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Shiksha Copilot: Teacher-AI Collaboration For Curating And Customizing Lesson Plans In Low-Resource Schools

Date
Publisher
arXiv
This study investigates Shiksha copilot, an AI-assisted lesson planning tool deployed in government schools across Karnataka, India. The system combined LLMs and human expertise through a structured process in which English and Kannada lesson plans were co-created by curators and AI; teachers then further customized these curated plans for their classrooms using their own expertise alongside AI support. Drawing on a large-scale mixed-methods study involving 1,043 teachers and 23 curators, we examine how educators collaborate with AI to generate context-sensitive lesson plans, assess the quality of AI-generated content, and analyze shifts in teaching practices within multilingual, low-resource environments. Our findings show that teachers used Shiksha copilot both to meet administrative documentation needs and to support their teaching. The tool eased bureaucratic workload, reduced lesson planning time, and lowered teaching-related stress, while promoting a shift toward activity-based pedagogy. However, systemic challenges such as staffing shortages and administrative demands constrained broader pedagogical change. We frame these findings through the lenses of teacher-AI collaboration and communities of practice to examine the effective integration of AI tools in teaching. Finally, we propose design directions for future teacher-centered EdTech, particularly in multilingual and Global South contexts.
Study at a glance
  • Question: How do teachers collaborate with an AI lesson planning tool, and how does it reshape their work practices?
  • Setting and data: 757 government schools in Karnataka, India; 1,043 grade 5–10 teachers and 23 curators; December 2024 to March 2025.
  • Method: Mixed methods combining pre- and post-intervention teacher surveys, semi-structured interviews, and platform log analysis.
Why it matters

Teachers in low-resource schools face heavy administrative burdens and time constraints, yet little is known about how generative AI lesson planning tools perform in multilingual, Global South contexts.

Key findings
  • Teachers saved an average of 2.02 hours per week on lesson planning and reported a 0.72-point decline in teaching demands-related stress.
  • English lesson plans required few modifications, whereas 94.4% of Kannada content blocks required curator edits to fix awkward translations and specialized terminology.
  • Teachers used the tool primarily to fulfill administrative documentation requirements and obtain assessment questions, while also shifting toward activity-based pedagogy.

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

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