First-Year Engineering Students’ Strategies for Taking Exams

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F23%3A00359051" target="_blank" >RIV/68407700:21220/23:00359051 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21260/23:00359051 RIV/68407700:21730/23:00359051

Výsledek na webu

<a href="https://doi.org/10.1007/s40593-022-00303-4" target="_blank" >https://doi.org/10.1007/s40593-022-00303-4</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s40593-022-00303-4" target="_blank" >10.1007/s40593-022-00303-4</a>

Jazyk výsledku

angličtina

Název v původním jazyce

First-Year Engineering Students’ Strategies for Taking Exams

Popis výsledku v původním jazyce

Student drop-out is one of the most critical issues that higher educational institutions face nowadays. The problem is significant for first-year students. These freshmen are especially at risk of failing due to the transition from different educational settings at high school. Thanks to the massive boom of Information and Communication Technologies, universities have started to collect a vast amount of study- and student-related data. Teachers can use the collected information to support students at risk of failing their studies. At the Faculty of Mechanical Engineering, Czech Technical University in Prague, the situation is no different, and first-year students are a vulnerable group similar to other institutions. The most critical part of the first year is the first exam period. One of the essential skills the student needs to develop is planning for exams. The presented research aims to explore the exam-taking patterns of first-year students. Data of 361 first-year students have been analysed and used to construct “layered” Markov chain probabilistic graphs. The graphs have revealed interesting behavioural patterns within the groups of successful and unsuccessful students.

Název v anglickém jazyce

First-Year Engineering Students’ Strategies for Taking Exams

Popis výsledku anglicky

Student drop-out is one of the most critical issues that higher educational institutions face nowadays. The problem is significant for first-year students. These freshmen are especially at risk of failing due to the transition from different educational settings at high school. Thanks to the massive boom of Information and Communication Technologies, universities have started to collect a vast amount of study- and student-related data. Teachers can use the collected information to support students at risk of failing their studies. At the Faculty of Mechanical Engineering, Czech Technical University in Prague, the situation is no different, and first-year students are a vulnerable group similar to other institutions. The most critical part of the first year is the first exam period. One of the essential skills the student needs to develop is planning for exams. The presented research aims to explore the exam-taking patterns of first-year students. Data of 361 first-year students have been analysed and used to construct “layered” Markov chain probabilistic graphs. The graphs have revealed interesting behavioural patterns within the groups of successful and unsuccessful students.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

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/GJ18-04150Y" target="_blank" >GJ18-04150Y: Prediktivní modelování studentova výkonu s využitím výukových zdrojů</a><br>

Návaznosti

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

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

International Journal of Artificial Intelligence in Education

ISSN

1560-4292

e-ISSN

1560-4306

Svazek periodika

2023

Číslo periodika v rámci svazku

33

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

26

Strana od-do

583-608

Kód UT WoS článku

000836369300001

EID výsledku v databázi Scopus

2-s2.0-85135338361