91原创

AI and Teaching (Pedagogy) - Discussion Summary

July 14, 2026 Opening Remarks: Dr. Meghan McInnis-Dom铆nguez, Associate Professor of Spanish

Classroom use, academic integrity, guidance and guardrails.

A. Current State: What is already happening?

鈼� Pedagogy is strategy vs. teaching is technique

鈼� Very divided 鈥� embrace and repel CTAL resources and information for best

鈼� practices (evolving)

鈼� Challenged to completely rethink the way professors teach

鈼� Course vs. curriculum perspective 鈥� it鈥檚 ad hoc

鈼� Many use AI because resources are limited

鈼� 91原创 had not defined AI, there is not definition of AI

鈼� Varying capacity to prioritize discussion and implementation

鈼� Use of AI could increase if resources (e.g., journals) not available

鈼� Students crave AI experience

听

B. Opportunities: Where can AI strengthen 91原创鈥檚 work?

鈼� Administrative time saving (reinvest time into intentional work)

鈼� Instructional design support

鈼� Purpose/value proposition and need for clearer articulation

鈼� Accessibility

鈼� Assessment and shift to more in-person teaching

鈼� Research advancement and data application

鈼� Emphasize firsthand, experiential learning that helps students recognize what generative AI cannot fully capture, including experiences such as study abroad.

听

C. Risks and Guardrails: What concerns, risks, or guardrails require attention?

鈼� Tools

鈼� Professors wanting different tools

鈼� Teachers trying to keep up with evolving methods and products

鈼� Paid vs. free

鈼� Privacy

鈼� Ownership of content听 听听

鈼� Who sets the standards?

鈼� Departments

鈼� University

鈼� Professors

鈼� Students

鈼� Liability issues

鈼� Environmental dangers

鈼� How to teach thought processes

鈼� Cognitive processing

鈼� Alternative assessment

鈼嬏齈resentations (time sync)

鈼嬏齀n-class assessments

鈼� Uncontrolled vendor expansion

鈼� Students are AI Guinea pigs

鈼� Evaluating student output

鈼� AI plagiarism

鈼� Slop

鈼� Disclosure of use of AI

鈼� Professors and students should disclose when using AI

鈼� Subsidized now, what about the future?

听

D. Support Needed: What training, policies, resources, or capabilities are needed?

鈼� What is the institutional guidance on which LMs to use/not use and for what?

鈼� Solve for today and into the future

鈼� Google Notebook:

鈼� Who will teach us how to use/training

鈼� Who will have access

鈼� What are the limitations

鈼� Departmental reps who train/teach their departments

鈼� Central places for training 鈼� Hub for students/faculty

鈼� Resources

鈼� Application use

鈼� Assessment: Where is it in our core curriculum? Gen Ed?

鈼� Policy support

鈼� AI updates and changes too fast; problem keeping up

鈼� Policy focused on what NOT/CANNOT do with AI at the University

鈼� Policy surrounding transparency

鈼� Data security

鈼� Desire for an institutional repository

鈼� Sanctioned tools

鈼� Training

鈼� Course materials and AI integration ideas

鈼� How to on prompts

鈼� Link prompts associated with course exerciseLessons

鈼� Syllabi language

鈼� Activities

鈼� Departments/colleges need to have their own discussions

鈼� Accreditation: what is required for the units

鈼� Ethics and Family Educational Rights and Privacy Act

鈼� What is ethical? What is not ethical? (grading learning, assignments)

鈼� 91原创 needs to be able to defend pedagogical understanding with AI

鈼� Teaching in many tools of pedagogy

鈼� Understand the current AI literacy

鈼� Student level needs

鈼� Heat map of curricula

鈼� Matrix of when/how AI is being used

听

E. Next Steps: What actions, pilots or decisions should 91原创 consider?

鈼� Develop a shared working definition of AI for teaching and learning while recognizing faculty authority over course design and instruction.

鈼� Create a centralized AI teaching hub with tools, training, guidance, assessments, and effective classroom practices.

鈼� Pilot an assessment of faculty and student AI literacy to identify guidance, training, range, and support needs.

听

AI and Student Learning - Discussion Summary

July 21, 2026

Opening Remarks: Erin Sicuranza, Director, Academic Technology Services

Durable skills, career readiness and academic program evolution.

A.听 Current State: What is already happening?

