James D’Annibale, Director of Academic Technology

Written with help from ChatGPT to organize examples and bring consistency to the structure and tone.

*Academic Technology would like to thank the following Dickinsonians for their contributions to this page whether through direct edits or constructive conversations: Dr. Renee Cramer, Dr. Amy Steinbugler, Dr. Michel Kozimor, Dr. Kirk Anderson, Dr. Howard Rosen, and many more colleagues*

Purpose of This Guidance

Pedagogical transparency helps ensure that students:

• Understand the learning objectives behind each major assignment.
• Recognize how completing the assignment contributes to long-term intellectual and professional development.
• Are aware of which aspects of the assignment must be completed independently, and which may involve generative AI or other forms of assistance, including assistance from student peers.

This guidance is intended first and foremost to support student learning. When students understand the goals of an assignment and how they are expected to engage with it, they are better equipped to succeed. Research on pedagogical transparency has shown that when students clearly understand the purpose, tasks, and evaluation criteria of assignments, they experience greater academic confidence, stronger learning outcomes, and improved metacognitive awareness (Winkelmes, M. (2013). Transparency in Teaching: Faculty Share Data and Improve Students’ Learning. Liberal Education 99(2).). In this context, we extend the concept of transparency to a contemporary challenge: helping students navigate the appropriate use of generative AI tools. By making expectations and rationales explicit, instructors may reduce the likelihood of inadvertent academic integrity violations in this evolving landscape.

The work of athletic coaches is instructive when thinking about how pedagogical transparency can help students learn and make choices regarding shortcuts. When a student-athlete works out in the gym, it’s very clear to the student-athlete what is expected of them and how hard work and meeting/exceeding expectations will benefit them as individuals and as a member of a team. Athletes and teams that work hard in the gym and on the practice field, often see great results on the game field/arena while the opposite is true for athletes and teams that do not work hard.

The same clarity is being encouraged in this guidance document. We ought not assume that our students understand the purpose of assignments within the context of their learning or within the context of the liberal arts. Rather, we should be clearly explaining purpose, benefits, expectations, etc. so that our students truly understand why we’ve drawn whatever line in the proverbial AI sand that we’ve chosen to draw.

Guidance for Transparent Assignment Design

Faculty designing major assignments should ensure the following elements are communicated to students:

• Learning Objectives: Clearly state, in understandable terms, the specific skills or knowledge the assignment is meant to develop.
• Connection to Long-Term Learning: Briefly explain how the assignment supports the student’s academic, professional, or personal growth.
• Student-Generated Work: Indicate which portions of the assignment must be completed independently and why.
  • In some cases, it may be helpful to guide students in breaking down the assignment into steps that align with learning objectives, course content, and intended skills.
• Permitted Use of AI or Other Help: Clarify what kinds of assistance (AI tools, tutoring, peer review, etc.) are acceptable and in which stages.
  • It is often helpful to have a conversation as a community of learners to come to a collective understanding of how different types of AI use may or may not benefit student learning.
• Disclosure Requirement: If AI is permitted, explain how students should document or reflect on their use (e.g., Panopto video showing chat and having the student talk through process, appendix, in-paper note/citations, etc.).
• Invitation to Clarify: Encourage students to ask questions if they are unsure about the policy. Also, welcome students to share their own ideas for how they might use AI to enhance their learning, so that faculty can consider and respond to these suggestions constructively.
• Faculty Presence in the Process: Incorporate specific opportunities to engage with students throughout the development of the assignment (e.g., requiring outlines, holding progress check-ins, reviewing early drafts). This builds a learning relationship, supports student growth, and allows instructors to better understand the student’s thinking and voice as it evolves—helping evaluate the final product within the context of the process. The expert staff at the Writing Center and the Center for Teaching, Learning, and Scholarship are tremendous resources in this area.

Example Assignment Briefs

The examples below are intentionally brief and meant to serve as starting points.

