Students are guessing what is allowed
Ambiguity turns responsible learning choices into a private risk calculation.
African Higher Education Workshop
Drawing the Line
AI-Assisted Learning, Academic Integrity, and the Future of University Assessment
A free two-day virtual workshop where faculty, academic leaders, integrity officers, and student representatives work through one urgent question: How should higher education institutions define the boundary between legitimate AI-assisted learning and academic dishonesty?
Every university now has a position on AI. Very few have a framework.
Free
Virtual
2 Days
8 Contact Hours
Certificate with Validation Link
Max 45 Participants
The problem
The AI integrity problem is no longer theoretical
Universities are already dealing with AI-assisted essays, literature reviews, coding tasks, take-home exams, and academic writing. But many institutions still rely on silence, blanket bans, detection tools, or individual lecturer judgment. The result is inconsistency, confusion, unfairness, and growing uncertainty about what a university credential actually certifies.
Lecturers are improvising case by case
Individual judgment fills the vacuum where shared institutional guidance should be.
Institutions lack fair and usable frameworks
Without a practical boundary, enforcement becomes inconsistent and difficult to defend.
The problem is not simply that students are using AI. The deeper problem is that many institutions have not yet defined what responsible AI-assisted learning looks like.
The strategic shift
From catching cheating to designing better assessment
Old question
How do we catch students who are cheating with AI?
Better question
How do we design learning experiences that make AI use visible, intentional, and developmentally meaningful rather than hidden, substitutive, and integrity-eroding?
The offer
What Drawing the Line offers
This is not a technology demonstration. It is not a compliance briefing. It is a structured, output-oriented workshop that helps universities move from reactive AI management to principled assessment and governance design.
Clarify the boundary between AI assistance and AI substitution
Redesign assessment so learning remains visible
Build fair institutional processes for handling suspected misuse
What you build
You will not leave with slides. You will leave with usable governance products.
AI Boundary Framework
A practical framework for classifying AI use across clearly permitted, conditionally permitted, high-risk, clearly prohibited, and context-dependent cases.
Draft AI Acceptable Use Principles
Policy-ready principles that participants can adapt for course, departmental, faculty, or institutional use.
Redesigned Assessment Canvas
A redesigned assessment task that better aligns with learning outcomes in an AI-enabled environment.
Due Process Practice Framework
A fair process for handling suspected AI misuse without treating detection output as primary evidence.
30/60/90-Day Institutional Action Plan
A practical implementation pathway with named responsibilities, governance steps, and review milestones.
Student and Faculty Communication Templates
Plain-language guidance for students and assignment brief language for faculty.
Workshop journey
A two-day journey from uncertainty to institutional action
-
1
Diagnosis
Participants surface assumptions, disagreement, and blind spots through realistic AI-use scenarios.
-
2
Framing
Participants understand why AI has disrupted academic integrity and why bans, silence, and detection are insufficient.
-
3
Framework
Participants learn a structured Boundary Framework for classifying AI use fairly and consistently.
-
4
Application
Participants test the framework against discipline-specific cases from humanities, sciences, professional programmes, and postgraduate research.
-
5
Production
Participants redesign assessments, draft policy principles, map governance pathways, and leave with a concrete institutional action.
Day 1: Clarity
Participants surface disagreement, build shared vocabulary, learn the Boundary Framework, and classify realistic AI-use scenarios.
Day 2: Production
Participants redesign assessments, draft policy principles, work through due process cases, map governance pathways, and leave with a named 30-day action.
Who should attend
Built for the people who must make AI integrity decisions
The workshop is most effective when institutions send a cross-functional mix of participants.
Best suited for institutions that bring teaching, governance, student voice, and academic support into the same conversation.
African higher education context
Designed from African higher education realities
This workshop is designed for multilingual student populations, unequal AI access, disability-related tool use, resource-constrained integrity offices, slow governance cycles, and the need for policies that work in African institutional contexts.
African context is not an add-on. It is part of the design logic.
Why OSi
Built by OpenSchool Initiative
OpenSchool Initiative is a volunteer-powered, Africa-focused nonprofit building practical digital and AI capabilities for learning, work, and public value.
Across Africa
Applicants from 17 African countries
Applicants from 22 countries; 55 fellows graduated
Working with faculty, postgraduate researchers, policymakers, civil servants, and professional communities
Registration
Register for Drawing the Line
Join a focused cohort of African higher education professionals working together to build practical frameworks for AI-assisted learning, academic integrity, and assessment redesign.
Free
Virtual
Two Days
8 Contact Hours
Max 45 Participants
Certificate with Validation Link
- Date and Time
- [WORKSHOP_DATE], WAT
- Fee
- Free
- Format
- Virtual
- Duration
- Two days
- Contact Time
- 8 hours
- Cohort Size
- Maximum 45 participants
- Certificate
- Issued to full attendees with a validation link.
- Preparation
- Complete the pre-workshop survey and bring one assessment task for redesign.
- Contact
- ai-fellowship@openschool.sch.ng
FAQ
Common questions
Quick answers about eligibility, certificates, preparation, participation, and what institutions can expect after the workshop.
It is designed for university faculty, lecturers, academic integrity officers, teaching and learning specialists, postgraduate supervisors, heads of department, student representatives, university leaders, and academic boards working in African higher education contexts.
Yes. Participation is free. However, the cohort size is capped at 45 participants to preserve the quality of small-group work.
This is a workshop, not a passive webinar. Participants will classify scenarios, redesign assessments, draft policy principles, work through due process cases, and develop institutional action steps.
No. The workshop focuses on academic integrity, assessment design, governance, and responsible institutional practice. Participants do not need coding or technical AI experience.
Participants will leave with a working AI Boundary Framework, draft acceptable use principles, an assessment redesign canvas, due process guidance, and a 30/60/90-day institutional action plan.
Yes. Certificates of participation will be issued only to participants who fully attend the programme. Each certificate will include a validation link.
Yes. Student representation is encouraged because AI integrity decisions affect both teaching staff and learners.
Participants should complete the pre-workshop survey and bring one assignment brief, assessment task, or course activity they may want to redesign during the workshop.
The cohort is capped at 45 participants.
The workshop is designed to produce practical governance and assessment tools that participants can adapt for departmental, faculty, or institutional use.
Still have questions? Contact ai-fellowship@openschool.sch.ng
Build the framework before the cases arrive.
The question is not whether your university needs this capacity. It already does. The question is whether you build it now, with a structured programme designed for this purpose, or later, after the cases that make the absence visible have already arrived.
Cohort places are capped at 45 participants to protect the quality of small-group work.
Register for the Workshop