Abstract
L2 language learning is an activity that is becoming increasingly ubiquitous and learner-centric in order to support lifelong learning. Applications for learning are constrained by multiple technical and educational requirements and should support multiple platforms and multiple approaches to learning. This chapter investigates the possibility of applying ontology-based, dynamically generated learning objects implemented on a cloud computing infrastructure in order to satisfy these requirements. Previous work on using mobile learning objects is used as a starting point in an attempt to design a system that will preserve all of the advantages of utilizing learning objects, while eliminating any flaws and maximizing compatibility with existing systems. A model of a highly modular, flexible, multiplatform language learning system is presented along with some implementation remarks and advices for future implementation.
TopLiterature Review
Modern computing devices vary both in size and hardware characteristics, as well as in platform architectures utilized. Most of these devices are capable of supporting various applications and processes, with even the smallest devices being capable of accessing the Internet and utilizing remote resources or processing power. This has also influenced the development of software, bringing about a diversification and specialization of applications for certain platforms, as well as the opposite process of unification through Web-based services and interfaces.
Key Terms in this Chapter
Domain Ontology: An ontology that describes all of the relevant concepts in a single domain of interest.
Metadata: Data that describes other data; can be used by data users, managers, software agents and other entities to provide various services including data management, browsing, searching, restructuring, analysis, distribution, aggregation, and adaptation.
WordNet: Name used for lexical databases derived from the original Princeton WordNet; they group words into synonym sets and interlink them using lexical and conceptual-semantic relations. Used for computational linguistics and natural language processing.
Web Service: A software functionality available remotely (on the Internet or in the cloud) to any client that will conform to its typically platform-independent interface.
Ontology: A formal, explicit model describing concepts in the real world using classes, relations, and attributes.
Learning Management System (LMS): An application, often Web-based, that allows teachers and administrators to deliver learning materials and services to learners, and perform tracking and assessment of their learning progress.
Learning Object: A package containing educational resources on a single topic, described by a set of metadata.
Learning Object Repository: A type of a digital library for sharing, management, and retrieval of learning resources. Often involves both the resources and their metadata.
System Scalability: The ability of a system to adapt to changing, typically growing amounts of work.