Application of Particle Swarm Optimization to Create Multiple-Choice Tests

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F18%3A10241900" target="_blank" >RIV/61989100:27240/18:10241900 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.airitilibrary.com/Publication/alDetailedMesh?DocID=10162364-201811-201811050001-201811050001-1405-1423" target="_blank" >http://www.airitilibrary.com/Publication/alDetailedMesh?DocID=10162364-201811-201811050001-201811050001-1405-1423</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.6688/JISE.201811_34(6).0004" target="_blank" >10.6688/JISE.201811_34(6).0004</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Application of Particle Swarm Optimization to Create Multiple-Choice Tests

Popis výsledku v původním jazyce

Generating tests from question banks by using manually extracted items or involving random method consumes a great deal of time and effort. At the same time, the quality of the resulting tests is often not high. The generated tests may not entirely meet the requirements formulated in advance. Therefore, this study develops innovative ways to enhance this process by optimizing the execution time and generating results that closely meet the extraction requirements. The paper proposes the use of Particle Swarm Optimization (PSO) to generate multiple-choice tests based on assumed objective levels of difficulty. The experimental results reveal that PSO speed-ups the extraction process, and improves the quality of tests in comparison with the results produced by previously used methods such as Random or Genetic Algorithm (GA) optimized methods. In addition, PSO shows to be more efficient than GA and random selection in most criteria, such as execution time, search space, stability, and standard deviation.

Název v anglickém jazyce

Application of Particle Swarm Optimization to Create Multiple-Choice Tests

Popis výsledku anglicky

Generating tests from question banks by using manually extracted items or involving random method consumes a great deal of time and effort. At the same time, the quality of the resulting tests is often not high. The generated tests may not entirely meet the requirements formulated in advance. Therefore, this study develops innovative ways to enhance this process by optimizing the execution time and generating results that closely meet the extraction requirements. The paper proposes the use of Particle Swarm Optimization (PSO) to generate multiple-choice tests based on assumed objective levels of difficulty. The experimental results reveal that PSO speed-ups the extraction process, and improves the quality of tests in comparison with the results produced by previously used methods such as Random or Genetic Algorithm (GA) optimized methods. In addition, PSO shows to be more efficient than GA and random selection in most criteria, such as execution time, search space, stability, and standard deviation.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

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

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název periodika

Journal of Information Science and Engineering

ISSN

1016-2364

e-ISSN

—

Svazek periodika

34

Číslo periodika v rámci svazku

6

Stát vydavatele periodika

TW - Čínská republika (Tchaj-wan)

Počet stran výsledku

19

Strana od-do

1405-1423

Kód UT WoS článku

000451364100004

EID výsledku v databázi Scopus

2-s2.0-85056740523