Reviewer Survey: Course Quality & Experience

Questions 1–34 are multiple choice (Yes / Mostly / Partially / No unless otherwise noted). Question 35 is an open-ended essay response. Rationale: items 1–34 support easy analysis, while the essay lets reviewers share overall thoughts.

What to Expect

34 multiple-choice items + 1 essay question
No time limit; complete at your own pace
Responses are not anonymous (we collect data for analysis)
You may preview all questions before engaging with the course content

Survey Questions

Which of the four modules did you review? (mark all that apply): Part 1, Part 2, Part 3, Part 4
Would you consider the course student learning outcomes stated in the syllabus measurable? [Outcomes & Alignment]
- After completing the course, you will be able to:
  - Describe the basics of AI and point out what generative AI can and can’t do.
  - Plan and test AI help for a school task, a work task, and a personal task; compare results with and without AI.
  - Use an ethics checklist to judge an AI example, list risks (privacy, bias, giving credit), and suggest fixes.
  - Write and improve an AI prompt through at least two revisions, then check if the output meets a given checklist.
  - Complete a multi-step real task with two AI tools and submit a short write-up of what you did and what worked.
Are outcomes in each module’s learning content, activities, and knowledge checks clearly stated and aligned with the course outcomes? [Outcomes & Alignment]
Is there a clear skills progression (intro → practice → mastery) across each of the modules? [Outcomes & Alignment]
Do the learning outcomes clearly include AI skills such as understanding model limits, checking output quality, and using AI responsibly? [Outcomes & Alignment]
Is the basic AI content in the Foundations module explained in clear, everyday language with simple examples so a beginner can follow? [Content Accuracy & Currency]
For each module topic, are the examples and case studies up to date and relevant to today’s AI tools? [Content Accuracy & Currency]
Are things like AI “making things up” (hallucinations), bias, and how prompts change results shown with clear explanation and examples? [Content Accuracy & Currency]
Does the course warn that AI changes quickly and that some instructions or examples may become outdated—and explain how to handle those changes? [Content Accuracy & Currency]
Did you feel the course explicitly addressed fairness, bias, and harm mitigation (e.g., dataset bias, disparate impact)? [Responsible/Ethical AI]
Does the course explain ethics—transparency, accountability, explainability, and safety—and give clear steps to put them into practice? [Responsible/Ethical AI]
Was there enough clear guidance and short activities in the AI for Students module to show how to use AI responsibly (e.g., do/don’ts, brief scenarios, a simple checklist)? [Responsible/Ethical AI]
Was there enough clear guidance on how students should cite AI tools and disclose AI assistance in their work? [Responsible/Ethical AI]
Do the hands-on try-its and knowledge checks align to help participants build and check their understanding of what they learned in a module? [Assessment & Academic Integrity with AI]
Is it clear that participants are encouraged to choose any AI tool and practice the skills taught? [Assessment & Academic Integrity with AI]
Were any optional tips offered for safe/effective use (e.g., privacy reminders, what to share/not share)? [Assessment & Academic Integrity with AI]
Was there enough guidance to promote responsible use and avoid misuse of AI tools (e.g., privacy reminders, acceptable-use examples, basic fact-checking steps)? [Assessment & Academic Integrity]
Did you experience any accessibility problems with headings, lists, links, images (alt text), tables, or media while reviewing the course? [Accessibility & UDL]
Based on your review, did the videos include accurate captions and transcripts? [Accessibility & UDL]
Was there enough variety in formats to engage with the content and practice (e.g., video, text, code, diagrams)? [Accessibility & UDL]
Were the external links you tried functional (they opened as expected)? [Accessibility & UDL]
Did the course card image, front page, and orientation module feel welcoming and clearly explain how to get started and participate? [Canvas Organization & Clarity]
Was it clear that this course is fully asynchronous and does not include instructor or peer interaction? [Canvas Organization & Clarity]
Was there enough clear guidance warning participants not to enter sensitive or personally identifiable information into AI tools? [Data, Privacy, and Safety]
Did you feel you had enough guidance to choose and use an AI tool safely (e.g., privacy settings, account/log-in considerations, what to do if something seems unsafe)? [Data, Privacy, and Safety]
Do the examples and datasets avoid stereotypes and explain their limits or biases? [Equity, Inclusion, & Belonging]
Did you feel the readings and case studies included enough diverse perspectives? [Equity, Inclusion, & Belonging]
Did you feel there was enough setup and troubleshooting guidance (e.g., step-by-step tips, screenshots, or short clips) to try different AI tools? [Tooling & Technical Readiness]
Did you feel the directions were clear and sufficient to complete each activity on your own (e.g., where to start, steps to follow, what to try, how to know you’re done)? [Tooling & Technical Readiness]
Did you feel the overall course content was sufficient to understand the topics (clear explanations, examples, definitions)? [Evidence of Learning & Evaluation]
Did you feel the hands-on activities were sufficient to practice and check your understanding? [Evidence of Learning & Evaluation]
With the understanding that each module was designed for ~3 hours of engagement, did the amount of content and activities feel reasonable? [Workload, Pacing, & Support]
This course expectation is about 9 hours of engagement. With that in mind, did the pacing feel manageable?[Workload, Pacing, & Support]
If you sought technical assistance, did the support you received meet your needs in a timely and helpful way?[Workload, Pacing, & Support]
(Essay): Please share feedback about your review experience: what felt clear and useful, what felt insufficient (content or hands-on), and one quick win and one higher-effort change you’d recommend. Include any specific pages or activities if helpful.

Thank you for your careful review—your input directly informs course improvements.