Baseline and Endline AI Reflection

In this assignment, students completed a reflection at the beginning and end of the course to examine their assumptions, sense of agency, and relationship with AI. They could choose to complete the reflection using a traditional document, an AI-supported conversation, or a combination of both. 

Author: Dr. Christyna Serrano (“Dr. C”) – Course Instructor; Presidential Chair Fellow. Haas School of Business; part of the Berkeley Changemaker program. Dr. C also teaches across the Sutardja Center for Entrepreneurship & Technology (College of Engineering) and the Berkeley School of Education.

Course Number & Title: UGBA C12 / C196C — The Berkeley Changemaker Gateway (cross-listed with the College of Letters & Science)

This work is licensed under CC BY-NC-SA 4.0

Details
Assignment Title
 		Baseline and Endline AI Reflection
Delivery FormatOnline asynchronous instruction
Learning Objectives
  • Exercise AI agency: make purposeful, transparent choices about when AI supports learning, when it may hinder it, and when not to use it at all.
  • Establish an honest baseline of their current ideas, assumptions, hopes, and tensions about changemaking, agency, and technology — before course content shapes their thinking.
  • Name their relationship to AI: articulate what they would and would not want AI-supported learning to do, and what would make them trust or distrust it.
  • Treat choice as reflection: experience selecting between equivalent AI and non-AI pathways as a deliberate act rather than a default.
Brief Summary of Assignment

In Week 1, the Baseline Reflection asks students to capture “where they are entering from” — their assumptions, sense of agency, formative spaces, and current relationship to AI — before course content shapes them. What makes it AI-informed is choice: students answer the same 14 questions via a non-AI Google Doc, a Playlab voice-reflection bot, a Gemini self-interview, or a hybrid. Every pathway ends identically — answers in the student’s own voice, submitted as a PDF. Deciding whether and how to use AI is itself the lesson. 

In Week 6, an Endline Reflection returns students to the same questions.

Impact & FeedbackEven in the opening days, it has been striking to see who reaches for AI and who doesn’t — and students’ answers to “what would you want AI-supported learning to do for you?” have been genuinely insightful. Offering a real opt-out appears to make students more deliberate about when AI actually serves their learning.
Step-by-Step Instructions

Setting it up (instructor):

  1. Write one set of reflection questions (here, 14 across six parts) phrased so they can be answered again at the end of the term for a matched “baseline → endline” comparison.
  2. Build a single canonical template (a Google Doc or Form) that every pathway feeds into, so the deliverable is identical regardless of route.
  3. Offer parallel pathways to the same endpoint: a non-AI Google Doc; a Playlab bot that interviews students one question at a time (voice input supported), confirms each answer reflects their words, and exports a compiled document; a Gemini self-interview students then autofill and personally edit; or any hybrid.
  4. Keep it low-stakes (credit/no-credit on completeness and specificity) so honesty, not performance, is rewarded — and so the AI/no-AI choice carries no grade incentive.
  5. Add a brief transparency note asking students to record which pathway they used and why.

What students do:

  1. Choose a pathway (non-AI, Playlab, Gemini, or hybrid).
  2. Answer all 14 questions in their own words.
  3. Export to PDF and open it to confirm it is complete and readable.
  4. Submit the PDF on the assignment page by the Week 1 midweek deadline.
Grading or AsssessmentCredit/no-credit based on completeness and specificity: every question answered thoughtfully, in the student’s own voice. It is not graded on opinions, on the “right” answer, or on whether AI was used.
Assignment Details
  • Baseline Reflection template — 14 questions across six parts (changemaking; agency & constraint; the Three Cs; formative spaces; me and AI; early sparks).
  • Canvas course page describing the four pathways and the shared PDF submission.
  • Playlab Baseline Reflection bot: playlab.ai/embedded/cmr8tc3sw5u2umh0w6xeljdjz
  • Baseline Reflection rubric (credit/no-credit).
  • Related syllabus section: “AI Agency, Choice, and Transparency” (frames why every AI activity has a non-AI pathway).
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