Abstract
Several Learning Analytics applications are limited by the cost of generating a computer understandable description of the course domain, what is called an Intelligent Curriculum. The following work contributes a novel approach to (semi-)automatically generate Intelligent Curriculum through ontologies extracted from existing learning materials such as digital books or web content. Through a series of natural language processing steps, the semi-structured information present in existing content is transformed into a concept-graph. This work also evaluates the proposed methodology by applying it to learning content for two different courses and measuring the quality of the extracted ontologies against manually generated ones. The results obtained suggest that the technique can be readily used to provide domain information to other Learning Analytics tools.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of the 9th International Conference on Learning Analytics and Knowledge |
| Subtitle of host publication | Learning Analytics to Promote Inclusion and Success, LAK 2019 |
| Publisher | Association for Computing Machinery |
| Pages | 46-50 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781450362566 |
| DOIs | |
| State | Published - Mar 4 2019 |
| Event | 9th International Conference on Learning Analytics and Knowledge, LAK 2019 - Tempe, United States Duration: Mar 4 2019 → Mar 8 2019 |
Publication series
| Name | ACM International Conference Proceeding Series |
|---|
Conference
| Conference | 9th International Conference on Learning Analytics and Knowledge, LAK 2019 |
|---|---|
| Country | United States |
| City | Tempe |
| Period | 3/4/19 → 3/8/19 |
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Keywords
- Intelligent curriculum
- NLP
- Ontologies
ASJC Scopus subject areas
- Human-Computer Interaction
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Software
Cite this
Semi-automatic generation of intelligent curricula to facilitate learning analytics. / Fiallos, Angel; Ochoa, Xavier.
Proceedings of the 9th International Conference on Learning Analytics and Knowledge: Learning Analytics to Promote Inclusion and Success, LAK 2019. Association for Computing Machinery, 2019. p. 46-50 (ACM International Conference Proceeding Series).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Semi-automatic generation of intelligent curricula to facilitate learning analytics
AU - Fiallos, Angel
AU - Ochoa, Xavier
PY - 2019/3/4
Y1 - 2019/3/4
N2 - Several Learning Analytics applications are limited by the cost of generating a computer understandable description of the course domain, what is called an Intelligent Curriculum. The following work contributes a novel approach to (semi-)automatically generate Intelligent Curriculum through ontologies extracted from existing learning materials such as digital books or web content. Through a series of natural language processing steps, the semi-structured information present in existing content is transformed into a concept-graph. This work also evaluates the proposed methodology by applying it to learning content for two different courses and measuring the quality of the extracted ontologies against manually generated ones. The results obtained suggest that the technique can be readily used to provide domain information to other Learning Analytics tools.
AB - Several Learning Analytics applications are limited by the cost of generating a computer understandable description of the course domain, what is called an Intelligent Curriculum. The following work contributes a novel approach to (semi-)automatically generate Intelligent Curriculum through ontologies extracted from existing learning materials such as digital books or web content. Through a series of natural language processing steps, the semi-structured information present in existing content is transformed into a concept-graph. This work also evaluates the proposed methodology by applying it to learning content for two different courses and measuring the quality of the extracted ontologies against manually generated ones. The results obtained suggest that the technique can be readily used to provide domain information to other Learning Analytics tools.
KW - Intelligent curriculum
KW - NLP
KW - Ontologies
UR - http://www.scopus.com/inward/record.url?scp=85062801092&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85062801092&partnerID=8YFLogxK
U2 - 10.1145/3303772.3303834
DO - 10.1145/3303772.3303834
M3 - Conference contribution
AN - SCOPUS:85062801092
T3 - ACM International Conference Proceeding Series
SP - 46
EP - 50
BT - Proceedings of the 9th International Conference on Learning Analytics and Knowledge
PB - Association for Computing Machinery
ER -