Affiliation:
1. Capital Normal University, Beijing, China
2. Jiangxi Normal University, Nanchang, China
Abstract
Innovation capability has become a necessary requirement for qualified teachers in the context of informatization. However, the validity and objectivity of existing assessments are unclear. Therefore, this study selected nine researchers to evaluate the instructional innovation capabilities of 60 pre-service teachers from a Chinese normal university. The Many-Faceted Rasch Model (MFRM) was used to measure and analyze the rater severity, difficulty of evaluation criteria, and instructional innovation capability of pre-service teachers. Combined with qualitative analysis, the results showed that most participants had moderate instructional innovation capability, and only certain individuals demonstrated a high level. In addition, innovation related to teaching content and learning activities was easier than innovation related to instructional and evaluation strategies. These results suggest directions for fostering pre-service teachers’ instructional innovation capabilities.
Funder
2023 Open Research Project “Artificial Intelligence in Education” in the College of Education in Capital Normal University
Subject
General Social Sciences,General Arts and Humanities
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