Developing Institutional AI Policy & Assessment Frameworks for Academic Leadership
Zia Hassan
What do you want to learn?
IBM
DC Teaching
Microsoft
Now
- PhD student at Hopkins studying student motivation and engagement
- ICF-Certified Life & Engagement Coach
- EdTech Consultant
I help people find meaning in the midst of change.
Here's why this is so pressing...
Opportunities
- Pacing
- Feedback
- Access
- Adaptive Content
Challenges
- Academic integrity
- Algorithmic bias
- Faculty preparedness in a rapidly shifting world
92% students use AI.
88% have used it for an assessment
(Freeman, 2025)
Compass or map?
Agenda
- Learning Objectives in an AI-Enhanced Environment
- Assessment Frameworks That Maintain Integrity
- Developing Institutional AI Policies
- Plan for next actions
A quick primer
Learning Objectives in an AI-Enhanced Environment
A quick note about creativity
LLMs learn through text; humans learn through experience.
AI can create, but it isn't creative (Hassan et al., 2025).
How do preserve the creative habit in human students?
We need a bridge.
AIAS (Furze)
Practice
ziahassan.com/cisco/objectives
Maintaining Integrity
"You can't google these answers!" 🤦♂️
ChatGPT, did you write this? 🤔
Yes, it is highly likely that this was written by an AI.
What's your rationale?
It has complete sentences, proper grammar, and correct spelling. It is clear and concise.
Four score and seven years ago... ⚡
It is highly likely that this was written by an AI.
The essay is dead. RIP, essay. ✍️
(Kidding. Kinda.)
No one knows what to do. Time to experiment. 🥼
A central reason why students take shortcuts
(McCabe, 2021)
It's a motivation problem.
(Deci & Ryan, 1980; Miller et al., 2017)
My ideas/experiments
- Peer coaching
- Peer revision with multiple stopping points
- Ungrading/Alt Grading
- Values and vision at the student level
What ideas do you have to motivate students in this new era?
Developing institutional policies
What is AI Literacy?
Zia's definition
Knowing how GenAI works; knowing when/how to use it appropriately.
A Potential Taxonomy
AI Awareness (Foundational)
• Describe what artificial intelligence is and identify common AI applications, as well as ethical issues.
AI Literacy (General User Competency)
• Use AI tools to support learning, research, or creative tasks.
AI Collaboration (Advanced User/Domain Expert)
• Integrate AI capabilities into complex problem-solving within their discipline.
AI Creation (Specialist/Developer)
• Design, develop, or adapt AI models for novel purposes or domain-specific needs.
Human-Centered and Irreplaceable Skills
• Demonstrate skills and values that AI cannot replicate: empathy, ethical discernment, complex judgment, motivation, creative synthesis, and leadership.
What will we crave in an AI-powered world?
- Outside-the-box thinking. AI is literally inside the box.
- Moral and ethical reasoning; computers don't have core values.
- Emotional intelligence: we learn through experience
- Embracing vulnerability and incompetence
- Creating and guiding communities
- Interpersonal skills
- Using somatic (body) information
- Genuine human warmth
- Personal connection
What will we value in higher ed?
- Personalized student connection ➡️ Community and Relationships
- Students knowing their "why" ➡️ Positivity
- In-person teaching ➡️ Innovation & Creativity
- Mentorship, coaching, and critical thinking ➡️ Resilience
- Skills-based learning ➡️ Opportunity
- Community Engagement ➡️ Equity and Inclusion
Sample Policies
Synthesis
Write in the chat: what do you and your team value most?
Prompt
Given our shared values, if you had to pick two AI policies to implement at your school, but only two, what would they be and why?
What's your next step?
- Make it something that can be done in one sitting
- Be ready to share out
Thanks
zhassan4@jh.edu
linkedin.com/in/zia-s-hassan
Slides are available at
ziahassan.com/cisco
References
- Atchley, Paul, Hannah Pannell, Kaelyn Wofford, Michael Hopkins, and Ruth Ann Atchley. “Human and AI Collaboration in the Higher Education Environment: Opportunities and Concerns.” Cognitive Research: Principles and Implications 9, no. 1 (April 8, 2024): 20. https://doi.org/10.1186/s41235-024-00547-9.
- Deci, Edward L., and Richard M. Ryan. “Self-Determination Theory: When Mind Mediates Behavior.” The Journal of Mind and Behavior 1, no. 1 (1980): 33–43.
- Dweck, Carol S. Mindset: The New Psychology of Success. 1st ed. New York: Random House, 2006.
- Freeman, Josh. “Student Generative AI Survey 2025,” n.d.
- Kohn, Alfie. “The Case Against Grades (##).” Alfie Kohn (blog), November 2, 2011. https://www.alfiekohn.org/article/case-grades/.
- McCabe, Donald L., Linda Klebe Trevino, and Kenneth D. Butterfield. “Cheating in Academic Institutions: A Decade of Research.” Ethics & Behavior 11, no. 3 (July 2001): 219–32. https://doi.org/10.1207/S15327019EB1103_2.
- Miller, Angela D., Tamera B. Murdock, and Morgan M. Grotewiel. “Addressing Academic Dishonesty Among the Highest Achievers.” Theory Into Practice 56, no. 2 (April 3, 2017): 121–28. https://doi.org/10.1080/00405841.2017.1283574.
- Rogers, Carl R. Freedom to Learn. Studies of the Person. Columbus, Ohio: Merrill, 1969.
- Yeager, David S., Marlone D. Henderson, Sidney D’Mello, David Paunesku, Gregory M. Walton, Brian J. Spitzer, and Angela Lee Duckworth. “Boring but Important: A Self-Transcendent Purpose for Learning Fosters Academic Self-Regulation.” Journal of Personality and Social Psychology 107, no. 4 (October 2014): 559–80. https://doi.org/10.1037/a0037637.