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Explore past and current fundamental STEM education research projects across the three research areas that NSF's EDU Core Research (ECR) program funds, as well as across ECR funding types. Other search filters draw from both NSF's data and the ECR Hub's hand coding of award abstracts.

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Meta-Analysis of Effectiveness of Simulation and Adaptive Learning Systems in STEM Education

Effective Years: 2017-2020

This proposal was submitted in response to EHR Core Research (ECR) program announcement NSF 15-509. The ECR program of fundamental research in STEM education provides funding in critical research areas that are essential, broad and enduring. EHR seeks proposals that will help synthesize, build and/or expand research foundations in the following focal areas: STEM learning, STEM learning environments, STEM workforce development, and broadening participation in STEM. The ECR program is distinguished by its emphasis on the accumulation of robust evidence to inform efforts to (a) understand, (b) build theory to explain, and (c) suggest interventions (and innovations) to address persistent challenges in STEM interest, education, learning, and participation.

Simulation and adaptive learning systems are widely used instructional technologies in STEM education from K-12 to graduate levels. Their use was endorsed by the U.S. Department of Education in its 2016 national technology plan. Using simulation to provide rich learning experiences and timely formative assessment is aligned with the trend towards competency-based education and the NSF's work in advancing cyberlearning. However, evidence-based practices for using the two technologies to engage learners and enhance learning outcomes are lacking. To address this urgent need, this project will synthesize existing knowledge on the effectiveness of two technologies in STEM education and identify evidence-based practices of technology use. These efforts will generate new knowledge about how to use technology effectively to transform STEM education, build a larger and stronger STEM workforce for the U.S., and ultimately ensure the nation's future prosperity, innovation potential, and global economic competitiveness.

The project team will conduct two separate meta-analyses to quantify the effects of simulation and adaptive learning systems on STEM learning and engagement. Meta-analysis is a powerful method to synthesize findings from multiple research studies and produce robust and accumulative evidence to inform future research and practice. This project will focus on research studies that evaluated the effectiveness of simulation and adaptive learning systems in STEM education. For each study included in meta-analyses, effect sizes of technology use on learners' engagement (e.g., participation, enjoyment, interest) and achievement (e.g., grades) will be calculated. Effect size is a standardized statistical measure that quantifies the magnitude of effects and allows comparison of effects across research studies. Effect sizes from all included studies will be pooled to estimate an overall effect size for each technology and the degree to which effect sizes vary from one study to another. Analyses will also be conducted to determine the extent to which effect sizes are related to how technology was used (i.e., pedagogy) and whether effect sizes vary by learner characteristics (e.g., gender, age, ethnicity) and learning environments (e.g., delivery modes, courses, settings, institutions). This project will provide timely and robust evidence regarding the effectiveness of each technology to inform STEM learning, teaching, future research, and technology development