Connectivism: Implications for Distance Education

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Background
According to the connectivism learning theory, learning has a different form in the digital age compared to the industrial age, where traditional learning theories were applied. Thus, this study aimed at identifying and discovering implications of connectivism learning theory for distance education.
Methods
The present study was a qualitative research. Population of this study was all the documents that were published in Iran during 2007 and 2015. Based on this search, about 100 valid published academic materials including papers, books, websites, conferences, and other academic materials were recognized. Because of the large overlap of these materials, by using purposive sampling, 10 cases were selected as the research sample. In this study, Mayring’s deductive qualitative content analysis method was used to extract implications of connectivism learning theory for distance education. According to the deductive model of qualitative content analysis, research question was identified in the first step. In the second step, valid and relevant publications and texts were determined. In the third step, aspects of theoretical analysis and categories were defined. In the fourth step, encoding of analysis units was done to infer the subcategories. In the fifth step, the main categories were extracted based on their most consistency with the subcategories; and in the final step, results were interpreted and quantitative assessment (e.g., frequencies) was done.
Results
The results of this study referred to 9 connectivism implications as follow: networked teacher, networked students, networked learning, ecosystem, information and knowledge stream, connection and interaction, pluralism, and value measuring.
Conclusion
Findings of this study may be useful and helpful for instructional and learning designers in e-learning environments.
Language:
English
Published:
Interdisciplinary Journal of Virtual Learning in Medical Sciences, Volume:8 Issue: 3, Autumn 2017
Page:
1
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