| Autor: |
Maria Kramer, Julia Stürmer, Christian Förtsch, Tina Seidel, Stefan Ufer, Martin R. Fischer, Birgit J. Neuhaus |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Learning to Diagnose with Simulations ISBN: 9783030891466 |
| DOI: |
10.1007/978-3-030-89147-3_6 |
| Popis: |
Identifying and interpreting challenging instructional situations is important for teacher performance in the classroom, thus also for instructional quality. This project examines classroom situations in which pre-service teachers diagnose effective teaching in terms of instructional quality in the context of biology lessons. The interdisciplinary collaboration combines expertise in research on teachers’ professional competence, video-based teaching, and computer-supported case-based learning in several contexts. The video-based simulation DiKoBi (German acronym for “diagnostic competences of biology teachers in biology classrooms”) was developed to investigate, measure, and foster pre-service teachers’ diagnostic skills concerning the instructional quality of biology lessons. Staged videos embedded in the video-based simulation DiKoBi show six different classroom situations, each focusing on one biology-specific instructional quality feature. Validity of the content and tasks in DiKoBi were examined in interviews using think-aloud protocols and expert-novice comparisons. In future research, intervention studies will be used to analyze the effects of knowledge acquisition and scaffolding during teachers’ diagnosing on their diagnostic skills concerning instructional quality. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
|
