Exploring the multiple dimensions of context: Implications for the design and development of innovative technology-enhanced learning environments

Abstract: Technology evolution throughout history has initiated many changes in different aspects of human activities. Learning, as one of the most representative human activities has also been subject to these changes. Nowadays, the use of information and communication technologies has considerably changed the way people learn and collaborate. These changes have been accompanied by new approaches to support learning using a wide range of mobile devices, software applications and different communication platforms. In these technology rich landscapes, the notion of context emerges as a crucial component to be considered for the design and technical implementation of technology-enhanced learning environments. The main research question investigated in this thesis relates to the use of different context instantiations for the design and development of innovative technology-enhanced learning environments.This thesis is a collection of eight papers that describe the results of the research efforts conducted in four different experimental cases during a period of four years. These experiments have been designed and developed as part of two research projects. The theoretical foundations that guided this research were based on the view of context and interaction from a learning theory, human-computer-interaction perspective, as well as dimensional data modelling techniques. Different methodological approaches, (such as action-oriented, design-based research and case study) have been used while investigating the main research question. The main contribution that this thesis offers to the research community is a conceptual context model accompanied by a dimensional data model that can be used as a design tool for embedding learning activities in context. In the four trials that encompass my empirical work, the conceptual model proposed in the thesis guided the design and technical development of the different novel technology-enhanced learning activities. The outcomes of these efforts provided various insights regarding the use of different context instantiations that have implications for the design and development of these environments. This thesis advocates that computational context attributes should be used as metadata descriptors that would potentially promote personalization and interoperability of digital learning content. Content personalization offers opportunities for personalized learning that increases learners’ engagement and eventually could lead to better learning results. Furthermore, the research and industrial community could use the context model developed in this thesis as a guiding tool to promote the creation of new ways to personalize services and technologies.