Yükseköğretimde yaygın öğrenim (U-öğrenim) ortamının kişiselleştirilmesi

Yıl 2014, Cilt: 4 Sayı: 1, 54 - 60, 01.04.2014

Olapeju Latifat Ayoola Eleni Mangina

Öz

Bu makale, yükseköğretimde öğrenim deneyimini güçlendirmek amacıyla içerik özelleştirmeyi, işbirlikçi ve sosyal öğrenimi birleştiren ,"Kişiselleştirilmiş Yaygın Öğrenim Platformu" (PULP) adlı yaygın öğrenim (ubiquitous learning - u-Learning) sistemini sunmaktadır. Dublin Ulusal Üniversitesi (University College Dublin, UCD), üniversite içinde öğrencilerine farklı fakültelerden farklı dersler almalarına imkân tanıyan UCD Horizon aracılığıyla, gözetimli öğrenim ortamları (managed learning environments, MLE) sunmaktadır. Bu platformun ana amacı, uyarlanabilir ve işbirlikçi öğrenim ve herhangi bir yerde ve herhangi bir zamanda mobil ve masaüstü istemcilerinde insan-bilgisayar etkileşimi için koşullar sağlayacak ve bunları teşvik edecek mevcut MLE'lerin güçlendirilmiş bir sürümünü sunmaktır. Sistem, öğrencilerle bağlantı kurmak ve devam eden derslerinde içerik materyallerine erişmelerine yardımcı olmak amacıyla etmen odaklı öneri tekniği (agent-oriented recommendation technique) gibi kişiselleştirme tekniklerini kullanarak, yükseköğretim ortamında öğrencilerin öğrenim deneyimini güçlendirmeyi amaçlamaktadır.

Anahtar Kelimeler

m-Öğrenim, u-Öğrenim, çok etmenli sistem, etmen odaklı kişiselleştirme.

Personalisation of a U-Learning Environment for Third Level Education

Öz

This paper presents a ubiquitous learning (u-learning) system, the "Personalised Ubiquitous Learning Platform" (PULP), which integrates content personalisation, collaborative and social learning for the enhancement of the third level education learning experience. University College Dublin (UCD) provides its students with managed learning environments (MLEs) and adaptive learning via UCD Horizon which enables tertiary students to take different courses from different colleges throughout the university. The main objective of this platform is to provide an enhanced version of the current MLEs that will act as a single supported intelligent and personalised ubiquitous learning environment that will promote and make provisions for adaptive and collaborative learning, human computer interaction on mobile and desktop clients anywhere and anytime. The system aims to enhance the students' learning experience in third level educational environment by employing personalisation techniques such as the agent-oriented recommendation technique to engage students and help them access the content material for their on-going studies.

Anahtar Kelimeler

m-Learning, u-learning, multi-agents system, agent-oriented personalisation.

Kaynakça

• Alcaniz, M., and Rey, B. (2005). New technologies for ambient intelligence. In G. Riva, F. Vatalaro, F. Davide, M. Alcañiz (Eds.), Ambient Intelligence: The evolution of technology, communication and cognition towards the future of human-computer interaction (pp. 3-15). Amsterdam: IOS Press.
• Amin, A. H. M., Mahmud, A. K., Abidin, A. I. Z., and Rahman, M. A. (2006). M-learning management tool development in campus-wide environment. The Information Universe: The Journal of Issues in Informing Science & Information Technology, 3, 423-434.
• Ayoola, O. L., McGovern, E., Mangina, E., and Collier, R. (2008). Adaptive e-learning: Harnessing mobile e-learning to enhance the third level aca- demic experience. International Conference on Information Commu-nica- tion Technologies in Education. July 10-12, 2008, Corfu, Greece.
• Bates, T. (2005). Technology, e-learning and distance education. Oxford: Routledge.
• Dinsoreanu, M., Godja, C., Anghel, C., Salomie, L., and Coffey, T. (2003). Mobile agent-based solutions for knowledge assessment in elearning environments. In Proceedings of EUROMEDIA 2003, April 14-16, 2003, University of Plymouth, Plymouth, UK.
• Hwang, G. J. (2006). Criteria and strategies of ubiquitous learning. In Proceedings of the IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (pp.72-77), Los Alamitos: IEEE Computer Society.
• Issack, S. M., Hosany, M., & Gianeshwar, R. (2006). A M-E (mobile- learning) adaptive architecture to support flexible learning. Malaysian Online Journal of Instructional Technology, 3(1), 19-28.
• Keegan, D. (2008). The e-learner: The impact of technology on distance learn- ing students. European Consortium for the Learning Organisation (ECLO). Ireland: Ericsson.
• Laroussi, M. (2004). New e-learning services based on mobile and ubiq- uitous computing: Ubi-learn project. In International Conference on Computer Aided Learning in Engineering Education. February 16-18, 2004, Grenoble, France.
• Lee, H., Lee, W. B., and Kweon, S. C. (2013). Conjoint analysis for mobile devices for ubiquitous learning in higher education: The Korean case. The Turkish Online Journal of Educational Technology, 12(1), 45-51.
• Liu, G. Z., and Hwang, G. J. (2010). A key step to understanding para- digm shifts in e-learning: Towards context-aware ubiquitous learn- ing. British Journal of Educational Technology, 41(2), E1-E9.
• Miao, C., Yang, Q., Fang, H., and Goh, A. (2007). A cognitive approach for agent-based personalized recommendation. Knowledge-Based Systems, 20(4), 397-405.
• Mifsud, T., Casey, D. (2005). E-learning to u-learning, adapting learning environments to mobile devices. Faculty of Information Technology, Monash University, Australia.
• Sudhana, K. M., Raj, V. C., and Suresh, R. M. (2013). Content adapta- tion approach in context-aware delivery of learning material. Australian Journal of Basic and Applied Sciences, 7(9): 275-282.
• Yuen, S. C.-Y., and Wang, S. (2004). M-learning: Mobility in learning [CD-ROM]. In J. Nall, and R. Robson (Eds.), Proceedings of E-Learn 2004, World Conference on E-Learning in Corporate, Government, Healthcare, & Higher Education (pp. 2248-2252). Norfolk, VA: Association for the Advancement of Computing in Education (AACE).
• Zhu, F., Ip, H. H. S., Fok, A.W. P., and Cao, J. (2008). PeRES: A person- alized recommendation education system based on multi-agents and SCORM. In H. Lueng et al. (Eds.), Advances in Web Based Learning – ICWL 2007 (Vol. 4823, pp. 31-42). Heidelberg: Springer.