By engaging in a series of guided explorations to establish a common foundation, members of the Academics Work Group will engage in informed discussion about generative AI applications, approaches, and experiences in the classroom and their potential impact on teaching and learning. This group will:
Explore the applications, capabilities, and limitations of existing generative AI tools, both stand-alone products and current integrations in essential software programs and resources, to enhance teaching and learning.
Identify the skills students need to ethically leverage generative AI in the classroom and the workplace; consider appropriate areas within existing programs and curriculum to integrate said skill development.
Identify best practices for the use of generative AI by faculty and students to enhance teaching and learning.
Identify areas of academic policy that may require modification to address issues posed by generative AI and devise approaches that are actionable, flexible, and fair.
Because academic programs and even individual classes have their own unique requirements when it comes to generative AI use by students, departments and/or curriculum areas may need to devise their own policy in consultation with the AVP for Learning Culture & Innovation.
At the College level, the Academic Integrity policy as provided on course syllabi has been updated to include a purposefully general phrase - "generated content" - to indicate use of AI-generated content falls within the purview of Academic Integrity. Every course syllabus now includes this statement in the College Policies section:
Academic Integrity
Students in this course must know, observe, and not compromise the principles of academic integrity. It is not permissible to cheat, to plagiarize, to fabricate or falsify information, to submit the same academic work in more than one course without instructor approval, or to receive unfair advantage. Students must not submit work, in whole or in part, created by another person or content generator, unless directed by the instructor. All unoriginal work must be cited. Students must not allow anyone to log in to their course using their credentials. Students must follow standards of professional conduct when participating in off-site activities. The grade for this course includes the judgment that the student’s work is free from academic dishonesty of any type. Violations or infractions will be reported to the Student Affairs Office and may lead to failure of the course and other sanctions imposed by the College.
Additionally, instructors are expected to provide students with guidance regarding the extent of generative AI use permitted (understanding prohibition is not feasible nor enforceable) and the preferred citation method.
The Academic Integrity policy as published in the current Catalog and Student Handbook does not reference AI specifically, however the policy as stated still applies to all student work. If a student submits work as their own without proper citation or attribution of credit for content they did not create, academic integrity has been violated.
Academics Work Group Members |
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| Myrna Allen | Alexandra Asbille | Kristina Barnes |
| Chad Collins | Tekaylor Etienne | Thomas Flanagan |
| Jocelyn Gaffney | Summer Garrett | Matthew Giddings |
| Brian Holbert | Heather Jones | Edward Jordan |
| Mike Keller | MaryAnn Kester | Charlene Livaudais |
| Lisa Mahoney | Douglas Mikutel | John Paterson |
| Daniel Ray | Cory Roberts | Renee Ruffalo |
| Emily Schafer | Misty Sutton | Stephen Tomasovitch |
| Kim Van Vliet | Billy Veczko | Jason Whitmarsh |
| James Wray | James McCaughern-Carucci | Cheryl Giacomelli |
| Dana Smith | Christina Will, Facilitator | |
