Transcriptions of semi-structured interviews underlying: Preliminary Higher Order Thinking Skills Framework for Interdisciplinary Scientific Reasoning and Problem Solving in Engineering Science Education

This dataset supports a study investigating higher order thinking skills (HOTS) within the context of interdisciplinary problem solving and scientific reasoning (IDPSSR) in engineering science higher education. The primary aim of the research was to develop a preliminary HOTS framework for IDPSSR by synthesizing insights from relevant literature and expert interviews.The dataset contains transcriptions from semi-structured interviews conducted with experienced scientists and educators involved in interdisciplinary teaching and research in engineering and science. These interviews were conducted to gather expert perspectives on HOTS in higher education for interdisciplinary contexts. <br><strong>Content:</strong> Transcriptions of semi-structured interviews with experts. This dataset is valuable for researchers and educators interested in (i) developing frameworks for teaching HOTS in interdisciplinary contexts, (ii) exploring methods for fostering scientific reasoning and problem-solving in higher education, a and (iii) informing curriculum design in engineering and science education.<br>The dataset includes expert insights, which are context-specific and may require careful interpretation when applying findings to other educational settings. Data confidentiality is maintained, with identifying details anonymized to protect participant privacy. Also, it may contain grammatical and spelling errors.

本数据集支撑一项针对工程科学高等教育领域中跨学科问题解决与科学推理（Interdisciplinary Problem Solving and Scientific Reasoning, IDPSSR）情境下高阶思维技能（Higher Order Thinking Skills, HOTS）的研究。本研究的核心目标为，通过整合相关文献与专家访谈的研究结论，构建一套面向IDPSSR场景的初步HOTS分析框架。
本数据集收录了针对工程与科学领域从事跨学科教学与研究的资深科学家及教育工作者开展的半结构化访谈（semi-structured interviews）转录文本，本次访谈旨在收集专家针对跨学科情境下高等教育阶段HOTS培养的相关见解。
【数据集内容】：针对专家的半结构化访谈转录文本。本数据集对于以下三类研究者与教育工作者具有参考价值：其一，探索在跨学科情境下构建HOTS教学框架的研究者；其二，探究高等教育阶段培养科学推理与问题解决能力方法的学者；其三，为工程与科学教育领域课程设计提供参考的从业者。
本数据集收录的专家见解均具有情境特异性，若将研究结论推广至其他教育场景时，需谨慎解读。本数据集已严格保障数据保密性，对所有可识别参与者身份的信息进行了匿名化处理，以保护受访者隐私。此外，数据集可能存在语法与拼写错误。