Research Wednesday | October 29, 2025

This interesting article in New Approaches in Educational Research, published in August 2025, describes new ways to predict student academic performance using AI. The goal of the research is to help avoid student dropouts.  

Typical predictors of student success include family income, attendance, student academic goals, and family support for student study habits.  This study suggests that there are more complex ways to predict student performance. This makes intuitive sense, as parental pressure for students to become doctors, lawyers, or other professions, may lead to enrollment in professional schools, but not necessarily to happiness and job satisfaction. There is also the inertia effect – once a student starts on a course of study, it’s difficult to stop.  

I confess to being a bit apprehensive about the quest to predict student futures. Princeton reported that 76% of seniors finished their degrees with a different major than they expected to pursue as first-year students. There is great value in the policies of schools, such as the University of Chicago, that prohibit students from making rash decisions too early and, instead, require a wide range of exploration in literature, science, mathematics, and philosophy. If, after that exploration, a wise 20-year-old really wants to become a doctor or lawyer, then go for it.  But if, after some exploration, that person wants to be a kindergarten teacher, then that is an equally valued profession.  

 Here’s the link:

https://link.springer.com/article/10.1007/s44322-025-00038-9

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