Using data-informed learning design to support teacher to understand students' learning sentiment via journal entries.

Autor:	Tu, Chih-Hsiung, Peterson, Patricia, Yen, Cherng-Jyh, Harati, Hoda, Shelton, Catharyn, Sujo-Montes, Laura
Předmět:	COVID-19 pandemic SOCIAL emotional learning ONLINE education SENTIMENT analysis DECISION making
Zdroj:	Educational Media International; Sep-Dec2023, Vol. 60 Issue 3/4, p169-182, 14p
Abstrakt:	COVID-19 has emphasized the importance of holistic education with fostering stu- dents' multiple intelligences through effective social and emotional learning (SEL). Understanding students' SEL not only supports students' learning performance, it's also beneficial to inform teachers to provide more adequate social-communicative, metacognitive, and affective learning. This study examined: How does Data-Informed Learning Design (DILD) support online teaching on students' social and emotional learning? The study concluded that DILD is an effective design model to support teachers to probe students' socio-communicative, metacognitive, and affective learnings. The findings inform the educators to set high expectations for teaching and provide appropriate personal, social, data, and instructional support to enable teachers to regulate and support students to achieve ideal social and emotional learning. [ABSTRACT FROM AUTHOR]
Databáze:	Complementary Index
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