A COMPARISON OF DIFFERENT APPROACHES USED IN THE LEARNING PROCESS BY MEANS OF THE MOODLE DATA ANALYSIS

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23510%2F20%3A43959285" target="_blank" >RIV/49777513:23510/20:43959285 - isvavai.cz</a>

Výsledek na webu

<a href="http://hdl.handle.net/11025/42529" target="_blank" >http://hdl.handle.net/11025/42529</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

A COMPARISON OF DIFFERENT APPROACHES USED IN THE LEARNING PROCESS BY MEANS OF THE MOODLE DATA ANALYSIS

Popis výsledku v původním jazyce

The contribution deals with the application of data mining methods in the log data of the Moodle learning management system. In the first step the attention is paid to the pre-processing of data cleaning, transformation, and aggregation. This pre-processing of data preparation focuses on logs that describe the students’ assignments and quiz activities in detail. The selected activities do not belong to the evaluation quizzes, but these quizzes and assignments are constructed as training activities. The developed automatic generator of parameterized tasks allows to assemble such quizzes with unique assignments for each student in the course. The used data mining methods analyse the relationship between students’ activities during the preparation for the final exam quiz and the final exam grade. The data of the courses with optional exercises are compared with the data of the courses with obligatory exercises. Based on these data the activities and success rate are analysed. The activities of both types of courses are compared and then the dependency between the activities and success rate is studied. Students with optional and obligatory exercises do not have any statistically significant different results. The data in the group with optional exercises show a significant difference in success between the volunteering students and the students without any activity. The tests confirm the dependency between the activity indicators and the results of the final exercise. On the other hand, these activities had no such effect on the outcome of the final exam.

Název v anglickém jazyce

A COMPARISON OF DIFFERENT APPROACHES USED IN THE LEARNING PROCESS BY MEANS OF THE MOODLE DATA ANALYSIS

Popis výsledku anglicky

The contribution deals with the application of data mining methods in the log data of the Moodle learning management system. In the first step the attention is paid to the pre-processing of data cleaning, transformation, and aggregation. This pre-processing of data preparation focuses on logs that describe the students’ assignments and quiz activities in detail. The selected activities do not belong to the evaluation quizzes, but these quizzes and assignments are constructed as training activities. The developed automatic generator of parameterized tasks allows to assemble such quizzes with unique assignments for each student in the course. The used data mining methods analyse the relationship between students’ activities during the preparation for the final exam quiz and the final exam grade. The data of the courses with optional exercises are compared with the data of the courses with obligatory exercises. Based on these data the activities and success rate are analysed. The activities of both types of courses are compared and then the dependency between the activities and success rate is studied. Students with optional and obligatory exercises do not have any statistically significant different results. The data in the group with optional exercises show a significant difference in success between the volunteering students and the students without any activity. The tests confirm the dependency between the activity indicators and the results of the final exercise. On the other hand, these activities had no such effect on the outcome of the final exam.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2020

Kód důvěrnosti údajů

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

Název statě ve sborníku

DIVAI 2020 - 13th International Scientific Conference on Distance Learning in Applied Informatics

ISBN

978-80-7598-841-6

ISSN

2464-7470

e-ISSN

2464-7489

Počet stran výsledku

12

Strana od-do

521-532

Název nakladatele

Wolters Kluwer

Místo vydání

Prague

Místo konání akce

Štúrovo

Datum konání akce

21. 9. 2020

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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