人工智慧（Artificial Intelligence, AI）的迅速發展，為科學教育中的探究與 實作評量帶來契機與挑戰。本文聚焦機器學習（Machine Learning, ML）與生成 式人工智慧（Generative Artificial Intelligence, GenAI）在科學探究評量中的應 用，探討如何結合這些技術以推動評量創新，並特別著重於中小學階段的教育 實踐。文章基於探究為本的學習架構，分析AI 於「定題」、「概念化」、「調 查」、「討論」與「結論」等探究面項的潛在應用。然而，AI 評量也面臨資 料偏見、缺乏多元性支持等挑戰。據此，本文提出一個整合ML 與GenAI 的動 態評量系統以驅動教學與課程，並揭示教師與研究者在AI 時代需具備的素養 發展策略。

The rapid advancement of artificial intelligence (AI) presents both opportunities and challenges for assessing scientific inquiry and practice. This study examined the integration of machine learning and generative AI in inquiry-based assessments in K-12 education. Grounded in an inquiry-based learning framework, the study examined AI’s role across key inquiry components: problem formulation (orientation), conceptualization, investigation, discussion, and conclusion. AI-driven assessments face challenges, including data biases and limitations in capturing the diversity and complexity of scientific inquiry. To address these challenges, this study proposed a dynamic assessment system that leverages machine learning and generative AI to enhance teaching and curriculum development. Additionally, the study highlighted the essential competencies that educators and researchers must develop to effectively integrate AI into education.

人工智慧、生成式人工智慧、探究與實作評量、機器學習

artificial intelligence, generative artificial intelligence, assessment of scientific inquiry and practice, machine learning