Development of Generative Learning Objects Using Feature Diagrams and Generative Techniques
نویسندگان
چکیده
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.
منابع مشابه
On the Technological Aspects of Generative Learning Object Development
The Learning Objects (LOs) are digital resources that can be used (and reused) to support learning process. The 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 ...
متن کاملDesign of Ontology-based Generative Components Using Enriched Feature Diagrams and Meta- Programming
A product line (PL) approach is emerging as the most promising design paradigm for embedded software design domain, where a great variability of requirements and products exists. The implementation of the PL approach requires thorough domain analysis and domain modelling. We propose to represent embedded software components using Enriched Feature Diagrams (EFDs). EFDs are an extension of tradit...
متن کاملSpecular 3D Object Tracking by View Generative Learning
This paper proposes a novel specular 3D object tracking method. Our method works with texture-less specular objects and objects with background reflections on the surface. It is a keypoint-based tracking using a view generative learning. Conventional local features are robust to scale and rotation, but keypoint matching fails when the viewpoint significantly changes. We apply a view generative ...
متن کاملFast Adaptation in Generative Models with Generative Matching Networks
Despite recent advances, the remaining bottlenecks in deep generative models are necessity of extensive training and difficulties with generalization from small number of training examples. Both problems may be addressed by conditional generative models that are trained to adapt the generative distribution to additional input data. So far this idea was explored only under certain limitations su...
متن کاملImprovement of generative adversarial networks for automatic text-to-image generation
This research is related to the use of deep learning tools and image processing technology in the automatic generation of images from text. Previous researches have used one sentence to produce images. In this research, a memory-based hierarchical model is presented that uses three different descriptions that are presented in the form of sentences to produce and improve the image. The proposed ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Informatics in Education
دوره 7 شماره
صفحات -
تاریخ انتشار 2008