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Glossary

AI Glossary for Higher Education

Clear, practical definitions of AI concepts grounded in pedagogy, ethics, and real classroom use.

AI has introduced a new vocabulary to education (and not everyone asked for the lesson!)  Whether you’re a faculty member trying to understand what your institution’s AI policy actually means, an administrator evaluating tools, or an instructor wondering what “cognitive offloading” has to do with your writing assignments — you’re in the right place.

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  • Close-Ended Question

    What it means: Your question may have a yes-or-no answer.

    Close-ended questions are those that can be answered with a simple yes or no. For example, “Is the sky blue?” Packback’s AI flags these because they tend to shut conversation down rather than open it up. The best discussion questions invite multiple thoughtful perspectives and can’t be dispatched in a single word.

    What to do: Rephrase your question so it invites exploration. Instead of “Is the sky blue?” try “Could the sky appear different colors on a planet with a different atmospheric composition?” Open-ended questions generate richer discussion and deeper thinking from peers.

    Note: If you disagree with this assessment, you can dismiss the flag.

  • Cognitive Offloading

    Cognitive offloading occurs when students rely on AI to perform thinking tasks like generating ideas, constructing arguments, drawing conclusions, instead of engaging in those processes themselves.

    Why it matters: Unchecked cognitive offloading undermines learning outcomes, particularly in writing-intensive and discussion-based courses. The assignment gets done. The learning doesn’t happen.

    Instructional implication: Well-designed AI experiences reduce offloading by prompting reflection, revision, and metacognition rather than providing ready-made answers. The goal is to make thinking visible and unavoidable.

    Related: Dead Education Theory, Self-Regulated Learning

  • Cognitive Offloading

    Cognitive Offloading is the act of strategically delegating only certain tasks to AI. When a student offloads a low-level task like formatting, outlining, or debugging, they are still retaining their critical thought. They act as a manager, maintaining total ownership of the ideas. Similarly to using a calculator instead of an abacus.

  • Cognitive Surrender

    Cognitive Surrender is when a student completely delegates their thinking and critical judgment to an AI tool. Instead of using the tool to aid their workflow, they remove their own judgment from the equation entirely. As one student noted in our recent survey, this phenomenon has “severely diminished the feeling I have of the work being ‘mine.'” Cognitive Surrender is considered the fail state. 

  • Cognitive Vigilance

    The active, systematic scrutiny of AI output. It requires the student to verify reasoning, cross-reference sources, and provide a “misconception audit.” This is the design goal.

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