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Pearson: Asking to Learn – What Student Queries to Generative AI Reveal About Cognitive Engagement

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Summary of https://plc.pearson.com/sites/pearson-corp/files/asking-to-learn.pdf

Analyzing student queries to an AI-powered study tool reveals that while many questions focus on basic factual and conceptual knowledge, a significant portion demonstrates higher-order thinking skills, suggesting the tool can support deeper learning.

Insights from this study are being used to develop features that encourage students to ask more complex questions. The authors emphasize that meaningfully integrating AI tools into learning can foster a richer, more active educational experience.

  • A large-scale study analyzed 128,725 student queries from 8,681 unique users interacting with the "Explain" feature of an AI-powered study tool embedded in an eTextbook. The analysis focused on the open-ended nature of the Explain feature queries as insights into student thought processes.
  • Using Bloom's Taxonomy, the analysis found that 80% of student inputs related to basic Factual or Conceptual knowledge, such as definitions or understanding connections. This aligns with the introductory biology course context.
  • However, the data also showed that about one-third of inputs reflected more advanced cognitive complexity, and 20% were at levels suggesting higher-order thinking skills (Analyze and above), indicating potential for deeper learning beyond basic recall.
  • The presence of higher-level queries suggests that many students are actively framing their inquiries rather than passively seeking information, pointing to the tool's potential to foster more advanced cognitive skills when thoughtfully integrated.
  • Insights from the analysis have directly informed the development of a new "Go Deeper" feature which suggests follow-up questions targeting higher cognitive levels to encourage deeper engagement.
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