Inductive learning algorithms and representations for text categorization
Proceedings of the seventh international conference on Information and knowledge management
Information Retrieval
Computer-Based Instruction: Methods and Development
Computer-Based Instruction: Methods and Development
ML-KNN: A lazy learning approach to multi-label learning
Pattern Recognition
The application of nearest neighbor algorithm on creating an adaptive on-line learning system
FIE '01 Proceedings of the Frontiers in Education Conference, 2001. on 31st Annual - Volume 01
Investigating the Performance of Naive- Bayes Classifiers and K- Nearest Neighbor Classifiers
ICCIT '07 Proceedings of the 2007 International Conference on Convergence Information Technology
Introduction to Information Retrieval
Introduction to Information Retrieval
Nearest neighbor classification by relearning
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
Exploring query matrix for support pattern based classification learning
ICMLC'05 Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics
pGPA: a personalized grade prediction tool to aid student success
Proceedings of the sixth ACM conference on Recommender systems
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We study the problem of predicting student performance in an online course. Our specific goal is to identify at an early stage of the course those students who have a high risk of failing. We employ the k-nearest neighbour method (KNN) and its many variants on this problem. We present extensive experimental results from a 12-lesson course on touch-typing, with a database of close to 15,000 students. The results indicate that KNN can predict student performance accurately, and already after the very first lessons. We conclude that early tests on skills can also be strong predictors for final scores also in other skill-based courses. Selected methods described in this paper will be implemented as an early warning feature for teachers of the touch-typing course, so they can quickly focus their attention to the students who need help the most.