Informatics in Education logo


Login Register

  1. Home
  2. Issues
  3. Volume 8, Issue 2 (2009)
  4. Aggregating of Learning Object Units Der ...

Informatics in Education

INFORMATION Submit your article Help
  • Article info
  • Related articles
  • More
    Article info Related articles

Aggregating of Learning Object Units Derived from a Generative Learning Object
Volume 8, Issue 2 (2009), pp. 295–314
Vytautas STUIKYS   Ilona BRAUKLYTE  

Authors

 
Placeholder
https://doi.org/10.15388/infedu.2009.18
Pub. online: 15 October 2009      Type: Article     

Published
15 October 2009

Abstract

Aggregating and sequencing of the content units is at the core of e-learning theories and standards. We discuss the aggregating/sequencing problems in the context of using generative learning objects (GLOs). Proposed by Boyle, Morales, Leeder in 2004, GLOs provide more capabilities, focus on quality issues, and introduce a solid basis for a marked improvement in productivity. We use meta-programming techniques to specify GLOs and then to automatically generate LO units on demand. Aggregating of the generated units to form a compound at a higher granularity level can be performed in various ways depending on the selected criteria or their trade-offs (e.g., complexity, granularity level, semantic density, time constraints, capabilities of modelling the learning process, etc.) that enable to evaluate units in advance. We describe aggregating as an internal sequencing of the content units derived from a GLO. Our contribution is a formal graph-based model to specify the problem when the variability of LO units is large. First we formulate the problem and consider properties of the proposed model; and then we analyze a case study, implementation capabilities, and evaluate the approach for e-learning.

Related articles PDF XML
Related articles PDF XML

Copyright
No copyright data available.

Keywords
learning object (LO) generative learning object (GLO) granularity level of LO aggregating model sequencing model

Metrics
since February 2020
1171

Article info
views

0

Full article
views

524

PDF
downloads

274

XML
downloads

Export citation

Copy and paste formatted citation
Placeholder

Download citation in file


Share


RSS

INFORMATICS IN EDUCATION

  • Online ISSN: 2335-8971
  • Print ISSN: 1648-5831
  • Copyright © 2024 Vilnius University
  •  

For contributors

  • Submit
  • OA Policy

Contact us

  • Institute of Data Science and Digital Technologies,
  • Vilnius University, Akademijos St. 4, 08412, Vilnius, Lithuania
  • E-mail: gabriele.stupuriene@mif.vu.lt
Powered by PubliMill  •  Privacy policy