Network models for mapping educational data
| Autor: | Luwen Huang, Karen Willcox |
|---|---|
| Přispěvatelé: | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics, Willcox, Karen E, Huang, Luwen |
| Rok vydání: | 2017 |
| Předmět: |
Visual Arts and Performing Arts
Computer science Concept map 05 social sciences General Engineering Learning analytics 050301 education Data science 050105 experimental psychology Data mapping Visualization Modeling and Simulation Curriculum mapping ComputingMilieux_COMPUTERSANDEDUCATION 0501 psychology and cognitive sciences Use case Adaptive learning 0503 education Curriculum |
| Zdroj: | Cambridge University Press |
| ISSN: | 2053-4701 |
| DOI: | 10.1017/dsj.2017.18 |
| Popis: | Educational mapping is the process of analyzing an educational system to identify entities, relationships and attributes. This paper proposes a network modeling approach to educational mapping. Current mapping processes in education typically represent data in forms that do not support scalable learning analytics. For example, a curriculum map is usually a table, where relationships among curricular elements are represented implicitly in the rows of the table. The proposed network modeling approach overcomes this limitation through explicit modeling of these relationships in a graph structure, which in turn unlocks the ability to perform scalable analyses on the dataset. The paper presents network models for educational use cases, with concrete examples in curriculum mapping, accreditation mapping and concept mapping. Illustrative examples demonstrate how the formal modeling approach enables visualization and learning analytics. The analysis provides insight into learning pathways, supporting design of adaptive learning systems. It also permits gap analysis of curriculum coverage, supporting student advising, student degree planning and curricular design at scales ranging from an entire institution to an individual course. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|