A COMPARISON OF DIFFERENT APPROACHES USED IN THE LEARNING PROCESS BY MEANS OF THE MOODLE DATA ANALYSIS
The result's identifiers
Result code in 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>
Result on the web
<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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Alternative languages
Result language
angličtina
Original language name
A COMPARISON OF DIFFERENT APPROACHES USED IN THE LEARNING PROCESS BY MEANS OF THE MOODLE DATA ANALYSIS
Original language description
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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
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
Number of pages
12
Pages from-to
521-532
Publisher name
Wolters Kluwer
Place of publication
Prague
Event location
Štúrovo
Event date
Sep 21, 2020
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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