Discovering the Learning Gradient of Students’ Preferences for Learning Environment
The aim of this study was to examine the effects of online learning self-regulation on learning outcomes during the COVID-19 pandemic lockdown among university college students. Quantitative k-means cluster analysis was used to examine the relationship among students in three different clusters base...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-10-01
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| Series: | Journal of Intelligence |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-3200/11/11/206 |
| _version_ | 1797458760549007360 |
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| author | Carsten Kronborg Bak Simon Schulin Jeanne Krammer |
| author_facet | Carsten Kronborg Bak Simon Schulin Jeanne Krammer |
| author_sort | Carsten Kronborg Bak |
| collection | DOAJ |
| description | The aim of this study was to examine the effects of online learning self-regulation on learning outcomes during the COVID-19 pandemic lockdown among university college students. Quantitative k-means cluster analysis was used to examine the relationship among students in three different clusters based on their preferences toward online learning. The results indicated that online learning self-regulation had a significant positive effect on learning outcomes due to the shift to online learning. Thus, we identified a “learning gradient” among students, showing that cluster 1 students (preferences for 100% online) have the most positive preferences toward online teaching and the highest degree of self-regulation and learning outcome, cluster 2 students (moderate preferences for both physical and online teaching) are mixed (both positive and negative experiences) and moderate self-regulation and learning outcomes while cluster 3 students (preferences for physical classroom teaching) have the most negative preferences and the lowest self-regulation and learning outcome. The results from this study show that students’ self-regulated learning strategies during online teaching environments are important for their learning outcomes and that cluster 1 and 2 students especially profited from the more flexible online learning environment with organized and deep learning approaches. Cluster 3 students need more support from their educators to foster their self-regulation skills to enhance their learning outcomes in online teaching environments. |
| first_indexed | 2024-03-09T16:42:47Z |
| format | Article |
| id | doaj.art-2e19e7e56a3e4e6d9ca4da5c9bb3fb6a |
| institution | Directory Open Access Journal |
| issn | 2079-3200 |
| language | English |
| last_indexed | 2024-03-09T16:42:47Z |
| publishDate | 2023-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Intelligence |
| spelling | doaj.art-2e19e7e56a3e4e6d9ca4da5c9bb3fb6a2023-11-24T14:50:08ZengMDPI AGJournal of Intelligence2079-32002023-10-01111120610.3390/jintelligence11110206Discovering the Learning Gradient of Students’ Preferences for Learning EnvironmentCarsten Kronborg Bak0Simon Schulin1Jeanne Krammer2Department of Social Work, University College of Southern Denmark, 6700 Degnevej, DenmarkDepartment of Social Work, University College of Southern Denmark, 6700 Degnevej, DenmarkDepartment of Social Work, University College of Southern Denmark, 6700 Degnevej, DenmarkThe aim of this study was to examine the effects of online learning self-regulation on learning outcomes during the COVID-19 pandemic lockdown among university college students. Quantitative k-means cluster analysis was used to examine the relationship among students in three different clusters based on their preferences toward online learning. The results indicated that online learning self-regulation had a significant positive effect on learning outcomes due to the shift to online learning. Thus, we identified a “learning gradient” among students, showing that cluster 1 students (preferences for 100% online) have the most positive preferences toward online teaching and the highest degree of self-regulation and learning outcome, cluster 2 students (moderate preferences for both physical and online teaching) are mixed (both positive and negative experiences) and moderate self-regulation and learning outcomes while cluster 3 students (preferences for physical classroom teaching) have the most negative preferences and the lowest self-regulation and learning outcome. The results from this study show that students’ self-regulated learning strategies during online teaching environments are important for their learning outcomes and that cluster 1 and 2 students especially profited from the more flexible online learning environment with organized and deep learning approaches. Cluster 3 students need more support from their educators to foster their self-regulation skills to enhance their learning outcomes in online teaching environments.https://www.mdpi.com/2079-3200/11/11/206online teachinglearning approachesself-regulationmeta cognitivecluster analysislearning gradient |
| spellingShingle | Carsten Kronborg Bak Simon Schulin Jeanne Krammer Discovering the Learning Gradient of Students’ Preferences for Learning Environment Journal of Intelligence online teaching learning approaches self-regulation meta cognitive cluster analysis learning gradient |
| title | Discovering the Learning Gradient of Students’ Preferences for Learning Environment |
| title_full | Discovering the Learning Gradient of Students’ Preferences for Learning Environment |
| title_fullStr | Discovering the Learning Gradient of Students’ Preferences for Learning Environment |
| title_full_unstemmed | Discovering the Learning Gradient of Students’ Preferences for Learning Environment |
| title_short | Discovering the Learning Gradient of Students’ Preferences for Learning Environment |
| title_sort | discovering the learning gradient of students preferences for learning environment |
| topic | online teaching learning approaches self-regulation meta cognitive cluster analysis learning gradient |
| url | https://www.mdpi.com/2079-3200/11/11/206 |
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