Course Offerings

This is a survey course covering the basics of the informatics professions. We cover some history of informatics as an academic discipline and profession, review some of the significant concepts that students can expect to cover later in the Informatics major and minor, and review the different concentrations available to Informatics students. Assessment in this course is conducted through weekly quizzes and discussion questions; a short, persuasive, group presentation; and a longer-term persuasive essay project with both individual and group components.

This class offers students hands-on practice with Canvas and other digital tools in order to scaffold success in the informatics program. Students will conduct an independent, iterative research project including the following steps: crafting a research question, finding and evaluating sources, and presenting information.

Survey the ethical foundations for informatics, incorporating non-Western and feminist perspectives. Apply these ethical foundations to contemporary problems in informatics. Examine the confrontation of ethical dilemmas in the workplace, including recognizing value trade-offs, affected stakeholders, and potential solutions. Offered on the letter-grade basis only. This course carries the Writing Flag and the Ethics flag Ethics courses are designed to equip students with skills that are necessary for making ethical decisions in their adult and professional lives. Students should therefore expect a substantial portion of their grade to come from assignments involving ethical issues and the process of applying ethical reasoning to real-life situations.

Introduction to computer programming for those without any prior knowledge or experience in computer programming. We will introduce four broad areas related to success in computer programming: language, software engineering concepts, programming environment, and practical know-how.

In this age of information, we repeatedly hear the phrase “Do your research!”, but what does that mean? And more importantly, why does it matter? This course is broken into two parts designed to provide a foundation to begin answering these questions: 1. The first half of the course is an introduction to research, exploring what research is, what research can look like within the field of Informatics, and how Informatics research can be leveraged for social good. 2. The second half of the course dives deeper into “research methodology,” how research is done and some of the most common tools we use to explore the field’s most burning questions. Students will learn about the functions of qualitative and quantitative methods, as well as how the pieces of the research process fit together to explore challenges and potential solutions by applying human-centered values to the intersections of information, people, and technology. This course is held in-person and rather than exams, assignments are designed to encourage students to apply course concepts to their own interests. Students will leave this course empowered as citizens to critically evaluate research in terms of process, ethics, and equity.

We will describe data using visual and numerical descriptions (visualization and summary statistics). We will learn to make predictions and draw inferences using simple and multiple linear regression. We will learn classification using logistic regression. We will learn how to interpret diagnostic plots that accompany linear models. We will practice all these things using R and RStudio, which will be taught as part of the class. Some math and programming is not required but will be helpful in reducing the workload in the class. A statistics course is required but other statistics courses can be substituted for this one. This course counts for the Quantitative Reasoning flag, starting in Fall 2024.

This course is designed to help set students majoring in Informatics up for career success post-graduation. What does career success look like? Well, philosophically many things depending on context. This course, however, focuses on the transition between the last year of college and the first year of a career. The semester is broken into three units as a foundation to begin answering these questions: 1. The Landscape: What opportunities exist for graduates with my skillsets and interests? What do different job titles actually mean? How do I know which path is right for me? How do I find jobs and opportunities I’m interested in and qualified for? 2. The Application & Interview Process: After Unit 1, I know the kinds of positions and career paths I’m interested in post-graduation, but how I do actually get the job/position or accepted to my program of interest? In a sea of hundreds (sometimes thousands) of applicants, how do I show I’m a good fit in an application and an interview? Once I have options, how do I choose what’s right for me? 3. The First Year: How do I make sure my first year is successful? How do I navigate a new professional space? How do I set myself up to build relationships and perform well? How do I apply what I’ve learned in the Informatics Major and at UT to grow as an ethical, equitable leader and information professional? This course is held in-person and rather than exams, assignments are built as concrete materials students can use in their career searches and professional endeavors. Students will leave this course empowered to successfully navigate the Informatics-related job market and professional opportunities

