Detailed Information on Publication Record
2015
Student Performance Prediction Using Collaborative Filtering Methods
BYDŽOVSKÁ, HanaBasic information
Original name
Student Performance Prediction Using Collaborative Filtering Methods
Authors
BYDŽOVSKÁ, Hana (203 Czech Republic, guarantor, belonging to the institution)
Edition
Madrid, 17th International Conference on Artificial Inteligence in Education - AIED 2015, p. 550-553, 4 pp. 2015
Publisher
Springer International Publishing
Other information
Language
English
Type of outcome
Stať ve sborníku
Field of Study
10201 Computer sciences, information science, bioinformatics
Country of publisher
Spain
Confidentiality degree
není předmětem státního či obchodního tajemství
Publication form
storage medium (CD, DVD, flash disk)
Impact factor
Impact factor: 0.402 in 2005
RIV identification code
RIV/00216224:14330/15:00082601
Organization unit
Faculty of Informatics
ISBN
978-3-319-19772-2
ISSN
UT WoS
000365041100059
Keywords in English
Student Performance; Prediction; Collaborative Filtering Methods; Recommender System
Tags
International impact, Reviewed
Změněno: 2/5/2016 06:00, RNDr. Pavel Šmerk, Ph.D.
Abstract
V originále
This paper shows how to utilize collaborative filtering methods for student performance prediction. These methods are often used in recommender systems. The basic idea of such systems is to utilize the similarity of users based on their ratings of the items in the system. We have decided to employ these techniques in the educational environment to predict student performance. We calculate the similarity of students utilizing their study results, represented by the grades of their previously passed courses. As a real-world example we show results of the performance prediction of students who attended courses at Masaryk University. We describe the data, processing phase, evaluation, and finally the results proving the success of this approach.