satisfaction and Attitudes Towards Technology. Tech Know Learn 25, 297–313 (2020). https://doi.org/10.1007/s10758-017-9347-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10758-017-9347-7

Keywords

Navigation