鈼徧� Very siloed within 91原创

鈼徧� Copilot and Gemini chat

鈼徧� Library has AI Literacy program

鈼徧� (one-stop shop for off-campus jobs and other career resources)

鈼嬏� AI Fellowships in the last 6 months (90 students)

鈼徧� Working group for students

鈼徧� Student facing chat bot currently with Admissions, IT, Library

鈼徧� ATS (Academic Technology Services) - 91原创 study aide

鈼徧� : 91原创 Google AI certificate program

鈼徧� Canvas has the capacity for AI training - not yet activated

鈼徧� MEEG one of the only department with AI communication in the curriculum.

鈼徧� for teaching innovation

鈼徧� Considerations for Integrating AI Within Teaching and Learning

B.听 Opportunities: Where can AI strengthen 91原创鈥檚 work?

鈼徧� Is AI a pedagogical tool or curriculum topic?

鈼徧� Is this about student learning or student success?

鈼徧� How do we create an equitable learning environment for AI?

鈼徧� When introducing AI what assessments can be used to evaluate what students learned?

鈼嬏� Reinvestment in durable skills (Information Literacy)

鈼嬏� Skills transcript: AI skills learned with undergrad

鈼徧� Make AI Literacy apart of the First Year Experience

鈼嬏� Have intro course a part of new student orientation

鈼嬏� How are students exposed to AI Literacy?

鈼徧� 91原创 has the opportunity to serve the community by partnering with high schools to help combat AI literacy gap

鈼徧� Bridge the 鈥榓rms race鈥� gap. Students will find a way to use AI with or without 91原创.

鈼徧� Determine what sources 91原创 will use to gain AI information

鈼徧� Learn more about ethical implications

鈼徧� Provide opportunities to learn more about how AI algorithms work; learn more about prompting.

鈼徧� Create more individual AI courses

鈼徧� How is the uptake of AI the same as vs.different from the introduction of calculators

鈼徧� Now opportunity to conduct a survey to understand how AI is being used now within the 91原创 community

鈼徧� Value in plotting AI readiness along these dimensions:

AI and Research, Innovation, and Workfoce Development 鈥� Discussion Summary

July 28, 2026

Opening Remarks: Sunita Chandrasekaran, Associate Professor, Computer and Information Sciences
Discovery, translation, competitiveness, industry needs and workforce alignment.


A. Current State: What is already happening?
Discovery:

鈼徧� AI development and research are happening across individuals, labs, institutes, and departments, but these efforts are often siloed and not consistently shared

Translation:

鈼徧� AI research and tools are not yet easily translated across internal units or from higher education into practical workforce applications

Industry Needs:

鈼徧� Impact on entry level positions and job availability.

鈼徧� Due to the need in industry, 91原创 needs to change how students are prepped for employment

鈼徧� Industry wants demonstrable abilities not certificates. Ability to compete within workforce

Workforce Alignment:

鈼徧� Students without AI skills are behind

鈼徧� Students need fundamental skills and understanding

鈼徧� t is currently using AI to reduce R&D by 10x

鈼徧� uses AI in their network behavior analysis tools

鈼徧� Fundamental knowledge is more important for job success that AI literacy

鈼徧� Students are more effective when they have the skills to direct AI

B.听 Opportunities: Where can AI strengthen 91原创鈥檚 work?

Discovery:

鈼徧� Expanded AI-enabled research opportunities for students and faculty across disciplines

鈼徧� Use of AI to analyze, organize, and synthesize large datasets and information

鈼徧� Baseline findings to support grant applications and research scaling

鈼徧� Greater interdisciplinary collaboration across colleges, departments, institutes, and research centers

鈼徧� Showcasing innovative applications such as the Poison Book Project and other research collaborations

Translation:

鈼徧� Mechanisms to share AI-related research, tools, pilot programs, and best practices across campus

鈼徧� A central hub or communication network for AI projects, resources, expertise, and events

鈼徧� Campus-wide events such as AI in Action to encourage interdisciplinary engagement and knowledge sharing

鈼徧� Translation of AI research and innovation into practical industry and workforce applications

Competitiveness:

鈼徧� A secure AI sandbox with access to multiple models and guardrails for privacy, security, and cost

鈼徧� Clear measures of when and why AI should be used, how it adds value, and how success is defined

鈼徧� Strategies for managing token costs, institutional demand, and responsible scaling

鈼徧� Processes that allow 91原创 to respond quickly to changing technologies and workforce needs

