教师评估反馈表设计

论点陈述
本反馈表旨在为《大学英语》课程建立一套具有内容效度、结构效度与可用性的学生评价工具，以促进教学改进与项目质量保障。设计以建构式对齐为指导，将教学目标、教学活动与评估一致化，并借鉴学生评教量表的维度化研究与语言学习成效框架（CEFR），在保证信度的同时尽量降低已知偏差，遵循教育与心理测量标准的伦理与技术要求（AERA, APA, & NCME, 2014; Biggs, 1996; Marsh, 1982; Council of Europe, 2020）。

一、量表框架与理论依据
- 维度设置
  1) 课程目标与结构（建构式对齐：目标—教学—评估一致性；Biggs, 1996）
  2) 教学实施与互动（学生评教的多维结构与可解释性；Marsh, 1982; Marsh & Roche, 1997）
  3) 学习资源与支持（可获得性与可用性）
  4) 评估与反馈质量（形成性反馈的效力与透明性；Hattie & Timperley, 2007; Black & Wiliam, 1998）
  5) 学习投入与学习负担（学习动机与努力）
  6) 自我感知的语言能力提升（基于CEFR B1–B2目标的自评增益；Council of Europe, 2020）
  7) 学习氛围与包容性（公平、尊重与安全的课堂环境）
  8) 整体评价（目标达成与推荐意愿）
- 测量原则
  - 使用5点评分的李克特量表以平衡区分度与答题负荷（Likert, 1932）。
  - 子量表内部采用多个条目以提高内部一致性（Nunnally & Bernstein, 1994）。
  - 明确“不可适用”选项以降低无信息性反应并减少系统性缺失。

二、作答说明（提供给学生）
- 本问卷匿名、用于教学改进。请基于本学期的真实经历作答。
- 评分方式（除特别说明外）：
  1=非常不同意；2=不同意；3=不确定/一般；4=同意；5=非常同意；NA=不适用。
- 预计用时：8–10分钟。

三、量表条目（供正式施测）
A. 课程目标与结构
1. 课程学习目标表述清晰、可理解。
2. 课堂活动、作业与考试与学习目标一致。
3. 课程内容与我的专业或通识需求具有相关性。
4. 课程难度与我的先修知识与能力基本匹配。

B. 教学实施与互动
5. 教师以英语进行条理清晰的讲解。
6. 教师有效促进英语课堂互动与讨论。
7. 教师采用多样化的教学策略以支持不同水平的学生。
8. 课堂节奏与活动安排有助于达成学习目标。

C. 学习资源与支持
9. 学习资源（教材、讲义、学习平台）质量高且易获取。
10. 课程提供了充足且有意义的英语实践机会（如口语、小组任务）。
11. 技术工具（平台、听力材料、自动化练习等）的使用提升了学习效果。
12. 教师课后答疑与个性化支持及时且有效。

D. 评估与反馈质量
13. 评估任务能较真实地反映实际语言使用（任务真实性）。
14. 评分标准/量表明确、可理解，并在评估前已告知。
15. 作业与测验反馈具体、可操作且及时。
16. 评估过程公平公正，评分符合既定标准。

E. 学习投入与学习负担
17. 本课程的学习负担与学分要求基本相称。
18. 本课程提升了我持续学习英语的动机。
19. 我通常能按时完成预习、作业与小组任务。

F. 自我感知的语言能力提升（基于B1–B2目标的增益自评）
提示：以下条目意在了解本课程对语言能力的促进，请据本学期感受作答。
20. 听力：我能理解熟悉主题的授课或对话要点。
21. 口语互动：我能在课堂讨论中较为自如地表达并回应观点。
22. 口语表达：我能进行结构清晰的简短口头报告或陈述。
23. 阅读：我能理解与学术或专业相关的中等难度文章主旨与关键细节。
24. 写作：我能撰写结构清晰、语法较准确的短文或简短报告。
25. 词汇与语法：我能更灵活地使用常见学术词汇与语法结构。

