Blended learning: A data-literate science teacher is a better teacher

TL;DR

This paper emphasizes the importance of data literacy for science teachers in blended learning environments, highlighting how it enhances teaching effectiveness through better data management and instructional adjustments.

Contribution

It summarizes pedagogical models of blended learning and underscores the critical role of data literacy for teachers in improving educational outcomes.

Findings

Data literacy correlates with increased teaching effectiveness.

Blended learning models include rotational and flexible configurations.

Digital technology enables more frequent data collection and analysis.

Abstract

The COVID-19 pandemic has underscored the importance of blended learning in contemporary physics and, more generally, STEM education. In this contribution, we summarize current pedagogical models of blended learning, such as rotational and flexible non-rotational models, and customizable configurations of physical and virtual learning spaces. With the inevitable integration of digital technology as one of the pillars of blended learning, teachers find themselves in an unprecedented position to not only obtain data more frequently but also analyze it and adjust instruction accordingly. Consequently, we discuss a crucial element of blended learning effectiveness: data management and usage. In this context, data literacy for teaching emerges as an essential skill for effective blended learning, encompassing the ability to transform various data types into actionable instructional knowledge and practices. In other words, current research in physics education shows that a data-literate science teacher is a more prosperous and effective teacher.