School of Kinesiology
School of Kinesiology
Students are required to attend the first meeting of the classes (both lectures and labs) in which they are registered and they must notify their instructors in advance if they are unable to attend. Students in online courses are required to login to the course before the deadline stated in the UFV calendar. Students who fail to attend the first meeting of a class in which they are registered and who do not notify the instructor in advance will likely be withdrawn from the course.
Students are responsible for meeting other attendance requirements specified by instructors and are expected to attend the entire class. Please note that KIN labs typically require attendance at all classes. Students are responsible for all material presented in the missed class, and should not expect instructors to provide make-up content notes.
Students should be respectful of their classmates and instructors by avoiding unnecessary tardiness. While unforeseen circumstances may occasionally prevent you from arriving on time, repeated tardiness may warrant disciplinary action and loss of grades. If you are late, please enter the class with as little disruption as possible and be aware that some instructors may refuse you entry in the classroom after class begins.
Time management is an important aspect of student life. Students are expected to meet all assigned deadlines. Failure to do so will result in a loss of grades. Note that some instructors do not accept late assignments, except for documented medical reasons.
A student is permitted to withdraw from a course at any time before 60% of a course duration. A withdrawal in the first 30% of the course duration will not be recorded on the official transcript.
Course withdrawal after the 30% duration point will be designated “W” and will be shown on the transcript. A student who wants to have a seat in a class but not receive credit may, with instructor permission, register as an Audit (AU) student. The audit designation assumes a minimum amount of attendance and participation as determined by the instructor. A course with an audit designation is not included in the GPA nor does it count towards completion of the program.
Students are required to conduct themselves in a mature and responsible manner, consistent with the University mission, policies, and regulations. Specifically students are expected to be attentive in class, and avoid conduct and behaviour that is disruptive to others. Depending on the instructor’s guidelines, this may include the use of phones, computers, and other devices in the classroom.
Student misconduct, which includes, but is not limited to, plagiarism, cheating, and disruption of the learning environment, is not tolerated.
In-class exam dates are typically indicated on course outlines. Rewrites are not permitted.
Deferred exams are granted only in exceptional circumstances outlined in the KIN exam deferral procedure below. Students wishing to seek an alternative exam date must read the KIN Exam Deferral Procedure and make their request to the School of Kinesiology by email, not to the course instructor.
Final exams are scheduled during the final exam period. Students must be available for the entire period and will not be granted different writing times due to personal reasons such as travel. Students are not permitted to start the exam after 15 minutes have passed and cannot leave and re-enter the room once the exam has started except in extenuating circumstances. All forms of cheating will be treated seriously in accordance with UFV policies.
Students who are members of UFV sports teams may be granted a deferred exam for travel games, if advance notice is given to the instructor. Student athletes must comply with the KIN exam deferral procedure.
In-class exam (e.g., midterm. quiz) dates are typically indicated on course outlines. Rewrites are not permitted.
Deferred exams are granted only in exceptional circumstances outlined in the KIN exam deferral procedure below. Students wishing to seek an alternative exam date must read the KIN Exam Deferral Procedure and make their request at least one week prior to the scheduled exam, except in exceptional circumstances (e.g., illness, accident, bereavement). Deferral requests must be made prior to the scheduled time of the exam. Deferral requests made after the exam has started will not be granted.
Final exams are scheduled during the final exam period. Students must be available for the entire period and will not be granted different writing times due to personal reasons such as travel. Students are not permitted to start the exam after 15 minutes have passed and cannot leave and re-enter the room once the exam has started except in extenuating circumstances. All forms of academic misconduct will be treated seriously in accordance with UFV Policy 70. Please refer to UFV’s Student Academic Misconduct Policy for examples of academic misconduct.
Kinesiology tribunal decisions are final and cannot be appealed at the School level. If the request is denied, the student may appeal to the Dean's Office.
Provide a time when you are available to write the exam. This should be your first available time block, between 9:00 a.m. and 4:00 p.m., AFTER the scheduled exam time. Please also provide alternate times.
Without expressed consent from course instructors, students are not permitted to record (audio, video, images or otherwise) course lectures, seminars or laboratories for in-person or online courses.
Students who are requesting permission to record materials due to disability-related reasons, are asked to provide a recommendation from the Centre for Accessibility Services outlining the need for this accommodation.
All students must receive permission from the instructor to record lectures. In instances where consent/accommodation has been granted, the information contained in the lecture recordings is solely for the personal use of the student receiving consent/accommodation. Lectures recorded for this purpose may not be shared with other people without the expressed written consent of the instructor.
Recorded lectures may not be used in any way against a faculty member, other lecturers, teaching assistants, or students whose classroom comments are recorded during the normal course of the lecture. Students are cautioned that lectures, demonstrations, and any other course material produced by an instructor are the intellectual property of the instructor. Information contained in the recordings may not be published (including on the internet) or quoted without the expressed written consent of the instructor.