G. 学习氛围与包容性
26. 课堂氛围安全、包容，尊重不同文化与水平差异。
27. 我在课堂上使用英语表达时感到被支持而非被嘲笑。
28. 教师能及时处理不当言行，维护公平与尊重。

H. 整体评价
29. 总体而言，课程基本达成了其声明的学习目标。
30. 我愿意向其他学生推荐本课程。

四、开放性问题（定性证据）
- Q1. 本课程中对你学习最有帮助的1–2项教学做法或学习活动是什么？请尽量举例说明。
- Q2. 你认为哪一类作业或评估最能体现语言能力？原因是什么？
- Q3. 请指出最需要改进的1–2个方面，并提出可操作的建议。
- Q4. 其他建议或意见（可涉及资源、技术支持、课堂管理、评估设计等）。

五、选填背景信息（用于公平性与差异分析）
- 年级与专业（开放式）
- 本课程性质：必修/选修
- 班级类型：综合英语/口语/写作/学术英语（选择）
- 自评英语水平：A2/B1/B2/C1（参照CEFR）
- 预期课程成绩区间（仅用于统计控制）：90+ / 80–89 / 70–79 / <70 / 不确定
- 每周课外投入时间：<1小时 / 1–2 / 3–4 / 5–6 / >6

六、施测与伦理建议
- 时间点：建议在学期中期（形成性反馈）与期末（总结性反馈）各一次，以便持续改进（Black & Wiliam, 1998）。
- 匿名性：确保完全匿名与自愿，明确告知数据仅用于改进与质量保障，避免高风险人事决策的单一依据（AERA et al., 2014）。
- 施测方式：在线或纸笔均可；在线建议随机呈现同一维度内条目的顺序，以降低顺序效应。
- 指导语中强调：请基于课程经历作答，避免受单一事件过度影响。

七、评分与报告
- 计分原则
  - 各维度得分为所含条目的算术平均（排除NA）。可同时提供总分（各维度平均值的平均）。
  - 对于样本量≥30的班级报告95%置信区间，以反映估计不确定性。
  - 建议阈值（用于筛查而非绝对判断）：<3.0需优先改进；3.0–3.5基本达标；3.51–4.0良好；>4.0表现突出。应结合开放题证据解读。
- 缺失与NA处理
  - 若某维度应答比例<70%，不报告该维度分数，仅提供定性摘要。
- 报告结构
  - 班级层面：各维度均值、置信区间、与项目/院系基准比较、开放题主题归纳与代表性引语（匿名）。
  - 项目层面：按课程类型与学生水平（CEFR自评）分组，检视是否存在系统性差异。

八、信度与效度证据的收集计划
- 内容效度：由至少3名大学英语与测量专家进行条目审查，依据课程大纲与CEFR对齐情况修订（AERA et al., 2014）。
- 内部结构：在首轮数据（建议N≥300，总体上每条目受试数≥5–10）上进行EFA与CFA；使用多分序数据的多分序相关；CFA适配指标建议CFI≥.95、TLI≥.95、RMSEA≤.06、SRMR≤.08（Hu & Bentler, 1999）。
- 可靠性：报告各维度的Cronbach’s α与McDonald’s ω，目标≥.70（Nunnally & Bernstein, 1994; McDonald, 1999）。
- 关系效度：检验与相关外部变量的关系，如与独立的语言表现指标（如标准化口语/写作评分）之间的适度正相关；同时警惕与期望成绩的潜在混淆（Messick, 1995）。
- 反应过程：对少量学生开展认知访谈，确认条目理解一致性与指向性（DeVellis, 2017）。
- 公平性与后果：检测不同性别、年级、英语水平组的测量不变性；监测用途后果，避免将学生评价结果作为单一高风险决策依据（AERA et al., 2014; Uttl, White, & Wong, 2017）。

九、偏差控制与使用注意
- 控制变量：收集班级规模、课程性质、学生预期成绩、课外投入时间，以便统计控制已知偏差来源（Marsh & Roche, 1997）。
- 解释谨慎：学生评分更多反映感知的教学质量与学习体验，需与学习结果、同侪评议、课堂观察等证据三角互证（AERA et al., 2014）。
- 条目表述尽量避免双重否定与反向题，以减少理解偏差；提供NA以降低强迫作答偏差。

