Towards data-informed teaching practice

Autor: Merike Saar, María Jesús Rodríguez-Triana, Luis Pablo Prieto Santos
Rok vydání: 2022
Předmět:
Zdroj: Journal of Learning Analytics. 9:88-103
ISSN: 1929-7750
DOI: 10.18608/jla.2022.7505
Popis: Data-informed decision making in teachers’ practice, now recommended by different teacher inquiry models and policy documents, implies deep practice change for many teachers. However, not much is known how teachers perceive the different steps that analytics-informed teacher inquiry into their own practice entails. This paper presents the results of a study into developing an Analytics Model for Teacher Inquiry (AMTI), which was then used to understand how teachers (N=10) construe the steps in the model and to explore the possible constraints as well as incentives for Teaching and Learning Analytics (TLA)-informed teacher practices. In the final iteration experts (N=7) and teacher-researchers (N=2) tested and evaluated the developed model. Their feedback was used to improve the model and provide example cases with insights into possible scenarios for TLA-informed analyses of teaching.
Databáze: OpenAIRE