Modeling the Prediction of Students' Success in the Context of Small Universities

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F18%3A00503460" target="_blank" >RIV/67985807:_____/18:00503460 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.21125/iceri.2018.1398" target="_blank" >http://dx.doi.org/10.21125/iceri.2018.1398</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.21125/iceri.2018.1398" target="_blank" >10.21125/iceri.2018.1398</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Modeling the Prediction of Students' Success in the Context of Small Universities

Popis výsledku v původním jazyce

The prediction of the success of college students becomes one of the most important but at the same time very demanding themes of university research. Early detection of students at risk of failure is of great importance both for students themselves and for universities that seek to reduce students' failure in courses leading to their early school leaving. Researchers in this field involve methods from the field of classification and regression algorithms or probability models. Frequent interest of researchers is the orientation in the large amount of data currently available to universities through datamining methods. The aim of this paper is to find a method for predict the success of students in the environment of small universities. In this environment, we encounter mainly the problem of the low number of students associated with a small range of the group. This is a case where commonly used methods fail and it is necessary to look for specific approaches that would allow predictions on such limited data. On the other hand, a small number of students give these universities a great advantage in the form of a very effective intervention. Finding suitable methods for modeling student success is therefore very beneficial in this environment.

Název v anglickém jazyce

Modeling the Prediction of Students' Success in the Context of Small Universities

Popis výsledku anglicky

The prediction of the success of college students becomes one of the most important but at the same time very demanding themes of university research. Early detection of students at risk of failure is of great importance both for students themselves and for universities that seek to reduce students' failure in courses leading to their early school leaving. Researchers in this field involve methods from the field of classification and regression algorithms or probability models. Frequent interest of researchers is the orientation in the large amount of data currently available to universities through datamining methods. The aim of this paper is to find a method for predict the success of students in the environment of small universities. In this environment, we encounter mainly the problem of the low number of students associated with a small range of the group. This is a case where commonly used methods fail and it is necessary to look for specific approaches that would allow predictions on such limited data. On the other hand, a small number of students give these universities a great advantage in the form of a very effective intervention. Finding suitable methods for modeling student success is therefore very beneficial in this environment.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název statě ve sborníku

ICERI 2018 Proceedings

ISBN

978-84-09-05948-5

ISSN

2340-1095

e-ISSN

—

Počet stran výsledku

10

Strana od-do

1791-1800

Název nakladatele

IATED Academy

Místo vydání

Seville

Místo konání akce

Seville

Datum konání akce

12. 11. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000562759301131