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Biometric and Intelligent Student Progress Assessment System

  • Artūras KaklauskasEmail author
  • Edmundas Kazimieras Zavadskas
  • Mark Seniut
  • Andrej Vlasenko
  • Gintaris Kaklauskas
  • Algirdas Juozapaitis
  • Agne Matuliauskaite
  • Gabrielius Kaklauskas
  • Lina Zemeckyte
  • Ieva Jackute
  • Jurga Naimaviciene
  • Justas Cerkauskas
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 457)

Abstract

A number of methodologies (Big Five Factors and Five Factor Model, intelligence quotient tests, self-assessment) and strategies for web-based formative assessment are used in an effort to predict a student’s academic motivation, achievements and performance. These methodologies, biometric voice analysis technologies and 13 years of authors’ experience in distance learning were used in development of the Biometric and Intelligent Student Progress Assessment System for psychological assessment of student progress. Also the BISPA system was developed in consideration of worldwide research results involving the interrelation between a person’s knowledge, self-assessment and voice stress along with instances of available decision support, recommender and intelligent tutoring systems.

Keywords

e-Learning Voice Stress Analysis Intelligent System e-Self- Assessment e-Examination Historical Information Reliability of Results 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Artūras Kaklauskas
    • 1
    Email author
  • Edmundas Kazimieras Zavadskas
    • 1
  • Mark Seniut
    • 1
  • Andrej Vlasenko
    • 1
  • Gintaris Kaklauskas
    • 1
  • Algirdas Juozapaitis
    • 1
  • Agne Matuliauskaite
    • 1
  • Gabrielius Kaklauskas
    • 1
  • Lina Zemeckyte
    • 1
  • Ieva Jackute
    • 1
  • Jurga Naimaviciene
    • 1
  • Justas Cerkauskas
    • 1
  1. 1.Vilnius Gediminas Technical UniversityVilniusLithuania

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