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

ABSTRACT

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.

KEYWORDS:

• Data-informed learning
• sentiment analysis
• digital journal
• social learning analyt- ics
• data-decision making

Disclosure statement

No potential conflict of interest was reported by the author(s).