Projects per year
Intelligent Tutoring Systems (ITSs) are aimed at promoting acquisition of knowledge and skills by providing relevant and appropriate feedback during students’ practice activities. ITSs for literacy instruction commonly assess typed responses using Natural Language Processing (NLP) algorithms. One step in this direction often requires building a scoring mechanism that matches human judgments. This paper describes the challenges encountered while implementing an automated evaluation workflow and adopting solutions for increasing performance of the tutoring system. The algorithm described here comprises multiple stages, including initial pre-processing, a rule-based system for pre-classifying self-explanations, followed by classification using a Support Virtual Machine (SVM) learning algorithm. The SVM model hyper-parameters were optimized using grid search approach with 4,109 different self explanations scored 0 to 3 (i.e., poor to great). The accuracy achieved for the model was 59% (adjacent accuracy = 97%; Kappa = .43).
|Title of host publication||Artificial Intelligence in Education|
|Subtitle of host publication||19th International Conference, AIED 2018, London, UK, June 27-30, 2018, Proceedings, Part I|
|Editors||C. P. Rosé, R. Martínez-Maldonado, H. U. Hoppe, R. Luckin, M. Mavrikis, K. Porayska-Pomsta, B. McLaren, B. d. Boulay|
|Place of Publication||Cham|
|Publisher||Springer International Publishing AG|
|Number of pages||11|
|Publication status||Published - 2018|
|Event||International Conference, AIED 2018 - London, United Kingdom|
Duration: 27 Jun 2018 → 30 Jun 2018
|Series||Lecture Notes in Computer Science|
|Series||Lecture Notes in Artificial Intelligence (subseries)|
|Conference||International Conference, AIED 2018|
|Abbreviated title||AIED 2018|
|Period||27/06/18 → 30/06/18|
- Natural language processing
- Intelligent tutoring systems
- Support vector machines
FingerprintDive into the research topics of 'Bring It on! Challenges Encountered While Building a Comprehensive Tutoring System Using ReaderBench'. Together they form a unique fingerprint.
- 1 Finished
Rage: Realising an Applied Gaming Eco-system
Westera, W., Georgiadis, K., Saveski, G., van Lankveld, G., Bahreini, K., van der Vegt, W., Berkhout, J., Nyamsuren, E., Kluijfhout, E. & Nadolski, R.
1/02/15 → 31/07/19