Christopher Oswald is a social science researcher and data-driven methodologist with nine years of experience applying advanced statistical and machine learning techniques to educational psychology. Currently pursuing a master's thesis at UNC Chapel Hill, he focuses on stabilizing protocol analyses of think-aloud data to resolve multicollinearity issues that have muddled a decade of self-regulated learning research. He has led analyses published in top journals and presented MOOC retention and hypermedia learning findings using GLMs and survival analysis. Comfortable programming "for the love of the game," he blends rigorous quantitative training with practical data engineering to turn noisy behavioral datasets into reproducible, theory-aligned insights.
The Wiki Optimal Quest Guide bangs but requires work that I don't wanna do when moving between computers.
Contributions:5 reviews, 43 commits, 21 PRs in 2 years 6 months
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