Georgia State University’s 2026 unDistance Learning Conference began October 5 with a session examining whether polished AI-assisted online work still gives instructors reliable evidence of student learning and connection.
Editorial Note
The unDistance Learning Conference is a professional-learning event rather than a new Georgia statute, regulation, or statewide institutional mandate.
Ideas presented by speakers should therefore be treated as professional and scholarly perspectives rather than binding policy.
This article focuses on the educational significance of the October 5 opening session rather than merely recapping an event schedule.
When AI Produces the Work, What Can an Instructor Actually See?
Georgia State University’s fourth annual unDistance Learning Conference began October 5 with virtual programming centered on the theme “Bridges not Barriers: Reimagining Connection in Online Learning.”
The conference continues virtually through October 8 before an in-person component scheduled for October 9.
One of the opening-day sessions asked a particularly timely question: when artificial intelligence can help generate student assignments and even instructor feedback, what does a polished final product still tell educators about what a student actually understands?
The session focused on the relationship between AI, evidence of learning, instructor-student connection, and the experiences of early-college online learners.
Bottom Line
Generative AI is making a longstanding online-learning problem harder.
Instructors have always needed ways to determine whether students are genuinely engaging with material rather than simply submitting completed work.
AI can now produce grammatically polished writing, summaries, explanations, discussion posts, coding output, and even simulated reflection.
That means the quality of a final product may no longer be a reliable proxy for the quality of the learning process.
What Happened
The October 5 session was part of Georgia State University’s 2026 unDistance Learning Conference.
Its description asks whether faculty may mistake polished output for meaningful engagement and how instructors can decide what to automate, what to redesign, and what still depends on human judgment and relationships.
The conference itself is designed around connection in online learning.
Its audience includes higher-education faculty, instructional designers, administrators, student-support professionals, and education innovators.
What This Means for Online Assessment
AI creates a measurement problem.
Suppose an instructor assigns a 1,000-word explanation of a theory.
Before generative AI, a strong response offered at least some evidence that the student had read, organized, and articulated ideas.
It was never perfect evidence because students could receive outside help, but the writing process itself usually required substantial participation.
Now a student can generate an organized response in seconds.
That does not make writing assignments worthless.
It means instructors need more evidence from the learning process.
What Instructors May Need to Redesign
AI-aware assessment can include oral explanation, staged drafts, annotated research decisions, in-class application, personalized examples, reflective commentary, peer discussion, demonstrations, practical scenarios, and opportunities for students to defend or revise their reasoning.
The goal should not be to make every assignment impossible to complete with technology.
That quickly becomes an arms race.
The better question is whether the assessment gives the instructor enough evidence to make a defensible judgment about the student’s own knowledge and abilities.
Why Connection Matters
This issue becomes especially important in online courses because instructors have fewer informal opportunities to observe students thinking.
In a physical classroom, a professor may notice confusion in a student’s expression, hear an uncertain answer during discussion, observe a student working through a problem, or have a spontaneous conversation after class.
Online environments can remove many of those signals.
If AI makes every submitted product look polished as well, an instructor may have even less visibility into who is struggling.
That could disproportionately affect students who need support but do not know how to ask for it.
What This Does Not Mean
The October 5 conference session does not establish that AI should be banned from online courses.
It also does not mean every traditional assignment is obsolete.
AI can support brainstorming, accessibility, language assistance, formative feedback, tutoring, research organization, and other legitimate forms of learning when used under appropriate expectations.
The instructional problem is not simply whether AI was involved.
It is whether the educator can still determine what the student knows and whether the technology supports or substitutes for the learning objective.
The Bigger Picture
Schools spent years talking about AI detection.
That approach has obvious limits.
Even accurate detection would answer only whether software may have contributed to a piece of work.
It would not tell an instructor how much the student learned, whether permitted AI assistance was used responsibly, or whether the assignment itself remains an appropriate measure of competence.
Assessment redesign is therefore becoming more important than detection alone.
Students also need to understand verification, limitations, ethical use, academic expectations, and situations in which human judgment remains essential.
What Happens Next
The unDistance conference continues through the week with additional programming related to remote students, AI-aware teaching, course design, and online engagement.
For institutions, the longer-term challenge will be converting these discussions into usable faculty support such as assignment templates, sample policies, assessment redesign assistance, professional development, and realistic workload expectations.
Why This Matters
AI is forcing educators to clarify what assignments are actually for.
If the purpose of an assignment is to produce a polished document, AI may accomplish that efficiently.
If the purpose is to develop reasoning, disciplinary knowledge, communication, judgment, or problem-solving, instructors need ways to see those abilities more directly.
That may ultimately improve education even beyond the AI debate.
Key Takeaways
- Georgia State’s 2026 unDistance Learning Conference began October 5.
- An opening session examined how AI can obscure evidence of learning in online courses.
- Polished student output is becoming less reliable as a stand-alone measure of understanding.
- Online courses may need more process-based, oral, applied, and personalized assessment.
- AI-aware assessment does not automatically require banning AI.
- Human connection remains particularly important when technology makes student difficulty harder to see.
Frequently Asked Questions
Is Georgia State banning AI?
Nothing in the October 5 conference materials establishes a university-wide AI ban.
What is AI-aware assessment?
It is assessment designed with the recognition that students may have access to generative tools while still producing credible evidence of the learner’s own knowledge and skills.
Should teachers stop assigning essays?
No. Essays can remain valuable, but educators may need drafts, conferences, source analysis, oral follow-up, or other evidence showing how the student developed the final work.
Final Thoughts
Generative AI may ultimately force education to become more precise about assessment.
For years, instructors could sometimes assume that a polished product represented student thinking.
That assumption is increasingly fragile.
The challenge now is to design learning in which technology can be useful without making the learner invisible.
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Sources
https://navigator.discovere.org/opportunity/163328
https://calendar.gsu.edu/event/the_undistance_learning_conference
