Build AI literacy into real coursework

Students are already using AI. AI Integrated Assignments give them a structured place to learn to use it well, while turning critical thinking, communication, and judgment into work instructors can evaluate and grade at scale.

See it in action View assignment types

Make student thinking visible, even when AI is part of the work.

When students use AI, the final submission only tells part of the story.

AI Integrated Assignments capture the process: students plan, evaluate, verify, revise and challenge AI output as part of the assignment, leaving a record of every decision.

AI flags how well a student explained an idea, then grading moves to the instructor, who applies the rubric and sees the full record of how the student reached their answer.

Designed to keep students doing the thinking.

Every AI Integrated Assignment follows a shared set of design principles. AI has a role in the work, but students remain responsible for the reasoning, judgment, and decisions behind it.

  • Students start with their own ideas

    Students state a position or plan before AI enters the task, giving instructors a baseline of what each student brought to the work.

  • Students critically evaluate AI output

    Assignments deliberately introduce cognitive challenges and desirable difficulties so students engage with AI output rather than simply offloading the work.

  • Students make their own decisions

    Students make meaningful choices throughout the assignment. A “show your work” view surfaces draft history, transcripts, prompt logs, and reflections so instructors can see those decisions in context.

  • Students reflect on how their thinking changed

    Reflection happens within the work and connects to decisions the student actually made, like a claim they changed, a suggestion they rejected, or a challenge that shifted their thinking.

Build AI literacy across the curriculum.

AI literacy isn’t one skill, and it shouldn’t be taught through one kind of assignment. AI Integrated Assignments give instructors multiple ways to build meaningful AI use into existing coursework, from defending an argument to verifying claims against source material to making intentional decisions while writing with AI.

Conversational Reasoning

Students talk with an AI that asks questions and pushes back.

Close Reading and Analysis

Students check what AI says against a real source.

Co-Writing with AI

Students write with AI while making their choices visible.

  • Assignment type

    Teach the AI

    Students explain a concept to a novice AI and correct its errors, demonstrating their understanding as they teach. The AI evaluates the student’s understanding against a concept map.

    Interactive demo
  • Assignment type

    Argument Lab

    Students lock in a position, then defend it against AI-generated counterarguments aimed at their specific claims.

  • Assignment type

    Claim–Source Verification

    AI makes claims about a source selected by the instructor. Students determine whether each claim is accurate, misleading, or false, and support their judgment with evidence from the text.

  • Assignment type

    Co-Authored Essay

    Students plan first, then accept, rewrite, or reject AI suggestions paragraph by paragraph. Their decision record becomes part of the work they submit.

See how students think, use AI, and make decisions.

Instructors don’t just see the final answer. They see how a student reasoned, where AI came in, and what the student decided to do with it.

  • Student Thinking

    Planning, reasoning, evidence use, revision, and reflection.

  • The Role of AI

    What AI generated, challenged, summarized, or suggested.

  • Student Agency

    What students accepted, revised, verified, clarified, or pushed back against.

Assess the process,
not just the final answer.

The final product still matters. But when students work with AI, the path they took to get there matters, too.

AI Integrated Assignments capture that path as part of the coursework, giving instructors more visibility into how students reason, use evidence, respond to feedback, and exercise judgment while working with AI.

  1. 1

    Think

  2. 2

    Interact with AI

  3. 3

    Make Decisions

  4. 4

    Reflect

  5. 5

    Submit Work

Benefits across the institution.

  • For Faculty

    The “show your work” dashboard surfaces draft history, prompt logs, and reflections at a glance, so faculty spend their judgment on ideas and reasoning.

  • For Students

    Students learn to direct, challenge, and co-create with AI, building the judgment employers now expect. Over 55% of students report more confidence in their writing with rubric-aligned scaffolding.

  • For Administrators

    Bring a shared approach to AI literacy across programs. Instructors get assignments that fit their existing courses while the institution gets consistent evidence of how students use AI.

Built for higher education.

AI Integrated Assignments work within the systems institutions already use, with the privacy and security standards higher education expects.

  • LMS-Native

    LTI 1.3 support for Canvas, Blackboard, and D2L Brightspace, with SSO.

  • Privacy

    FERPA and COPPA compliant.

  • Security

    SOC 2 Type II certified infrastructure.

  • Data Trust

    Student data is never sold or used to train AI models.

FAQs

How do AI Integrated Assignments build AI literacy?

Each assignment requires students to evaluate, verify, revise, or challenge AI output rather than accept it. Students practice judgment, explanation, coordination, and agency inside real coursework, and every decision becomes visible evidence an instructor can grade.

Do faculty need to redesign their courses to use AIA?

No. AI Integrated Assignments drop into existing courses through LTI 1.3 Advantage integrations with Canvas, Blackboard, and D2L Brightspace. Faculty assign them the same way they assign any other coursework, with SSO for students.

What do instructors see when students work with AI?

Instructors see the student’s plan before AI entered the task, the full record of what AI generated, and every decision the student made: claim ratings, evidence selections, revisions, and responses to challenge. Reflections tie directly to those specific moments.

How do AI Integrated Assignments support academic integrity?

Visible process evidence answers the authorship question constructively. When instructors can see planning, drafting, revision, and the decision trail behind AI collaboration, they evaluate real thinking with confidence and students build a verifiable authorship record.

Which assignment types are available now?

Teach the AI (Conversational Reasoning) is in beta now, and Argument Lab will be available by the end of the Fall. Close Reading and Analysis (Claim-Source Verification) and Co-Writing with AI (Co-Authored Essay) arrive in 2027.

Is student data used to train AI models?

No. Packback never sells student data or uses it to train foundation AI models. The platform is FERPA and COPPA compliant and runs on SOC 2 Type II certified infrastructure.

What is learning intelligence?

Learning intelligence is the continuous collection and interpretation of evidence about how learning is happening, used to improve teaching, learning, and assessment. AI Integrated Assignments are one of the instruments Packback, the Learning Intelligence Platform, uses to generate that evidence.

See AI Integrated Assignments in Action

Help students learn how to think with AI, rather than surrendering their thinking.

AI isn’t leaving the classroom. The opportunity is to design coursework that asks students to use it with intention, judgment, and accountability.

AI Integrated Assignments make those skills part of the work, and make the thinking behind that work visible to instructors.

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