<aside> 🪧

Welcome to

Introduction to Human-Computer Interaction

COSC 67/267 • Fall 2025 • Dartmouth College

</aside>

A Dartmouth depiction of human-computer interaction, created by human-computer interaction.

The two hardest problems in Computer Science are: (i) people, and (ii) convincing computer scientists that the hardest problem in Computer Science is people. — Jeff Bigham’s Law of Computational Difficulty

Table of Contents

<aside> <img src="/icons/table_green.svg" alt="/icons/table_green.svg" width="40px" />

</aside>

Course Staff

Overview

Computing systems increasingly shape how we think, act, and interact with the world. This course examines interactive computing systems through the lenses of design$^1$ and evaluation$^2$, grounded in foundational theories and methods from the field of Human-Computer Interaction (HCI). Because HCI is most often an interdisciplinary and translational discipline, these principles and methods apply to a range of important application domains which we will also examine, from data visualization to wearables to AI systems. We will study both quantitative and qualitative research methods to understand human behavior in service of designing effective interactive systems. Students will learn to design, engineer, and evaluate usable, useful, and contextually appropriate systems through lectures, readings, and hands-on assignments.

Students will learn to design, engineer, and evaluate usable, useful, and contextually appropriate systems through lectures, readings, and hands-on projects. The course culminates in a team project where students work with a real-world problem and are expected to complete the full HCI research cycle: from formative research and iterative design, through a working high-fidelity implementation, to empirical evaluation with real users. The course balances scientific rigor with practical application.

This course is ideal for students who:

• Want to understand how people interact with technology
• Seek to ground interaction design decisions in evidence
• Are motivated to learn both quantitative methods (controlled experiments, statistical modeling) and qualitative approaches (interviews, ethnography, observational studies)
• Want to contribute new knowledge to the study of human-computer interaction