十、实施与本地化建议
- 依据本校《大学英语》培养目标（如B1至B2）对F维度表述作本地化微调。
- 若课程细分为学术英语、口语强化、写作强化班，可在C与D维度中增加与该子领域高度贴合的条目（如写作反馈的语言与内容双评分明确性）。

参考文献（APA第7版）
- AERA, APA, & NCME. (2014). Standards for educational and psychological testing. American Educational Research Association.
- Bachman, L. F., & Palmer, A. S. (1996). Language testing in practice: Designing and developing useful language tests. Oxford University Press.
- Biggs, J. (1996). Enhancing teaching through constructive alignment. Higher Education, 32, 347–364.
- Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education, 5(1), 7–74.
- Council of Europe. (2020). Common European framework of reference for languages: Learning, teaching, assessment—Companion volume. Council of Europe.
- DeVellis, R. F. (2017). Scale development: Theory and applications (4th ed.). SAGE.
- Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112.
- Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis. Structural Equation Modeling, 6(1), 1–55.
- Likert, R. (1932). A technique for the measurement of attitudes. Archives of Psychology, 140, 1–55.
- Marsh, H. W. (1982). SEEQ: A reliable, valid, and useful instrument for collecting students’ evaluations of university teaching. British Journal of Educational Psychology, 52(1), 77–95.
- Marsh, H. W., & Roche, L. A. (1997). Making students’ evaluations of teaching effectiveness effective. American Psychologist, 52(11), 1187–1197.
- McDonald, R. P. (1999). Test theory: A unified treatment. Lawrence Erlbaum.
- Messick, S. (1995). Validity of psychological assessment. American Psychologist, 50(9), 741–749.
- Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
- Uttl, B., White, C. A., & Wong, G. (2017). Meta-analysis of faculty’s teaching effectiveness: Student evaluation of teaching ratings and student learning are not related. Studies in Educational Evaluation, 54, 22–42.

附注
- 本表为通用版本，建议先在1–2学期内开展小规模试点，收集量表性能证据后再定版。对条目进行本地化时请保留维度结构与评分框架，以便跨学期纵向比较。

论点陈述
本反馈表旨在以高测量质量、可解释性与公平性为原则，系统收集学生对王老师课堂教学的证据，覆盖课程设计、教学清晰度、学习促进、评价与反馈、学习收获以及课堂氛围等关键维度。设计遵循教育与心理测量标准，采用经验证的维度结构与李克特量表，配套明确的施测、评分与证据收集方案，以支持对教学的改进性决策与谨慎的评价性使用（AERA, APA, & NCME, 2014; Marsh, 1982; Messick, 1995）。

一、设计原则与证据依据
1. 结构效度与内容代表性：维度参考学生教学评价经典模型（如SEEQ）与实践共识，确保题项覆盖课程目标-教学-评价一致性、师生互动、反馈质量与学习收获等核心构念（Marsh, 1982; Marsh & Roche, 1997）。
2. 反应过程与量表设计：采用5点李克特同意度量表并提供“不适用/未涉及”，减少猜测性作答与测量误差（Likert, 1932; Tourangeau, Rips, & Rasinski, 2000）。
3. 多元证据汇聚：强调学生反馈应与同侪听评课、教学材料分析与学习结果证据共同使用，以控制单一来源偏差与难度/评分宽严影响（Kane et al., 2013; AERA et al., 2014）。
4. 公平与偏差控制：在解释与使用上控制班级规模、课程层级、预期成绩与投入等协变量；开展差异项功能分析以检视群体公平（AERA et al., 2014）。
5. 谨慎解释学习成效：据实证研究，学生评分与实际学习增益相关性有限，应避免将其作为学习成效的直接替代（Uttl, White, & Wong Gonzalez, 2017）。

二、量表结构与作答方式
1. 量表维度与题量
- 课程设计与组织（4题）
- 教学清晰度与可理解性（4题）
- 学习促进与互动（4题）
- 作业、测评与反馈（4题）
- 学习收获与自我效能（3题）
- 教学环境与尊重（3题）
- 综合评价（2题）
合计24个闭合题，另设开放题。控制答卷时长约5–8分钟，有利于作答质量与完成率（Krosnick, 1991）。