Misuse of these recordings will be considered non-academic misconduct.
KIN procedures are bound by UFV's policies.
Frequently requested policies include:
This guiding document discusses the use of artificial intelligence (AI), especially generative AI, by faculty and students in the School of Kinesiology. A standard definition of artificial intelligence is “the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings.” (https://www.britannica.com/technology/artificial-intelligence). IBM defines generative AI as a system “that can create original content such as text, images, video, audio, or software code in response to a user’s prompt or request.” (What is Generative AI? | IBM).
The following foundational goals should ultimately direct the school’s use of AI (especially generative AI). We should ensure that:
• Faculty and students use AI in ways that support learning and strengthen student–faculty relationships, rather than undermining them. This includes avoiding the de-skilling and erosion of instructor expertise (i.e. any skill related to academia that requires critical thinking, practice, and intentional development – e.g. exam preparation) due to an overreliance on AI.
• Faculty clearly articulate what form AI use will take in the course syllabus and will provide explicit instructions regarding AI use on the first day of class.
• Students maintain academic integrity in their work by not falsifying data, cheating, plagiarizing, and/or fabricating data.
• Faculty will equip students with the knowledge and skills to use AI technologies ethically, safely, and thoughtfully, while preparing them to meet the evolving demands of an AI-driven workforce. Faculty maintain the integrity and authenticity of their own teaching and research, modeling best practices for students, shaping the curriculum, and sustaining public trust in academia.
• Faculty comply with the relevant privacy laws, copyright legislation, UFV academic integrity policies (Policy 70), and the Tri-Council Policy Statement on Research Ethics (TCPS2).
This guiding document is meant to support faculty in achieving these aims by:
• Outlining AI uses that are not recommended.
• Providing ideas and examples of how AI could be used to support our goals.
• Provide templates that ease instructors' workload and promote consistent (or harmonized approaches) AI integration in the classroom. Providing an annually updated document that reflects new technological, legal, and policy related developments.
Scope: Applies to all faculty members, supporting consistency while allowing flexibility. Alignment: Reflects UFV’s mission, vision, and values, and is consistent with UFV-wide AI principles (2025).
•The guiding principle for AI use in the School of Kinesiology is deliberate and responsible use: faculty and students should pause to ask whether AI use in a particular circumstance is necessary, beneficial, and consistent with our core values, and consider whether non-AI tools, which avoid the costs and risks of AI, are sufficient for a particular task.
• Uphold Integrity: uphold academic integrity, professional ethics, accountability, and transparency in all uses of AI.
• Prioritize student learning: AI should enhance—not replace—the human dimensions of teaching, learning, and mentorship.
• Promote equity & inclusion: ensure accessibility and fairness, mindful of systemic biases and diverse learning needs.
• Protect privacy & data sovereignty: protect personal, health, and Indigenous data; comply with FOIPPA and ethical protocols.
• Be adaptable: recognize AI as a rapidly evolving tool; remain flexible and critical in its adoption.
• Inputting 3rd party personal, health, or Indigenous data into public systems without prior permission.
Why: Doing so violates relevant privacy laws (FOIPPA, PIPEDA) and Indigenous data sovereignty principles (OCAP). Public AI tools may store or repurpose inputs, leading to an ability to manage risk.
• Generating or altering research data using AI tools without both transparency and justification.
Why: This constitutes data fabrication or falsification, which breaches the Tri-Council Policy Statement (TCPS2) and undermines the credibility of research.
• Misrepresenting AI-generated content as original human work.
Why: Failing to disclose AI involvement is dishonest, undermines academic integrity, and can damage public trust in academia.
• Replacing human grading or substantive feedback with unreliable AI methods.
Why: Faculty are responsible for evaluating student work. AI-generated grading can be unreliable and biased, which can undermine fairness. Furthermore, inputting student assignment data, where the student’s identity is apparent, into public AI systems, where the data may be stored and repurposed, could violate the student’s copyright. These actions can harm the faculty–student relationship and present a legal risk.
• Relying on unreliable AI detection software.
Why: AI detection tools can produce false positives and negatives, leading to unfair accusations. Online detection tools may also store and repurpose input data. Diligence is needed to select appropriate tools. An alternative approach is to set clear expectations, require disclosure, and design assessments that prevent the inappropriate use of AI.
• Classroom Practices: Integrate AI where it supports engagement and outcomes.
• Academic Integrity: Clearly define what constitutes acceptable and unacceptable AI use (e.g., brainstorming vs. completing assignments). Align with Policy 70: Academic Misconduct.
• Introduction to AI: Provide basic definitions and examples of relevant tools (e.g., large language models, prompt engineering tools, virtual assistants).
