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Everything about Networked learning
Networked learning is a process of developing and maintaining connections with people and information, and communicating in such a way so as to support one another's learning. The central term in this definition is connections. It adopts a relational stance in which learning takes place both in relation to others and in relation to learning resources. In design and practice, networked learning is intended to facilitate evolving sets of connections between learners and their interpersonal communities, knowledge contexts, and digital technologies. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Networked learningA 5-minute orientation
- Skim a recent paper: Scientific Machine Learning Through Physics–Informed Neural Networks: Where we are and What’s NextInfluential work since 2022
- Pick up a classic book: Advanced Computing and Systems for SecurityThe most-reprinted book on the subject
- Read the landmark paper: Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equationsCited 21,009 times
- Go sideways: George SiemensA closely related topic
- Go sideways: ConnectivismA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🏆 Landmark papers (most cited)
Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
Deep learning in neural networks: An overview
Interorganizational Collaboration and the Locus of Innovation: Networks of Learning in Biotechnology
Learning about networked learning communities
Networked Learning: Inviting Redefinition
Researching Networked Management Learning
Networked Learning and Postdigital Education
Learning Networks, Networked Learning
🆕 Influential since 2022
Scientific Machine Learning Through Physics–Informed Neural Networks: Where we are and What’s Next
Transfer learning enables predictions in network biology
Learning From Noisy Labels With Deep Neural Networks: A Survey
Deep learning resilience inference for complex networked systems
Scalable Reinforcement Learning for Multiagent Networked Systems
📚 Books worth reading
Advanced Computing and Systems for SecurityRituparna Chaki, Agostino Cortesi · 2015
Teaching and learning with technologyJudy Lever-Duffy, Jean B. McDonald · 2002
PerceptronsMarvin Minsky, Seymour Papert · 1969
Introduction to machine learning with applications in information securityMark Stamp · 2017
The New Social LearningTony Bingham, Marcia L. Conner · 2010
Deep Learning with PythonFrancois Chollet, Matthew Watson · 2017- 📕Social Power of AlgorithmsDavid Beer · 2018
- 📕Knowledge and Innovation in Regional IndustryRoel Rutten · 2005
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
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