Abstract
We design and study ExamParser, an innovative intelligent semantic automatic indexing method, for orchestrating today's programming classes. ExamParser automatically processes paper-based exams by associating sets of concepts to the exam questions, which provide graders semantic grading guidelines and leave personalized semantic feedback. Results showed that the ExamPraser significantly extract more and diverse concepts from exams. It also achieves high coherence within exam, indicating the automatic concept extraction from exams is promising and could be a potential technological solution to provide personalized feedback for large-size programming classes.
Original language | English (US) |
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Title of host publication | Proceedings - IEEE 16th International Conference on Advanced Learning Technologies, ICALT 2016 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 65-69 |
Number of pages | 5 |
ISBN (Electronic) | 9781467390415 |
DOIs | |
State | Published - Nov 28 2016 |
Event | 16th IEEE International Conference on Advanced Learning Technologies, ICALT 2016 - Austin, United States Duration: Jul 25 2016 → Jul 28 2016 |
Other
Other | 16th IEEE International Conference on Advanced Learning Technologies, ICALT 2016 |
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Country/Territory | United States |
City | Austin |
Period | 7/25/16 → 7/28/16 |
Keywords
- Computing education
- Personalized learning
- Programming
- Semantic feedback
- Visual analytics
ASJC Scopus subject areas
- Human-Computer Interaction
- Education
- Computer Networks and Communications
- Computer Science Applications