Using decision trees to predict the likelihood of high school students enrolling for university studies
The result's identifiers
Result code in 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>
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
Using decision trees to predict the likelihood of high school students enrolling for university studies
Original language description
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.
Czech name
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Czech description
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Classification
Type
C - Chapter in a specialist book
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EE2.3.20.0170" target="_blank" >EE2.3.20.0170: Building of Research Team in the Field of Environmental Modeling and the Use of Geoinformation Systems with the Consequence in Participation in International Networks and Programs</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Book/collection name
Computational and Statistical Methods in Intelligent Systems
ISBN
978-3-030-00210-7
Number of pages of the result
9
Pages from-to
111-119
Number of pages of the book
386
Publisher name
SPRINGER INTERNATIONAL PUBLISHING AG
Place of publication
Cham
UT code for WoS chapter
000502603900012