Skip to Main Content

Green River College AI Taskforce

Empowering education through responsible AI integration
Level 3 Assignment Toolkit: AI Collaboration

Level 3 Assignment Toolkit: AI Collaboration

3

Assignments That Invite AI Into the Process

Level 3 assignments focus on students revising, reflecting, and collaborating using AI tools. The final output is primarily student-led, with AI serving as a collaborative partner in the learning process.

3

AI Collaboration Assignments

Level 3 assignments emphasize student ownership while incorporating AI as a collaborative tool. Students engage in an iterative process where they maintain creative control while leveraging AI to enhance their work and develop critical evaluation skills.

Iterative Process

Students work through multiple drafts, using AI feedback to improve their work.

Student Ownership

Students maintain creative control and decision-making throughout the process.

Transparent Documentation

Students document AI interactions and reflect on how they shaped their work.

Assignment Workflow

1

Students Create Initial Draft

Students begin with their own ideas and create a first draft independently.

2

AI Collaboration

Students engage with AI tools for feedback, suggestions, or to explore alternatives.

3

Student Revisions & Reflections

Students critically evaluate AI input, make revisions, and reflect on the process.

Faculty Checklist: When to Use Level 3 Assignments

Consider implementing Level 3 AI collaboration assignments when your course objectives include any of the following:

Faculty Tip: Level 3 assignments work best when students have clear guidelines for how to document their AI interactions and specific criteria for evaluating the effectiveness of their collaboration with AI tools.

Design Tips for AI Collaboration Assignments

Implement these strategies to create effective Level 3 assignments

Document the Process

Require students to maintain a log of their AI interactions, including prompts used, responses received, and decisions made about incorporating AI suggestions.

Require Critical Reasoning

Ask students to explain why they accepted or rejected specific AI suggestions, encouraging them to develop criteria for evaluating AI contributions.

Include Reflection Components

Build in opportunities for students to reflect on how AI collaboration affected their learning process and final product compared to working independently.

Assess the Process

Evaluate both the final product and the documented process, including how effectively students engaged with AI tools and applied critical thinking to their work.

Level 3 Assignment Toolkit: AI Collaboration

Level 3 Assignment Toolkit: AI Collaboration

Empower students to work with AI as a collaborative tool while developing critical thinking and digital literacy skills

Why Faculty Love This Toolkit

7+
Assignment Templates

Ready-to-use across disciplines

15
Reflection Prompts

For various learning styles

200+
Feedback Comments

Ready-to-use statements

Cross-Disciplinary Application

Designed for any discipline and course level, with examples from Psychology, Biology, Math, and more.

Streamlined Assessment

Four adaptable rubric models (analytic, reflective, contract, and comparative) plus feedback tools to make grading efficient.

Digital Literacy Development

Cultivates essential student skills in evaluating AI-generated content while emphasizing transparency and ethical engagement.

Reflection-Focused

Over 6 distinct feedback tools including feedback ladders, plus/delta reflections, self-assessment scorecards, and peer AI use audits.

Explore the Level 3 Assignment Toolkit

PSYCHOLOGY

Research Proposal

Students develop a research proposal on social media's impact, using AI for clarity and coherence while ensuring original content. They submit original and AI-assisted drafts with a reflective commentary.

BIOLOGY

Lab Report

Students write a lab report on an experiment, using AI to improve clarity and organization without altering scientific accuracy. They submit original and AI-enhanced drafts with a reflective commentary.

MATHEMATICS

Problem Set Refinement with AI

Students solve a problem set, then use AI to review their steps, identify errors, and explore alternate approaches, reflecting on the process.

ASSESSMENT

Rubric Library

This library offers different rubric models (analytic, reflective, contract, comparative) for assessing AI-collaborative assignments. They focus on evaluating the integration of AI and student work, revision quality, student voice, and ethical transparency.

REFLECTION

Guided Reflection Worksheet

A worksheet for students to track and document their use of AI tools during an assignment, promoting transparency and ethical engagement.

COLLABORATION

Group Reflection Protocols

Structured protocols to guide meaningful group discussions and reflections after assignments that may have involved AI tools, collaboration, or creative exploration.

Already assigning something? Add these layers for collaboration.

Compare Drafts in Peer Review

Have students generate an AI draft alongside their own, then compare both during peer review sessions to identify strengths and weaknesses.

Annotated Bibliographies w/ AI Output

Students can generate AI summaries of sources, then critically evaluate and revise these summaries for their annotated bibliographies.

AI Coaching with Human Reflection

Encourage students to use AI as a writing coach, documenting the feedback received and reflecting on how they implemented or challenged it.

Level 3 assignments help students revise thoughtfully, engage ethically with AI, and reflect on their writing process. They emphasize transparency, student ownership, and metacognition.

By incorporating AI collaboration into assignments, students develop critical digital literacy skills while learning to leverage AI as a tool rather than a replacement for their own thinking. These assignments create opportunities for students to:

  • Compare their writing with AI-generated content
  • Make informed decisions about revisions
  • Document their process transparently
  • Reflect on the strengths and limitations of AI in academic contexts
  • Develop transferable skills for working with emerging technologies

Contact & Support