Studying context: a comparison of activity theory, situated action models, and distributed cognition
Context and consciousness
Design for multimedia learning
Design for multimedia learning
Multimedia Computing: Case Studies from Mit Project Athena
Multimedia Computing: Case Studies from Mit Project Athena
Understanding and Using Context
Personal and Ubiquitous Computing
What we talk about when we talk about context
Personal and Ubiquitous Computing
Computer Supported Cooperative Work
Ontology-based framework for context-aware mobile learning
Proceedings of the 2006 international conference on Wireless communications and mobile computing
Human-Computer Interaction
Deep learning design for sustainable innovation within shifting learning landscapes
EC-TEL'10 Proceedings of the 5th European conference on Technology enhanced learning conference on Sustaining TEL: from innovation to learning and practice
Emerging technologies, ubiquitous learning, and educational transformation
EC-TEL'11 Proceedings of the 6th European conference on Technology enhanced learning: towards ubiquitous learning
Orchestration signals in the classroom: managing the Jigsaw collaborative learning flow
EC-TEL'11 Proceedings of the 6th European conference on Technology enhanced learning: towards ubiquitous learning
ICALT '11 Proceedings of the 2011 IEEE 11th International Conference on Advanced Learning Technologies
Journal on Computing and Cultural Heritage (JOCCH)
Hi-index | 0.00 |
Conceptual clarification is essential if we are to establish a stable and deep discipline of technology enhanced learning. The technology is alluring; this can distract from deep design in a surface rush to exploit the affordances of the new technology. We need a basis for design, and a conceptual unit of organization, that are applicable across constant technological change. These are the issues addressed in this article. The article first explores the nature of 'deep learning design' where the aim is to shape the possibilities of the technology to most effectively enhance learning. These design insights need to be applied to a unit of organization that is not dependent on any particular technology. They should interact with and shape technology possibilities rather than be narrowly defined by them. The key unit of organization proposed is that of context. At a theoretical level, the article explores context as a shared interpretation of situation. The implications of the nested nature of contextual interpretation on design, implementation and evaluation are explored in depth. The internal dynamics of learning contexts are then discussed initially in terms of principles, heuristics and scripts. The contribution of this article is to present a coherent argument for context as the central unit for deep learning design, and to articulate the incisive theoretical and practical consequences of this position.