Special topics courses

Special topics courses include courses that address a current or timely topic, that are in a "pilot" phase before being offered on an ongoing basis, or that are known to be one time offerings. Special topics course offerings can vary from term to term.  This list includes course descriptions and meeting information for current UMSI Special Topics courses.

Fall 2017

SI 699.001 UX Research and Design (Tawanna Dillahunt) - Mastery Course
This course will require students to demonstrate mastery in application of design theories, concepts, and principles to defining valid problems, uncovering user needs, articulating service requirements, documenting UX research results, proposing, refining, and prototyping design solutions, and communicating with stakeholders effectively. Students will have opportunities to integrate methods and theories about user experience design in this course by engaging in a whole process from identifying design issues to developing design solutions. Students will work on a single project end-to-end during the semester. They will either work on a project individually or in pairs. For the most part, projects will be chosen and designed by students from scratch, though projects for real-world clients will be allowed as long as they meet the course requirements.

SI 699.002 Search and Recommender Systems (Kevyn Collins-Thompson) - Mastery Course
The search and recommender systems mastery course will require students to demonstrate mastery of theoretical models, algorithms, evaluation methods, and user interfaces for search and recommender systems. Students will synthesize methods from information retrieval, natural language processing, machine learning, and related fields. Students will work on semester-long projects that address real-world problems. Aligned with best industry practices, students will be expected to work in a fast-paced environment and to demonstrate independence and creativity as well as technical mastery.

SI 699.003 Developing Social Computing (Erik Hofer) - Mastery Course
This course provides students an opportunity to develop and demonstrate mastery in user research, application design, and system implementation by creating novel social computing applications. This course challenges students to build on prior coursework in human-computer interaction and programming to apply and adapt their existing skill sets to identify and solve the problems that arise in the design of a new social computing system, including the areas of user experience, technical implementation, and stakeholder communication. It is intended for students who want to go beyond prototypes to understand the full experience around creating and launching a new system.

SI 710.003 Social Network Experiments (Tanya Rosenblat) - Methods
This course provides an introduction on how to use experimental methods to study behavior in social networks.  Social networks are conduits of information; they provide crucial support in times of need and access to financial and other resources. The extent of an agent’s social network is a measure of her social capital. Estimating the effects of social networks poses special statistical problems which are hard to overcome when using only observational data. This is where carefully designed experiments can be very helpful.  This course explores experimental methodology and social networks applications by concentrating on series of experiments, to see how experiments build on one another.

In this class we first learn how to map relevant social networks and then discuss several major themes in the social network literature that have been studied using laboratory and field experiments including: (1) social learning, (2) trust in networks, (3) coordination in networks and (4) the relationship between networks and markets. Within each theme, we study the relevant theory literature and existing experimental research. In the process, we revisit classic experimental topics such as individual choice, market experiments, bargaining, social preferences to see how they can be enriched by social networks.  Applications range from online experiments using social media such as Facebook and Twitter to field experiments in developing countries. Each of the modules concludes with an assignment to design a new experiment.  Students are expected to expand one of these assignments as a term paper.  Students are encouraged to work in groups.

Students are introduced to social network theories and experimental methodology through lectures, by participating in interactive in-class experiments and demonstrations, critically reading and discussing related research papers and eventually designing and implementing their own research experiment(s).  At the end of the course, students will be able to understand how general principles of experimental design can be applied to study of social networks.  Students will be able to design and implement their own experiments and critically evaluate published work in the field.  Interested students will have an opportunity to complete their research projects and write up results for publication and conference presentations.


Winter 2018

SI 699-00X Digital Curation (Margaret Hedstrom) - Mastery Course
This mastery course prepares students for careers in data management, access, and preservation in many different venues: research libraries as data services librarians and digital collections managers, digital archives and domain repositories (e.g. ICPSR, NOAA and NASA data centers, NCAR), the publishing and entertainment industry as digital product managers, corporations and not-for-profits as internal data management specialists, and as consultants. Students will be prepared to participate in, manage, and create elements of the rapidly developing digital curation infrastructure that is the outcome of efforts by industry, government and not-for-profit entities.

