Spodbujevano učenje diskretnih markovskih jeder

Strmšek, Manca

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Title:	Spodbujevano učenje diskretnih markovskih jeder
Authors:	ID Strmšek, Manca (Author) ID Bokal, Drago (Mentor) More about this mentor...
Files:	MAG_Strmsek_Manca_2022.pdf (2,03 MB) MD5: 2DB090FC6AC68D2629D428049218A3B2
Language:	Slovenian
Work type:	Master's thesis/paper
Typology:	2.09 - Master's Thesis
Organization:	FNM - Faculty of Natural Sciences and Mathematics
Abstract:	V magistrskemu delu predstavimo akademijo učenja logičnih operatorjev z markovskimi jedri, katero so rešili študentje predmeta matematično modeliranje. Ob reševanju z elementi formativnega spremljanja opazujemo, v katerem čustvenem stanju se nahajajo, saj želimo, da pri učenju doživijo zanos. V prvem delu podrobno predstavimo uvodne pojme preslikav, teorije mere, verjetnosti in markovskih jeder ter teorijo optimalnega izkustva učenja z njeno matematizacijo. Pojasnimo čustvena stanja, katera doživlja agent ob reševanju nalog in se nanašajo na njegove sposobnosti ter zanimanje. V drugem delu predstavimo pojem akademije in elemente formativnega spremljanja v visokošolskem izobraževanju. Pojasnimo teorijo logičnih operatorjev in predstavimo akademijo, katere naloge z rešitvami se nahajajo na koncu magistrskega dela. Opišemo študijo primera, kjer kot mentorji, z vnaprej pripravljenimi cilji formativnega spremljanja, vodimo študente, da doživijo optimalno izkušnjo učenja.
Keywords:	diskretne naključne spremenljivke, markovska jedra, učenje, optimalna izkušnja učenja, zanos, akademija, logični operatorji, mentorstvo, formativno spremljanje.
Place of publishing:	Maribor
Publisher:	[M. Strmšek]
Year of publishing:	2022
PID:	20.500.12556/DKUM-82289
UDC:	519.217:004.8:159.976(043.2)
COBISS.SI-ID:	119691267
Publication date in DKUM:	31.08.2022
Views:	810
Downloads:	110
Metadata:
Categories:	FNM
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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:	10.08.2022

Secondary language

Language:	English
Title:	Reinforcement learning of discrete markov kernels
Abstract:	In this thesis, we present the academy of learning Boolean logical operators with Markov kernels, which was solved by the students of the course Matematično modeliranje. During the academy solving, we observe them with elements of formative assessment due to determining their emotional states, because we want them to experience flow. In the first part, we represent the terms of maps, measurement theory, probability and Markov kernels along with the theory of optimal learning experience and its mathematization. We explain the emotional states of an agent who is performing tasks, which depend on his skill and challenge levels. In the second part, we represent the term of academy and elements of formative assessment in higher education. We explain the theory of Boolean logical operators and we present the academy, whose tasks and solutions are presented at the end of this thesis. We describe the case study, where we participate as mentors and lead students towards accomplishing their optimal learning experience.
Keywords:	discrete random variables, Markov kernels, learning, optimal learning experience, flow, academy, logical operators, mentoring, formative assessment.

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