Abstract
This work investigates the effect a Web 2.0 learning environment may have in higher education in adding value to the students’ existing competencies. The major issues that this work examines are whether the incorporation of a Web 2.0 environment in higher education has an effect on the students’ performance and what are the significant factors that should be taken into account in the deployment of these technologies to achieve the maximum possible benefits and whether and how they correlate to each other. These factors are derived from the students’ views on the use of technology in a university course deployment and from the students’ personal opinions about a pilot course in a Web 2.0 learning environment. Although the results indicate no direct effect on the students’ performance, significant factors have been revealed via a thorough assessment, which has been performed in the context of a semester–long course, utilizing statistical process control techniques. The derived factors are namely: “Technology as an educational reinforcement”, “Technology as a tool to enhance comprehension” and “Enhancement of student interest and experience”, while in the second one “Completeness of the educational approach”, “Satisfaction from the educational approach” and “Course demands”. These factors can then form the basis for a feedback processes and a monitoring mechanism for a continuously updated educational process.

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Anderson, L., & Krathwohl, D. (2001). A taxonomy for learning, teaching and assessing: A revision of Bloom's taxonomy of educational objectives. New York: Longman.
Bailey, M., Ifenthaler, D., Gosper, M., Kretzschmar, M., & Ware, C. (2015). The changing importance of factors influencing students’ choice of study mode. Technology, Knowledge and Learning. https://doi.org/10.1007/s10758-015-9253-9.
Bartholomew D. J., Steele, F., Moustaki, I., & Galbraith, J. A. (2008). Analysis of multivariate social science data (2nd ed.). Boca Raton: Chapman and Hall/CRC.
Blackwelder, W. C. (2004). Current issues in clinical equivalence trials. Journal of Dental Research, 83(Special Issue C), C113–C115.
Breen, R., Lindsay, R., Jenkins, A., & Smith, P. (2001). The role of information and communication technologies in a university learning environment. Studies in Higher Education. https://doi.org/10.1080/03075070123233.
Carter, L., & Salyers, V. (2015). A model for meaningful e-learning at Canadian universities. In J. Keengwee (Ed.), Handbook of research on educational technology integration and active learning (pp. 78–114). Hershey: IGI Global.
Chimos Κ., Karvounidis T., Douligeris C., Bersimis S., and Bassios M. (2013). Unisuite: An innovative integrated suite for delivering synchronous and asynchronous online education, IEEE EDUCON 2013 Conference, March 11-13, 2013, Berlin, Germany, doi: https://doi.org/10.1109/EduCon.2013.6530136.
Christensen, E. (2007). Methodology of superiority vs. equivalence trials and non-inferiority trials. Journal of Hepatology, 46, 947–995.
Clayson, D. E., Frost, T. F., & Sheffet, M. J. (2006). Grades and the student evaluation of instruction: A test of the reciprocity effect. Academy of Management Learning and Education, 5(1), 52–65 Retrieved from: http://amle.aom.org/content/5/1/52.abstract.
Cooper, J. (2006). The digital divide: The special case of gender. Journal of Computer Assisted Learning. https://doi.org/10.1111/j.1365-2729.2006.00185.x.
Deng, L., & Tavares, N. J. (2013). From Moodle to Facebook: Exploring students’ motivation and experiences in online communities. Computers and Education. https://doi.org/10.1016/j.compedu.2013.04.028.
Dyson, M. C., & Campello, S. B. (2003). Evaluating virtual learning environments: What are we measuring? Electronic Journal of e-Learning, 1(1), 1–20 http://www.ejel.org.
Harris, A. L. & Rea, A. (2009). Web 2.0 and virtual worled technologies: A growing impact on IS education. Journal of Information Systems Education, 20(2), 137–143.
Hung, M.-L., & Chou, C. (2015). Students' Perceptions of instructors' roles in blended and online learning environments: A comparative study. Computers and Education, 81, 315–325. https://doi.org/10.1016/j.compedu.2014.10.022.