SI 699-00X Big Data Analytics (Mei Qiaozhu) - Mastery Course
This course requires students to demonstrate mastery of data collection, processing, analysis, retrieval, mining, visualization, and prediction. Students synthesize methods from information retrieval, statistical data analysis, data mining, machine learning, and other big-data related fields. They work on semester-long projects that deal with industry-scale data sets and solve real-world problems. Aligned with best industry practices, students are expected to work in a fast-paced, collaborative environment and to demonstrate independence and leadership. Students must be able to create and use tools to handle very large transactional, text, network, behavioral, and/or multimedia data sets.

SI 699-00X UX Research and Design (Silvia Lindtner) - Mastery Course
This course will require students to demonstrate mastery in application of design theories, concepts, and principles to defining valid problems, uncovering user needs, articulating service requirements, documenting UX research results, proposing, refining, and prototyping design solutions, and communicating with stakeholders effectively. Students will have opportunities to integrate methods and theories about user experience design in this course by engaging in a whole process from identifying design issues to developing design solutions. Students will work on a single project end-to-end during the semester. They will either work on a project individually or in pairs. For the most part, projects will be chosen and designed by students from scratch, though projects for real-world clients will be allowed as long as they meet the course requirements.

SI 699-00X Learning and the Learner (Kristin Fontichiaro) - Mastery Course
Students build on the foundational skills in planning for, facilitating, and evaluating learning acquired in SI 643 and other courses and deploy those skills in a practicum setting. Students partner with professional mentors in software firms, instructional technology settings, schools, libraries, and museums for real-world teaching and learning practice, gaining face-to-face and virtual experience in effective contemporary instructional practices.

SI 710.004 Practical Use and Communication of Bayesian Statistics (Matthew Kay) – Methods
This course provides a practical introduction to Bayesian regression with an eye towards analyzing experimental results. It walks through the basics of probability theory, Bayes' rule, linear regression, the generalized linear model, mixed effects models, prior selection, and model comparison/averaging using information criteria. All content will be presented within a single coherent statistical framework, to give students the knowledge necessary to move away from a "decision tree" approach to statistical test selection. The focus is practical and accessible analysis: students will build models in R, with the primary language of discourse being code and samples rather than math. Attention will also be paid to communicating model estimates and predictions effectively, and fully acknowledging the uncertainty in statistical results.

SI 710.005 Collaboration Through Technology (Lionel Robert) – Theory
This course is designed to give the student a basic understanding of research on theories of collaboration through technology. The term collaboration is intended to include communication, cooperative and coordination. Therefore, theories of collaboration through technology refers to theories that describe technology mediated communication, cooperative and coordination. In this course we will survey contemporary theories and findings from the social sciences (especially organizational behavior, information systems and social psychology), with special attention to how these concepts influence our understanding of collaboration. This course employs weekly readings and relevant discussions of key issues associated with the assigned reading.

SI 710.006 Work and Labor in the Age of Tech Entrepreneurialism & Platform Capitalism (Silvia Lindtner) – Theory
From unwaged work performed on Uber to the rise of flexible and freelance work marked by low-pay and the decline in social security for the creative class, precarious labor has become normative in the information economy. At the same time, politicians, corporations, educators and advocates of the free culture movement alike promote a techno-utopian vision of self-reliance, entrepreneurial thinking, and hands-on innovation to address contemporary social and economic instability. If you give people the tools to make their own technologies, they will be empowered to make their own jobs, education, governance, and livelihoods, so the story often goes. Neoliberal tendencies are masked with an enticing rhetoric of innovation thinking. Technological intervention and scientific progress are rendered once again as inevitable pathways to deal with and address contemporary conditions of utmost political, social and economic insecurity and instability.

In this seminar, we will explore questions such as: What are the analytical tools that account for these contradictions between innovation thinking and utopian ideals on the one hand and the rise of neoliberal conditions, political control, and economic and social instability on the other? How do the promises of techno-utopian visionaries from open source movements to digital activists butt against the rise of socio-economic disparity and the rise of racism, fascism and fear? What are the social, economic and political shifts that occurred on a global scale over the last decades that lead up this current moment? What kind of resistance is possible today in times of the neoliberal expansion?