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Adaptive learning systems are increasingly common in U.S. classrooms, but it is not yet clear whether their positive impacts are realized equally across all students. This study explores whether nuanced identity categories from open-ended self-reported data are associated with outcomes in an adaptive learning system for secondary mathematics. As a measure of impact of these social identity data, we correlate student responses for 3 categories: race and ethnicity, gender, and learning identity—a category combining student status and orientation toward learning—and total lessons completed in an adaptive learning system over one academic year. Results show the value of emergent and novel identity categories when measuring student outcomes, as learning identity was positively correlated with mathematics outcomes across two statistical tests.

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Exploring Student Identity in Adaptive Learning Systems Through Qualitative Data

  • 会议论文

  • 发表日期：

    2025年

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  • Clara Belitz,
  • HaeJin Lee,
  • Nidhi Nasiar,
  • Stephen E. Fancsali,
  • Frank Stinar,
  • Husni Almoubayyed,
  • Steve Ritter,
  • Ryan S. Baker,
  • Jaclyn Ocumpaugh,
  • Nigel Bosch

摘要

Adaptive learning systems are increasingly common in U.S. classrooms, but it is not yet clear whether their positive impacts are realized equally across all students. This study explores whether nuanced identity categories from open-ended self-reported data are associated with outcomes in an adaptive learning system for secondary mathematics. As a measure of impact of these social identity data, we correlate student responses for 3 categories: race and ethnicity, gender, and learning identity—a category combining student status and orientation toward learning—and total lessons completed in an adaptive learning system over one academic year. Results show the value of emergent and novel identity categories when measuring student outcomes, as learning identity was positively correlated with mathematics outcomes across two statistical tests.