Performance-oriented measurement of teachers’ competence in linguistically responsive teaching, relevant learning opportunities and beliefs
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Chronological data
Date of first publication2024-05-27
Date of publication in PubData 2024-11-07
Language of the resource
English
Abstract
This study conducted a quantitative study analysis of teacher competence in linguistically responsive teaching (LRT). To assess performance-oriented competence, we used a test instrument with video vignettes and corresponding items based on situation-specific skills perception (What do you perceive?) and decision-making (How would you act if you were teacher in this situation?). Participants were required to respond orally. The research questions focused on LRT competence and the connection between (pre-service and in-service) teachers’ LRT competence and individual characteristics (subjects of study and LRT-relevant teaching experience), LRT-relevant learning opportunities, and beliefs about multilingualism in school and teaching. We found that experienced teachers and those who studied English as a foreign language had higher test scores, and participants with positive beliefs were more likely to perform better on the test. Positive beliefs appear to play a fundamental role in teachers’ identities as linguistically responsive professionals. Also, findings indicate a valid innovative performance-oriented LRT measurement. We suggest a learning environment should be implemented with opportunities to reflect on (pre-service) teachers’ beliefs and creating sufficient space for reflecting on experiences, as professionalization succeeds with self-reflection to raise awareness of blind spots. Future research should focus on the relation of teachers’ actual classroom performance and situation-specific skills. Furthermore, LRT-relevant learning opportunities should be evaluated in detail to learn more about teacher professionalization in this field.
Keywords
Decision Making; Teacher; Teacher Education; Teaching
Faculty / department
Notes
This publication was funded by the German Research Foundation (DFG).