Multi-Swarm Optimization for Extracting Multiple-Choice Tests From Question Banks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F21%3A10248865" target="_blank" >RIV/61989100:27240/21:10248865 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/9348944" target="_blank" >https://ieeexplore.ieee.org/document/9348944</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ACCESS.2021.3057515" target="_blank" >10.1109/ACCESS.2021.3057515</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Multi-Swarm Optimization for Extracting Multiple-Choice Tests From Question Banks

Popis výsledku v původním jazyce

In this study, a novel method for generating multiple-choice tests is presented, which extracts the required number of tests of the same levels of difficulty in a single attempt and approximates the difficulty level requirement given by users. We propose an approach using parallelism and Pareto optimization for multi-swarm migration in a particle swarm optimization (PSO) algorithm. Multi-PSO is proposed for shortening the computing time. The proposed migration of PSOs increases the diversity of tests and controls the overlap of extracted tests. The experimental results show that the proposed method can generate many tests from question banks satisfying predefined levels of difficulty. Additionally, the developed method is shown to be effective in terms of many criteria when compared with other methods such as manually extracted tests, a simulated annealing algorithm (SA), random methods and PSO-based approaches in terms of the number of successful solutions, accuracy, standard deviation, search speed, and the number of questions overlapping between the exam questions, as well as for changing the search space, changing the number of individuals, changing the number of swarms, and changing the difficulty requirements.

Název v anglickém jazyce

Multi-Swarm Optimization for Extracting Multiple-Choice Tests From Question Banks

Popis výsledku anglicky

In this study, a novel method for generating multiple-choice tests is presented, which extracts the required number of tests of the same levels of difficulty in a single attempt and approximates the difficulty level requirement given by users. We propose an approach using parallelism and Pareto optimization for multi-swarm migration in a particle swarm optimization (PSO) algorithm. Multi-PSO is proposed for shortening the computing time. The proposed migration of PSOs increases the diversity of tests and controls the overlap of extracted tests. The experimental results show that the proposed method can generate many tests from question banks satisfying predefined levels of difficulty. Additionally, the developed method is shown to be effective in terms of many criteria when compared with other methods such as manually extracted tests, a simulated annealing algorithm (SA), random methods and PSO-based approaches in terms of the number of successful solutions, accuracy, standard deviation, search speed, and the number of questions overlapping between the exam questions, as well as for changing the search space, changing the number of individuals, changing the number of swarms, and changing the difficulty requirements.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

10200 - Computer and information sciences

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název periodika

IEEE Access

ISSN

2169-3536

e-ISSN

—

Svazek periodika

9

Číslo periodika v rámci svazku

14.3.2021

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

18

Strana od-do

32131-32148

Kód UT WoS článku

000623414400001

EID výsledku v databázi Scopus

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