VVZ API is not affiliated with ETH Zurich. Data might be outdated or incorrect. Please view the official ETHZ Vorlesungsverzeichnis for binding information.

851-0257-00L 3 Credits DS , DR D-GESS
You're viewing possible stale or outdated data. Please check the latest semester for more up-to-date information.

Quantitative User Experience Research: Surveys and Logs Analysis

Lecturers & Examiners: Prof. Dr. Christoph Hölscher, Dr. Iva Barisic, Dr. Leonel Aguilar Melgar, Dr. Benjamin Davison
VVZ CR n/a

Last Updated: 2026-06-01 11:30:56

Abstract

Quantitative user experience research is a human-centered perspective on problems, using large amounts of data to make general conclusions about people and technology. Solving these problems effectively requires a mix of technical skills and critical thinking. This course covers social considerations in quantitative research and the process of creating effective surveys and data logs.

Objective

Students will 1. understand how user consent has shifted with logs and surveys and the impact on society 2. be familiar with case studies of when large-scale research has been effective or problematic 3. be capable to tie research questions to survey and logs research 4. have skills to deploy and analyze surveys 5. have skills to analyze user logs

Content

Quantitative user experience research is a human-centered perspective on problems, using large amounts of data to make general conclusions about people and technology. Solving these problems effectively requires a mix of technical skills and critical thinking.The course draws from behavioral science (cognitive science & psychology) as well as from human-computer interaction techniques, providing a bridge to computer science and engineering / design disciplines that develop digital and physical systems with human users. This course focuses on two key methodologies from quantitative research, surveys and user activity logs. Students will learn how to design, deploy, analyze, and report log data and survey results. They will learn and apply key techniques for large-scale data collection, such as best practices for consent and recruiting, tradeoffs with different types of survey questions, and creating generalizable results using inferential statistics. Throughout the course, students will be faced with larger, societal challenges in the area of Big Data. How does participation consent change when it is buried in a license agreement? When does large-scale analysis get it wrong? How does the shift to participants at the lowest cost impact scientific rigor? It is not required to know advanced statistics or how to program in order to take this class. Students will collect and analyze data, but we will provide pre-fabricated data, clear statistical examples, and code for initial analysis. The class will focus on higher-level concepts, such as tradeoffs with different survey questions or statistical methods, and give students a chance to apply the concepts to situations and data. Students will be responsible for class work and a final project and paper. Class work will focus on societal issues and challenges related to research execution. At the end of the semester, students will create a research project which applies research methods learned in class to evaluate an idea or a product and report findings. At the end of the course, students will understand high-level considerations with surveys and logs, and have a core toolkit to collect and understand user behavior and feedback. In addition, they will have a larger view of the field of quantitative user experience research and its impact on society.

General Information

Language
English
Levels
DS , DR

Examination

Type
graded semester performance

Registration & Places

Max Places
35

Course Components

Type Title Time & Place Hours
seminar Quantitative User Experience Research: Surveys and Logs Analysis
  • Thu 10:15-12:00 (ML J 37.1)
2 h weekly

Offered In