What does implementing case‐centered teaching of evaluation look like in practice?

Abstract

Rooted in the pedagogical literature, three evaluation educators, guided by a facilitator, engaged in reflective practice regarding case-centered teaching and learning. We engaged in (D)escription, (A)nalysis, (T)heorizing, and (A)cting (DATA model) in relation to case-centered teaching. Based on a cross-case analysis, we identified five common actions in our teaching with cases: (1) Use case-centered teaching in various contexts to support a variety of different learning outcomes for students from different backgrounds;(2) Choose cases intentionally; (3) Integrate student learning activities, supports, and materials; (4) Evaluate students' learning experiences with cases; and (5) Engage in collaborative reflection to facilitate learning and improvement on instructional practices with casecentered teaching.This article offers readers a glimpse into case-centered teaching in action as three instructors and a facilitator collectively reflect on their use of cases in evaluation education. Although we had previously learned from and taught with cases, we approached casecentered teaching and learning with new insights based on the previous articles in this volume (Bourgeois et al., this issue; Ensminger et al., this issue; Kallemeyn et al., this issue; Linfield & Tovey, this issue; Montrosse-Moorhead et al., this issue). Most evaluation educators who teach with cases draw from their own experiences in designing and using cases in their teaching (Bourgeois et al., this issue). Rather than maintaining our teaching as a private, individual practice, we engaged in collaborative reflection on our practice (Smith et al., 2015). This article follows a tradition of various forms of self-study on evaluation (Boyce & McGowan, 2018;Chouinard & Boyce, 2017;He et al., 2021; van Draanen, 2017). The purpose of this article is to share our collective actions regarding how to implement case-centered teaching in evaluation courses and how it shapes learning experiences.

Artificial intelligence and the future of evaluation education: Possibilities and prototypes

“…This alludes to a key issue experienced and reported by many young and emerging evaluators, that (1) inquiry can be difficult to learn and apply, and (2) in order to get hired for evaluation work, many potential employers or clients expect prior evaluation experience. Case studies (Kallemeyn et al., 2021) are helpful tools for helping students learn what evaluation practice could involve.…”