This is a four-year Information Technology Experiences for Students and Teachers (ITEST) scale-up project aimed at developing Computational Thinking (CT) with 200 teachers and 15,000 middle school students in nine states' diverse learning environments, such as urban, remote rural areas, and Native American communities. Embedded in existing computing education and STEM courses, the project-developed curriculum--Scalable Game Design (SGD)--introduces students to CT through game design and advances them to STEM simulation design. The project builds on a previous NSF-funded ITEST effort, which suggests that a combination of professional development (PD) types (face-to-face, online, and blended) using SGD can result in high participation of diverse students with high degrees of motivation across gender and ethnicity. The study's key goal is to determine the extent to which the use of three models of PD for teaching CT support classroom teaching and student learning, motivation, and performance; thus a replicable model for scaling-up CT education.
Framed within a scale-up working theory that identifies capacity, reach, and sustainability as fundamental requirements, the key research question is: How do face-to-face, online, and blended professional PD models for teaching computing support classroom and student learning outcomes in various school contexts? To address this question, the project (a) develops a highly adoptable middle-school CT curriculum (a structured expansion of SGD) that addresses issues of access, capacity, replicability, fidelity, and cost), integrated into existing computer education and STEM courses; (b) creates a scalable set of game-design activities so that students with no programming background can produce complete and exciting games; (c) builds computational instruments that analyze student-produced projects for CT skills; and (d) investigates the interaction of pedagogical approaches and students' motivational levels, so that teachers can broaden participation. To assess motivation across gender and ethnicity, the study employs established valid and reliable motivation instruments. To measure performance, the project uses Computational Thinking Pattern Analysis, an embedded assessment instrument that measures computational thinking patterns, illustrates divergence between tutorial and student projects, and computes learning trajectories from students' projects.
The project's key outcome is a research-informed and field-tested scalable prototype to promote middle and high school CT based on game and STEM simulation design.
