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Title:Blend.FL na Fakulteti za logistiko : diplomsko delo
Authors:ID Trafela, Sabrina (Author)
ID Kramberger, Tomaž (Mentor) More about this mentor... New window
Files:.pdf UNI_Trafela_Sabrina_i2010.pdf (1,10 MB)
MD5: FB764513EB1AFAA14B0ED7137EE60A4D
PID: 20.500.12556/dkum/4ad7053b-d073-4da3-b29f-565384c1cdfb
 
Language:Slovenian
Work type:Undergraduate thesis
Organization:FL - Faculty of Logistic
Abstract:Vseživljensko učenje je sodoben trend, ki se je v različnih oblikah poskušal uveljaviti že v zadnjih dvesto letih. Učni proces na FL UM poteka kot kombinacija avditornih vaj in predavanj ter študija s pomočjo tehnologije preko virtualne fakultete. Le-ta nudi študentu vse potrebne informacije za uspešen študij. Drugi del t.i. virtualnega učnega procesa so e-gradiva, ki so objavljena na spletu, dostop do njih pa imajo študentje FL z vpisom v portal s svojim uporabniškim imenom in geslom. V praktičnem delu naloge smo potrdili, da je sprotno delo študentov z e-gradivi nujen pogoj za njihovo uspešnost pri opravljanju predpisanih izpitnih obveznosti. Pripravili smo model, ki nam omogoča ločiti uspešne študente od neuspešnih na osnovi njihovega samostojnega dela v spletni učilnici. Model najprej napove višino končne ocene pri predmetu KML na osnovi povprečne ocene opravljenih kvizov. Na osnovi napovedi pa le-te klasificira v pozitivni in negativni razred. Model je zgrajen s konzervativnim pristopom, saj nobenega primera ne napove preoptimistično, to je v nobenem primeru negativne ocene, le-te ne napove kot pozitivno vrednost. Točnost klasifikacije je zelo visoka, saj napačno razvrsti manj kot 10% primerov.
Keywords:ežgradiva, napovedni model, linearna regresija, hibridno učenje
Place of publishing:Celje
Publisher:[S. Trafela]
Year of publishing:2010
PID:20.500.12556/DKUM-16902 New window
UDC:378:004(043.2)
COBISS.SI-ID:512256061 New window
NUK URN:URN:SI:UM:DK:PPZBFRK8
Publication date in DKUM:30.11.2010
Views:8436
Downloads:845
Metadata:XML DC-XML DC-RDF
Categories:FL
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Secondary language

Language:English
Title:Blend.FL at Faculty of logistics
Abstract:Lifelong learning is a modern trend, which was held in various forms in last two hundred years. Learning process at FL UM is a combination of traditional learning process, combined with e-learning system. In this way, student can get all necessary data. The other part of FL UM learning process is a web page with e-materials, which are placed online for the students and they can reach them with their username and a password. In the practical part we have confirmed that the ongoing work of students with e-materials is a necessary condition for their success in carrying out the prescribed exams. We have created a model that allows us to separate the successful from the unsuccessful students based on their individual work in the online classroom. The model first predicts the amount of the final evaluation at the course KML on the average estimate of quizzes. Based on the projections they classify the positive and negative class. The model is built with the conservative approach, because does not predict any case too optimistic, this means in any case of a negative assessment, they do not predict a positive value. Classification accuracy is very high, because it classifies wrong only 10% of the cases.
Keywords:prediction model, linear regression, hybrid learning


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