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2016 | 129 | 5 | 1071-1076
Article title

Key Courses of Academic Curriculum Uncovered by Data Mining of Students' Grades

Content
Title variants
Languages of publication
EN
Abstracts
EN
Learning is a complex cognitive process that depends not only on an individual capability of knowledge absorption but it can be also influenced by various group interactions and by the structure of an academic curriculum. We have applied methods of statistical analyses and data mining (principal component analysis and maximal spanning tree) for anonymized students' scores at Faculty of Physics, Warsaw University of Technology. A slight negative linear correlation exists between mean and variance of course grades, i.e. courses with higher mean scores tend to possess a lower scores variance. There are courses playing a central role, e.g. their scores are highly correlated to other scores and they are in the centre of corresponding maximal spanning trees. Other courses contribute significantly to students' score variance as well to the first principal component and they are responsible for differentiation of students' scores. Correlations of the first principal component to courses' mean scores and scores variance suggest that this component can be used for assigning ECTS points to a given course. The analysis is independent of declared curricula of considered courses. The proposed methodology is universal and can be applied for analysis of students' scores and academic curriculum at any faculty.
Keywords
EN
Publisher

Year
Volume
129
Issue
5
Pages
1071-1076
Physical description
Dates
published
2016-05
Contributors
author
  • Faculty of Physics, Center of Excellence for Complex Systems Research, Warsaw University of Technology, Koszykowa 75, PL-00662 Warsaw, Poland
  • Faculty of Physics, Center of Excellence for Complex Systems Research, Warsaw University of Technology, Koszykowa 75, PL-00662 Warsaw, Poland
author
  • Faculty of Physics, Center of Excellence for Complex Systems Research, Warsaw University of Technology, Koszykowa 75, PL-00662 Warsaw, Poland
  • ITMO University, 19, Kronverkskiy av., 197101 Saint Petersburg, Russia
References
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Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.bwnjournal-article-appv129n532kz
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