2. 作答选项（闭合题）
1=强烈不同意；2=不同意；3=中立/不确定；4=同意；5=强烈同意；不适用/未涉及

三、施测与评分建议
1. 施测时点与方式
- 时间：学期末最后1–2周；不在考试当堂施测，避免压力与印象偏差。
- 方式：匿名、线上优先；教师不在场；明确用途与保密声明。
2. 计分与解释
- 维度得分为该维度题项的平均分；不计入“不适用/未涉及”。
- 维度分需至少回答50%题项方计算；综合得分为各维度平均。
- 报告以均值±标准差与样本量呈现，同时给出校内同类课程参考分布。
- 小样本班级（如n<10）避免用于人事决策，仅作改进性参考（AERA et al., 2014）。
3. 协变量收集与分析
- 出勤比例、每周投入时长、修读属性（必修/选修）、预期成绩、课程难度感知用于解释性分析与横向比较时的统计控制（Benton & Cashin, 2012）。

四、信效度与公平性保障方案
1. 内容效度：基于教学目标与课程实践对照编制；由3–5名学科与教学专家复审；进行5–8名学生认知访谈以验证题意理解（AERA et al., 2014）。
2. 内部一致性：对各维度计算McDonald’s ω与Cronbach’s α，建议ω或α≥0.70用于群体改进，≥0.80用于较重要决策（Nunnally & Bernstein, 1994）。
3. 结构效度：进行验证性因子分析（CFA），检验六维结构（CFI/TLI≥0.90，RMSEA≤0.08作为参考）。
4. 公平性与偏差：检视不同群体（性别、年级、课程属性）测量等值性与差异项功能（DIF）；监测极端天花板/地板效应与排列式作答（Krosnick, 1991）。
5. 效标关联：与同侪听评课评分、教学材料评审、学习成果证据进行相关分析，避免以课程打分宽严或课业轻重作为唯一解释。

五、数据使用与反馈
- 以改进为先：优先向王老师提供维度性反馈与可操作建议，辅以历年趋势。
- 三角验证：用于职评或奖项时，须与多元证据合并判定（Kane et al., 2013）。
- 透明沟通：向学生公开用途与保护措施，提升参与与数据质量。

六、学生评估王老师的反馈表（可直接使用）
A. 基本信息（仅用于分析，不影响个人身份）
1) 课程名称/班级：__________    上课频次：每周__次
2) 课程属性：必修 / 选修
3) 本学期本人出勤比例：约__%
4) 每周课堂外投入时长（含预习/作业/复习）：约__小时
5) 预计课程成绩：A / B / C / 其他
6) 课程难度感知：低 / 适中 / 高

B. 闭合题（1=强烈不同意 … 5=强烈同意；不适用/未涉及）
课程设计与组织
1) 课程目标清晰且与教学活动一致。
2) 教学大纲/资料明确说明了要求与评价标准。
3) 课程内容结构合理、循序渐进。
4) 课堂节奏与课后工作量与学分相称。

教学清晰度与可理解性
5) 王老师对关键概念和步骤的讲解清楚易懂。
6) 使用示例或类比帮助理解难点。
7) 课程重点与难点被明确强调。
8) 我能识别课堂应掌握的具体技能与要求。

学习促进与互动
9) 课堂活动促进积极思考与参与。
10) 王老师鼓励提问并给予尊重与建设性回应。
11) 讨论或小组合作对我的学习有帮助。
12) 课前/课中/课后提供的学习资源能支持不同水平的学生。

作业、测评与反馈
13) 评价方式（作业/测验/考核）与课程目标保持一致。
14) 评分标准明确且在评估前已说明。
15) 反馈及时且具有可操作性，能帮助我改进。
16) 评分公正、一致。

学习收获与自我效能
17) 我对课程核心知识/技能的掌握有所提升。
18) 我将所学迁移到新情境或问题的能力有所提高。
19) 我对本领域进一步学习的兴趣或自信增强。

