请先点击上方链接阅读参与者信息说明书，然后在下方完成在线知情同意确认。 / Please open and read the Participant Information Sheet above, then complete the online consent form below.
EN: Human-AI Relationships in Collaborative, AI-Supported Professional Learning: A Q Methodological Study Based on Stephenson's Theoretical Framework
中文：协作式 AI 支持专业学习中的人机关系：一项基于 Stephenson 理论框架的 Q 方法论研究
EN: Version #1: 2026.04.20
中文：版本 #1：2026.04.20
EN: You are being invited to take part in a research study conducted by Yuhong Zhao, Doctor of Education (EdD) student at Xi'an Jiaotong-Liverpool University (XJTLU), supervised by Qing Zhang. Before deciding whether to participate, please read this information carefully. You may ask questions before deciding. Participation is voluntary.
中文：诚邀您参与一项研究。本研究由西交利物浦大学教育博士（EdD）学生赵玉宏开展，导师为 Qing Zhang。在决定是否参与前，请您仔细阅读本说明。如有任何问题，您可以在决定前向研究者咨询。参与完全自愿。
EN: This study explores how higher education professionals understand and experience their relationship with AI in collaborative, AI-supported professional learning. The study aims to identify distinct viewpoint profiles using Q Methodology and to consider how these profiles can inform facilitation principles for AI-supported professional learning activities.
中文：本研究旨在探讨高校专业人员如何理解和体验其在协作式 AI 支持专业学习中与 AI 的关系。本研究将使用 Q 方法论识别不同的观点画像，并进一步思考这些画像如何为 AI 支持专业学习活动的引导原则提供依据。
EN: You have been invited because you are a higher education professional, such as a teacher, lecturer, educational developer, learning designer, or other staff member involved in teaching, learning, or professional development. The study seeks participants with varying levels of AI experience, including active users, occasional users, and those who are cautious, uncertain, or still exploring AI use.
中文：邀请您参加，是因为您属于高校专业人员，例如教师、讲师、教学发展人员、学习设计师，或其他参与教学、学习、专业发展的工作人员。本研究希望邀请具有不同 AI 使用经验的参与者，包括积极使用者、偶尔使用者，以及对 AI 使用持谨慎、观望或仍在探索阶段的人员。
EN: No. Taking part is entirely voluntary. You may choose not to participate, and this will not disadvantage you in any way. If you decide to participate, you may withdraw without giving a reason up to the point at which your data have been included in factor analysis or aggregated findings. After this point, it may not be possible to remove individual data from aggregated results.
中文：不需要。参与完全自愿。您可以选择不参加，这不会给您带来任何不利影响。如果您决定参加，您可以在您的数据被纳入因子分析或汇总研究结果之前，无需说明理由而退出研究。在此之后，由于数据可能已经进入汇总分析结果，研究者可能无法再从汇总结果中移除您的个人数据。
EN: The study has two stages. First, you will complete a Q Sort, in which you will rank-order a set of statements about human-AI relationships in professional learning. This may be completed online or in a structured research session. The Q Sort is expected to take approximately 20-30 minutes. Second, you may be invited to take part in a post-sort interview lasting approximately 30-45 minutes. The interview will ask you to explain your sorting choices, especially the statements you most agreed or disagreed with. Not everyone who completes the Q Sort will be invited for interview, and you are not obliged to take part if invited.
中文：本研究包括两个阶段。第一阶段是 Q 排序，您需要对一组关于专业学习中人机关系的陈述进行排序。该过程可在线完成，也可在结构化研究场景中完成，预计需要 20-30 分钟。第二阶段是排序后访谈，部分参与者可能会被邀请参加约 30-45 分钟的半结构化访谈。访谈将请您解释排序理由，尤其是您最认同或最不认同的陈述。并非所有完成 Q 排序的参与者都会被邀请访谈；即使被邀请，您也没有义务参加。
EN: A single consent form will cover your participation in the Q Sort and your agreement to be contacted about a possible post-sort interview. If you take part in a post-sort interview, you will be asked separately whether you consent to audio recording. You may complete the Q Sort without agreeing to audio recording or without taking part in an interview.
中文：本研究将使用一份统一的同意书，涵盖您参加 Q 排序以及同意研究者在必要时联系您参加排序后访谈。如果您参加排序后访谈，研究者会另行询问您是否同意录音。您可以只完成 Q 排序，而不同意录音或不参加访谈。
EN: There are no costs or payments involved in participating.
中文：参与本研究不涉及任何费用，也不提供报酬。
EN: This study is considered low risk. Some participants may experience minor discomfort when reflecting on AI use, professional judgement, teaching practice, or concerns about AI in education. You may skip any question you do not wish to answer. If you take part in an interview, you may pause or stop the interview at any time.
中文：本研究被视为低风险研究。部分参与者在反思 AI 使用、专业判断、教学实践或对教育中 AI 的担忧时，可能会产生轻微不适。您可以跳过任何不愿回答的问题。如果您参加访谈，也可以随时暂停或停止访谈。
EN: There may be no direct personal benefit. However, participation may give you an opportunity to reflect on your own views about AI in professional learning. The findings may help inform the design and facilitation of future AI-supported professional learning activities.
