Assessment Objectives  

As part of Advanced Cardiorespiratory Physiology (KPE360, Fall 2024), this introductory laboratory assignment aims to familiarize students with the experimental environment and develop data collection skills essential for subsequent full laboratory experiments. In addition, the assessment introduces students to the use and critical evaluation of generative AI tools within scientific contexts. 

Assessment Process 

1. Experimental Setup: Students set up equipment including PowerLab, blood pressure sensors, and ECG electrodes. 
2. Data Collection: Students perform a series of trials, including Upright Rest (2 minutes), Squat-to-Stand (2 minutes rest + 1 minute squat + 2 minutes recovery), Stand-to-Lying down (2 minutes rest + 2 minutes lying down) and a Valsalva Maneuver (2 minutes rest + 10 sec Valsalva + 2 minutes recovery).
3. Data Analysis: Students analyze heart rate and blood pressure data using LabChart software.
4. Generative AI Component: Students use ChatGPT or Microsoft Copilot to generate a response to the question “In 250 words, explain why I feel light headed when rising from a squat?” They then critically evaluate and correct the AI-generated response based on provided scientific literature. 
5. Report Writing: Students prepare a report including: Title Page; Methods; Written Results; Tables/Figures; and Generative AI Question response. 

Future-Focused Skilled Development 

This laboratory assignment exemplifies key aspects of the University of Calgary’s STRIVE model, particularly in terms of student-centeredness and validity. The student-centered approach is evident in how the laboratory engages students directly with experimental equipment and data analysis software, promoting hands-on learning and critical thinking; students collect their own physiological data, analyze it using LabChart software, interpret the results, and analyze Generative AI output. This active engagement allows students to take ownership of their learning process and develop practical skills essential for junior scholars of kinesiology and physical education. The validity of the assessment is ensured through its multi-component nature and clear alignment with specific learning objectives. The inclusion of a generative AI component further supports the validity by requiring students to critically evaluate AI-generated content against scientific literature, developing their digital literacy and critical thinking skills. This comprehensive approach ensures that the assessment accurately measures a range of skills and knowledge relevant to the course objectives and future professional practice.   

Student Feedback 

Professor Bentely shares: “Overall, students appreciated the incorporation of generative AI, and the resulting development of AI literacy, given its rapidly developing relevance. Further, some students were surprised that the generated AI response was seemingly unrelated to the provided prompt while other students thought the AI did a reasonable layman’s explanation but lacked detail. It seems the takeaway by the students is that while generative AI may provide a starting point, critical assessment is required.“