Using decision trees to predict the likelihood of high school students enrolling for university studies

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F19%3A73596476" target="_blank" >RIV/61989592:15310/19:73596476 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.springerprofessional.de/en/using-decision-trees-to-predict-the-likelihood-of-high-school-st/16082622" target="_blank" >https://www.springerprofessional.de/en/using-decision-trees-to-predict-the-likelihood-of-high-school-st/16082622</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-00211-4_12" target="_blank" >10.1007/978-3-030-00211-4_12</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Using decision trees to predict the likelihood of high school students enrolling for university studies

Popis výsledku v původním jazyce

This article presents the use of decision trees to identify the main factors which predict the likelihood of high school students matriculating at the Department of Geoinformatics, Palacky University in Olomouc (Czech Republic). The Department of Geoinformatics has been running a continuous and systematic information campaign about studying the fields of geoinformatics and geography within the department. In order to collect feedback about the information campaign, students who apply to study at the department are then given a questionnaire. Answers received from this questionnaire in two years, (2016 and 2017), were analyzed using decision trees that help us understand what specific type of information positively affects the likelihood of a student actually commencing studies at our department.

Název v anglickém jazyce

Using decision trees to predict the likelihood of high school students enrolling for university studies

Popis výsledku anglicky

This article presents the use of decision trees to identify the main factors which predict the likelihood of high school students matriculating at the Department of Geoinformatics, Palacky University in Olomouc (Czech Republic). The Department of Geoinformatics has been running a continuous and systematic information campaign about studying the fields of geoinformatics and geography within the department. In order to collect feedback about the information campaign, students who apply to study at the department are then given a questionnaire. Answers received from this questionnaire in two years, (2016 and 2017), were analyzed using decision trees that help us understand what specific type of information positively affects the likelihood of a student actually commencing studies at our department.

Druh

C - Kapitola v odborné knize

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/EE2.3.20.0170" target="_blank" >EE2.3.20.0170: Budování výzkumně-vzdělávacího týmu v oblasti modelování přírodních jevů a využití geoinformačních systémů, s vazbou na zapojení do mezinárodních sítí a programů.</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2019

Kód důvěrnosti údajů

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

Název knihy nebo sborníku

Computational and Statistical Methods in Intelligent Systems

ISBN

978-3-030-00210-7

Počet stran výsledku

9

Strana od-do

111-119

Počet stran knihy

386

Název nakladatele

SPRINGER INTERNATIONAL PUBLISHING AG

Místo vydání

Cham

Kód UT WoS kapitoly

000502603900012