Student Performance Prediction Using Collaborative Filtering Methods

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F15%3A00082601" target="_blank" >RIV/00216224:14330/15:00082601 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-319-19773-9_59" target="_blank" >http://dx.doi.org/10.1007/978-3-319-19773-9_59</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-19773-9_59" target="_blank" >10.1007/978-3-319-19773-9_59</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Student Performance Prediction Using Collaborative Filtering Methods

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Student Performance Prediction Using Collaborative Filtering Methods

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

17th International Conference on Artificial Inteligence in Education - AIED 2015

ISBN

9783319197722

ISSN

0302-9743

e-ISSN

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Počet stran výsledku

4

Strana od-do

550-553

Název nakladatele

Springer International Publishing

Místo vydání

Madrid

Místo konání akce

Madrid, Spain

Datum konání akce

1. 1. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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