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Title:Adaptivno postavljanje vprašanj na elektronskih testih : diplomsko delo
Authors:ID Donko, Žiga (Author)
ID Ojsteršek, Milan (Mentor) More about this mentor... New window
ID Majninger, Sandi (Comentor)
Files:.pdf UN_Donko_Ziga_2019.pdf (1,40 MB)
MD5: 8A159A78915E4304111529B1909C3D35
PID: 20.500.12556/dkum/84b8d212-ffd9-4b5d-8435-f628db496b67
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V diplomskem delu smo raziskali področje adaptivnega postavljanja vprašanj na elektronskih testih. Slednje temelji na teoriji odgovora na postavko. Gre za matematični model, ki temelji na statističnih metodah. Sistemi adaptivnega postavljanja vprašanj imajo pet temeljnih korakov, ki omogočajo različne pristope. Posamezna vprašanja smo modelirali kot postavke ter raziskali različne pristope posameznih korakov sistema za adaptivno postavljanje vprašanj. Implementirali smo prototip, uporabili nekatere opisane pristope ter primerjali posamezne pristope med seboj.
Keywords:adaptivno postavljanje vprašanj, elektronski testi, elektronska učna okolja, avtomatsko ocenjevanje, teorija odgovora na postavko
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[Ž. Donko]
Year of publishing:2019
Number of pages:VI, 35 str.
PID:20.500.12556/DKUM-74967 New window
UDC:004.777(043.2)
COBISS.SI-ID:22910742 New window
NUK URN:URN:SI:UM:DK:AZ8WB8JS
Publication date in DKUM:22.11.2019
Views:1005
Downloads:63
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:15.09.2019

Secondary language

Language:English
Title:Adaptive generation of questions for electronic tests
Abstract:In this thesis we researched the field of computerized adaptive testing. It is based on the item response theory. That is a mathematical model based on statistical methods. Computerized adaptive testing systems have five fundamental steps, which permit different approaches which we have analysed and compared. We have modelled individual questions as items and researched different approaches to implement a computerized adaptive testing system. With the help of acquired knowledge, we have implemented a prototype which uses some of the described approaches.
Keywords:adaptive generation of questions, e-exams, e-learning platforms, automatic grading, item response theory


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