鈼徧� An integrated institutional strategy connecting teaching, research, innovation, and workforce development

Industry Needs:

鈼徧� Stronger engagement with industry partners and alumni to align 91原创鈥檚 AI strategy, programs, and research with evolving needs

鈼徧� More opportunities for students to learn directly from industry professionals and alumni

鈼徧� (reverse) Mentorship connecting students with professionals across generations

鈼徧� Integration of technical AI knowledge with human-centered workplace skills

鈼徧� AI-powered simulations and role-playing tools for communication, decision-making, and workplace scenarios

Workforce Alignment:

鈼徧� Greater student understanding of how AI is affecting careers, job opportunities, and workforce expectations with an understanding that it is a rapidly changing environment

鈼徧� Understanding of the responsible, effective, and ethical use of AI in professional settings

鈼徧� Continued development of critical thinking, communication, problem-solving, and other durable human skills

鈼徧� Clearer distinction between AI-enabled critical thinking and uniquely human skills

鈼徧� Guidance on appropriate and inappropriate uses of AI

C.听 Risks and Guardrails: What concerns, risks, or guardrails require attention?

Concerns:

鈼徧� 91原创鈥檚 capacity to keep pace with rapidly changing AI tools, demand, and training needs

鈼徧� Erosion of research, communication, critical-thinking, problem-solving, and judgment skills

鈼徧� Lack of clarity around ethical use, citation, research quality, and platform-specific risks

鈼徧� Difficulty keeping coursework and institutional guidance current

Risks:

鈼徧� Use of unauthorized AI tools or personal subscriptions without appropriate review

鈼徧� Exposure of sensitive data or intellectual property

鈼徧� Inability to fully assess or control data, security, compliance, and cost risks

鈼徧� Poor prompts, limited user knowledge, and inadequate review of AI-generated information

鈼徧� Adoption of AI solutions that are unreliable, impractical, or difficult to scale

Guardrails:

鈼徧� Provide clear guidance on what data may and may not be entered into AI systems

鈼徧� Establish standards for IRB-, HIPAA-, FERPA-, and other protected information

鈼徧� Tailor security and compliance requirements to the needs of different units

鈼徧� Require appropriate review and verification of AI-generated information

鈼徧� Assess whether AI tools improve learning outcomes and strengthen critical-thinking skills

Questions for Consideration:

鈼徧� How much can 91原创 trust AI platforms with internal information and data?

鈼徧� Should 91原创 develop a secure, university-supported AI environment?

鈼徧� How many AI platforms can 91原创 responsibly support?

鈼徧� How can instructors identify inappropriate AI use?

鈼徧� Do users understand the costs associated with AI?

鈼徧� What skills are needed now and in the future?

鈼徧� Could overly restrictive guardrails limit research and innovation?

D.听 Support Needed: What training, policies, resources, or capabilities are needed?

Trainings:

鈼徧� Training on all the tools and tool usage

鈼徧� High tailored training for all the different subgroups within the University 鈥� based on experience

鈼徧� Create an ambassador program within 91原创 to help support large group training

Policies:

鈼徧� Could 91原创 present a position statement? Difference between a position statement and policy statement.

鈼徧� Does every college and/or department need to have its own position statement umbrella under the 91原创 policy?

Resources:

鈼徧� Infrastructure

鈼徧� Criteria to determine whether AI appropriate to use in situations

鈼嬏� Criteria to determine which AI tools are appropriate to use

What Is Needed:

鈼徧� The development of a secure, university-supported AI environment that faculty, staff, and students can use confidently

E.听 Next Steps: What actions, pilots or decisions should 91原创 consider?

鈼徧� Pilot a secure internal AI sandbox with approved tools and guardrails for privacy, security, compliance, and cost.

鈼嬏� This should contain a crowd-sourced repository of prompt templates and techniques organized by research discipline to facilitate safe adoption of AI assistance in research where appropriate.

鈼嬏� Should also include citation templates to acknowledge use.

鈼徧� Expand industry and alumni engagement to align student preparation and university research with evolving workforce needs

鈼徧� Develop a university-wide position statement (vs. policy statement) on responsible AI use, with flexibility for colleges and departments to establish specific guidance

Topics: Administrative modernization, efficiency, and faculty/staff support

Topics: Monitoring AI progress, staying current and adapting responsibly as the technology evolves