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Modeliranje vpliva lastnosti študentov na uspešno reševanje algoritmično usmerjenih problemskih nalog
Ferlin, Sara (Author), Nančovska Šerbec, Irena (Mentor) More about this mentor... This link opens in a new window, Todorovski, Ljupčo (Co-mentor)

URLURL - Presentation file, Visit http://pefprints.pef.uni-lj.si/3879/ This link opens in a new window

Abstract
Diplomsko delo je motiviralo stereotipno prepričanje, da so nekateri posamezniki »bolj nadarjeni za programiranje«. Zanima nas, koliko je posamezniku prirojeno in pridobljeno v splošnem ali bolj natančno – ali je sposobnost reševanja problemov oziroma algoritmično usmerjenih problemskih nalog, ki je v literaturi navedena kot veščina, potrebna za uspešno učenje programiranja, prirojena ali pridobljena z učenjem. V ta namen v prve delu teoretičnega dela opišemo in primerjamo različna mnenja stroke. V drugem delu teoretičnega dela diplomske naloge se osredotočimo na rudarjenje podatkov, predvsem na metodo gradnje napovednega drevesa, ki ga kot napovedni model kasneje uporabimo v empiričnem delu. V empiričnem delu opišemo postopek pridobivanja podatkov preko pripravljenega dvodelnega vprašalnika, s katerim smo ocenili uspešnost posameznikov na testu reševanja algoritmično usmerjenih problemskih nalog ter pridobili demografske podatke o anketirancih ter podatke o njihovih lastnostih, ki bi po naši domnevi lahko vplivale na uspešnost posameznika pri reševanju algoritmično usmerjenih nalog. Opišemo tudi modeliranje podatkov s pomočjo metod podatkovnega rudarjenja in strojnega učenja ter povzamemo izsledke, ki nakazujejo, da obstaja povezava med določenimi lastnostmi posameznikov, kot so uspešnost na maturi iz matematike, izbira maturitetnih predmetov, pogostost reševanja logičnih ugank idr., in uspešnostjo na testu reševanja algoritmično usmerjenih problemskih nalog.

Language:Slovenian
Keywords:prirojene in pridobljene sposobnosti
Work type:Bachelor thesis/paper (mb11)
Tipology:2.11 - Undergraduate Thesis
Organization:PEF - Faculty of Education
Year:2016
COBISS.SI-ID:11213129 Link is opened in a new window
Views:381
Downloads:104
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Secondary language

Language:English
Title:Modeling the influence of student characteristics on successfull solving of algorithmically based exercises
Abstract:
The inspiration for this diploma thesis is a stereotype that some individuals are more talented to program than others. We investigate the innate and acquired origin of abilities in general and in a more specific domain - whether is the ability of solving algorithmically based exercises, stated in literature as a necessary skill for successful learning how to program, innate or acquired by learning. The first part of the theoretical part of diploma thesis is therefore a summary and comparison of read literature on the subject. In the second part of the theoretical part of this diploma thesis we focus on the field of data mining, especially on decision tree induction, being the model later used in the empirical part. In the empirical part of this diploma thesis we then describe the method of acquiring needed data through designing a two-part questionnaire, one part of which was used to evaluate the successfulness of individuals at solving algorithmically based exercises. The other part was used to acquire the data about student characteristics, which we believed could be linked to individuals’ success at solving algorithmically based exercises. We also describe the process of data modeling, with the use of machine learning and data mining methods, and then discuss the findings, which indicate the connection between certain characteristics of individuals (for example: success at mathematics matura exam, the selection of matura exam subjects, the frequency of solving logical puzzles) and the success at a algorithmically based exercises solving test.

Keywords:innate and acquired abilities

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