Use AI-correcting and AI-mediating episodes as cases in teacher professional development for AI-based mathematics teaching¶

Strategy · All strategies
Evidence · 4 claims (4 for) · 1 study (1 qualitative), q1 · 0 of 1 report an effect size · 4 claims rest on one study

Description¶

The authors propose that the documented orchestration episodes serve as concrete material for teacher education. They state that the 'AI-수정하기' and 'AI-매개하기' cases show how teachers understand AI tools' functional characteristics and limits, respond actively to AI errors, and reinterpret AI feedback in curriculum context, and that these cases should be treated in teacher training as "구체적인 사례로써 제공된다". Dashboard-monitoring cases are likewise recommended for explicitly building dashboard-based lesson-management competency in teacher education programs.

Design Implications¶

Context¶

Requirements¶

• Teacher education programs that include case-based work on AI-based lesson orchestration practices

Constraints¶

• Cases derive from one highly experienced teacher; the authors call for extension to teachers of varied career stages, technical skill, and school levels

Target Learners¶

• In-service and pre-service secondary mathematics teachers in professional development

Target Learning Goals¶

• Orchestrating AI-based tools, responding to AI feedback errors, and using dashboards for instructional decisions

Affordances¶

• Instrumental Orchestration Extended Agentic Ai

Claims¶

• AI-correcting is a newly observed orchestration type in which the teacher identifies erroneous AI feedback, points it out to students, and re-guides or edits AI prompts (10 of 46 episodes) [+W]
• AI-mediating is a newly observed orchestration type in which the teacher concretizes or supplements correct AI feedback for students in curriculum context (12 of 46 episodes) [+W]
• Dashboard-monitoring is a newly observed orchestration type in which the teacher uses real-time AI dashboards to grasp student status and adjust lesson direction and pace (14 of 46 episodes) [+W]
• Teacher roles vary by orchestration type, with content-related and ethical roles prominent when the teacher intervenes in AI-generated feedback, and a knowledge-transmitter role emerging in explain-the-screen [+W]

Related Strategies¶

Examples¶

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Key Sources¶

• Yun Hwa Noh & Hee-jeong Kim. (2026). Exploring teachers' instrumental orchestration and roles in high school mathematics classes using AI-based digital tools. The Mathematical Education 65(2), 309-335. https://doi.org/10.63311/mathedu.26.6525