Authors:
Fatema Nafa
and
Javed Khan
Affiliation:
Kent State University, United States
Keyword(s):
Learning Analytics, Higher Order Thinking Skills, Domain Knowledge and Relationships Extraction.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence and Decision Support Systems
;
Computer-Supported Education
;
Educating the Educators
;
e-Learning
;
Enterprise Information Systems
;
Higher Order Thinking Skills
;
Information Technologies Supporting Learning
;
Intelligent Tutoring Systems
;
Learning Analytics
;
Learning/Teaching Methodologies and Assessment
Abstract:
In this paper, we propose an approach that can improve the quality of pedagogies based on Bloom's Taxonomy
(BT) cognitive theory. Theoretically, any domain knowledge can be learned and taught at multiple cognitive
domain levels. Moreover, other cognitive domain levels might be called, for learn specific domain knowledge.
If we know the dependencies between the domain knowledge, many interesting pedagogical applications are
possible. However, until now, the relationship levels between domain knowledge are highly sophisticated and
required tedious human judgment to be deduced. BT theory has been explored in the psychological sciences
paradigm, but has not been examined automatically. No comprehensive computer science map is currently
available. This paper, explores how the BT- relationships between various domain knowledge is automatically
extracted. A Bloom Topic Graph (BTG) that encodes concept space is extracted. BTG provides concept space
connected as BT cognitive relationships. Ou
r approach utilizes verbs to discover the BT cognitive
relationships between computer sciences, domain knowledge. We evaluate the BT cognitive relationships
using ground truth, and our approach achieves an accuracy of average 65-75%, which is significantly high.
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