Reflections From the Pandemic: Is Connectivism the Panacea for Clinicians?

The COVID-19 pandemic and the recent increased interest in generative artificial intelligence (GenAI) highlight the need for interprofessional communities’ collaboration to find solutions to complex problems. A personal narrative experience of one of the authors compels us to reflect on c...

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Bibliographic Details
Main Authors: Jennifer Benjamin, Tyson Pillow, Heather MacNeill, Ken Masters, Anoop Agrawal, Neil Mehta
Format: Article
Language:English
Published: JMIR Publications 2024-12-01
Series:Journal of Medical Internet Research
Online Access:https://www.jmir.org/2024/1/e53344
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Summary:The COVID-19 pandemic and the recent increased interest in generative artificial intelligence (GenAI) highlight the need for interprofessional communities’ collaboration to find solutions to complex problems. A personal narrative experience of one of the authors compels us to reflect on current approaches to learning and knowledge acquisition and use solutions to the challenges posed by GenAI through social learning contexts using connectivism. We recognize the need for constructivism and experiential learning for knowledge acquisition to establish foundational understanding. We explore how connectivist approaches can enhance traditional constructivist paradigms amid rapidly changing learning environments and online communities. Learning in connectivism includes interacting with experts from other disciplines and creating nodes of accurate and accessible information while distinguishing between misinformation and accurate facts. Autonomy, connectedness, diversity, and openness are foundational for learners to thrive in this learning environment. Learning in this environment is not just acquiring new knowledge as individuals but being connected to networks of knowledge, enabling health professionals to stay current and up-to-date. Existing online communities with accessible GenAI solutions allow for the application of connectivist principles for learning and knowledge acquisition.
ISSN:1438-8871