Course Offerings

In this class, students will first learn some fundamentals of cultural heritage informatics and be introduced to the major kinds of institutions in this space: galleries, libraries, archives, and museums. Students will also see case studies of how fundamental concepts like access or metadata get used in contemporary examples.

This course we will explore the concepts and values of open knowledge and knowledge equity and how they intersect with the ongoing evolution of digital environments. Open knowledge can be described as information that is freely available to the public to use and redistribute. Knowledge equity extends beyond information access and use to also include what is valued as knowledge, whom that knowledge represents, and who creates it.

Engage in modern ethical dilemmas within archives, libraries, and museums, considering issues of collections management and preservation within changing cultural frameworks. This I 320C topic carries the Cultural Diversity in the United States flag. The purpose of the Cultural Diversity in the United States Flag is for students to explore in-depth the shared practices and beliefs of one or more underrepresented cultural groups subject to persistent marginalization. In addition to learning about these diverse groups in relation to their specific contexts, you’ll also reflect on your own cultural experiences.

This course introduces digital archival collections that can be accessed and used as data for research and inquiry. Topics will focus on the transformation, analysis, and interpretation of digital cultural heritage in archival contexts, including digitization, web archiving, software emulation, and data archiving. From text messages, Spotify playlists, to the President's tweets--how are digital traces collected, preserved and managed by archives? What are the ethics of managing digital archives and making them accessible to researchers, the public, and machines?

What does it really mean to be user-centered? How do we practice user-centered design in a professional and methodical manner? What research findings can we rely on to help us improve user experiences? This is a readings/discussion course that examines in depth what we know about people (that is, what does scientific research actually tell us) and how can we apply this knowledge in the real-world of experience design. We examine human psychology, from physical ergonomics to cultural dispositions, stopping off on cognition and social analyses en route, so as to have a holistic, robust perspective on what it means to understand users. The readings are complemented with an examination of methods e.g., what is a cognitive walkthrough and how do you do it reliably? what are the limitations of heuristic evaluations? The goal is to give you a solid grounding in the practices of user-centered thinking, regardless of your area of application, and prepare you for professional level contributions in the user-experience world. There is no teamwork, all students deliver individual term papers and design critique diaries. There are also no pre-requisites -- technical or theoretical, the class is open to all.

Explore common data collection, management, and sharing practices in information technology and emerging technologies, such as search engines and AI systems. Students will read papers and engage in discussions about the pros and cons of established data practices and learn about the three main components of responsible data management: 1) consent and ownership, 2) privacy and anonymity, and 3) broader impact. Students will also practice how to collect data, make data-driven decisions, and design data-driven products through group projects as UX designers, researchers, and data scientists. The course will bring in interdisciplinary perspectives with guest speakers from archive science, engineering, and respponsible AI, to provide a holistic view of broader data ecosystems and infrastructures.

In this course, we will work to understand and address the challenges of misinformation, disinformation, and strategic manipulation in online environments. First, we will work to develop a deep understanding of the problem space. We will read and discuss existing research (both historical and contemporary) on how and why misinformation and disinformation spread. Next, we will explore the process, both personal and interpersonal, by which these issues can be approached and addressed in our own lives. This will involve reflecting on our own presuppositions, beliefs, and biases about information; and doing a project in which we apply the principles of Human-Centered Design to investigate different design directions for addressing misleading information. Students will gain important contextual knowledge and hands-on design experience that they can take into future professional domains (from education to policy to technology), where they can contribute to building more trustworthy information systems.

Accessible UX provides students working (or planning to work) in any area of UX, Digital Product Management, or Development with key skills and insights into the current accessibility landscape, in addition to specific guidelines and WCAG conformance specifications. The course is divided into foundational and tactical modules. The first half of the course provides a comprehensive overview of Accessibility and its importance. The second half of the course involves evaluating real-world applications and websites per the WCAG guidelines, producing Accessibility reports, planning studies (with persons with disabilities), and designing for accessibility. Course Goals 1. Become proficient in recognizing accessibility issues in key domains 2. Understand successful team and organizational behaviors in Accessibility 3. Learn how Accessible UX and Development is accomplished 4. Evaluate Web and App experiences using the WCAG framework from W3.org/WAI

The purpose of this course is to provide theoretical and practical foundations for information professionals who wish to design and evaluate search systems and services, taking user-centered approaches. This course explores search user interfaces, search behavior, search interaction, search user experience, search as learning, search for creativity, and research methods for understanding information behavior and evaluating search systems. Students will learn search behavior across various contexts, including academic and professional settings, everyday life, and digital learning environments. Students will gain insights into how people interact with, use, and evaluate information in a variety of application areas, such as web search engines, domain-specific search systems, digital libraries, social search platforms, and generative AI-based systems.

Learning key data wrangling maneuvers in abstract and implementations in SQL, Excel, R Tidyverse, and Python Pandas. Maneuvers in data transformations include Nest, Pivot, Mutate (inc. separate/unite), Group/Summarize and Rectangling. Projects include working with "wild caught" data datasets (usually CSV or JSON) and computational notebook environments (e.g., iPython, Jupyter, Rmarkdown, Quarto). Fall 2024 has changes from previous syllabus now that we have Database Design and Introduction to Programming. Nonetheless, the previous syllabus is still useful as it links to course materials that show the teaching approach and type of assignments. http://howisonlab.github.io/datawrangling/#Schedule_of_classes

Introduction to combining human and machine intelligence to benefit people and society. Explore cutting-edge research on a number of subjects related to human-AI interaction, including the psychological and societal impacts of AI as well as design guidelines and methods for human-centered AI.