• Benefits of AI: Use AI to enhance efficiency, personalize learning (adaptive study tools), and provide resources (summarization, assessment, and tools).
• Accessibility: Leverage AI for inclusive teaching (speech-to-text, translation, closed captioning).
• Accountability: Intended use by students and faculty in the classroom via wording in course syllabi, web content, and introductory lectures.
• Ethics Approvals: If participant data is to be analyzed using AI software, pertinent information about data storage and retention should be disclosed to the HREB and to candidate participants.
• Data Integrity: Maintain accuracy and transparency in AI-assisted analysis. Document and clearly state how tools are to be used.
• Responsible Tool Use: Evaluate AI platforms for reliability, security, and ethical standards before adoption.
• Practicum Sites: Model professionalism when students and faculty interact with health or community partners. Do not share sensitive practicum information with AI tools.
• External Partners: Communicate openly about AI’s role in collaborations. Use tools that are compliant with privacy and security standards.
• Public Discourse: Be transparent and responsible when using AI-driven platforms (blogs, social media) to represent the School of Kinesiology.
• Collaboration and Communication: AI-powered project management and scheduling tools may support teamwork—but should not replace interpersonal dialogue.
• Workload Balance: Consider using AI to streamline routine tasks (meeting notes, scheduling), ensuring equitable workloads across faculty.
Even when AI is used appropriately, faculty and students must remain attentive to the following ethical issues:
• Hallucinations and Artificial Data: AI systems can generate factually incorrect or entirely fabricated information. Users must verify accuracy and avoid relying on fabricated data in scholarship, teaching, or professional contexts. When you choose to use AI, you are responsible for the product.
• Deception: AI systems can sometimes mislead users intentionally, pretending to have capabilities that they do not, or sycophantically agreeing with the user. Faculty and students must recognize this risk, use sources outside the model, and weigh AI feedback appropriately.
• Bias: AI reflects the biases of its training data. Users must remain alert to systemic or cultural biases, cross-check outputs, and help students critically evaluate AI responses. Faculty and students should be aware of and avoid confirmation bias.
• Disclosure and Citation: Any substantive contribution from AI must be acknowledged. Students and faculty should cite AI tools using discipline-appropriate formats (APA, MLA, Chicago, etc.).
• Privacy and Consent: Beyond prohibitions, faculty and students must carefully consider when consent is required, whether data are truly anonymized, and how Indigenous data sovereignty principles apply.
• Equity of Access: Some AI tools are behind paywalls or require technical skills. If faculty design assignments assuming access, they risk disadvantaging students with fewer resources.
• Environmental Impact: Large-scale AI systems consume significant energy and water. Faculty and students should weigh the benefits of AI use against its ecological costs and adopt tools appropriate to the task.
• Faculty Support: Thorough training sessions, peer support, and access to UFV Teaching & Learning Centre resources will help faculty adopt AI responsibly.
• Feedback Loop: Annual review of this document by a faculty working group to ensure relevance and responsiveness.
• Shared Commitment: Emphasize that responsible AI use is a collective effort that protects students, faculty, and UFV’s reputation.
Artificial Intelligence (AI) Use in This Course
The School of Kinesiology supports the deliberate and responsible use of AI tools in teaching and learning. In this course, students may use AI tools (e.g., ChatGPT, Grammarly, coding assistants, translation software) under the following conditions:
Guiding Principles for AI Use
• Deliberate and Responsible Use
Consider whether AI use is necessary, beneficial, and aligned with our core values. Non-AI methods may be preferable when they better support learning or reduce risks.
• Uphold Integrity
Maintain academic integrity, professional ethics, and transparency. Misrepresenting AI-generated work as your own is a violation of academic conduct.
• Prioritize Student Learning
AI should support—not replace—the human aspects of education, including mentorship, collaboration, and critical thinking.
• Promote Equity and Inclusion
Be mindful of systemic biases and diverse learning needs. Ensure AI use is accessible and fair.
• Protect Privacy and Data Sovereignty
Do not input personal, health, or Indigenous data into AI tools. Comply with FIPPA and relevant ethical protocols.
• Be Adaptable and Critical
AI is rapidly evolving. Stay informed, flexible, and critical in its use.
Course-Specific Expectations
• AI use must be disclosed when used to assist with assignments (e.g., in a footnote or appendix).
• Some assignments may restrict or prohibit AI use; always follow specific instructions provided by the instructor.
• Students are responsible for verifying the accuracy and appropriateness of any AI-assisted work.
The kinesiology program has not only exposed me to the theory, but has equipped me with a vast amount of practical knowledge, applications, and tools to use in the future. This program has led me to pursue a career in medicine where I can have a positive impact on other and help them live a healthy life.