MEASURING SELF-REGULATED LEARNING AND ONLINE LEARNING EVENTS TO PREDICT STUDENT ACADEMIC PERFORMANCE
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28150%2F18%3A63520250" target="_blank" >RIV/70883521:28150/18:63520250 - isvavai.cz</a>
Result on the web
<a href="https://www.phil.muni.cz/journals/index.php/studia-paedagogica/article/view/1870" target="_blank" >https://www.phil.muni.cz/journals/index.php/studia-paedagogica/article/view/1870</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5817/SP2018-4-5" target="_blank" >10.5817/SP2018-4-5</a>
Alternative languages
Result language
angličtina
Original language name
MEASURING SELF-REGULATED LEARNING AND ONLINE LEARNING EVENTS TO PREDICT STUDENT ACADEMIC PERFORMANCE
Original language description
The aim of this study is to identify whether the combination of self-reported data that measure self-regulated learning (SRL) and computer-assisted data that capture student engagement with an online learning environment could be used to predict student academic achievement. Personally engaged study strategies focused on deep-level learning, the process of taking control, and the evaluation of students’ own learning characterize SRL. Diverse theories on how students benefit from SRL underline its positive impact on student academic outcomes. Similarly, there is no doubt that the future trend in education leans towards the integration of technolog y into teaching in order to exploit its full potential. To benefit from both approaches, a combination of self-reported data and detailed online learning events obtained from an online learning environment were investigated in relation to their ability to predict student academic achievement. A case study of 54 university students enrolled in a blended-learning course showed that of the tested SRL variables and observed learning activities, student interaction with auxiliary materials that were part of the course helped to predict academic outcomes. Despite the relatively low ability of the model to explain why some students were able to become successful learners, the presented results highlight the importance of analysing online learning events in computer-assisted teaching and learning.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
50301 - Education, general; including training, pedagogy, didactics [and education systems]
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Studia Paedagogica
ISSN
1803-7437
e-ISSN
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Volume of the periodical
23
Issue of the periodical within the volume
4
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
28
Pages from-to
"91–118"
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85061615231