Development of a Data Model for an Adaptive Multimedia Presentation System

This source preferred by David Newell and Suzy Atfield-Cutts

Authors: Newell, D., Davies, P., Atfield-Cutts, S. and Rowe, N.

http://eprints.bournemouth.ac.uk/17161/

http://www.iaria.org/conferences2011/MMEDIA11.html

Start date: 17 April 2011

Place of Publication: Budapest, Hungary

We investigate the requirements and nature of data models for a multimedia learning system that presents adaptable learning objects based on a range of stimuli provided by the student and tutor. A conceptual model is explored together with a proposal for an implementation using the well-known relational data model. We also investigate how to describe the learning objects in the form of hierarchical subject ontology. An ontological calculus is created to allow knowledge metrics to be constructed for evaluation within data models. We further consider the limitations of the relational abstract data model to accurately represent the meaning and understanding of learning objects and contrast this with less structured data models implicit in ontological hierarchies. Our findings indicate that more consideration is needed into how to match traditional data models with ontological structures, especially in the area of database integrity constraints.

This data was imported from Scopus:

Authors: Newell, D., Davies, P., Atfield-Cutts, S. and Rowe, N.

http://eprints.bournemouth.ac.uk/17161/

Journal: MMEDIA - International Conferences on Advances in Multimedia

Pages: 44-49

ISBN: 9781612081298

ISSN: 2308-4448

We investigate the requirements and nature of data models for a multimedia learning system that presents adaptable learning objects based on a range of stimuli provided by the student and tutor. A conceptual model is explored together with a proposal for an implementation using the well-known relational data model. We also investigate how to describe the learning objects in the form of hierarchical subject ontology. An ontological calculus is created to allow knowledge metrics to be constructed for evaluation within data models. We further consider the limitations of the relational abstract data model to accurately represent the meaning and understanding of learning objects and contrast this with less structured data models implicit in ontological hierarchies. Our findings indicate that more consideration is needed into how to match traditional data models with ontological structures, especially in the area of database integrity constraints.

This source preferred by Philip Davies

This data was imported from Web of Science (Lite):

Authors: Newell, D., Davies, P., Atfield-Cutts, S. and Rowe, N.

http://eprints.bournemouth.ac.uk/17161/

Journal: PROCEEDINGS OF THE THIRD INTERNATIONAL CONFERENCES ON ADVANCES IN MULTIMEDIA (MMEDIA 2011)

Pages: 44-49

The data on this page was last updated at 04:40 on November 22, 2017.