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This lesson is designed to aid students in understanding how to engage generative AI in an academic setting without breaching academic integrity policy.
This lesson is designed to be implemented directly into an LMS. We encourage you to remix this lesson to fit your institution and it’s policies. This lesson was created using Rise Articulate.
Creative Commons Attribution (CC BY)
This work is licensed under a CC BY license, allowing sharing and adaptation with proper attribution.
https://creativecommons.org/licenses/by/4.0/If you have modified or adopted this resource, share your version here. Tracking adaptations helps us measure impact and connects others with useful updates.
Purpose of the MTU Student Guidelines
Supports Academic Integrity Principles and MTU’s Academic Integrity Policy by:
1. Explaining what academic integrity is.
2. Helping students avoid bad decisions during assessments.
3. Outlines and signposts supports available across MTU
The resource comprises of a literature review and an executive summary, developed as part of the Maynooth University Leadership and EducAtion Framework (LEAF) initiative. It explores how education frameworks can enhance teaching, learning and curriculum design in higher education, supporting inclusive, sustainable and values-led academic practice.
Academic Integrity Handbook for MTU staff.
Chapters:
1. Upholding Academic Integrity and Preventing Academic Misconduct
2. Detecting Academic Misconduct
3. Dealing with Academic Misconduct
This guideline document seeks to support the implementation of MTU policies and procedures which underpin Academic Integrity and help to address the implications of Generative Artificial Intelligence on assessment practices.
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