Teaching & Learning
- Student use of AI in coursework and assignments is at instructor discretion rather than governed by a single uniform rule
- The university expects original work when required and requires citation of AI tools when they are used, but individual instructors may allow AI broadly, limit it to certain assignments or uses, or prohibit it entirely
NDNU believes that academic institutions should provide students with appropriate guidelines and training to make informed decisions on how to ethically integrate AI into their work products and assignments. Our Academic Integrity policy expects students to produce original work when required and to cite supporting documents, resources, and tools as appropriate per APA guidelines – the requirement to cite supporting documents, resources, and tools includes AI tools.
Each course instructor will determine how AI language models may be used in their course. This may range from allowing AI tools in assignments as long as the student cites the information or ideas synthesized, limiting the use of AI tools to specific assignments, limiting the use of AI only as a starting point for what will be the student’s own analyses and critical thinking, or not allowing AI tools at all.
Students who have doubts about the appropriate use of an online learning support platform in their course should discuss their situation with their instructor.
- Use of AI in exams and assessments is not addressed through a specific AI-only exam rule
- Instead, exam-related use falls under instructor authorization and general academic misconduct rules, so unauthorized use during examinations would be misconduct, and instructors set class-specific AI guidelines
• Using unauthorized materials (such as notes, books, or online materials) as an aid during an examination
• Providing assistance to, or receiving assistance from, another person in any manner prohibited by the instructor
Note: Each instructor will address the specific guidelines related to use of Artificial Intelligence in their class. Students who have doubts about the appropriate use of an online learning support platform in their course should discuss their situation with their instructor.
- The AI Squared page and CETL materials may contain additional guidance on ethical AI use for learning support
- The university does not have a separate AI learning-assistance policy beyond its general instructor-discretion framework
- Students wishing to use AI tools as a study or learning-support resource must follow their course instructor's guidelines, and any doubts about appropriate use should be directed to the instructor
Students who have doubts about the appropriate use of an online learning support platform in their course should discuss their situation with their instructor.
Note: Each instructor will address the specific guidelines related to use of Artificial Intelligence in their class.
NDNU believes that academic institutions should provide students with appropriate guidelines and training to make informed decisions on how to ethically integrate AI into their work products and assignments.
Research
- The university does not state a university-wide research-writing policy for AI in theses, dissertations, or manuscripts in the provided sources
- One school-level article describes psychology faculty and students using AI for brainstorming, searches, organizing information, and scholarship development, while emphasizing source verification, critical thinking, and expressing ideas in students' own words
Meanwhile, under the direction of Dean Helen Marlo, the School of Psychology (SOP) is charging ahead with AI integration across academics, research, scholarship, and clinical practice. From embedding AI into core syllabi – including the Professional Ethics and Law course – to driving development of theses, capstones, community projects and scholarship for NDNU’s upcoming Research and Scholarship Symposium, the SOP is making the ethical use of AI a cornerstone of its expanding offerings.
In his Clinical Assessment & Treatment Planning and Research Methods and Design courses, Drexler helps students develop strong research habits—starting with crafting effective prompts and verifying sources.
AI, he says, is a powerful tool for brainstorming, but real learning happens when students interpret, reframe, and express new ideas in their own words.
- The university does not publish a dedicated university-wide policy on AI use in research data collection or analysis
- However, school-level practice in the School of Psychology explicitly addresses AI in research contexts, emphasizing verification of AI-generated sources, crafting effective prompts, and ensuring AI complements rather than replaces critical inquiry in research methods and design courses
In his Clinical Assessment & Treatment Planning and Research Methods and Design courses, Drexler helps students develop strong research habits—starting with crafting effective prompts and verifying sources. He even uses documents with intentional errors to sharpen their fact-checking skills. He emphasizes that the goal is not to replace human judgment but to strengthen it, ensuring that technology becomes a complement to—not a substitute for—critical inquiry.
AI, he says, is a powerful tool for brainstorming, but real learning happens when students interpret, reframe, and express new ideas in their own words.
- The provided sources do not set a specific university-wide AI policy for grant proposals, IRB applications, or ethics declarations
- However, institutional and school-level materials explicitly frame AI use in research and scholarship around ethical application, integrity, critical inquiry, and verification of sources
In the late spring, NDNU created an AI Oversight Committee led by Greg Zubacz, Associate Provost and Dean of Interdisciplinary Studies, to “provide strategic oversight and guidance on the integration, development, and ethical application of AI within the university’s academic, research, and administrative functions.”
Meanwhile, under the direction of Dean Helen Marlo, the School of Psychology (SOP) is charging ahead with AI integration across academics, research, scholarship, and clinical practice. From embedding AI into core syllabi – including the Professional Ethics and Law course – to driving development of theses, capstones, community projects and scholarship for NDNU’s upcoming Research and Scholarship Symposium, the SOP is making the ethical use of AI a cornerstone of its expanding offerings.
In his Clinical Assessment & Treatment Planning and Research Methods and Design courses, Drexler helps students develop strong research habits—starting with crafting effective prompts and verifying sources. He even uses documents with intentional errors to sharpen their fact-checking skills. He emphasizes that the goal is not to replace human judgment but to strengthen it, ensuring that technology becomes a complement to—not a substitute for—critical inquiry.
