Citation
Gagnon, D. J., Joshi, E., Arshan, N., Rulifson, E., Levin-Güracar, E., & Tiruke, T. (2023). Mathematics, 3D Printing, and Computational Thinking Through Work-Based Learning (MPACT): An Education Innovation and Research (EIR) Grant evaluation. Technical report. SRI International.
Abstract
The Mathematics, 3D Printing, and Computational Thinking Through Work-Based Learning (MPACT) program combines teacher professional development, specialized curriculum and materials and STEM industry mentors to provide grade 4–7 students with project-based experiences implemented across three learning modules. This technical report presents findings from SRI International’s evaluation of MPACT implementationin the 2021–22 school year by MPACT Fellows—i.e., teachers who participated in the MPACT program—in four U.S. states.
MPACT Fellows implemented the program in a year marked by ongoing difficulties due to the COVID-19 pandemic. Although MPACT professional development was delivered with fidelity, only 65% of MPACT Fellows implemented the full program (all three modules) with all of their classes. MPACT Fellows also provided fewer opportunities for students to meet with or learn about STEM industry mentors than intended. Despite this partial implementation, MPACT Fellows’ perceptions of and efficacy in programmatic concepts increased meaningfully after participating in MPACT. Further, grade 4 and 5 MPACT students grew nearly a full standard deviation on a measure of geometry, computational thinking, and spatial reasoning over one school year. However, significant differences were not observed in students’ socioemotional outcomes—specifically, behavioral engagement in math, behavioral disaffection in math, math self-efficacy, and math self-concept—between MPACT students and students in the comparison group.
The considerable growth of MPACT students on the assessment and the documented program impacts on teachers’ perceptions provide limited but suggestive evidence that the program could demonstrate improved student outcomes in ideal conditions, if examined over a longer time frame or using different impact measures.