Student progress assessment with the help of an intelligent pupil analysis system

Authors:
Arturas Kaklauskas;Andrej Vlasenko;Vidas Raudonis;Edmundas Kazimieras Zavadskas;Renaldas Gudauskas;Mark Seniut;Algirdas Juozapaitis;Ieva Jackute;Loreta Kanapeckiene;Silva Rimkuviene;Gabrielius Kaklauskas
Affiliations:
Vilnius Gediminas Technical University, Sauletekio av. 11, Vilnius, LT-10223, Lithuania;Vilnius Gediminas Technical University, Sauletekio av. 11, Vilnius, LT-10223, Lithuania;Kaunas University of Technology, K. Donelaicio St. 73, Kaunas, LT-44029, Lithuania;Vilnius Gediminas Technical University, Sauletekio av. 11, Vilnius, LT-10223, Lithuania;Martynas Mazvydas National Library of Lithuania, Vilnius, Lithuania;Vilnius Gediminas Technical University, Sauletekio av. 11, Vilnius, LT-10223, Lithuania;Vilnius Gediminas Technical University, Sauletekio av. 11, Vilnius, LT-10223, Lithuania;Vilnius Gediminas Technical University, Sauletekio av. 11, Vilnius, LT-10223, Lithuania;Vilnius Gediminas Technical University, Sauletekio av. 11, Vilnius, LT-10223, Lithuania;Vilnius Gediminas Technical University, Sauletekio av. 11, Vilnius, LT-10223, Lithuania;Vilnius University, Universiteto St. 3, LT-01513, Vilnius, Lithuania
Venue:
Engineering Applications of Artificial Intelligence
Year:
2013

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Abstract

Students and lecturers would like to know how well students have learned the study materials being taught. A formal test or exam would cause needless stress for students. To resolve this problem, the authors of this article have developed an Intelligent Pupil Analysis (IPA) System. A sufficient amount of studies worldwide prove an interrelation between pupil size and a person's cognitive load. The obtained research results are comparable with the results from other similar studies. The original contribution of this article, compared to the research results published earlier, is as follows: the IPA System developed by the authors is superior to the traditional pupil analysis research due to the integration of pupil analysis with subsystems of decision support, recommender and intelligent tutoring systems and innovative Models of the Model-base, which permit a more detailed analysis of the knowledge attained by a student. This article ends with a case study to demonstrate the practical operation of the IPA System.