Academic Integrity
- When AI is used in student work, the university requires it to be cited under APA guidelines
- In courses where instructors allow AI in assignments, students must cite the information or ideas synthesized from the tool
Our Academic Integrity policy expects students to produce original work when required and to cite supporting documents, resources, and tools as appropriate per APA guidelines – the requirement to cite supporting documents, resources, and tools includes AI tools.
Each course instructor will determine how AI language models may be used in their course. This may range from allowing AI tools in assignments as long as the student cites the information or ideas synthesized
- Sanctions range up to expulsion for serious or repeated misconduct
- No AI-specific detection software policy is described in available sources, and the AI Squared page may contain additional enforcement guidance not captured in this extraction
- The university's academic misconduct policy encompasses submitting work that is not one's own and misrepresenting another's ideas, which would apply to unauthorized AI use by extension
The section of this NDNU Student Handbook entitled Academic and Professional Misconduct addresses the consequences of misrepresenting your work. A brief overview of these consequences follows:
University policy permits discipline up to and including expulsion for academic, professional, and/or other form of serious or repeated misconduct.
• Submitting any course materials or activities not the student's own, allowing such a submission to be made for oneself, or making such a submission for another
• Representing another person's ideas, processes, results, or words as your own; using the ideas, organization, or words of another from a book, article, paper, computer file, or another source in any assignment without giving proper credit following accepted citation rules (plagiarism)
Note: Each instructor will address the specific guidelines related to use of Artificial Intelligence in their class.
Institutional & Administrative
- Faculty are encouraged and supported to use generative AI for course development and instruction, with consultation available through instructional design support
- Faculty also retain authority to set course-level student AI policies, and school-level materials describe faculty guiding students to use AI responsibly and critically rather than as a substitute for human judgment
Faculty are encouraged to consult with their program leadership for more guidance regarding the AI syllabus statement and policy for their program.
Generative AI tools can support course development in a variety of ways. Discuss options related to Gen AI tools and course development with an Instructional Designer and/or In School Support.
Generative AI tools can support and enrich instruction in a variety of ways. Discuss options for using AI for course delivery including student engagement with an Instructional Designer and/or In School Support.
Each course instructor will determine how AI language models may be used in their course.
Artificial Intelligence (AI) is transforming education—and at Notre Dame de Namur University (NDNU), the Center for Excellence in Teaching and Learning (CETL) is helping faculty embrace the change with purpose, integrity and clarity.
Faculty guide future educators to understand the broader implications of AI—how it shapes learning environments, influences equity, and affects student identity and agency.
- This classification should be revisited once the AI Squared page and any administrative subcommittee outputs are reviewed
- No explicit university-wide policy on institutional data protection or a list of approved AI platforms was identified in the sources reviewed
- The AI Oversight Committee's administrative subcommittee may govern platform approvals and data protection, but specific policies are not publicly articulated in the available documents
In the late spring, NDNU created an AI Oversight Committee led by Greg Zubacz, Associate Provost and Dean of Interdisciplinary Studies, to 'provide strategic oversight and guidance on the integration, development, and ethical application of AI within the university's academic, research, and administrative functions.' There are three subcommittees which focus on specific areas: academic, administrative, and enrollment & marketing. [No specific institutional data protection or approved platform policy has been identified in publicly available sources at this time.]
- The university has established an institutional AI governance structure and strategy
- It created an AI Oversight Committee with subcommittees across academic, administrative, and enrollment and marketing areas, provides updates to the Board of Trustees, and charges deans and department heads with developing strategic AI integration plans across programs and operations
In the late spring, NDNU created an AI Oversight Committee led by Greg Zubacz, Associate Provost and Dean of Interdisciplinary Studies, to “provide strategic oversight and guidance on the integration, development, and ethical application of AI within the university’s academic, research, and administrative functions.” There are three subcommittees which focus on specific areas: academic, administrative, and enrollment & marketing. These subcommittees began meeting in the fall.
The Committee also provides institution-wide updates to the Student Learning and Success Committee of the Board of Trustees.
Deans and department heads are also charged with developing a strategic plan to integrate AI into their academic programs and operational processes.
“We recognized that we had to engage with AI immediately—or risk being left behind,” says NDNU President Beth Martin. “When the Council of Colleges (CIC) extended the invitation to take part in their national initiative, AI Ready, we came running.”
DocuMark: Responsible AI Use for Academic Integrity
Knowing your institution's AI policy is step one. DocuMark helps enforce it fairly by empowering universities to manage AI-generated content, prevent cheating, and support student writing through responsible AI use.
Common Questions About Notre Dame de Namur University's AI Policies
Notre Dame de Namur University has defined AI policies in 11 of 12 categories, with an overall coverage score of 92%.
When AI is used in student work, the university requires it to be cited under APA guidelines. In courses where instructors allow AI in assignments, students must cite the information or ideas synthesized from the tool.
The university's academic misconduct policy encompasses submitting work that is not one's own and misrepresenting another's ideas, which would apply to unauthorized AI use by extension. Sanctions range up to expulsion for serious or repeated misconduct. No AI-specific detection software policy is described in available sources, and the AI Squared page may contain additional enforcement guidance not captured in this extraction.
No explicit university-wide policy on institutional data protection or a list of approved AI platforms was identified in the sources reviewed. The AI Oversight Committee's administrative subcommittee may govern platform approvals and data protection, but specific policies are not publicly articulated in the available documents. This classification should be revisited once the AI Squared page and any administrative subcommittee outputs are reviewed.