An undergraduate laboratory to study exercise thresholds

In exercise physiology, laboratory components help students connect theoretical concepts to their own exercise experiences and introduce them to data collection, analysis, and interpretation using classic techniques. Most courses include a lab protocol that involves exhaustive incremental exercise during which expired gas volumes and concentrations of oxygen and carbon dioxide are measured. During these protocols, there are characteristic alterations in gas exchange and ventilatory profiles that give rise to two exercise thresholds: the gas exchange threshold (GET) and the respiratory compensation point (RCP). The ability to explain why these thresholds occur and how they are identified is fundamental to learning in exercise physiology and requisite to the understanding of core concepts including exercise intensity, prescription, and performance. Proper identification of GET and RCP requires the assembly of eight data plots. In the past, the burden of time and expertise required to process and prepare data for interpretation has been a source of frustration. In addition, students often express a desire for more opportunities to practice/refine their skills. The objective of this article is to share a blended laboratory model that features the “Exercise Thresholds App,” a free online resource that eliminates postprocessing of data and provides a bank of profiles on which end-users can practice threshold identification skills with immediate feedback. In addition to including prelaboratory and postlaboratory recommendations, we present student accounts of understanding, engagement, and satisfaction following completion of the laboratory experience and introduce a new quiz feature of the app to assist instructors with evaluating student learning. NEW & NOTEWORTHY We present a laboratory to study exercise thresholds from gas exchange and ventilatory measures that features the “Exercise Thresholds App,” a free online resource that eliminates postprocessing of data and provides a bank of profiles on which end-users can practice threshold identification skills. In addition to including prelaboratory and postlaboratory recommendations, we present student accounts of understanding, engagement, and satisfaction and introduce a new quiz feature of the app to assist instructors with evaluating learning.