The paper's contribution is a methodology that integrates two basic technologies (GLO and LEGO robot) to teach Computer Science (CS) topics at the school level. We present the methodology as a framework of 5 components (pedagogical activities, technology driven processes, tools, knowledge transfer actors, and pedagogical outcomes) and interactions among the components. GLOs are meta-programmed entities to generate LO instances on demand depending on the context of use and learning objectives. A GLO is a black-box entity, which is integrated in the framework through the generating process to source the teaching and learning process via robot-based visualization to demonstrate how programs and algorithms are transformed into real-world tasks and processes. The methodology is tested in the real e-learning setting. The pedagogical outcomes are evaluated by empirical data showing the increase of student engagement level, higher flexibility and reuse enhancement in learning.
Domain ontology as an instrument for knowledge representation, sharing, reuse and interoperability takes an increasingly important role in the approaches for personalised intelligent e-learning architectures and systems. However, wider practical acceptance of domain ontology as an engineering product and as a part of web-based learning systems is still needed. We believe that one of the barriers for wider spreading of domain ontologies in different fields, including e-learning, is the problem of the design and maintenance of high quality ontologies. As the importance of the quality of learning resources is obvious, the quality of domain ontology for e-learning is even more important, because ontology is intended to be re-used in design and implementation of various learning resources. In this paper, we analyse the quality-related characteristics of domain ontology. We propose a framework for evaluation of the quality of domain ontology for web-based learning. Further, we propose a model for ontology evaluation, based on its technical and complexity-related characteristics. We identify main conceptual (semantic) quality characteristics, and analyse the relationship between both types of ontology quality characteristics. Also we present an application of proposed framework to the evaluation of ontologies for web based learning.
Learning Objects (LOs) play a key role for supporting eLearning. In general, however, the development of LOs remains a vague issue, because there is still no clearly defined and widely adopted LO specification and development methodology. We combined two technological paradigms (feature diagrams (FDs) and generative techniques) into a coherent methodology to enhance reusability and productivity in the development of LOs. FDs are used for knowledge representation, modelling variability of the LO content and relationships between its features, and as a high-level specification for generative reuse. The paper describes the specification of LOs using FDs and some design principles to design generative LOs.