All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Application of Particle Swarm Optimization to Create Multiple-Choice Tests

The result's identifiers

  • Result code in 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>

  • Result on the web

    <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>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Application of Particle Swarm Optimization to Create Multiple-Choice Tests

  • Original language description

    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.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

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

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2018

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Journal of Information Science and Engineering

  • ISSN

    1016-2364

  • e-ISSN

  • Volume of the periodical

    34

  • Issue of the periodical within the volume

    6

  • Country of publishing house

    TW - TAIWAN (PROVINCE OF CHINA)

  • Number of pages

    19

  • Pages from-to

    1405-1423

  • UT code for WoS article

    000451364100004

  • EID of the result in the Scopus database

    2-s2.0-85056740523