Virtual Communities of Practice (VCoPs) are networks of people who share a common interest and a desire to learn together in the same domain via ICT. The limitations of the existing concepts for developing VCoPs in general contexts are not explained in terms of the integration between virtual learning technologies and digital learning strategies used to promote expected learning outcomes in the agricultural sector. This research aims to propose the conceptual framework for developing the Virtual Communities of Practice through Digital Inquiry (VCoPs-DI Model) to promote digital agriculturists’ learning competencies and engagement. The research methodology was divided into three stages: the first stage involves a literature review for document analysis and synthesis, the second stage involves constructing the conceptual framework, and the third stage involves evaluating the content validity index. The key results showed that the developed conceptual framework has three parts: (1) The fundamentals of concept formation were divided into four concept bases: (1.1) Communities of Practice (CoPs), (1.2) Virtual Learning Environments (VLEs), (1.3) Digital Learning Resources (DLRs), and (1.4) Critical Inquiry Method; (2) The identification of the manipulated variable was divided into two compositions: (2.1) VCoPs and (2.2) Digital Inquiry (DI); (3) The identification of the dependent variable was divided into two compositions: (3.1) Digital agriculturists' learning competencies, and (3.2) learning engagement. Findings from an expert’s review show that the scale levels of the content validity index (SCVI) were 0.958. We anticipate that our conceptual framework could be used for reference as part of the design and development of the VCoPs model to promote learning in the agricultural sector.
CITATION STYLE
Manyuen, M., Boonlue, S., Neanchaleay, J., & Nittayathammakul, V. (2022). Virtual Communities of Practice to Promote Digital Agriculturists’ Learning Competencies and Learning Engagement: Conceptual Framework. International Journal of Advanced Computer Science and Applications, 13(9), 523–528. https://doi.org/10.14569/IJACSA.2022.0130960
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