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Teaching with Gemini: Measuring the impact of Guided Learning on student mathematics progress in Sierra Leone

Date
Publisher
Google
We conducted a preregistered randomized controlled trial in Sierra Leone to evaluate the impact of the Guided Learning feature in Gemini on student learning outcomes in mathematics. The trial enrolled __ = 1763 junior secondary school students across 48 mathematics classrooms. We asked teachers to incorporate Gem- ini into half of their weekly lessons for eight weeks, adding up to a requested total of 12 hours. Guided Learning significantly improvedstudentlearningoutcomes,withanintent-to-treateffect of +0.258 SD (__ = 0.029). Uptake exceeded our expectations, with 69.0% of students engagingwith GuidedLearning for atleast 12 hours over the trial. Reaching this threshold yielded a signifi- cant treatment-on-the-treated effect of +0.380 SD (__ = 0.029). In focus groups, teachers emphasized students’ enthusiasm for GuidedLearningsessionsandcreditedGeminiwithhelpingreveal new ways to teach familiar topics.
Study at a glance
  • Question: How does using Gemini's Guided Learning feature affect student mathematics learning in junior secondary school classrooms?
  • Setting and data: Sierra Leone, 1,763 junior secondary school students across 48 mathematics classrooms, eight-week trial.
  • Method: Preregistered randomized controlled trial and teacher focus groups (Mixed methods)
Why it matters

Evidence is needed on how generative AI features like Guided Learning affect student learning outcomes in mathematics.

Key findings
  • Gemini Guided Learning significantly improved student mathematics learning outcomes, with an intent-to-treat effect of +0.258 standard deviations.
  • For the 69.0% of students who engaged with Guided Learning for at least 12 hours, the treatment-on-the-treated effect was +0.380 standard deviations.
  • In focus groups, teachers highlighted student enthusiasm for Guided Learning and noted that Gemini helped reveal new ways to teach familiar topics.

Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.

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