Biometric and intelligent self-assessment of student progress system

Abstract

All distance learning participants (students, professors, instructors, mentors, tutors and the rest) would like to know how well the students have assimilated the study materials being taught. The analysis and assessment of the knowledge students have acquired over a semester are an integral part of the independent studies process at the most advanced universities worldwide. A formal test or exam during the semester would cause needless stress for students. To resolve this problem, the authors of this article have developed a Biometric and Intelligent Self-Assessment of Student Progress (BISASP) System. The obtained research results are comparable with the results from other similar studies. This article ends with two case studies to demonstrate practical operation of the BISASP System. The first case study analyses the interdependencies between microtremors, stress and student marks. The second case study compares the marks assigned to students during the e-self-assessment, prior to the e-test and during the e-test. The dependence, determined in the second case study, between the student marks scored for the real examination and the marks based on their self-evaluation is statistically significant (the significance >0.99%). The original contribution of this article, compared to the research results published earlier, is as follows: the BISASP System developed by the authors is superior to the traditional self-assessment systems due to the use of voice stress analysis and a special algorithm, which permits a more detailed analysis of the knowledge attained by a student.