In the midst of the onslaught of COVID-19, the field of education was severely constrained and continues to be so in 2022. The purpose of this study is to find clues on how to implement Proactive, Interactive, and Deep Learning in online learning during the school closure period at the beginning of the 2020 school year in Japan. From several previous studies, it can be said that Proactive, Interactive, and Deep Learning in science education is a problem-solving learning activity based on the investigative activity process. In addition, it has been pointed out that rubrics for performance assessment are necessary to contribute to the realization of such learning. Therefore, we incorporated the process of teacher and child collaboratively creating a rubric into the classroom practice and analyzed whether proactive, interactive, and deep learning can be realized in online learning.
As a result, in an environment without direct face-to-face contact, the performance assessment based on the rubric jointly created by students and teachers using the pass-the-hat model revealed that students' problem-solving learning activities were realized. Although the online learning was carried out in the specific situation of school closures due to COVID-19, the creation of rubrics and the performance assessment through their use were seen as suggesting the possibility of promoting Proactive, Interactive and Deep Learning.

教育