教学环境与尊重
20) 课堂氛围安全、包容，尊重多元观点。
21) 王老师遵守时间并有效管理课堂。
22) 王老师对学生既专业又具支持性。

综合评价
23) 总体而言，我对王老师的教学满意。
24) 如果可选，我愿意向其他同学推荐王老师的课程。

C. 开放题（请尽量具体、基于证据）
1) 本课程中最帮助你学习的2–3项做法是？
2) 你建议王老师在下次开课时优先改进的2–3项具体方面是？
3) 你仍感到困惑的概念或技能是？你希望得到何种支持？
4) 其他意见或表扬（可举例说明）。

说明与隐私
- 本问卷仅用于教学改进与课程质量提升。数据以汇总形式呈现，不反馈可识别个体信息。
- 请基于本学期的实际体验作答，避免因单次事件或个人好恶产生整体性判断。

七、实施与解释的注意事项
- 保证匿名与自愿，避免将结果用于惩戒；在样本小于10人时不发布个体课程的对外比较结果。
- 报告维度分时附带置信区间与同侪分布，以减少过度解读单次波动。
- 将开放题做主题分析，生成可操作改进建议，并与量化结果相互印证。

参考文献（APA第7版）
- AERA, APA, & NCME. (2014). Standards for educational and psychological testing. American Educational Research Association.
- Benton, S. L., & Cashin, W. E. (2012). Student ratings of teaching: A summary of research and literature (IDEA Paper No. 50). The IDEA Center.
- Kane, T. J., McCaffrey, D. F., Miller, T., & Staiger, D. O. (2013). Have we identified effective teachers? Validating measures of effective teaching using random assignment. MET Project, Bill & Melinda Gates Foundation.
- Krosnick, J. A. (1991). Response strategies for coping with the cognitive demands of attitude measures in surveys. Applied Cognitive Psychology, 5(3), 213–236.
- Likert, R. (1932). A technique for the measurement of attitudes. Archives of Psychology, 140, 1–55.
- Marsh, H. W. (1982). SEEQ: A reliable, valid, and useful instrument for collecting students’ evaluations of university teaching. British Journal of Educational Psychology, 52(1), 77–95.
- Marsh, H. W., & Roche, L. A. (1997). Making students’ evaluations of teaching effectiveness effective. American Psychologist, 52(11), 1187–1197.
- Messick, S. (1995). Validity of psychological assessment: Validation of inferences from persons’ responses and performances as scientific inquiry into score meaning. American Psychologist, 50(9), 741–749.
- Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
- Tourangeau, R., Rips, L. J., & Rasinski, K. (2000). The psychology of survey response. Cambridge University Press.
- Uttl, B., White, C. A., & Wong Gonzalez, D. (2017). Meta-analysis of faculty’s teaching effectiveness: Student evaluation of teaching ratings and student learning are not related. Studies in Educational Evaluation, 54, 22–42.

附：若需本量表的电子版与自动计分模板（含缺失值处理与信度分析脚本），可告知施测平台与数据格式（如CSV、XLSX、LMS导出字段），我可据此提供对接方案与质量监测指标。

Statement of purpose
This instrument is designed to obtain high-quality student feedback on a Project Management course. The measure emphasizes constructs with established relevance in course evaluation (e.g., clear goals and standards, good teaching, appropriate assessment and workload, development of generic skills), adapted to the project management domain (Marsh, 1982; Marsh & Roche, 1997; Ramsden, 1991; Richardson, 2005). Items are mapped to a multi-dimensional structure to enable reliable subscale scores and actionable diagnostics. A five-point, positively keyed Likert format is used to reduce response error and facilitate interpretation (DeVellis, 2016). Self-efficacy items reflect evidence that perceived capability is a sensitive indicator of learning gains when constructed with domain specificity (Bandura, 2006).

Administration guidance
- Target respondents: Students enrolled in the Project Management course.
- Timing: Last two weeks of the term, ideally after major assignment feedback but before final grades are posted, to reduce grade-related bias (Spooren et al., 2013).
- Anonymity: Responses are anonymous; results will be reported in aggregate. Do not collect directly identifying information.
- Estimated completion time: 8–10 minutes.
- Response scale: Unless otherwise noted, use 1–5 Likert options: 1 = Strongly disagree; 2 = Disagree; 3 = Neither agree nor disagree; 4 = Agree; 5 = Strongly agree; plus Not applicable (N/A).

Student feedback on Project Management course (instrument)
Instructions: Please indicate your agreement with each statement about this course. Select N/A if the item does not apply to your experience.

