Practice of forestry safety education game by AI advisor and verification of learning effectiveness

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Key Points

This research aims to examine whether an AI advisor can effectively facilitate safety education in forestry without the presence of veteran educators.
Implemented an AI-assisted forestry safety game with pre-and post-tests to measure learning outcomes.
Collected data on confidence in responses and safety behavior metrics via a 40-item scale before and after the intervention.
Conducted qualitative analysis of spoken content during the game and post-game interviews, categorizing responses through clustering.
Confidence levels in responses significantly increased across all question cards (p<0.05).
Safety behavior scores showed significant improvement in all factors (t-test results).
Qualitative analysis revealed five key categories enhancing learning: term understanding, acceptance of errors, clarity of AI explanations, effects of information presentation, and depth of dialogue.

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Assesses learning effectiveness of AI-assisted forestry safety education for young workers, suggesting significant improvements.

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HAYASHI et al. (2026) studied this question.

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