Analysis of the Implications Connectivism Theory on the Elements of the Curriculum

Document Type : Original Article

Authors

Abstract

Abstract: This research looks for analysing connectivism theory and its implications on the elements of curriculum. In this study, "Speculative Essay" is used as research method and "Review of Documentation" is used as a tool for information gathering. The analysis of literature and documents related to connectivism theory approach was reflective and due to the comprehensiveness and relevance more radical elements of the curriculum in terms of connectivism theory on the basis of Miller characteristics were extracted curriculum elements. Based on this theory curriculum, goals are flexible, productive, interactive, divergent and valuable. Students are aware and up to date, independent and in the centre of the learning process. The teacher with ongoing presence in the learning process is responsible for creating an ecosystem. Learning- teaching methods are technological, process-oriented, indirect and is based on educational factors communication. Connectivism environment is open, flexible, collaborative and technological. Evaluation methods are process-oriented, perpetual and non-linear, and despite the rapid assessment, assessment error is low and its accuracy is high.

Keywords

References

Admiraal, W.; Huisman, B. & Pilli, O. (2015). Assessment in massive open online courses, Journal of e-Learning, 13 (4), 207-216.
Anderson, T. & Dron, J. (2011). Three generations of distance education pedagogy. In M. E. Kite (Ed.), Effective evaluation of teaching: A guide for faculty and administrators. Retrieved from the Society for the Teaching of Psychology web site: http://teachpsych.org/ebooks/evals2012/index.php
Bleakley, A.; Bligh, J. & Brown, J. (2011). Medical education for the future: Identity, power and location. Dordrecht: Springer.
Couros, A. (2008). What Does The Network Mean To You? Open Thinking [Internet]. [Retrieved 2016 November 26]. Available From: Http://Educationaltechnology.Ca/Couros/799.
Creswell, J. W. (2012). Educational research: Planning, Conducting, and Evaluating Quantitative and Qualitative Research, Pearson Education International.
Downes, S. (2008). Types of knowledge and Connective Knowledge. Stephens Web. Retrieved November 1, 2016, from http://halfanhour.blogspot.com/2008/09/types-ofknowledge-.
Dynarski, M.; Agodini, R.; Heaviside, S.; Novak, T.; Carey, N.; Campuzano, L. et al. (2007). Effectiveness of reading and mathematics software products: Findings from the first student cohort. Washington D.C.: U.S. Department of Education, Institute of Education Sciences.
Elliott, R. & Martin, S. (2011). Connectives' Role as a Learning Theory and its Application in the Classroom, Boise State University, Retrieved November 1, 2016, from https://shaunwmartin.files.wordpress.com/2011/12/connectivismresearchpaperedtech504.pdf.
Esther Del Moral, M.; Cernea, A. & Villalustre, L. (2013). Connectivist learning objects and learning styles. Interdisciplinary Journal of E-Learning and Learning Objects, 9, 105-124.
Foroughi, A. (2015). The theory of connectivism: Can it explain and guide learning in the digital age? Journal of Higher Education Theory and Practice, 15 (5), 11-26.
Hung, N. M. (2014). Using ideas from connectivism for designing new learning models in Vietnam. International Journal of Information and Education Technology, 4 (1), 76-82.
Kultawanich, K.; Koraneekij, P. & Songkhla, J. N. (2015). A proposed model of connectivism learning using cloud-based virtual classroom to enhance information literacy and information literacy self-efficacy for undergraduate students. Social and Behavioural Sciences, 191, 87 – 92.
Marhan, A. (2006). Connectivism: Concepts and Principles for emerging Learning Networks, the 1st International Conference on Virtual Learning. Faculty of Mathematics and Computer Science, Bucharest, 209-216.
Mugisha, W. R. & Mugimu, C. B. (2015). Application of learning theories in curriculum development and implementation of the MLT diploma programme in Uganda. British Journal of Education, Society & Behavioural Science, 5 (3), 256-275.
Nardi, B. & O’day (2010). Information ecologies: Using technology with the heart. American Library.
Orlando, J. (2011). How to effectively assess online learning, a Magna Publications White Paper.
Ozturk, H, T. (2015). Examining value Change in MOOCs in the scope of connectivism and open educational resources movement. International Review of Research in Open and Distributed Learning, 16 (5), 1-25.
Siemens, G. (2004). A learning theory for the digital age. Elearnspace Everything Learning, 1-8.‏
Siemens, G. (2005). Connectivism: Learning as network-creation. ASTD Learning News, 10 (1).‏
Siemens, G. (2006). Knowing knowledge. Vancouver, Bc: Lulu. Retrieved from http://www.elearnspace.org/KnowingKnowledge_LowRes.pdf.
Siemens, G. (2010). Teaching in social and technological networks. Retrieved on 27 May 2017 from http://www.connectivism.ca/?p=220
Techakosit, S. & Wannapiroon, P. (2015). Connectivism learning environment in augmented reality science laboratory to enhance scientific literacy. Social and Behavioural Sciences, 174, 2108 – 2115.
Trna, J. & Trnova, E. (2013). Implementation of connectivism in science teacher training. Journal of Education and Instuctional Studies in the World, 3 (1), 191-196.
Trnova, E. & Trna, J. (2012). Connectivism in science and technology education with emphasis on international cooperation. Journal of Social Sciences, USA, New York, Science Publications, 8 (4), 490-496.
Voogt, J. (2008). IT and curriculum processes: dilemmas and challenges. In International Handbook of Information Technology in Primary and Secondary Education (eds J. Voogt & G. Knezek), pp. 117–132. Springer, New York, NY.
Higher Education Letter
Volume 10, Issue 37
June 2017
Pages 131-158

Files

Share

How to cite

Statistics