Example 1: First-Year Seminar Research Paper

• Learning Objectives: Critical thinking, academic writing, source integration.
• Long-Term Value: Foundational for college-level writing and future coursework.
• AI Use Policy: Students may use AI for brainstorming, although brainstorming with peers will likely be more productive. All research, outlining, and writing must be done independent of AI.
• Disclosure: No AI-related reflection required since use is limited to pre-writing.
• Faculty Presence in the Process: Students are required to submit a research question and a preliminary outline for feedback before beginning the draft. A brief one-on-one check-in will also be held during the writing week.

Example 2: Environmental Case Study Presentation

• Learning Objectives: Collaborative analysis, synthesis of data, presentation skills.
• Long-Term Value: Prepares students for workplace collaboration and civic decision-making.
• AI Use Policy: AI may be used for slide design and grammar editing, but students must analyze data and draw conclusions themselves.
• Disclosure: Students must submit a transcript of their AI interactions with final materials.
• Faculty Presence in the Process: Teams must submit a draft of their slides and a one-paragraph summary of their case analysis for instructor feedback one week before the presentation.

Example 3: Literature Review in Psychology Capstone

• Learning Objectives: Academic research, synthesis of findings, discipline-specific writing.
• Long-Term Value: Directly relevant for graduate school preparation or research-based careers.
• AI Use Policy: Students may use AI to draft sections only after submitting an outline and annotated bibliography.
• Disclosure: Students must include a paragraph reflecting on how AI supported their writing process.
• Faculty Presence in the Process: Students meet with the instructor after submitting their outline and bibliography to discuss the structure of the review before any drafting begins.

Example 4: Biology Research Paper with AI Integration

• Learning Objectives: Synthesize biological concepts, interpret scientific literature, communicate findings in clear academic writing.
• Long-Term Value: Develops skills in scientific writing, critical reading, and ethical integration of digital tools—applicable in advanced coursework, lab settings, and scientific communication careers.
• AI Use Policy: Students are encouraged to use generative AI throughout the process, including brainstorming, outlining, drafting, and revising. However, students must clearly document their process and maintain responsibility for scientific accuracy and integrity.
• Disclosure: Students must submit an appendix with annotated excerpts from their AI interactions, noting what parts were AI-generated, revised, or rejected. A short reflection should describe how AI helped or hindered their understanding and writing.
• Faculty Presence in the Process: Students will meet with the instructor during the proposal, outline, and near-final stages to discuss how they are using AI, what challenges they’ve encountered, and how they’re ensuring scientific accuracy in their work.

Introducing Transparency to Students

For faculty who are beginning to integrate greater transparency about assignment design and AI use, it’s important to build trust, clarity, and student engagement. Below are some suggested steps to help introduce these concepts, especially in courses where this level of openness may not have been present previously:

• Acknowledge the Shift: Let students know that you’re working to be more explicit about expectations and learning goals. A simple statement like, “I’ve revised how I present assignments to help you better understand not just what to do, but why it matters,” can be effective.
• Explain the Rationale: Be clear about why certain parts of the assignment must be done independently, and where AI or other forms of help may be beneficial. Framing this around their long-term learning and success helps build buy-in.
• Invite Discussion: Consider hosting a short class discussion or informal survey about how students have encountered AI tools and where they might see value in using them. This gives you insight and models an open learning environment.
• Introduce Policies in Context: Rather than just listing AI rules, walk students through a specific assignment and explain which parts are meant to develop their own thinking versus where AI could be used to support workflow or clarity.
• Model Transparency: Briefly explain your instructional design choices. For example: “I’ve designed this project so that you get practice developing your own argument. That’s why the initial analysis must be your own, but I’ll let you use AI to help polish the writing after you submit your draft.”
• Stay Open to Feedback: Let students know you’re learning too. Invite them to let you know what works and where things could be clearer.

By taking time to introduce your approach and show its connection to student learning, you help reduce confusion, prevent integrity issues, and support a healthier academic environment.

Link to AI Syllabus Statement Guidance

Faculty should ensure consistency between their assignment-specific guidance and the course-wide AI policy stated in their syllabus. Sample language for syllabus policies can be found in the Sample AI Syllabus Statements document.