As the culminating experience of the undergraduate Informatics Program, I 379C allows every student to apply their unique skillsets and learnings to a "degree-capping" project that is focused on a real-world problem or initiative. Informatics Capstone projects can take many forms, but typically involve aligning on a specific project and plan with an industry or faculty project sponsor, and then completing the project over the course of the semester. This course is designed to support your capstone journey throughout the semester as you work on your project with your Field Supervisor. Progress in the course is measured through weekly updates and documents submitted directly to Canvas. During the semester, the course meets once per week, and during these sessions we'll focus on items and issues relevant to your capstone experience. You'll have an opportunity to present your work also, through class presentations and the final poster session where your sponsors, faculty, and other students can meet you and discuss your project. Summary of Course Goals 1. Deliver a professional-level project/solution to showcase your knowledge, skills, and abilities. 2. Take direction and feedback from a supervisor working in your applied field of study. 3. Strengthen communication and presentation skills. 4. Manage expectations around project goals, schedule, and deliverables.

This course explores the fundamental principles and practical applications of Information Architecture (IA). Drawing from the seminal work "Information Architecture: For the Web and Beyond" by Louis Rosenfeld, Peter Morville, and Jorge Arango, students will delve into the essential concepts, methodologies, and best practices shaping the organization and presentation of information in digital environments. Simply, this course addresses how to make content organized and findable based on human understanding. Throughout the course, students will examine the critical role of IA in enhancing user experience, facilitating navigation, and optimizing content discoverability. Topics covered include information organization, navigation design, metadata implementation, taxonomy development, and user-centered design principles. Through a combination of theoretical discussions, case studies, hands-on exercises, and a real project with a real client and real world constraints, students will gain proficiency in designing effective IA solutions tailored to diverse user needs and contexts. Emphasis will be placed on understanding user behavior, conducting user research, and iteratively refining IA structures to align with evolving user requirements and organizational goals. Course Objectives: Gain a comprehensive understanding of Information Architecture principles and methodologies. Learn how to analyze and evaluate existing IA structures in digital environments. Develop proficiency in designing and implementing effective IA solutions for websites and digital products. Explore techniques for conducting user research and applying user-centered design principles to IA. Understand the role of IA in enhancing usability, findability, and overall user experience. Acquire practical skills in wireframing, prototyping, and usability testing within an IA context. Explore emerging trends and technologies shaping the field of Information Architecture.

This course will give students a foundational introduction to user experience (also known as UX, CX, HCI) and introduce some of the core UX research methods in use today, as well as applying these methods to a product to create a final presentation that can hopefully be used in their portfolio/job seeking adventures. Accordingly, the class will cover 5 major areas: 1. Have an in-depth understanding of some primary UX methods relevant to product development (e.g. Heuristic evaluation, Moderated User testing, UX Benchmarking). 2. Understand the principles of other important UX tools/methods (e.g. Information architecture tests (card-sorts), RITE testing, Competitive Analysis, Thematic coding of qualitative data, etc.). 3. Have a working understanding of the most frequently used UX methods at each point of the development lifecycle, with a specific focus on which methods are best suited to evaluative research. 4. Learn the scientific underpinnings of the various methodologies, including the specific advantages and disadvantages of each. 5. The “real world” application of these skills to industry-paced projects

A practical introduction and guide for using statistics to solve quantitative problems in user research. Many designers and user researchers view usability and user research as qualitative activities, which do not use formulas and numbers. However, usability practitioners and user researchers are increasingly expected to quantify the benefits of their efforts. The impact of good and bad designs can be quantified in terms of user performance, task completion rates and times, perceived user satisfaction. The course will address questions frequently faced by user researchers, such as, how to compare usability of products for A/B testing and competitive analysis, how to measure the interaction behavior and attitudes of users, how to estimate the number of users needed for usability testing. The course will introduce students to a foundation for statistical theories and the best practices needed to apply them. It will cover descriptive statistics, confidence intervals, standardized usability questionnaires, correlation, regression, and analysis of variance. It will also address how to effectively communicate the quantitative results.