AI Glossary for Higher Education

Writing & Feedback

Instant Feedback

Packback’s Instant Feedback provides detailed, responsive, and actionable guidance to students as they write their discussion posts, before they submit. This feature uses AI to support Mastery Learning at scale through instant, non-punitive feedback and clear direction on how students can improve.

The goal isn’t to penalize. It’s to coach. Every flag is a prompt to reflect, not a mark against a grade.

Packback perspective: Instant Feedback is one of the ways Packback operationalizes Instructional AI by putting formative guidance in students’ hands at exactly the moment they can use it.

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.

Hedge Words

What it means: Your writing may be less assertive than it could be.

Hedge words are qualifiers that soften or distance a writer from their own claims; words and phrases like maybe, somewhat, it seems like, kind of, or I think perhaps. While appropriate hedging has its place in academic writing, overuse makes arguments feel uncertain or uncommitted. As a basic rule of thumb, try not to include more than one hedge term in a single sentence. If hedging against two or more separate ideas, consider splitting the sentence.

What to do: Review your post for places where you can state your position more directly. You don’t need to overstate. Jjust own your argument.

Packback perspective: Encouraging students to shed unnecessary hedging is a small intervention with outsized effects on critical thinking. When students write with conviction, they think with conviction.

Note:  This piece of Instant Feedback is intended as guidance to help improve your writing.  It is not used as part of your Curiosity Score calculation, and if you disagree with the feedback it can safely be dismissed without impacting your score.

Passive Voice

What it means: Some of your sentences may be written in passive voice.

Passive voice places the receiver of an action before the doer. For example, “The experiment was conducted by the team” instead of “The team conducted the experiment.” Passive constructions can make writing feel flat, indirect, and harder to follow.

What to do: Rewrite flagged sentences so the subject performs the action. Active voice tends to be cleaner, more direct, and more engaging to read.

Reading Ease

What it means: Your post may be difficult to read.

Packback uses the Flesch Reading Ease scale to assess how accessible your writing is. A low score typically means sentences are too long, words are too complex, or both. It’s about making them accessible to the widest possible audience.

What to do: Break long sentences into shorter ones. Where a simpler word works just as well as a complex one, use it. Your ideas should do the heavy lifting, not your sentence structure.

Transitional Words

What it means: Your writing may need stronger connections between ideas.

Transitional words and phrases like however, therefore, in contrast, building on this, help readers follow your reasoning from one point to the next. Without them, writing can feel disjointed even when the individual ideas are strong.

What to do: Look for places where one idea ends and another begins. Add a transitional word or phrase that signals the logical relationship between them. Need inspiration? Search online for “lists of transitional words” to find options that fit your meaning.

Instructional AI

Instructional AI

Instructional AI refers to artificial intelligence designed to support learning, critical thinking, and instruction. Instructional AI tools are intentionally aligned with pedagogy, transparency, and formative feedback.

Why it matters in education: Not all AI improves learning. Instructional AI is built to scaffold thinking, prompt reflection, and support instructors bt helping students do the hard work of learning themselves, rather than bypassing it.

How Packback uses this concept: Packback’s platform uses Instructional AI to guide writing, discussions, and originality feedback in ways that reinforce – not shortcut – academic effort.

If a definition could appear unchanged on a general AI company’s website, it’s not Instructional AI.

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

Formative Feedback

Formative feedback is guidance provided during the learning process while students are still working to help them improve before final evaluation.

AI context: AI-powered formative feedback can scale instructor support to class sizes where 1:1 coaching isn’t realistic. But it only works when it’s transparent, explainable, and aligned with learning goals; not just error-flagging or text generation.

Packback perspective: Packback’s AI feedback focuses on why something needs improvement and how to revise, rather than simply marking errors or generating replacement text.

Human-in-the-Loop AI

Human-in-the-loop AI systems are designed so instructors and learners remain active decision-makers, with AI providing guidance, not final judgment.

In practice: In education, this means instructors retain control over assessment, feedback, and the interpretation of AI-generated insights. The AI surfaces information. The human decides what to do with it.

Why Packback emphasizes this: Learning is relational and contextual. An AI model doesn’t know a student’s history, anxiety, or growth arc. Packback’s AI supports and never replaces instructor expertise.

Generative AI

Generative AI refers to AI systems capable of producing new content like text, images, code, audio based on patterns learned from large datasets. Tools like ChatGPT, Claude, and Gemini are generative AI.

Educational context: Generative AI is neither inherently beneficial nor harmful to learning. The outcome depends entirely on how it’s used. . . whether it scaffolds student thinking or substitutes for it.

The key question for educators: Does this tool make thinking more visible, or less?

Related: What Educators Get Wrong About AI

AI Ethics & Policy

Originality in education emphasizes the development of students’ own thinking and voice. Detection focuses on identifying policy violations after the fact.

Why the distinction matters: Detection-first approaches can create adversarial relationships between students and faculty — a surveillance dynamic that rarely produces better learning. Originality-first approaches emphasize accountability, reflection, and intellectual growth.

Packback approach: Packback prioritizes originality through transparency, revision, and process documentation — using AI as a teaching aid rather than a policing mechanism.

Related: Punitive AI, Transparency in AI, Process-Oriented Learning

AI Slop

AI slop refers to low-quality, generic, or uncritical content generated by AI without meaningful human thought or revision. It’s text is grammatically complete, factually passable but contains no real thinking.

Educational risk: Overexposure to AI slop can normalize shallow thinking and erode standards for what constitutes genuine intellectual work.

Instructional response: Courses that emphasize revision, originality, discussion, and process documentation reduce reliance on low-effort AI output. When the process is the assignment, AI slop can’t satisfy it.

Ethics & Policy

Transparency in AI

Transparency in AI means students and instructors understand what the AI is doing, why it’s doing it, and how its outputs should be used.

Why it matters: Opaque AI systems erode trust and invite misuse. When students don’t know how feedback is generated, they can’t evaluate it critically (which defeats the purpose of formative guidance).

Packback commitment: Packback designs AI features so users can see how feedback is generated and how it connects to learning goals. Explainability isn’t optional, but part of responsible instructional design.

Student Engagement (AI Context)

Student engagement refers to meaningful participation in learning activities like writing, discussion, reflection, peer interaction.

AI connection: AI can either increase engagement (by lowering barriers to feedback and participation) or decrease it (by enabling shortcuts that remove the struggle that makes learning stick).

Packback insight: Engagement increases when AI is used to ask better questions, guide revision, and surface thinking.