Metode podatkovne analitike za nadzor kakovosti študijev : delo diplomskega seminarja

Gaberšček, Maj (author), Orbanić, Alen (mentor)

Metode podatkovne analitike pri nadzoru kakovosti študija si lahko pogledamo skozi analize ocen (po predmetih, po času), analize pretočnosti (skozi predmete ter skozi letnike) in analize prepisov študentov med programi. Skupaj te analize tvorijo celosten in kompleksen pregled skoraj vseh aspektov študija. S pomočjo grafov in vizualizacij, diagramov in tabel pri vsaki analizi na hiter in preprost način lahko ugotavljamo dobre in slabe lastnosti poteka študija, prednosti in slabosti. V oko takoj padejo posebnosti, ki morda samo iz golih tabel podatkov ne izstopajo. Celotna metodologija podatkovne analize, opisana v tej diplomski nalogi, lahko olajša delo in prihrani precej časa tistim, ki se s takimi pregledi študijev tudi profesionalno ukvarjajo. Vse analize in metode, ki nastopajo v tej diplomski nalogi, sem tudi sprogramiral v programskem jeziku R in program hranil na privatnem repozitoriju. Če v program vstavimo dejanske podatke o nekem študiju, vrne grafe, diagrame ter tabele, opisane v tej nalogi.

• Language: Slovenian
• Keywords: evalvacija študijev, analiza študijev, podatkovna analitika
• Work type: Final seminar paper
• Typology: 2.11 - Undergraduate Thesis
• Organization: FMF - Faculty of Mathematics and Physics
• Year: 2021
• PID: 20.500.12556/RUL-131036
• UDC: 519.2
• COBISS.SI-ID: 77677315
• Publication date in RUL: 22.09.2021

Secondary language

• Language: English
• Title: Data analysis methods for study program quality control

Abstract

Data analysis in quality control of university level studies could be viewed through the analysis of grades (by course, by time), flow analysis (through subjects and through years) and analysis of student transfers between programs. Together, these analyses form a comprehensive and complex overview of almost all aspects of the studies. Graphs, visualizations, diagrams and tables help us to identify the advantages and disadvantages of each program or course. Features that may not be identified from the raw data tables immediately stand out. The entire methodology of data analysis described in this thesis can facilitate the work of and save a lot of time for those who are professionally engaged in such study program reviews. All the analyses and methods that appear in this diploma thesis were also implemented in the R programming language and the whole code is stored in a private repository. If we insert actual data about a study program into implemented procedures, they return graphs, diagrams, and tables described in this thesis.

• Keywords: evaluation of studies, analysis of studies, data analysis