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  • The authors present, on the base of their own experiments and large variety of recent studies, the great potential of data, obtained from physiological measurement, for immediate and individualized reaction on the learning process of the learning subject in virtual learning environments. They emphasized simple, non invasive methods, easily available, for eyes tracking, blink rate and blink speed measurements electrodermal activities , and heart/respiration rate. They highlight the advantages and constraints of different data acquisition approaches and methods (including technical and physiological), as well as constraints, caused by the hardware and software limits, by the necessity of individual setup (often continuous), by the problems with real time data processing, including wrong data recognition and elimination, etc. Analyzing data of GSR, EEG and eye tracking studies (with sample size of 6, later 8) employing a wide range of cognitive tasks.
  • The authors present, on the base of their own experiments and large variety of recent studies, the great potential of data, obtained from physiological measurement, for immediate and individualized reaction on the learning process of the learning subject in virtual learning environments. They emphasized simple, non invasive methods, easily available, for eyes tracking, blink rate and blink speed measurements electrodermal activities , and heart/respiration rate. They highlight the advantages and constraints of different data acquisition approaches and methods (including technical and physiological), as well as constraints, caused by the hardware and software limits, by the necessity of individual setup (often continuous), by the problems with real time data processing, including wrong data recognition and elimination, etc. Analyzing data of GSR, EEG and eye tracking studies (with sample size of 6, later 8) employing a wide range of cognitive tasks. (en)
Title
  • Acquiring Physiological Data for Automated Educational Feedback In Virtual Learning Environments
  • Acquiring Physiological Data for Automated Educational Feedback In Virtual Learning Environments (en)
skos:prefLabel
  • Acquiring Physiological Data for Automated Educational Feedback In Virtual Learning Environments
  • Acquiring Physiological Data for Automated Educational Feedback In Virtual Learning Environments (en)
skos:notation
  • RIV/00216208:11320/10:10062330!RIV11-MSM-11320___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • S
http://linked.open...iv/cisloPeriodika
  • 2
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 245261
http://linked.open...ai/riv/idVysledku
  • RIV/00216208:11320/10:10062330
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • eye tracking; GSR; learning; neurophysiology (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • PL - Polská republika
http://linked.open...ontrolniKodProRIV
  • [01FB56B209FA]
http://linked.open...i/riv/nazevZdroje
  • New Educational Review
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 21
http://linked.open...iv/tvurceVysledku
  • Malčík, Martin
  • Lustigová, Zdena
  • Malach, Josef
  • Dufresne, Aude
  • Courtemanche, Francois
http://linked.open...ain/vavai/riv/wos
  • 000280429700008
issn
  • 1732-6729
number of pages
http://localhost/t...ganizacniJednotka
  • 11320
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