Azala

An e-Learning Collaborative Filtering Approach to Suggest Problems to Solve in Programming Online Judges

Gorde:
Argitaratua izan da:International Journal of Distance Education Technologies vol. 12, no. 2 (2014), p. 51
Egile nagusia: Toledo, Raciel
Beste egile batzuk: Mota, Yailé
Argitaratua:
IGI Global
Gaiak:
Transformations (mathematics)
Programming
Recommender systems
Distance learning
Filtration
Learning
Collaborative learning
Internet
Cooperative learning
Computer assisted instruction > CAI
Collaboration
Writers
Computer Oriented Programs
Copyrights
World Problems
Electronic Learning
Influence of Technology
Distance Education
Automation
Grading
Periodicals
Calculus
Sarrera elektronikoa:Citation/Abstract
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Laburpena:The paper proposes a recommender system approach to cover online judge's domains. Online judges are e-learning tools that support the automatic evaluation of programming tasks done by individual users, and for this reason they are usually used for training students in programming contest and for supporting basic programming teachings. The proposal pretends to suggest problems assuming that a user must try to solve those problems already successfully solved by similar users. With this goal, the authors adopt the traditional collaborative filtering method with a new similarity measure adapted to the current domain, and the authors propose several transformations in the user-problem matrix to incorporate specific online judge's information. The authors evaluate the effect of the matrix configurations using Precision and Recall metrics, getting better results comparing with the authors method without transformations and with a representative state-of-art approach. Finally, the authors outline possible extensions to the current work.
ISSN:1539-3100
1539-3119
DOI:10.4018/ijdet.2014040103
Baliabidea:ABI/INFORM Global