Islam, A. K. M. N. (2012). The role of perceived system quality as the educators’ motivation to continue E-learning system use. AIS Transaction of Human-computer Interaction, 4(1), 25–44 Retrieved from: http://aisel.aisnet.org/thci/vol4/iss1/2/.
Johnson, R. A., & Wichern, D. W. (2007). Applied multivariate statistical analysis (6th ed.). Upper Saddle River: Prentice Hall.
Karvounidis, T., Chimos, Κ., Bersimis, S., & Douligeris, C. (2015). I-SERF - an integrated self-evaluated and regulated framework for deploying web 2.0 Technologies in Higher Education. The Electronic Journal of e-Learning, 13(5), 319–333.
Landow, L. (2000). Current issues in clinical trial design: Superiority versus equivalency studies. Anesthesiology, 92, 1814–1820.
Lazzari, M. (2009). Creative use of podcasting in higher education and its effect on competitive agency. Computers and Education, 52(1), 27–34. https://doi.org/10.1016/j.compedu.2008.06.002.
Lesaffre, E. (2008). Superiority, equivalence, and non-inferiority trials. Bulletin of the NYU Hospital for Joint Diseases, 66(2), 150–154.
Mason, R., & Rennie, F. (2007). Using web 2.0 for learning in the community. Internet and Higher Education, 10, 196–203. https://doi.org/10.1016/j.iheduc.2007.06.003.
Montgomery, D. C. (1996). Introduction to statistical quality control (3rd ed.). New York: Wiley.
Nunnally, J., & Bernstein, L. (1994). Psychometric theory. New York: McGraw-Hill Higher.
Păuleţ-Crăiniceanu, L. (2014). Integrating the web 2.0 Technologies in Romanian Public Universities. Towards a blended learning model that addresses troubled student-faculty interaction. Procedia - Social and Behavioral Sciences. https://doi.org/10.1016/j.sbspro.2014.07.618.
Rabah, J. (2015). Benefits and constraints of technology integration in Quebec English schools. Turkish Online Journal of Educational Technology, 14(2), 24–31.
Streiner, D. (2003). Starting at the beginning: An introduction to coefficient alpha and internal consistency. Journal of Personality Assessment, 80, 99–103.
Swan, K., Day, S. L., Bogle, L. R., & Matthews, D. B. (2013). A collaborative, design-based approach to improving an online program. Internet and Higher Education. https://doi.org/10.1016/j.iheduc.2013.10.006.
Tang, T. L.-P., & Austin, M. J. (2009). Students’ perceptions of teaching technologies, application of technologies, and academic performance. Computers and Education. https://doi.org/10.1016/j.compedu.2009.06.007.
Ullrich, C., Shen, R., & Gillet, D. (2010). Not yet ready for everyone: An experience report about a personal learning environment for language learning. In X. Luo, M. Spaniol, L. Wang, Q. Li, W. Nejdl, &W. Zhang (Eds.), Advances in web-based learning – ICWL 2010. ICWL 2010. Lecture notes in computer science, vol. 6483. Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-642-17407-0_28.
Venkatesh, V., Rabah, J., Fusaro, M., Couture, A., Varela, W. and Alexander, K. (2016). Factors Impacting University Instructors’ and Students’ Perceptions of Course Effectiveness and Technology Integration in the Age of Web 2.0, doi: https://doi.org/10.7202/1037358ar.
Youssef, A. B. and Dahmani, M. (2008). The impact of ICT on student performance in higher education: Direct effects, Indirect Effects and Organisational Change. http://www.uoc.edu/rusc/5/1/dt/eng/benyoussef_dahmani.pdf.
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Karvounidis, T., Chimos, K., Bersimis, S. et al. Factors, issues and interdependencies in the incorporation of a Web 2.0 based learning environment in higher education. Educ Inf Technol 23, 935–955 (2018). https://doi.org/10.1007/s10639-017-9644-8
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DOI: https://doi.org/10.1007/s10639-017-9644-8