School of Kinesiology, The University of Western Ontario, London, Ontario, Canada.
Sports Medicine Department, University Hospital of Tübingen, Tübingen, Germany.
Adv Physiol Educ. 2023 Sep 1;47(3):604-614. doi: 10.1152/advan.00055.2023. Epub 2023 Jun 29.
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. 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.
在运动生理学中，实验室组成部分帮助学生将理论概念与自己的运动经验联系起来，并介绍使用经典技术进行数据收集、分析和解释。大多数课程都包括一个实验室方案，其中涉及详尽的递增运动，在此期间测量呼出气体量以及氧气和二氧化碳的浓度。在这些方案中，气体交换和通气特征会发生特征性变化，从而产生两个运动阈值：气体交换阈值（GET）和呼吸补偿点（RCP）。能够解释为什么会出现这些阈值以及如何识别它们是运动生理学学习的基础，也是理解包括运动强度、处方和表现在内的核心概念的必要条件。正确识别 GET 和 RCP 需要组装八个数据图。过去，处理和准备数据以供解释所需的时间和专业知识的负担一直是令人沮丧的来源。此外，学生经常表示希望有更多机会练习/完善自己的技能。本文的目的是分享一种混合实验室模型，其特点是“运动阈值应用程序”，这是一个免费的在线资源，可消除数据的后处理，并提供一个用户可以练习阈值识别技能并获得即时反馈的配置文件库。除了包括实验室前和实验室后的建议外，我们还展示了学生在完成实验室体验后的理解、参与和满意度，并介绍了应用程序的新测验功能，以帮助教师评估学生的学习情况。我们提出了一个从气体交换和通气测量中研究运动阈值的实验室，其特点是“运动阈值应用程序”，这是一个免费的在线资源，可消除数据的后处理，并提供一个用户可以练习阈值识别技能并获得即时反馈的配置文件库。除了包括实验室前和实验室后的建议外，我们还展示了学生在完成实验室体验后的理解、参与和满意度，并介绍了应用程序的新测验功能，以帮助教师评估学生的学习情况。
