Tailoring Teacher Supports: A Mixed-Methods Analysis of Responses to Coaching and Self-Reflection

Abstract

To ensure that new teachers enter classrooms poised for success, we need more evidence regarding supports that can expedite skill development during teacher education. In this study, we capitalize on mixed-reality simulations as a setting for evaluating such supports. Using a randomized control trial, we examine the extent to which coaching improves text-focused instruction compared to the more typical practice of self-reflection. Then, employing a mixed-methods sequential explanatory design, we qualitatively and quantitatively explore the extent to which candidates’ individual characteristics might influence the effectiveness of those supports. We find that, on average, coaching is the more effective support for skill development, but we also surface potential drivers of heterogeneous effects of both coaching and self-reflection, including self-efficacy, extraversion, and prior skills. We conclude with implications for teacher education programs and researchers.