Primjena metoda analize i rudarenja podataka u edukaciji

master's thesis

• Author: Tea Bašić
• Mentor: Saša Singer (mentor)
• Committee member: Saša Singer (predsjednik povjerenstva)
• Committee member: Goranka Nogo (član povjerenstva)
• Committee member: Goran Igaly (član povjerenstva)
• Committee member: Marko Vrdoljak (član povjerenstva)
• Granter: University of Zagreb; Faculty of Science; (Department of Mathematics); Zagreb
• Defense date and country: 2020-07-21, Croatia
• Scientific / art field, discipline and subdiscipline: NATURAL SCIENCES; Mathematics

Abstract

Ovaj diplomski rad ima dva dijela. U prvom dijelu, opisano je što je znanost o podacima (eng. Data Science), gdje se koristi i zašto, s posebnim naglaskom na tzv. dubinsku analizu podataka. Također, detaljno je objašnjeno korištenje programskih jezika Python i R za tu svrhu, te analizirano koje su prednosti, nedostaci i razlike u korištenju jednog ili drugog. Drugi dio rada posvećen je korištenju metoda analize i rudarenja podataka u edukaciji. Konkretno, na koji način se ove metode mogu koristiti za poboljšanje nastave (posebno, nastave informatike) te prijedlog na koji način se “Data Science” može ukomponirati u trenutni kurikulum iz informatike i matematike.

Abstract (english)

This thesis has two parts. In the first part, it is described what Data science is, where it is used and why, with special emphasis on the so-called in-depth data analysis. Also, the use of programming languages Python and R is explained, and the advantages, disadvantages and differences in using one or the other are analyzed. The second part of the paper is dedicated to the use of data analysis and mining methods in education. In particular, how can these methods be used to improve teaching (in particular, teaching computer science) and a proposal on how "Data Science" can be incorporated into the current curriculum in computer science and mathematics.

• Keywords: znanost o podacima; dubinska analiza podataka; programski jezici Python i R; rudarenje podataka u edukaciji
• Keywords (english): Data science; in-depth data analysis; programming languages Python and R; mining methods in education
• Language: croatian
• URN:NBN: urn:nbn:hr:217:081259
• Study programme: Title: Mathematics and Computer Science Education; specializations in: Mathematics and Computer Science Education; Course: Mathematics and Computer Science Education; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra edukacije matematike i informatike (magistar/magistra edukacije matematike i informatike)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2020-11-12 16:21:01