magistrsko delo
Tajda Štrukelj (Author), Jože Rugelj (Mentor)

Abstract

Učne analitike so mlado področje računalniško podprtega učenja, ki bi lahko v prihodnosti pomembno vplivalo na izobraževanje. Gre za skupke analitičnih orodij, ki merijo, zbirajo, analizirajo in poročajo o učenčevih podatkih, da bi lahko bolje razumeli ter optimizirali učenje in okolja, v katerih se to učenje pojavlja. Dandanes se mnoge aktivnosti, povezane z učenjem, selijo na splet. Učitelji jih umeščajo v tako imenovana virtualna učna okolja, kjer se nato s sodelovanjem učencev generira množica podatkov. Ti podatki spadajo med tako imenovane »velike podatke« in imajo ob pravilni uporabi potencial, ki učiteljem in drugim izobraževalnim delavcem omogoča, da bolje razumejo proces učenja in ga tako lažje optimizirajo in prilagajajo učencem. Pri interpretaciji teh podatkov zato uporabljamo učne analitike, s katerimi se ustrezni podatki izberejo in obdelajo, kot rezultat pa pridobimo uporabne informacije, s katerimi lahko dosežemo osnovni cilj, to je izboljšanje poučevanja učiteljev in učnih dosežkov učencev. Področje učnih analitik je še v začetnih fazah razvoja in čeprav se rezultati uporabe programskih orodij za učne analitike že kažejo v današnjem izobraževanju, gre še vedno za relativno slabo razširjen pojem med učitelji in drugimi izobraževalnimi delavci. V magistrskem delu zato predstavljamo način delovanja učnih analitik, pri čemer predstavimo zgodovino učnih analitik in z njimi povezane pojme, opišemo referenčni model za učne analitike ter naštejemo njihove faze in komponente. Ena izmed značilnosti učnih analitik je tudi ta, da jih velikokrat povežemo z močnimi in kompleksnimi programskimi orodji, ki pa so, vsaj zaenkrat, draga in tako večini šol in učiteljem nedosegljiva. V okviru magistrskega dela zato predstavljamo lastno programsko orodje za učne analitike, POUK, ki smo ga izdelali s pomočjo orodja Microsoft Excel, programskega jezika Visual Basic for Applications in virtualnega učnega okolja Moodle.

Keywords

analitična obdelava podatkov;podatkovno rudarjenje;računalniško podprto učenje;virtualna učna okolja;

Data

Language: Slovenian
Year of publishing:
Typology: 2.09 - Master's Thesis
Organization: UL PEF - Faculty of Education
Publisher: [T. Štrukelj]
UDC: 004:37(043.2)
COBISS: 10747721 Link will open in a new window
Views: 1519
Downloads: 175
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Other data

Secondary language: English
Secondary title: Learning analytics in education
Secondary abstract: Learning analytics is a young field in computer supported learning, which could have a great impact on education in the future. It is a set of analytical tools which measure, collect, analyze and report about students' data for the purpose of understanding and optimizing students' learning and environments in which this learning occurs. Today, more and more learning related activities are placed on the web. Teachers are creating virtual learning environments (VLE), in which a great set of data about students is created. This data falls into category of »big data«. If used correctly, this data has great potential for teachers and other educational workers to better understand the process of learning and thus optimize it better and adapt it for their students. To interpret the data from VLEs we use learning analytics. They allow us to choose, collect and process the data, which is the used to extract useful information, bringing us closer to our main goal of improving teachers' way of teaching and students' learning outcomes. Learning analytics are still in the early phases of development. Although there are already some good results, which indicate that using tools for learning analytics can really improve learning outcomes, learning analytics are still relatively unknown among teachers and other educational workers. This Master’s thesis consequently introduces learning analytics and presents their history and connected concepts. We also describe a reference model for learning analytics and we discuss their phases and components in detail. One of the main features of learning analytics is their connection with powerful and complex programming tools, which are, at least for now, expensive and therefore unavailable for most schools and teachers. In this Master’s thesis we introduce our own programming tool for learning analytics, POUK. This tool was built with Microsoft Excel and programming language Visual Basic for Applications and is processing the data from virtual learning environment Moodle.
Secondary keywords: education;computer science;vzgoja in izobraževanje;računalništvo;
File type: application/pdf
Type (COBISS): Master's thesis/paper
Thesis comment: Univ. v Ljubljani, Pedagoška fak., Matematika in računalništvo
Pages: 121 str.
ID: 9057685