Exploring exam strategies of successful first year engineering students

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11410%2F20%3A10410154" target="_blank" >RIV/00216208:11410/20:10410154 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21220/20:00340502 RIV/68407700:21730/20:00340502
Result on the web
<a href="https://doi.org/10.1145/3375462.3375469" target="_blank" >https://doi.org/10.1145/3375462.3375469</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3375462.3375469" target="_blank" >10.1145/3375462.3375469</a>

Result language
angličtina
Original language name
Exploring exam strategies of successful first year engineering students
Original language description
At present, universities collect study-related data about their students. This information can be used to support students at risk of failing their studies. At the Faculty of Mechanical Engineering (FME), Czech Technical University in Prague (CTU), the group of the first-year students is the most vulnerable. The most critical part of the first year is the winter exam period when students usually divide into those who will pass and fail. One of the most important abilities, students need to learn, is exam planning, and our research aims at the exploration of the exam strategies of successful students. These strategies can be used for improving first-year students retention. The outgoing research on the analysis of exam strategies of the first-year students in the academic year 2017/2018 is reported. From a total of 361 first-year students, successful students have been selected. The successful student is the one who finished all three mandatory exams before the end of the first exam period. From the exam sequences of 153 selected students, a "layered" Markov chain probabilistic model has been constructed. It uncovered the most common exam strategies taken by those students. (C) 2020 Copyright held by the owner/author(s).
Czech name
—
Czech description
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Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project
<a href="/en/project/GJ18-04150Y" target="_blank" >GJ18-04150Y: Predictive modeling of student performance using learning resources</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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