Open AccessAn Intelligent Computer System for Assessing Student Performance
Author(s) -
Wenzhuo Wu,
Anna Berestova,
Alisa Lobuteva,
Natalia Stroiteleva
Publication year - 2021
Publication title -
international journal of emerging technologies in learning/international journal: emerging technologies in learning
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.454
H-Index - 24
eISSN - 1868-8799
pISSN - 1863-0383
DOI - 10.3991/ijet.v16i02.18739
Subject(s) - formative assessment , summative assessment , test (biology) , online assessment , pearson product moment correlation coefficient , computer science , correlation coefficient , correlation , mathematics education , medical education , psychology , machine learning , medicine , statistics , mathematics , paleontology , geometry , biology
The purpose of the study is to identify and compare the influence of formative and summative assessment approaches based on an intelligent computer system that provides automatic feedback; the assessment is carried out in paper format, but obtaining feedback requires an appointment with a teacher. The study was conducted among 50 students in I.M. Sechenov First Moscow State Medical University (Russia) and Wuxi Institute of Technology (China). The assessment was carried out based on online tools and an intelligent learning system (ASP.NET web applications and MCQ tests). It was found that the average score of the formative test of students who passed an assessment test in the electronic format is higher than the score of those who passed the test in the classroom [t (165 = 5.334, p <0.05]. Pearson's correlation coefficient in the experimental (r2 = +0.329; p = 0.009) and control (r2 = +0.176; p = 0.076) groups confirmed a sig-nificant positive correlation. The solution can be integrated into the educational process as an additional student tool that will reduce the burden of teacher work-load and increase the assessment objectivity along with the overall performance of students.