The relations between Czech undergraduates' motivation and emotion in self-regulated learning, learning engagement, and academic success in blended course designs: Consistency between theory-driven and data-driven approaches

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18440%2F22%3A50019818" target="_blank" >RIV/62690094:18440/22:50019818 - isvavai.cz</a>

Alternative codes found

RIV/70883521:28150/22:63556758

Result on the web

<a href="https://www.frontiersin.org/articles/10.3389/fpsyg.2022.1001202/full" target="_blank" >https://www.frontiersin.org/articles/10.3389/fpsyg.2022.1001202/full</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3389/fpsyg.2022.1001202" target="_blank" >10.3389/fpsyg.2022.1001202</a>

Result language

angličtina

Original language name

The relations between Czech undergraduates' motivation and emotion in self-regulated learning, learning engagement, and academic success in blended course designs: Consistency between theory-driven and data-driven approaches

Original language description

Combining theory-driven and data-driven approaches, this study used both self-reported and observational measures to examine: (1) the joint contributions of students’ self-reported undergraduates’ motivation and emotion in their self-regulated learning, their observed online learning interactions, and their academic success in blended course designs; and (2) the extent to which the self-reported and observational measures were consistent with each other. The participants in the study were 54 social sciences undergraduates in the Czech Republic. The participants’ self-reported self-efficacy, intrinsic goals, and anxiety were assessed using a Czech version of three scales from the Motivated Strategies for Learning Questionnaire. Their online engagement was represented by students’ observed frequency of interactions with the six online learning activities recorded in the learning management system. The results of a hierarchical regression analysis showed that the self-reported and observational measures together could explain 71% of variance in academic success, significantly improving explanatory power over using self-reported measures alone. Departing from the theory-driven approach, students were clustered as better and poorer self-regulated learners by their self-reports, and one-way ANOVAs showed that better self-regulated learners had significantly more frequent online interactions with four out of six online learning activities and better final exam results. Departing from the data-driven approach, students were clustered as higher and lower online-engaged learners by the observed frequency of their interaction with online learning activities. One-way ANOVAs showed that higher online-engaged learners also reported having higher self-efficacy and lower anxiety. Furthermore, the strong association between the students’ profiles in both self-reported measures and observational measures in cross-tabulation analyses showed that the majority of better self-regulated learners by self-reporting also had higher online engagement by observation, whereas the majority of poorer self-regulated learners by self-reporting were lower online-engaged learners, demonstrating consistency between theory-driven and data-driven approaches.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

50103 - Cognitive sciences

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2022

Confidentiality

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

Name of the periodical

Frontiers in psychology

ISSN

1664-1078

e-ISSN

1664-1078

Volume of the periodical

13

Issue of the periodical within the volume

18.11.2022

Country of publishing house

CH - SWITZERLAND

Number of pages

13

Pages from-to

"Article Number: 1001202"

UT code for WoS article

000912171700001

EID of the result in the Scopus database

—