Language markers of student beliefs signal college success

Can we detect students’ hidden beliefs about fitting in at college in ways that predict academic success and inequality? Using computational language‑based measures, we analyzed 25,000 pre‑college essays from students at 23 U.S. colleges to infer two beliefs about belonging. One belief—simple optimism—reflects confidence in a smooth college transition without acknowledging potential challenges. The other—a process‑oriented perspective—acknowledges potential struggles but represents them as common and temporary. Students from socially disadvantaged backgrounds more often expressed simple optimism and less often the process‑oriented view. These patterns mattered: simple optimism predicted lower grades and rates of full‑time enrollment through the first year of college, whereas a process‑oriented view predicted higher GPA and persistence, controlling for academic preparation, among other factors. A short social‑belonging exercise shifted students’ language toward the process‑oriented perspective by 25 percentage points, reducing differences by disadvantaged status. These findings suggest that latent beliefs about belonging are evident in everyday language and predict student outcomes, offering a tool for education leaders to better understand their students and support college success. This study applies natural language processing to 25,000 pre-college essays to detect two beliefs about belonging: simple optimism predicts worse first-year outcomes, while a process-oriented view predicts success—offering a scalable diagnostic for student support.