Feedback Loop Explorer: An Interactive Learning Tool for Understanding Homeostatic Regulation

Feedback Loop Explorer is an interactive learning tool designed to reinforce foundational concepts in homeostatic regulation through active engagement, physiological applications, and immediate feedback. The activity guides students through five scenarios illustrating negative and positive feedback mechanisms across multiple physiological systems. For each scenario, students first determine whether the mechanism represents negative or positive feedback. They then use a drag-and-drop interface to construct the feedback pathway by identifying the stimulus, receptor, afferent pathway, integration center, efferent pathway, effector, and response. These activities challenge students to distinguish among the components of a feedback loop, recognize how information is communicated between structures, and examine how physiological responses either reverse or amplify an initial stimulus. Immediate feedback provides opportunities to evaluate responses, identify misconceptions, and reinforce understanding. Students receive targeted explanations and progressively more detailed hints when incorrect responses are submitted, with the correct answer revealed after three unsuccessful attempts. Upon completing each scenario, students can review the assembled feedback pathway and an explanation of the underlying regulatory mechanism. The tool is designed primarily for undergraduate anatomy and physiology courses but may also be appropriate for introductory biology and related courses. Instructors can incorporate it into classroom activities, assign it as an independent learning exercise, or recommend it as a supplemental resource for reviewing course material and preparing for examinations. Feedback Loop Explorer is freely accessible through GitHub Pages and can be completed using a standard web browser without downloading additional software or creating an account. The tool was developed with the assistance of generative artificial intelligence (AI), with the instructional content, scientific accuracy, and pedagogical design guided and reviewed by the author.