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teaching
Industrial Design
Intelligence; A Cognitive Science Approach to Engineering
The
look, feel and use of objects communicate their value to us. This course
applies cognitive science and technology to the industrial design process. The
course will introduce prototyping techniques and approaches for objective
evaluation as part of the design process. Students will practice evaluating
products with mechanical and electronic aspects. The evaluation process will
then be applied to creating functioning product prototypes. This is a
project-oriented course that will draw on engineering, aesthetic, and creative
skills. The course is geared towards students interested in creating physical
products which encompass electronics and computers in order to include them in
scenarios. Students will present readings, learn prototyping skills, create a
product prototype, and complete a publication style paper. We will mill, cut,
mold solder, program and draw our way to evaluating product design.
download class description and schedule: [ doc / pdf ]
Context Aware Computing
This project-based course will teach students to
create context-aware and intention- based computing systems. Most computing systems have required people
to communicate with them using directives. Students will use Artificial Intelligence (AI) and sensors to create
computing systems that figure out what to do based on situation. The system's physical or symbolic actions may be dependent on time, place, or the
history of interaction; in other words, dependent upon context. We explore perspectives from machine learning,
sensors and effectors, embedded devices, information visualization, philosophy and psychology. We will see how each treats the problem of context,
and discuss the implications for design of context-sensitive hardware and software. Course requirements will include presentations and critiques of
class reading from research literature (about 2 papers/week) and a final project including a computer implementation, evaluation and publication-quality paper.
download class description and schedule: [ doc / pdf ]
Voting Technology: What Has Been and What Can Be
Whose vote counts in an election? Voting process does affect election results.
For the first time in history we are in a position to create technology and processes that can probably allow detection and correction of
human error and fraud in voting. Improving voting technology should be central to protecting our democratic process. As well, it can instill
confidence in our government and system. Digital technology may even improve our government and process.
Improved voting technology can also
transfer to other areas. Solving problems of disenfranchisement of people relative to socioeconomic, physical, and cognitive disabilities in
voting can be applied to other universal access problems. Solving problems of security, reliability and integrity in voting can help improve
other transaction processing systems.
This course will survey voting systems and how they can be improved. We will give broad coverage of user
experience, reliability, security and integrity of voting systems. The course will consist of weekly topic areas and lectures from voting technology
experts. Topics will follow the largest areas of lost votes and topics of public debate.