Instructor | TA | |||||||||||||
David McDonald Office: Sieg 428 Email: dwmc@uw.edu
|
Ray Hong Office: Sieg 424 Email: rayhong@uw.edu
|
Thursday, 6:00pm-10:00pm in Savery Hall 264
(except Thursday March 2, 6:00pm-10:00pm in Allen Library, Research Commons - breakout spaces)
Introduces basic computational concepts and programming skills needed to work with interactive systems in HCDE. Draws on topics such as log analysis, visualization, prototyping, and data mining. Students analyze data to inform user research and design.
Social media data collection and analysis will be taken as the motivating example through which HCDE computational concepts are taught. Social Media is an important and growing phenomena on the Internet. These systems enable hundreds of thousands of people to contribute their own content and meta-data to web enabled systems. Since these systems grow and change as a function of the individuals who participate, understanding the individuals, the forms of participation, the types and styles of contributions are important to designing and refining social media systems.
The course is composed of assignments, quizzes, reading and a project.
Assignments | 45% | (7 assignments, almost weekly) | ||
Quizzes | 10% | (5 during the quarter) | ||
Team Project | ||||
Project Proposal | 10% | |||
Project Presentation | 10% | |||
Project Write-Up | 25% |
All assignments, quizzes, project proposal and project write up are due by 5:00pm on the specified date. All assignments, project proposal and project write-up will be submitted to the course Catalyst Dropbox. Late turn-in will be penalized 5% of the total possible grade per hour (or fraction of an hour) that it is late.
Grade (not less than) |
Percentage | |
3.8 | 95% | |
3.6 | 90% | |
3.3 | 85% | |
3.0 | 80% | |
2.5 | 75% | |
2.0 | 70% |
During the quarter the Instructor and TA will provide some supplemental office hours that will occur on Saturdays.
The course has one highly recommended text. Suggested readings from the book are listed on the reading schedule. The book has a very practical tone. The best way to understand this book is to skim through the chapter, then sit down at a computer with the book and work through the examples in the assigned chapter or section. The optional books are only if you want more help learning Python.
Recommended Text | |
Russell, Matthew (2014) Mining the Social Web. (Second Edition) O'Reilly Media Inc. | |
ISBN: 978-1449367619 | |
Optional Texts | |
Berry, Paul (2010) Head First Python O'Reilly Media Inc. | |
ISBN: 978-1449382674 | |
Ascher, David and Lutz, Mark (2013) Learning Python book (5th edition) O'Reilly Media Inc. | |
ISBN: 978-1449355739 |