Impact of Data-Driven Feedback and Coaching on Preservice Teachers’ Questioning Skills for Higher-Order Thinking within a Mixed-Reality Simulation Environment

Abstract

In this exploratory study, constructs related to self-efficacy theory were embedded in a treatment to improve the use of higher-order thinking (HOT) questioning skills in candidates enrolled in a teaching-methods course enhanced by mixed-reality simulations (MRS). The problem of designing an effective feedback and coaching model to improve the delivery of HOT questions in 10 min lessons was addressed. Thirty undergraduates were asked to incorporate HOT questions into each of the three lessons presented during a 15-week semester. Treatment candidates received individual data-driven feedback and coaching that included tailored guidance provided at regular intervals throughout the term. Quantitative analyses indicated that there was no significant difference in self-efficacy between conditions and that treatment group members posed significantly more HOT questions in their lessons (effect size = 1.26) than their non-treatment peers. An optimal ratio of two knowledge/comprehension to one HOT question in a 10 min period was proposed and three criteria for high-quality HOT questions are presented. Interviews revealed that those who participated in the treatment were more likely to recognize improvements in their self-efficacy, lesson planning, and performance than comparison group members. Data-driven feedback and coaching also provided candidates with opportunities for reflection.