Can Machine Learning Solve the STEM Diversity Gap?


Today, only 11 percent of low income, underrepresented minority, or first-generation students meet the ACT Benchmark in science—a standard for college readiness—which holds big implications for increasing diversity. With the advent of AI and personalized learning, can new approaches to teaching and learning such as ML-based computational psychometrics close the STEM diversity gap? Hear from experts working with major institutions to ensure all students have the tools to pursue the STEM fields.

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  1. Understand the causes of the STEM achievement gap.
  2. Understand how smart courses can help level the playing field for low-income, minority, or first-generation students.
  3. Conceptualize the role AI & ML play in improving completion rates & retention of course material for students at risk of dropping out of STEM majors.



Chelsea Goldsmith, Event Coordinator & Marketer, Smart Sparrow

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