D 2015

Student Performance Prediction Using Collaborative Filtering Methods

BYDŽOVSKÁ, Hana

Basic 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.