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

Abstract

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.

Evaluation process for an introductory programming course using blended learning in engineering education

“…The remaining 23 students did all the activities, with 4 failings. The problem of these Bash exercises, and others using online judges such as BOCA , URI , and others , is that grading occurs only when the exercise is correct, becoming rigorous and discouraging for students in an introductory course on programming.…”

“…Considering that 1,560 students should attend IP every year (not counting the extra classes for failing students of previous terms), 18 theoretical classes are usually prepared (90 students each), and 52 practical classes (30 students) involving up to 70 teachers in total. Although there is a discipline coordinator (attributed to one of the teachers) in each period in which the course is offered, a mandatory assessment standard has not been adopted, such as the application of unified exams, which results in discrepancies and variations in the evaluations results.…”

Education Data-Driven Online Course Optimization Mechanism for College Student

“…Course comments are short and have few valid information. e traditional text classification model does not have good effects [21]. In this paper, we use deep learning algorithm to score comments and use Word2-Vector [22] to represent short text information as low-dimensional vectors.…”

SCFH: A Student Analysis Model to Identify Students’ Programming Levels in Online Judge Systems

“…In recent years, different support systems and recommendation systems have been proposed for online judge programming environment [14,15]. The support system includes problem difficulty assessment [16,17], problem suggestion [18,19] and other services. Most of the proposed support systems are based on collaborative filtering [14,16,17] and are limited to classroom data.…”