Influence Rate Evaluation by Students’ Opinion: University, Library, Courses and Professors: Case of Mongolian Universities
This paper describes a cooperative study of university lecturers with a focus on figuring out influence factors of students’ achievements in higher education. The evaluation survey is applied as the main method for research. Several lecturers (research team) who teach different courses in the univer...
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Veröffentlicht in: | Embedded Selforganising Systems 2023-09, Vol.10 (7), p.77-81 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | This paper describes a cooperative study of university lecturers with a focus on figuring out influence factors of students’ achievements in higher education. The evaluation survey is applied as the main method for research. Several lecturers (research team) who teach different courses in the university together developed influence factors in the form of survey questions, which are divided into four core groups: university, library, courses, and professors. The research team plans to collect as much data periodically from all universities in the country which is open to supporting this study. This paper showed the analyses of the first step of the study. 291 students from eight different universities voluntarily sent responses to an online survey.The collected data is processed by structure-oriented evaluation (SURE) model and by standard statistic function. The SURE evaluation score was calculated as 0.88 which we can read that all defined influence factors received evaluation scores from students with very high positive answers. The statistic maximum scores emphasized some factors that influence a lot to students’ achievement and students confirmed by their responses that some factors are very important for them. Further statistic ANOVA test was made for the case of the university group with 13 factors.For the ANOVA test, the null hypothesis. H0 – Null hypothesis stands for no difference between groups. No influence of study years on evaluation scores. By the ANOVA test, the null hypothesis isn’t proven. This concludes first step analyses as not significant statistically. Therefore, the researchteam needs to continue data collection and may apply some other statistical methods to compare the first results. |
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ISSN: | 1869-5213 1869-5213 |
DOI: | 10.14464/ess.v10i7.631 |