Open AccessVisualization of Learning Outcome Structure for Self-Learning
Author(s) -
Athitaya Nitchot,
L Gilbert
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1438/1/012012
Subject(s) - computer science , contextualization , subject matter expert , vocabulary , visualization , competence (human resources) , knowledge management , outcome (game theory) , subject matter , artificial intelligence , psychology , curriculum , pedagogy , mathematics , social psychology , linguistics , philosophy , mathematical economics , expert system , interpretation (philosophy) , programming language
The success and quality of an educational or training system is assessed by its match to the competences it claims to develop. In this research, we propose a conceptual model of contextualized competence (or learning outcome), being a learner’s capability with respect to some subject matter. We also suggest a controlled vocabulary of capability verbs, based upon Merrill’s theory insight that a particular capability should be associated with a particular type of subject matter. At this stage, the model is deployed as a subject matter graph without contextualization in the domain of programming fundamentals. The implemented tool associates learning resources (mainly html links) with the domain knowledge structures, offering graph creation and visualization, resource suggestions, and learning paths. Future work will include learning outcomes and related context, and will evaluate user satisfaction and accessibility.