Introductory programming students routinely struggle with the “invisible” aspects of modular programs: where values come from, how they move between functions, and what it means to “return” a result. Amp Stack is a lightweight, visual methodology that makes data flow and modular structure explicit by having students design programs as top-to-bottom stacks of “amps” (Input, Compute, and Output blocks) wired together by named ports before they write any code. In this 3-hour, hands-on workshop, participants will experience Amp Stack from the student point of view, translate diagrams into runnable Python, and then step back to examine how the approach scaffolds CS1 concepts such as IPO structure, parameter passing, and modular decomposition. Attendees will leave with ready-to-use classroom materials (worksheets, sample exercises, and rubrics) and a plan for integrating Amp Stack into their own introductory courses with minimal disruption to existing syllabi.

Students often struggle to understand data structures due to the challenges of developing mental models of concepts like abstract data representations, memory organization, and the ways these structures evolve during program execution. This tutorial introduces a suite of hands-on activities designed to make abstract data structures tangible by manipulating concrete physical models.

Drawing on insights from active learning in STEM education, we will present ready-to-use activities that allow students to explore common data structures and fundamental algorithms by manipulating physical objects. By initially focusing on the development of accurate mental models, these activities help students scaffold their understanding towards formal representations or code-based implementations.

The tutorial is aimed at instructors interested in active learning approaches. Participants will engage with several of these activities firsthand and discuss strategies for integrating them into CS1, CS2, and early algorithms courses, leaving with classroom-ready activities, implementation guidance, and materials that can be easily adapted to their own institutional contexts.