Section A. Course design and alignment
A1. The intended learning outcomes were clearly stated at the outset.
A2. Weekly topics and activities were logically sequenced to support learning.
A3. There was clear alignment between learning outcomes, teaching activities, and assessments.
A4. The course schedule, deadlines, and expectations were communicated clearly.

Section B. Instruction and facilitation
B1. The instructor explained complex project management concepts clearly.
B2. The instructor encouraged questions and active participation.
B3. Feedback on my work was timely and helped me improve.
B4. Examples and cases effectively connected theory to real project contexts.

Section C. Assessment and standards
C1. Assessment tasks validly measured the intended learning outcomes.
C2. Rubrics/criteria for major assignments were provided and clear in advance.
C3. Grading was fair and applied consistently across students/teams.
C4. Academic integrity and collaboration expectations were clear.

Section D. Team-based project experience
D1. Team formation and role expectations were established fairly.
D2. Mechanisms existed to address team conflict and workload imbalance (e.g., team contracts, escalation paths).
D3. Peer evaluation processes, if used, contributed to fair recognition of contributions.
D4. My team applied core PM processes effectively (e.g., scope, schedule, risk, quality).
D5. The team project meaningfully integrated stakeholder engagement and communication practices.

Section E. Application of PM tools and methods
E1. I had sufficient opportunities to practice key PM techniques (e.g., WBS, scheduling, budgeting, risk analysis).
E2. I developed skill using relevant PM tools/software (e.g., MS Project, Jira, Trello), as appropriate for the course.
E3. The course addressed selecting and tailoring life cycles (predictive, agile, hybrid) to project context.
E4. The course provided useful templates or standards (e.g., charters, risk registers, status reports).

Section F. Learning resources and environment
F1. Readings and resources (e.g., PMBOK, standards, cases) were current and relevant.
F2. The learning environment supported inclusive, respectful, and psychologically safe participation.
F3. Access to required tools, data, or platforms was adequate.

Section G. Workload, pacing, and modality
G1. The workload was appropriate for the course’s credit value.
G2. The pacing allowed time to absorb and apply new material.
G3. The course design functioned well in this delivery mode (face-to-face, online, or hybrid).

Section H. Learning gains and self-efficacy in project management
H1. I can plan and baseline a project’s scope, schedule, and budget.
H2. I can identify, analyze, and plan responses to project risks and issues.
H3. I can lead and contribute effectively in project teams.
H4. I can tailor project management approaches to different project contexts and constraints.
H5. I can communicate progress, risks, and decisions to stakeholders using appropriate artifacts and cadence.

Section I. Overall evaluation
I1. Overall, this course improved my capability to manage projects.
I2. I would recommend this course to other students.
I3. Net Promoter item (0–10 scale): How likely are you to recommend this course to a peer? 0 = Not at all likely; 10 = Extremely likely.

Section J. Open-ended questions
J1. Which aspects of the course most supported your learning, and why?
J2. Which aspects hindered your learning, and how could they be improved?
J3. How could the team project experience (e.g., formation, coordination, assessment) be improved?
J4. Which topics or skills should receive more or less emphasis in future offerings?
J5. Additional comments for the instructor or program.

Section K. Background (optional; for group-level analysis only)
K1. Program/major and level (e.g., undergraduate, master’s, doctoral).
K2. Prior project management coursework/certifications (e.g., none; completed a PM course; CAPM/PMP).
K3. Approximate years of project-related work experience (0; 1–2; 3–5; 6+).
K4. Typical weekly time spent on this course outside class (0–3; 4–6; 7–9; 10+ hours).
K5. Course delivery mode experienced (face-to-face; online; hybrid).
K6. Typical team size in this course (2–3; 4–5; 6+).

