Indianapolis Assessment Guide
Beyond AI Detection: How Indianapolis Schools Can Redesign Assessment
An Indianapolis blueprint for replacing detector anxiety with oral defense, staged work, authentic tasks, fair investigations, and better assessment.
2026-08-26 · 13 min read
Easy-read summary
The big idea for Indianapolis, Indiana schools
Indianapolis teachers are under pressure to determine whether a student or a chatbot produced an assignment. Automated detectors appear to offer certainty, but their scores are not the same as proof and can distract from a more useful question: did the assessment reveal the student's learning? A system centered on detection encourages an arms race in which students disguise outputs and educators scrutinize style. A system centered on evidence asks learners to show decisions, sources, drafts, explanations, and application. Urban, township, charter, and independent schools can reduce misuse by redesigning high-value tasks while preserving reasonable workloads. The objective is not to make every assignment impossible to automate. It is to ensure essential grades rest on enough human evidence that a polished generated submission cannot stand alone.
Teach students to disclose AI help when a teacher or assignment requires it.
Use AI as a coach for questions, practice, feedback, and revision—not as a ghostwriter.
Verify important AI claims with reliable sources before sharing or submitting them.
Protect student privacy by avoiding personal, family, medical, or school-identifying details in prompts.
Section 2
Detection is not an instructional strategy
Redesign begins by naming the exact construct. If the goal is factual recall, a brief controlled quiz may be appropriate. If the goal is argument, students should defend evidence and respond to a counterargument. If the goal is revision, compare versions and explain changes. When an assignment tries to measure research, writing, creativity, collaboration, and presentation all at once, AI boundaries become muddy. Indianapolis departments can audit major assessments and write one sentence: ‘This task provides evidence that a student can…’ They then decide which tools would invalidate that evidence and which could enrich it. Clear purpose makes permission easier to explain and gives students a reason beyond ‘because the teacher said so.’
Teens reported using generative AI for school assignments in Common Sense Media research.
RAND reported student AI homework use among middle school grades and up by December 2025.
College Board reported high school students using generative AI for schoolwork.
Section 3
Start with the skill the assessment must reveal
Staged checkpoints discourage ghost production and improve teaching. A research project might include a question conference, annotated source, claim map, in-class paragraph, peer feedback, and final reflection. Not every checkpoint needs a grade; some can be photographed, sampled, or discussed. Digital version history may help but should not become constant surveillance, since students work in different ways and have different access. The strongest checkpoint requires a small intellectual decision: choosing evidence, explaining a calculation, or rejecting a design. If AI is allowed, students record where it entered and what changed afterward. This trail makes authorship visible while providing timely opportunities for feedback before a final deadline.
Section 4
Collect checkpoints instead of surveillance
Oral defense sounds time-consuming, but it can be brief. An Indianapolis teacher can hold two-minute checks while classmates begin another activity or use rotating conference days. Questions target the assignment's core: Why did you choose this source? What does this variable represent? Which sentence changed most? What would happen under a different condition? Students may also submit a short audio explanation when accessibility and privacy rules allow. The goal is not to surprise or intimidate them. Share question types in advance and let every learner practice. Oral evidence should complement, not replace, accommodations for students whose disability, language development, or anxiety affects spontaneous speech. Used thoughtfully, it confirms understanding and strengthens communication.
Section 5
Use oral defense efficiently
Courses need both closed-AI and open-AI moments. Closed moments establish independent foundations: handwriting a brief analysis, solving representative problems, reading a passage, or demonstrating a procedure. Open moments assess judgment: compare two generated answers, improve a weak explanation, test code, or identify bias and unsupported claims. Labeling the mode before work begins removes the trap of unwritten expectations. It also mirrors adult life, where some responsibilities require unaided recall and others permit extensive tools. Students should understand that access to AI during one project does not create permanent permission. The teacher selects conditions based on the evidence needed, just as a laboratory or performance course selects appropriate equipment.
Student prompt examples
- “Coach me, but do not complete the assignment for me.”
- “Ask me three questions before giving suggestions.”
- “Show what might be wrong or missing in this answer.”
Section 6
Design open-AI and closed-AI moments
When concerns remain, schools need a fair conference protocol. Begin with observable inconsistencies rather than a detector percentage. Ask the student to describe the process, locate sources, explain vocabulary, and apply the central idea to a new example. Review drafts and approved accommodations. Give the learner a chance to provide context, since tutoring, translation, editing support, or sudden improvement may have legitimate explanations. If evidence shows undisclosed substitution, connect the consequence to reassessment and published policy. Harmful fabrication or repeated deception may require escalation. Documenting the conference protects both student and teacher and helps administrators identify where assignment instructions were unclear.
Section 7
Investigate concerns fairly
Indianapolis leaders should evaluate whether redesign actually helps. Useful measures include fewer disputed accusations, stronger student disclosure, teacher confidence, completion of checkpoints, and the quality of oral explanations. Student surveys can test whether permission labels are understandable across classrooms. Departments can compare workload before adding more process artifacts and remove steps that produce little evidence. Families should receive examples of open and closed tasks so they do not unknowingly encourage prohibited help at home. Reviewing a small set of priority assessments is more sustainable than attempting to transform every worksheet immediately. Successful practices can then spread through teacher teams with concrete samples rather than another abstract policy memo.
Section 8
Measure whether the new approach works
Jim Jordan's Indianapolis AI school assembly prepares students to participate in this new assessment culture. His message is that ownership is something a learner can demonstrate: explain the choice, verify the claim, name the assistance, and stand behind the result. Jim's twenty years speaking to young people make the topic accessible, while his JimmyAI experience grounds it in real tools and future workplaces. Following the assembly, schools can launch permission labels, process checkpoints, and low-stakes oral defenses with a shared phrase: AI can support your work, but it cannot become your evidence of learning. That approach moves Indianapolis beyond unreliable detection and toward assessments that are fairer, clearer, and educationally stronger.
Action checklist
Use this after the assembly
- ●Create green, yellow, and red examples of acceptable AI help.
- ●Give students simple prompt language such as: coach me, do not complete it.
- ●Ask students to cite or explain how AI was used when appropriate.
- ●Revisit AI expectations during major writing, research, coding, and media projects.
Sources and citations