Abstract
Gamification is frequently employed in learning environments to enhance learner interactions and engagement. However, most games use pre-scripted dialogues and interactions with players, which limit their immersion and cognition. Our aim is to develop a semantic matching tool that enables users to introduce open text answers which are automatically associated with the most similar pre-scripted answer. A structured scenario written in Dutch was developed by experts for this communication experiment as a sequence of possible interactions within the environment. Semantic similarity scores computed with the SpaCy library were combined with string kernels, WordNet-based distances, and used as features in a neural network. Our experiments show that string kernels are the most predictive feature for determining the most probable pre-scripted answer, whereas neural networks obtain similar performance by combining multiple semantic similarity measures.
Original language | English |
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Title of host publication | Artificial Intelligence in Education |
Subtitle of host publication | 20th International Conference, AIED 2019, Chicago, IL, USA, June 25-29, 2019, Proceedings, Part II |
Editors | Seiji Isotani, Eva Millán, Amy Ogan, Peter Hastings, Bruce McLaren, Rose Luckin |
Place of Publication | Cham |
Publisher | Springer |
Chapter | 45 |
Pages | 242-246 |
Number of pages | 5 |
Volume | 2 |
ISBN (Electronic) | 9783030232078 |
ISBN (Print) | 9783030232061 |
DOIs | |
Publication status | Published - 21 Jun 2019 |
Event | 20th International Conference on Artificial Intelligence in Education - Palmer House Hilton Hotel, Chicago, United States Duration: 25 Jun 2019 → 29 Jun 2019 https://caed-lab.com/aied2019/ |
Publication series
Series | Lecture Notes in Computer Science |
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Volume | 11626 |
ISSN | 0302-9743 |
Conference
Conference | 20th International Conference on Artificial Intelligence in Education |
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Abbreviated title | AIED 2019 |
Country | United States |
City | Chicago |
Period | 25/06/19 → 29/06/19 |
Internet address |
Keywords
- answer matching
- semantic similarity
- natural language processing
- Neural network