Scoring and use
- Subscale formation: Compute mean scores (excluding N/A) for each section to create subscales: Design (A), Instruction (B), Assessment (C), Team Project (D), Tools/Methods (E), Resources/Environment (F), Workload/Pacing/Modality (G), Learning Gains/Self-efficacy (H), Overall (I1–I2). The NPS item (I3) is reported separately.
- Reliability: For internal quality monitoring, estimate internal consistency (e.g., omega or Cronbach’s alpha) for each subscale; values near or above .70 are acceptable for early-stage use, with higher thresholds for consequential decisions (Nunnally & Bernstein, 1994; DeVellis, 2016).
- Validity and bias checks:
  - Content validity is supported by mapping items to established course evaluation constructs and PM competency frameworks (Marsh, 1982; Ramsden, 1991; Project Management Institute, 2021).
  - Conduct periodic factor analyses to verify the expected multidimensional structure and refine items (Richardson, 2005; Spooren et al., 2013).
  - Compare subscale functioning across delivery modes and student subgroups (measurement invariance) before comparing means.
  - To reduce common-method bias, include both evaluative (A–G) and capability self-reports (H), keep instructions neutral, and ensure anonymity (Podsakoff et al., 2003).
- Reporting: Provide instructors with subscale means, confidence intervals, item-level distributions, and synthesized themes from open-ended responses. Emphasize diagnostic use (improvement) rather than solely summative judgments (Marsh & Roche, 1997).
- Continuous improvement: Pilot new or revised items, review item-total correlations, remove low-performing items, and refresh examples/resources to align with current standards (e.g., PMBOK 7th edition).

Rationale for key design choices
- Multidimensional structure: Research supports treating student evaluations as multi-faceted (e.g., clear goals, teaching quality, workload, assessment) rather than a single global score; this enhances actionability and validity (Marsh, 1982; Ramsden, 1991; Marsh & Roche, 1997).
- Positive, consistently keyed Likert items: This reduces respondent confusion and measurement error common with reverse-worded items (DeVellis, 2016).
- PM-specific self-efficacy outcomes: Domain-specific self-efficacy is a sensitive, educationally meaningful indicator of perceived learning gains when items are anchored in observable capabilities (Bandura, 2006), here aligned with core PM practices (Project Management Institute, 2021).
- Team dynamics and psychological safety: Because team projects are central to PM courses, items addressing conflict resolution, peer evaluation, and inclusive climates target known drivers of learning in teams (Edmondson, 1999).

Ethical and operational considerations
- Participation should be voluntary and non-coercive; communicate that results are used for course improvement and program review.
- Ensure accessibility (mobile-friendly, plain language) and data protection consistent with institutional policies.
- For high-stakes personnel decisions, triangulate with multiple evidence sources (e.g., peer review of teaching, direct assessment of student learning) to mitigate known limitations of student ratings (Richardson, 2005; Spooren et al., 2013).

References
Bandura, A. (2006). Guide for constructing self-efficacy scales. In F. Pajares & T. Urdan (Eds.), Self-efficacy beliefs of adolescents (pp. 307–337). Information Age.

DeVellis, R. F. (2016). Scale development: Theory and applications (4th ed.). Sage.

Edmondson, A. C. (1999). Psychological safety and learning behavior in work teams. Administrative Science Quarterly, 44(2), 350–383. https://doi.org/10.2307/2666999

Marsh, H. W. (1982). SEEQ: A reliable, valid, and useful instrument for collecting students’ evaluations of university teaching. British Journal of Educational Psychology, 52(1), 77–95. https://doi.org/10.1111/j.2044-8279.1982.tb02505.x

Marsh, H. W., & Roche, L. A. (1997). Making students’ evaluations of teaching effectiveness effective: The critical issues of validity, bias, and utility. American Psychologist, 52(11), 1187–1197. https://doi.org/10.1037/0003-066X.52.11.1187

Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.

Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879

Project Management Institute. (2021). A guide to the project management body of knowledge (PMBOK guide) (7th ed.). Project Management Institute.

Ramsden, P. (1991). A performance indicator of teaching quality in higher education: The Course Experience Questionnaire. Studies in Higher Education, 16(2), 129–150. https://doi.org/10.1080/03075079112331382944

Richardson, J. T. E. (2005). Instruments for obtaining student feedback: A review of the literature. Assessment & Evaluation in Higher Education, 30(4), 387–415. https://doi.org/10.1080/02602930500099193

Spooren, P., Brockx, B., & Mortelmans, D. (2013). On the validity of student evaluation of teaching: The state of the art. Review of Educational Research, 83(4), 598–642. https://doi.org/10.3102/0034654313496870