370 - Data Exploration
Data Exploration --- The exploratory data analysis and visualization course aims to help students get started with their own data acquisition and exploratory analysis. Exploratory data analysis is crucial to evaluating and designing solutions and applications, as well as understanding information needs and use. Students in this course will learn basic concepts of information visualization and techniques of exploratory data analysis, using scripting, text parsing, structured query language, regular expressions, graphing, and clustering methods to explore data. Students will be able to make sense of and see patterns in otherwise intractable quantities of data. In this course students will be able to work with the Pandas, seaborn, and scikit-learn packages of Python.
388 - Putting the H in HCI: Human Perception, Cognition and Mental Processes
Putting the H in HCI: Human Perception, Cognition and Mental Processes --- Designing effective interactive systems requires understanding the needs and capabilities of users. In this course, we'll examine human capabilities and behavior related to the design of interactive information systems. We'll survey theories and findings from the social and biological services, with attention to how these concepts influence design for interaction.
405 - Information Analysis Capstone I
Information Analysis Capstone I --- Students will learn about team development, positive group dynamics, professional interaction with clients, assessing project needs, development of initial project ideas, surveying related industry organization and technology, related information fields, decision-making, and working through challenging, conflicting, or ambiguous problems. On completion of the course, student teams with have created a coherent high-level project plan identified in collaboration with a client.
407 - User Experience Design Capstone I
User Experience Design Capstone I --- Students will learn about team development, positive group dynamics, professional interaction with clients, assessing project needs, development of initial project ideas, surveying related industry organization and technology, related information fields, decision-making, and working through challenging, conflicting, or ambiguous problems. On completion of the course, student teams will have created a coherent high-level project plan identified in collaboration with a client.
410 - Ethics and Information Technology
Ethics and Information Technology --- Applies an emergent philosophy of information to a variety of new technologies that are inherently social in their design, construction, and use. Learning modules include: social media interaction; remembering/forgetting; and game design ethics. By collaborating on building a wiki community, students explore ethical/unethical information behaviors and test information quality metrics.
422 - Needs Assessment and Usability Evaluation
Needs Assessment and Usability Evaluation --- Any product--whether a website, a technological system, or an electronically mediated service--benefits from evaluation before, during, and after the development cycle. Too often, the people who use a product cannot find what they want or accomplish what they need to do. Products are more successful when they are developed through a process that identifies how the products will be used, elicits input from potential users, and watches how the product function in real time with real users. This course provides a hands--on introduction to methods used throughout the entire evaluation process--from identifying the goals of the product, picturing who will use it, engaging users through a variety of formative evaluation techniques, and confirming a product's function through usability testing and summative evaluation. Specific methods include personas and scenarios, competitive analysis, observation, surveys, interviews, data analysis, heuristic evaluation, usability testing, and task analysis. Students will work on group projects that apply these techniques to real products in use or development.
425 - Introduction to User Modeling
Introduction to User Modeling --- This course provides an integrated overview of techniques to model user behavior from economic theory, behavioral economics and computer science. The rational model of consumer choice is concise and provides a useful benchmark. Behavioral economics discusses under which conditions the rational model holds. As economic activity has moved online, "big data" sets have become available to analysts. In addition to theories, students learn the special empirical challenges when analyzing such large-scale online datasets.
429 - Online Communities: Analysis and Design of Online Interaction
Online Communities: Analysis and Design of Online Interaction --- This course gives students a background in theory and practice surrounding online interaction environments. For the purpose of this course, a community is defined as a group of people who sustain interaction over time. The group may be held together by a common identity, a collective purpose, or merely by the individual utility gained from the interactions. An online interaction environment is an electronic forum, accessed through computers or other electronic devices, in which community members can conduct some or all of their interactions.
430 - Information Technology and Global Society
Information Technology and Global Society --- In this course, students will examine recent and current global events featuring information technology, and through both discussion and introspection, construct their own personal hypotheses of technology and society. Along the way, students will hear about the way in which information technology is touching the remotest places in the world, gain an introduction to formal theories of technology and society, and stress-test their critical thinking skills.
431 - Algorithms and Society
Algorithms and Society --- Algorithms are a set of rules for computers to follow. Algorithms affect myriad aspects of everyday life, from facial recognition to privacy to policing to social media. This course will examine the ways that algorithms impact individuals and communities, especially in ways that may not be obvious to people who are consumers of algorithmic technologies. We will investigate concepts of bias, discrimination, fairness, ethics, and justice, especially as they relate to attributes like gender, race, or health. Students will be tested via quizzes and will be given an opportunity to explore new ideas.