THE EFFECTIVENESS OF ADAPTIVE LEARNING OF MATH AND LANGUAGE

The work presented in this thesis focuses on adaptive and (personal) pervasive environments from a user-centric point of view. It investigates how high level abstractions and semantics, varying from generic vocabularies and metadata approaches to ontologies, can be exploited for the creation of such environments and to enrich and augment the end-user experience. We review the pervasive computing domain along its links with adaptive systems to grab the overall picture. Keeping in line with a user-centric approach, based on abstractions and semantics, we review the end-user aspects of Pervasive Computing in more detail along recent state of the art intersecting Knowledge Representation, Software Engineering, Logic, and the Semantic Web. Our reviews suggest that the use of abstractions, particularly ontologies, is promising for the development and run-time adaptation of individual context-aware applications and for the aggregation and orchestration of these applications to form personal and pervasive environments. The design and development of individual adaptive and pervasive applications is addressed at conceptual level. Regarding personal and pervasive environments, in this thesis, two complementary practical studies are realized. The first study concerns the widgetization of traditional applications, in a broader perspective in terms of ubiquitous web navigation and access, by harvesting semantics embedded into theinterfaces of web applications. The second study concerns the realization of a standard and open platform along an interoperability framework, based on the semantic web technologies, for the creation of widget-basedpersonal environments. We also provide methods and techniques for two notable orchestration approaches, namely user-driven and system-driven orchestration, to enable interplay between widgets. We compare our approaches and methods with a broad interdisciplinary literature. We provide prototypes for each practical contribution and conduct end-user experiments and usability assessments to prove the computational feasibility and usability of the proposed approaches and methods.