Use of Artificial Intelligence in Educational Research in the Context of Other Solution Methods

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17450%2F25%3AA2603BL3" target="_blank" >RIV/61988987:17450/25:A2603BL3 - isvavai.cz</a>

Výsledek na webu

<a href="https://sklep.uniwersytetradom.pl/pl/c/Ksiazki/" target="_blank" >https://sklep.uniwersytetradom.pl/pl/c/Ksiazki/</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Use of Artificial Intelligence in Educational Research in the Context of Other Solution Methods

Popis výsledku v původním jazyce

In educational research and other scientific disciplines, we often encounter the need to analyze relationships between different variables. For this purpose, statistical methods such as correlation analysis and regression analysis are used. Correlation helps determine whether there is a relationship between two variables and how strong that relationship is. Regression, on the other hand, is used to predict the value of one variable based on the value of another variable. In this article, we will focus on demonstrating these methods using a specific example, analyzing the relationship between students' scores in a pre-test and a post-test. The analysis will be conducted using PAST and Microsoft Excel, which are commonly available tools for statistical data processing. The obtained results will then be compared with predictions generated by artificial intelligence, allowing us to evaluate the accuracy and advantages of traditional statistical methods compared to modern machine learning approaches.

Název v anglickém jazyce

Use of Artificial Intelligence in Educational Research in the Context of Other Solution Methods

Popis výsledku anglicky

In educational research and other scientific disciplines, we often encounter the need to analyze relationships between different variables. For this purpose, statistical methods such as correlation analysis and regression analysis are used. Correlation helps determine whether there is a relationship between two variables and how strong that relationship is. Regression, on the other hand, is used to predict the value of one variable based on the value of another variable. In this article, we will focus on demonstrating these methods using a specific example, analyzing the relationship between students' scores in a pre-test and a post-test. The analysis will be conducted using PAST and Microsoft Excel, which are commonly available tools for statistical data processing. The obtained results will then be compared with predictions generated by artificial intelligence, allowing us to evaluate the accuracy and advantages of traditional statistical methods compared to modern machine learning approaches.

Druh

C - Kapitola v odborné knize

CEP obor

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OECD FORD obor

50301 - Education, general; including training, pedagogy, didactics [and education systems]

Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název knihy nebo sborníku

21st Century Computer Science - Challlenges and Dilemmas

ISBN

978-83-68172-25-6

Počet stran výsledku

12

Strana od-do

87-98

Počet stran knihy

155

Název nakladatele

Uniwersytet Radomski

Místo vydání

Radom

Kód UT WoS kapitoly

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