Data-informed Decision-making in TEFA Processes: An Empirical Study of a Process Derived from Peer-Instruction

Abstract

When formative assessment involves a large number of learners, Technology-Enhanced Formative Assessments are one of the most popular solutions. However, current TEFA processes lack data-informed decision-making. By analyzing a dataset gathered from a formative assessment tool, we provide evidence about how to improve decision-making in processes that ask learners to answer the same question before and after a confrontation with peers. Our results suggest that learners' understanding increases when the proportion of correct answers before the confrontation is close to 50%, or when learners consistently rate peers' rationales. Furthermore, peer ratings are more consistent when learners' confidence degrees are consistent. These results led us to design a decision-making model whose benefits will be studied in future works.

Programa evaluación formativa para mejorar el desempeño docente

“…Por otro lado, analizar las evidencias, implica recopilar un conjunto de datos a partir de la evaluación formativa, además proporciona evidencias para tomar decisiones en los procesos para lograr las competencias, asimismo la comprensión y confianza de los estudiantes aumenta cuando se les proporciona retroalimentación basada en las evidencias recogidas (Andriamiseza et al, 2021). En la misma línea Rodgers (2018) aconsejan que cuando el docente analiza las evidencias de los aprendizajes, se tienen que plantear preguntas auténticas sobre lo que el estudiante tiene confuso y no sobre lo que ya sabe.…”