Remember Me
Or use your Academic/Social account:


Or use your Academic/Social account:


You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.


Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message


Verify Password:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Publisher: ACM
Languages: English
Types: Unknown
Subjects: LB, QA76
Evidence points to the fact that the introduction of Social Networking Sites (SNS) features, into e-learning environments has been highly accepted by students, because of its benefits of improving the learning experience. Yet, not enough attention has been paid to what role learners’ profiles play in the use of social e-learning environments, which does not match the importance of profiles in SNS. This paper presents how profiles are implemented in the second version of Topolor, a social personalised adaptive e-learning environment (SPAEE), and learners’ perceived acceptance of the design and the implementation. To complement the findings, a case study is conducted to analyse the profilerelated features of Topolor, which illustrates a generally high level of learner acceptance of these features. The analysis is finally concluded to suggest future research directions, in order to further analyse and improve these features.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • [1] Anderson, T. and Dron, J. 2012. Learning Technology through Three Generations of Technology Enhanced Distance Education Pedagogy. European journal of open, distance and e-learning. (2012).
    • [2] Anderson, T. and Dron, J. 2010. Three generations of distance education pedagogy. The Intl Review of Research in Open and Distance Learning. 12, 3 (2010), 80-97.
    • [3] Brusilovsky, P. 2004. Adaptive educational hypermedia: From generation to generation. Proc. of 4th Hellenic Conf. on Information and Communication Technologies in Education, Athens, Greece (2004), 19-33.
    • [4] Brusilovsky, P. 2001.Adaptive hypermedia. User modeling and user-adapted interaction. 11, 1-2 (2001), 87-110.
    • [5] Burguillo, J.C. 2010. Using game theory and competitionbased learning to stimulate student motivation and performance. Comp. & Edu. 55, 2 (2010), 566-575.
    • [6] Carmines, E.G. and Zeller, R.A. 1979. Reliability and validity assessment. Sage.
    • [7] Connolly, T.M. et al. 2012. A systematic literature review of empirical evidence on computer games and serious games. Computers & Education. 59, 2 (2012), 661-686.
    • [8] Cristea, A.I. and Ghali, F. 2011. Towards adaptation in elearning 2.0. New Review of Hypermedia and Multimedia. 17, 2 (2011), 199-238.
    • [9] Dabbagh, N. 2012. Personal Learning Environments, social media, and self-regulated learning: A natural formula for connecting formal and informal learning. The Internet and higher education. 15, 1 (2012), 3-8.
    • [10] Davis, F.D. 1989. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly. (1989), 319-340.
    • [11] Downes, S. 2008. Places to go: Connectivism & connective knowledge. Innovate: Journal of Online Education (2008).
    • [12] Dunkin, M.J. Introduction to section 4: Classroom processes. Pergamon Press. 313-326.
    • [13] Ellison, N.B. and others 2007. Social network sites: Definition, history, and scholarship. Journal of ComputerMediated Communication. 13, 1 (2007), 210-230.
    • [14] Fu, F.-L. et al. 2009. An investigation of coopetitive pedagogic design for knowledge creation in Web-based learning. Computers & Education. 53, 3 (2009), 550-562.
    • [15] Herrington, J. and Oliver, R. 2000. An instructional design framework for authentic learning environments. Educational technology research and development. 48, 3 (2000), 23-48.
    • [16] Hsiao, I.-H. et al. 2011. Open Social Student Modeling: Visualizing Student Models with Parallel IntrospectiveViews. User Modeling, Adaption and Personalization. Springer Berlin Heidelberg. 171-182.
    • [17] Johnson, R.T. et al. 1986. Comparison of computerassisted cooperative, competitive, and individualistic learning. American Educational Research Journal. 23, 3 (1986), 382-392.
    • [18] Moreno, L. et al. 2007. Applying a constructivist and collaborative methodological approach in engineering education. Computers & Education. 49, 3 (2007), 891-915.
    • [19] Paramythis, A. and Loidl-Reisinger, S. 2003. Adaptive learning environments and e-learning standards. Proc. of the 2nd European Conf. on e-Learning (2003), 369-379.
    • [20] Richter, A. and Koch, M. 2008. Functions of social networking services. Proc. Intl. Conf. on the Design of Cooperative Systems (2008), 87-98.
    • [21] Rosmalen, P.V. et al. 2006. Authoring a full life cycle model in standards-based, adaptive e-learning. Journal of Educational Technology & Society. 9, 1 (2006).
    • [22] Shi, L. et al. 2013. A social personalized adaptive elearning environment: a case study in Topolor. IADIS Intl. Journal on WWW/Internet. 11, 2 (2013).
    • [23] Shi, L. et al. 2013. Designing Social Personalized Adaptive e-Learning. Proc. of the 18th ACM Conf. on Innovation and Technology in Computer Science Education, 341-341.
    • [24] Shi, L. et al. 2013. Evaluating System Functionality in Social Personalized Adaptive E-Learning Systems. Scaling up Learning for Sustained Impact. D. Hernández-Leo et al., eds. Springer Berlin Heidelberg. 633-634.
    • [25] Shi, L. et al. 2013. Evaluation of Social Interaction Features in Topolor-A Social Personalized Adaptive ELearning System. Proc. of the 13th IEEE Intl. Conf. on Advanced Learning Technologies (2013), 15-18.
    • [26] Shi, L. et al. 2012. Exploring participatory design for SNSbased AEH systems. (Madrid, Spain, 2012), 242-249.
    • [27] Shi, L. et al. 2013. Social e-learning in topolor: a case study. Proc. of the 7th IADIS Conf. e-Learning 2013 (Prague, Czech Republic, 2013), 57-64.
    • [28] Shi, L. et al. 2013. Social Personalized Adaptive ELearning Environment: Topolor - Implementation and Evaluation. Artificial Intelligence in Education. 708-711.
    • [29] Shi, L. et al. Students as Customers: Participatory Design for Adaptive Web 3.0. Evolution of the Internet in the Business Sector: Web 1.0 to Web 3.0. IGI Global.
    • [30] Shi, L. et al. 2013. To build light gamification upon social interactions: requirement analysis for the next version of Topolor. Proc. of the 6th York Doctoral Symposium on Computer Science and Electronics (2013).
    • [31] Shi, L. et al. 2013. Towards Understanding Learning Behavior Patterns in Social Adaptive Personalized ELearning Systems. Proc. of The 19th Americas Conf. on Information Systems, 1-10.
    • [32] Shin, N. 2006. Online learner's “flow” experience: an empirical study. British Journal of Educational Technology. 37, 5 (2006), 705-720.
    • [33] Wang, X. et al. 2012. Integration of E-learning 2.0 with Web 2.0. Journal of Information Technology in Construction. 17, (2012), 387-396.
    • [34] Wenger, E. 2000. Communities of practice and social learning systems. Organization. 7, 2 (2000), 225-246.
    • [35] Zimmerman, B.J. 2002. Becoming a self-regulated learner: An overview. Theory into practice. 41, 2 (2002), 64-70.
  • No related research data.
  • Discovered through pilot similarity algorithms. Send us your feedback.

Share - Bookmark

Cite this article