Software engineering with reusable components
Software engineering with reusable components
UML distilled (2nd ed.): a brief guide to the standard object modeling language
UML distilled (2nd ed.): a brief guide to the standard object modeling language
DIPES '98 Proceedings of the IFIP WG10.3/WG10.5 international workshop on Distributed and parallel embedded systems
Generative programming: methods, tools, and applications
Generative programming: methods, tools, and applications
Commonality and Variability in Software Engineering
IEEE Software
Feature-Oriented Project Line Engineering
IEEE Software
Feature Models are Views on Ontologies
SPLC '06 Proceedings of the 10th International on Software Product Line Conference
On Ontology, ontologies, Conceptualizations, Modeling Languages, and (Meta)Models
Proceedings of the 2007 conference on Databases and Information Systems IV: Selected Papers from the Seventh International Baltic Conference DB&IS'2006
Engineering a future for web-based learning objects
ICWE'03 Proceedings of the 2003 international conference on Web engineering
Accomplishments and research challenges in meta-programming
SAIG'01 Proceedings of the 2nd international conference on Semantics, applications, and implementation of program generation
A process model for the generative production of interactive simulations in engineering education
Proceedings of the First International Conference on Technological Ecosystem for Enhancing Multiculturality
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Learning Objects (LOs) are digital resources that can be used (and reused) to support the learning process. Generative Learning Objects (GLOs) are generic and reusable LOs from which the specific LO content can be generated on demand. We discuss the technological aspects required for implementing the GLOs: (1) variability modeling using feature diagrams, (2) multi-dimensional separation of the LO design concerns, (3) multiple languages for implementing a LO specification, (4) an external metalanguage for implementing parameterization, generalization and modification of a LO, and (5) heterogeneous metaprogramming techniques for generating LO instances from the generic LO specifications on demand. An example of a GLO for teaching array sorting algorithms in a programming curriculum is presented.