HCI Courses at UMD
HCIL has compiled a list of human-computer interaction courses to be offered in the Spring of 2008 at the University of Maryland. In addition to courses to be taught by HCIL members, there are courses being offered from several different departments which have shown interest in human-computer interaction issues.Below is a concise list of courses with only instructors, titles and times of their meetings. A detailed description of each course follows this list. For a complete schedule of UMD classes, visit: http://www.testudo.umd.edu/ScheduleOfClasses.html
HCI Course List, SPRING 2008
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ENGL758C - Literary Criticism and Theory: Simulations
Instructor: Matt Kirschenbaum
Meeting time: W 3:30pm- 6:00pm (MCK B0135) -
CMSC 434 - Introduction to Human-Computer Interaction
Instructor: Ben Bederson
Meeting time: Mon/Wed 2:00pm - 3:15pm (CSI 1121) -
CMSC 838V - Creativity Support Tools
Instructor: Vibha Sazawal
Meeting time: Tue & Thur 12:30pm- 1:45pm (CSI 2118) -
CMSC 828G - Link Mining and Dynamic Network Analysis
Instructor: Lise Getoor
Meeting time: Tue & Thur 11:00-12:15pm (CSI 2107) -
INFM220 - Information Users in Social Context
Instructor: Jennifer Golbeck
Meeting time: Tue & Thur 3:30pm- 4:45pm (EGR 0135) -
Psyc 798J: Graduate Seminar: Doing Psychological Research on the Internet: Issues and Methods
Instructor: Kent Norman
Meeting time: Tue 1:30pm- 4:00pm (BPS 1112)
Course Descriptions:
ENGL 758C - Literary Criticism and Theory: Simulations
(3 credits) Grade Method: REG
Is simulation the consummate genre of the 21st century? How can we
negotiate between simulation as a trope of science fiction and
cultural fantasy (the Matrix, to name one obvious example) and the
non-virtual reality of the Strip in Las Vegas, or the best-selling
video game franchise The Sims? The objective of this seminar will be
to range freely between simulation as the essential focalizer of the
postmodern, between practices of applied modeling in humanities
research online (such as the Virtual Vaudeville project, which
painstakingly recreates a performance in a turn of the century
Manhattan theater), and between simulation as an established mode and
form of digital gaming. We will read widely in the literature and
theory of simulation, from obvious high postmodern candidates like
DeLillo, Baudrillard, and Haraway to more exotic sites of engagement,
such as military technology, theoretical mathematics, artificial life,
and the philosophical discourse of modeling. Indeed, our goal will be
eventually to adjudicate among three interrelated terms: simulation,
modeling, and gaming; and to come to grips with their import and
distinctions in the contemporary environment. To what extent are these
forms and practices rivals or competitors to the literary? Can a
simulation (or a game) sustain a narrative? Is the virtual merely the
latest in an age-old progression of mimetic devices, or is it
something else? Something new?
A key component of the course will be a set of hands-on explorations
using the popular virtual world Second Life. Students will engage with
the cultures and sub-cultures of Second Life by creating avatars and
participating in the communities and events of this thriving virtual
world (current population: 10 million). With only slightly greater
investment, students may also learn to "build" in Second Life,
contributing their own objects, structures, and experiences to the
community. Part simulation, part model, and part game, Second Life
will be the social arena in which we seek to activate and literalize
our weekly conversations.
CMSC 434 - Introduction to Human-Computer Interaction
(3 credits) Grade Method: REG
This is an introductory course to the field of Human-Computer Interaction. It concentrates on the effectiveness and efficiency of computer technology from the user's point of view. While we will present basic human factor results and develop some technology to build interfaces, the focus is on user experience.
In this course, we look at the complete life cycle of interface development. Following a standard pattern of product development, we will discuss key aspects of the design process including: the Analysis of users needs, the formalization of these needs (Definition), the exploration of possible solutions to address these needs (Ideation), the evaluation of the potential of these solutions (Idea Evaluation), the Implementation of prototypes and their Evaluation.
CMSC 838V - Creativity Support Tools
(3 credits) Grade Method: REG/AUD
In this course, students will demonstrate their ability to create
software or hardware tools that promote collaborative discovery
and invention. Topics include brainstorming, mind mapping, flow,
incubation, and existing creativity support tools.
CMSC 828G - Link Mining and Dynamic Network Analysis
(3 credits) Grade Method: REG/AUD
There has been a recent surge of interest in the analysis of data describing all forms of networks, including communications networks, biological networks, social networks, financial transaction networks and more. Despite the diversity of domains, common difficulties and challenges include noisy and incomplete data, dynamic and streaming data, issues of scalability and statistical issues such as identifiability, stationarity, and so on. There are a number of different research communities working on network analysis including statisticians, physicists and computer scientists; each comes with their own view on the problem of network analysis, their own set of tools and their own style of analysis.
In this seminar, we will survey some of the recent work in network analysis. We will cover topics such as: random graph models, information diffusion and social contagion, probabilistic inference and collective classification in network data, link prediction, community formation and detection, clustering in graph data, entity resolution, visual analytic tools for network data, and other topics from graph mining and statistical network analysis as time permits.
The seminar will be very interactive and collaborative. The topics covered and the depth of coverage will depend on the participants' input and interests.
The goal of the course is to give you an overview of current topics in link mining and dynamic network analysis and practical machine learning and statistical modeling experience to analyze network data that arises in your research. The methods are applicable in many areas such as bioinformatics, computer vision, computational linguistics, databases, program analysis, networks and systems. Along the way, you will pick up some practical experience in reading and presenting research papers, writing a literature survey, and doing a course project that ideally will lead to a publishable paper.
In tandem with the course, throughout the semester there will be several invited speakers presenting current work in network analysis. Some of these will be during the scheduled course time, while others, due to schedule constraints, will be outside the regular course time. Students are highly encouraged to attend the invited talks and meet with the speakers.
Prerequisites: Background in machine learning and graphical models suggested. Mathematical maturity and a basic course in probability required.
INFM 220 - Information Users in Social Context
(3 credits) Grade Method: REG/P-F/AUD
Information Users in Social Context: Uses and users
of information, including where, by whom, for what purposes, and by what
technical means information is used. Information needs and behaviors of
social groups in workplace, the home, their communities, and government.
PSYC 798J - Graduate Seminar: Doing Psychological Research on the Internet: Issues and Methods
(3 credits) Grade Method: REG/AUD
In this course we will look at all of the issues regarding the use of this media and learn some of the programming and computer skills to host our own experiments online.
This course will cover the following topics: 1. techniques for hosting experiments online, 2. web page design, html, javascript, and web databases,
3. experimental design considerations, 4. ethical issues and concerns, 5. sampling methods and issues, and 6. data reliability, data filtering, data warehousing.
