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Application of statistical methods for curricula quality analysis

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Category: Information technologies, systems analysis and administration

Last Updated on 19 March 2014

Published on 26 February 2013

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Authors:

S.А. Us, Cand. Sci. (Phys.-Math.), Associate Professor, StateHigher Educational Institution “National Mining University”, Professor of the Department of System Analysis and Control, Dnipropetrovsk, Ukraine

L.A. Zakashvili, State Higher Educational Institution “National Mining University”, Bachelor, Dnipropetrovsk, Ukraine

Abstract:

Purpose. A balanced curriculum is the basis of high-quality training of specialists. The analysis of the curriculum’s plan includes the verification of compliance of the educational and professional program and structure and logical scheme of the specialists training, and evaluation of the uniformity of the distribution of workload during the whole period of the study and the quality of assimilation of individual disciplines. The purpose of this work is the study of the possibility to apply the statistical methods for analyzing the curriculum.

Methodology. The proposed approach includes the analysis of the uniformity of distribution of workload during the whole period of study and the analysis of the complexity of individual disciplines. The results of implementation of curriculum are considered as the results of the test’s implementation where every task is the separate discipline or the semester. Pass or fail the task is estimated based on the exam grade of the discipline or the average grade for the semester and is written in binary signification. The basic data transformed in such way is investigated by the methods of statistical analysis and by the results of this analysis the quality of curriculum is assessed, and the disciplines on which the special attention has to be paid are defined.

Findings. The proposed approach was used for analyzing the bachelors’ curriculum on special subject 6.040303 System Analysis. The basic data were the academic results of two students’ groups. By the results of the analysis we have defined which semesters and disciplines are the hardest and require additional analysis.

Originality. We have proposed the method for analyzing the curriculum which lets us to define the uniformity of distribution of workload during the whole period of study, define the weakness of the curriculum and the disciplines which require additional analysis.

Practical value. The proposed approach can be applied for analyzing the curricula of specialists of different profiles and contribute to the quality of specialists’ education.

References:

1.     Наказ № 161 від 2.06.93 р. Про затвердження положення про органiзацiю навчального процесу у вищих навчальних закладах [Електронний ресурс] / режим доступу:http://zakon2.rada.gov.ua/laws/show/ z0173-93

“Pro zatverdzhennia polozhennia pro organizatsiu navchalnogo protsesu u vyshchykh navchalnykh zakladakh” [About the Approval of the Educational Process Regulations in Higher Educational Institutions], Order no.161, dated June 2, 1993.

2.     Казиєв В.М. Введение в практическое тестирование: учебный курс [Електронний ресурс] / В.М. Казиев. – Режим доступу до курсу http://www.intuit.ru/ department/informatics/practest/

Kaziyev, V.M. Vvedeniye v prakticheskoye testirovaniye: uchebniy kurs [The Introduction to Practical Testing: The Training Course], available at: http://www.intuit.ru/department/informatics/practest/

3.     Гмурман В.Е. Теория вероятностей и математическая статистика [Текст] / В.Е. Гмурман. – М.: Высшая школа, 2002. – 479 с.

Gmurman, V.Ye. (2002), Teoriya veroyatnostey i matematicheskaya statistika [Probability Theory and Mathematical Statistics], Vyshaya shkola, Moscow, Russia.

4.     Елисеева И.И. Теория статистики с основами теории вероятностей [Текст] / И.И. Елисеева. – М.: ЮНИТИ-ДАНА, 2001. – 446 с.

Yeliseyeva, I.I. (2001), Teoriya statistiki s osnovami teorii veroyatnostey [Theory of Statistics with Introduction to Probability Theory], YuNITI-DANA, Moscow, Russia.

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