Goal-Oriented conceptualization of procedural knowledge

Authors:
Martin Možina;Matej Guid;Aleksander Sadikov;Vida Groznik;Ivan Bratko
Affiliations:
Faculty of Computer and Information Science, University of Ljubljana, Slovenia;Faculty of Computer and Information Science, University of Ljubljana, Slovenia;Faculty of Computer and Information Science, University of Ljubljana, Slovenia;Faculty of Computer and Information Science, University of Ljubljana, Slovenia;Faculty of Computer and Information Science, University of Ljubljana, Slovenia
Venue:
ITS'12 Proceedings of the 11th international conference on Intelligent Tutoring Systems
Year:
2012

Citing 5
Cited 0

Argument based machine learning

Artificial Intelligence
Fighting Knowledge Acquisition Bottleneck with Argument Based Machine Learning

Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Learning by teaching simstudent: technical accomplishments and an initial use with students

ITS'10 Proceedings of the 10th international conference on Intelligent Tutoring Systems - Volume Part I
Building Intelligent Interactive Tutors: Student-centered strategies for revolutionizing e-learning

Building Intelligent Interactive Tutors: Student-centered strategies for revolutionizing e-learning
Deriving concepts and strategies from chess tablebases

ACG'09 Proceedings of the 12th international conference on Advances in Computer Games

Quantified Score

Hi-index	0.00

Visualization

Abstract

Conceptualizing procedural knowledge is one of the most challenging tasks of building systems for intelligent tutoring. We present an algorithm that enables teachers to accomplish this task semi automatically. We used the algorithm on a difficult king, bishop, and knight versus the lone king (KBNK) chess endgame, and obtained concepts that could serve as textbook instructions. A pilot experiment with students and a separate evaluation of the instructions by experienced chess trainers were deemed very positive.