Learning Approaches and Coping with Academic Stress for Sustainability Teaching: Connections through Canonical Correspondence Analysis
| Autor: | María-Carmen Patino-Alonso, Purificación Galindo-Villardón, Ana-Belén Sánchez-García, Zaira-Jazmín Zárate-Santana |
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| Rok vydání: | 2021 |
| Předmět: |
Coping (psychology)
sustainability in higher education Process (engineering) lcsh:TJ807-830 education Geography Planning and Development lcsh:Renewable energy sources Context (language use) 010501 environmental sciences Management Monitoring Policy and Law coping with academic stress 01 natural sciences canonical correspondence analysis learning approaches Canonical correspondence analysis Stress (linguistics) ComputingMilieux_COMPUTERSANDEDUCATION Mathematics education lcsh:Environmental sciences 0105 earth and related environmental sciences lcsh:GE1-350 Renewable Energy Sustainability and the Environment business.industry lcsh:Environmental effects of industries and plants Deep learning 05 social sciences 050301 education lcsh:TD194-195 gender differences Sustainability Artificial intelligence business Psychology 0503 education |
| Zdroj: | Sustainability Volume 13 Issue 2 Sustainability, Vol 13, Iss 852, p 852 (2021) |
| ISSN: | 2071-1050 |
| DOI: | 10.3390/su13020852 |
| Popis: | Learning approaches are factors that contribute to sustainability education. Academic stress negatively affects students&rsquo performances in the context of sustainability teaching. This study analyzed how deep and surface approaches could be related to coping with academic stress and gender. An online survey was completed by 1012 university students. The relationship between gender, sources of stress and learning approaches was examined through a multivariate canonical correspondence analysis. Results showed differences in stress-coping strategies depending on the learning approach used. In both female and male students, academic stress was handled with a deep learning approach. The findings provide implications for professors and highlight the importance of variables such as deep learning and gender in the teaching and learning sustainability process. |
| Databáze: | OpenAIRE |
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