中文：参与本研究可能不会带来直接的个人收益。不过，参与过程可能为您提供一个反思自己对专业学习中 AI 使用看法的机会。研究结果也可能为未来 AI 支持专业学习活动的设计与引导提供参考。
EN: Your participation will be treated confidentially. The study is not anonymous at the point of data collection because the researcher may collect contact details for recruitment, scheduling, consent management, and possible post-sort interview follow-up. However, research data will be pseudonymised using participant codes, and contact details will be stored separately from research data. The code key linking names or contact details to participant codes will be accessible only to the researcher. Thesis chapters, publications, and presentations will use anonymised reporting and will not include information that identifies you or your institution.
中文：您的参与信息将被保密处理。本研究在数据收集阶段并非完全匿名，因为研究者可能需要收集联系信息，用于招募、预约、同意管理以及可能的排序后访谈联系。但研究数据将使用参与者编号进行编码处理，联系信息将与研究数据分开保存。姓名或联系信息与参与者编号之间的对应表仅研究者本人可访问。论文、发表和展示将采用匿名化报告方式，不会包含能够识别您或您所在机构的信息。
EN: Research data will be stored primarily on XJTLU provider cloud storage. Any local copies on the researcher's device will be password-protected and accessible only to the researcher. Data will be retained and disposed of in accordance with XJTLU research data management policy. Q Sort data may be analysed using Q Methodology software such as PQMethod or KADE. Interview recordings, if collected, will be stored securely and transcribed for analysis.
中文：研究数据将主要存储在西交利物浦大学云存储提供商的云空间中。研究者设备上的任何本地副本均将进行密码保护，且仅研究者本人可访问。数据将依据西交利物浦大学研究数据管理政策进行保存和处置。Q 排序数据可能会使用 PQMethod 或 KADE 等 Q 方法软件进行分析。若收集访谈录音，录音将被安全存储，并转录用于分析。
EN: Only anonymised or de-identified research materials may be processed using AI-assisted tools or third-party analysis platforms to support organisation, coding, interpretation, or writing. Raw audio recordings, contact details, names, institutional identifiers, or directly identifiable information will not be uploaded to public AI tools or third-party platforms. The researcher will review all AI-assisted outputs and will not rely on automated interpretation without human checking.
中文：研究者仅会在材料已匿名化或去标识化后，使用 AI 辅助工具或第三方分析平台帮助资料整理、编码、解释或写作。原始录音、联系信息、姓名、机构标识或其他可直接识别身份的信息不会上传至公共 AI 工具或第三方平台。研究者将人工检查所有 AI 辅助输出，不会在未经人工核查的情况下依赖自动化解释。
EN: The findings will be used in the researcher's EdD dissertation and may also be used in academic publications, presentations, or conference outputs. Results will be reported in a way that does not identify individual participants or institutions.
中文：研究结果将用于研究者的教育博士论文，也可能用于学术发表、学术报告或会议成果。结果将以不识别个人参与者或机构的方式呈现。
EN: You may withdraw without giving a reason up to the point at which your data have been included in factor analysis or aggregated findings. Before that point, you may request that your data be removed. After that point, it may not be possible to remove your individual data from aggregated factor analysis and findings. If you wish to withdraw, please contact the researcher using the details below.
中文：在您的数据被纳入因子分析或汇总研究结果之前，您可以无需说明理由退出研究，并要求移除您的数据。在此之后，由于您的数据可能已经进入汇总的因子分析和研究发现，研究者可能无法再移除您的个人数据。如需退出，请使用下方联系方式联系研究者。
EN: If you have concerns about the study, please contact the researcher first. If your concern is not resolved, you may contact the University Ethics Committee at ethics@xjtlu.edu.cn. When contacting the committee, please provide the name or description of the study and the details of your concern.
中文：如果您对本研究有任何疑虑，请先联系研究者。如果问题未能解决，您可以联系大学伦理委员会：ethics@xjtlu.edu.cn。联系伦理委员会时，请提供研究名称或研究描述，以及您的具体疑虑。
EN: Researcher: Yuhong Zhao
Email: Yuhong.Zhao23@student.xjtlu.edu.cn
Supervisor: Qing Zhang
中文：研究者：赵玉宏 Yuhong Zhao
邮箱：Yuhong.Zhao23@student.xjtlu.edu.cn
导师：Qing Zhang
EN: Thank you for considering participation in this study. Your time and input are greatly appreciated.
中文：感谢您考虑参与本研究。非常感谢您的时间与支持。
Project: Human-AI Relationships in Collaborative, AI-Supported Professional Learning · Researcher / 研究者: Yuhong Zhao / 赵玉宏 · Supervisor / 导师: Qing Zhang
为防止刷新、断网或意外退出造成内容丢失，本页面会将填写内容（包括姓名和联系方式）自动保存在本设备浏览器中，最长保留 24 小时；提交成功后会自动清除。
您的姓名与联系信息将与研究数据分开保存，仅研究者本人可访问（见说明书第 12 条）。
本研究需要参与者在过去一年内有在专业工作中使用生成式 AI 的经验。虽然这次未能邀请您参与排序，仍然非常感谢您愿意支持这项研究。
共 41 张卡片，逐张呈现。三堆没有数量要求，下一步可以自由调整。
这三堆只是正式排序的起点，不限制卡片最后的位置。
您的参与者编号：
请保存此编号。如您希望在数据纳入分析前撤回，请凭编号通过参与者信息表中的邮箱联系研究者。
本页不提供任何测评结果——您的排序将与其他参与者的数据一起进入因子分析。如果您对"AI 关系类型"的趣味自测感兴趣，可以访问大众版（与本研究数据完全独立）。
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