The Academic Integrity Fundamentals Tutorial will foster an understanding of Academic Integrity at RDP. The tutorial is aligned with RDP’s Student Rights and Responsibilities Policy and Academic Misconduct Procedure.
Key features of the tutorial:
Instructors are invited to integrate the tutorial into their courses or recommend it as a supplementary resource: https://guides.rdpolytech.ca/academicintegrityfundamentals
Please contact your Subject Librarian if you have any questions about the tutorial.
The Academic Integrity Remedial Tutorial is designed for students who have already committed their first offense of academic misconduct.
We recommend the following template to share with students:
The link to access the Academic Integrity Remedial tutorial is:
https://rdc-ab.libwizard.com/f/academicintegrity
The tutorial will take approximately 60 minutes to complete. We recommend completing it on a desktop computer, laptop, or tablet; this tutorial will be difficult to complete on a smartphone.
You must achieve 100% on the multi[le choice questions before proceeding to the self-reflection questions.
After completing the tutorial, you must schedule an appointment with Katelynn Mills, the Academic Integrity Coordinator:
Schedule Appointment
If you have any questions, please contact Katelynn at katelynn.mills@rdpolytech.ca
Katelynn Mills, Academic Integrity Coordinator, has developed customizable resources for faculty to refer to when managing cases of academic misconduct. These resources are designed to be adapted to the specific needs of each case, ensuring consistency while allowing for flexibility. For any questions, please contact Katelynn at katelynn.mills@rdpolytech.ca.
Artificial Intelligence detection tools come with many limitations. The following articles explore the limitations of AI detection tools in academics, including:
Understanding these factors helps faculty use AI detection responsibly.
"Notably, while AI detection tools can provide some insights, their inconsistent performance and dependence on the sophistication of the AI models necessitate a more holistic approach for academic integrity cases, combining AI tools with manual review and contextual considerations. The findings also call for reassessing traditional educational methods in the face of AI and digital technologies, suggesting a shift towards AI-enhanced learning and assessment while fostering an environment of academic honesty and responsibility." (Elkhatat et al., 2023, p. 14)