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<p>The question is the primary step in knowledge building (KB) learning. Students propose a profound question that can inspire them to engage in collaborative exploration actively, thereby forming deep KB. However, not all students can pose valuable questions in the current KB. Considering the potential role of questioning in promoting the development of community theory, this study employed an effectiveness validation research design to investigate how a data-driven assessment and feedback approach influences students’ ability to pose thoughtful questions in KB learning. Thirty-two sixth-grade students from a primary school in Yangzhou, China, participated in a 15-week KB learning process using the data-driven assessment and feedback method. The research findings indicated that by addressing challenges such as student anxiety over scores, challenges in teachers’ integration of feedback into instruction, and variations in students’ ability to interpret and apply feedback, the data-driven assessment and feedback approach was refined and optimized. This approach effectively supported students in posing deep questions by enhancing their domain contextuality, openness, and dynamicity. The data-driven assessment and feedback method proposed in this study provided researchers and teachers with operational references for human–computer collaboration and was expected to serve as effective tools for supporting KB learning and posing deep questions.</p>

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How to promote students to pose deep questions in knowledge building? A data-driven approach to assessment and feedback

  • 期刊论文

  • 发表日期：

    2025年12月29日

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  • Suping Yi,
  • Xiaocui Yin,
  • Yibing Zhang

摘要

The question is the primary step in knowledge building (KB) learning. Students propose a profound question that can inspire them to engage in collaborative exploration actively, thereby forming deep KB. However, not all students can pose valuable questions in the current KB. Considering the potential role of questioning in promoting the development of community theory, this study employed an effectiveness validation research design to investigate how a data-driven assessment and feedback approach influences students’ ability to pose thoughtful questions in KB learning. Thirty-two sixth-grade students from a primary school in Yangzhou, China, participated in a 15-week KB learning process using the data-driven assessment and feedback method. The research findings indicated that by addressing challenges such as student anxiety over scores, challenges in teachers’ integration of feedback into instruction, and variations in students’ ability to interpret and apply feedback, the data-driven assessment and feedback approach was refined and optimized. This approach effectively supported students in posing deep questions by enhancing their domain contextuality, openness, and dynamicity. The data-driven assessment and feedback method proposed in this study provided researchers and teachers with operational references for human–computer collaboration and was expected to serve as effective tools for supporting KB learning and posing deep questions.