HyFlex Learning Ecosystem with Social Emotional Learning
- Rattanakul Kongpha
- Kanita Hinon
- Panita Wannapiroon
Abstract
The model of the HyFlex Learning Ecosystem is with social emotional learning to enhance digital emotional intelligence. The concept is based on the integration of digital learning ecosystems. HyFlex Learning and social emotional learning this research has the objective (1) To study and synthesize the conceptual framework of The HyFlex Learning Ecosystem with Social-Emotional Learning to Enhance Digital Emotional Intelligence. (2) To develop model of The HyFlex Learning Ecosystem with Social Emotional Learning to Enhance Digital Emotional Intelligence. (3) To study the suitability of The HyFlex Learning Ecosystem with Social Emotional Learning. Research hypothesis: The suitability of the model of The HyFlex Learning Ecosystem with Social Emotional Learning is at a very high level. The participants in this research include seven experts from various institutions, all of whom are specialized in the design and development of instruction models and instruction systems. The results, which are in consistence with the expectation of the researchers, show that (1) This research can serve as a guideline for developing a flexible integrated learning ecosystem that can enhance digital emotional intelligence, consisting of a 6-step social emotional learning process, integrated with the digital learning ecosystem and HyFlex Learning. (2) the overall suitability of the development to the model of the HyFlex Learning Ecosystem with Social Emotional Learning to Enhance Digital Emotional Intelligence (Overall composition) It is at a very high level (Mean = 4.98, S.D. = 0.06, IR = 0.00, Q.D. = 0.00), and (3) Overall, In conclusion, The results of the evaluation certify the suitability of using the model of HyFlex Learning Ecosystem with Social Emotional Learning to Enhance Digital Emotional Intelligence is suitable for actual use at a very high level (Mean = 4.79, S.D. = 0.57, IQR = 0.00, Q.D. = 0.00).
- Full Text: PDF
- DOI:10.5539/ies.v18n1p67
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