Computational Techniques for HCDE

HCDE 530 Syllabus (Winter 2017)

Instructor   TA
David McDonald
Office: Sieg 428
Email: dwmc@uw.edu
  Office Hours: by appointment
     
  Ray Hong
Office: Sieg 424
Email: rayhong@uw.edu
  Office Hours: Thursdays 5:00pm-5:50pm, Sieg 424
    by appointment

Course Meetings

Thursday, 6:00pm-10:00pm in Savery Hall 264

(except Thursday March 2, 6:00pm-10:00pm in Allen Library, Research Commons - breakout spaces)

Description

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.

Evaluation Components

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%

 

Supplemental Office Hours

During the quarter the Instructor and TA will provide some supplemental office hours that will occur on Saturdays.

  • Saturday January 14, 2017 12:00-2:00 Sieg 427
  • Saturday January 21, 2017 12:00-2:00 Sieg 427
  • Saturday January 28, 2017 12:00-2:00 Sieg 427
  • Saturday February 11, 2017 12:00-2:00 Sieg 427
  • Saturday February 18, 2017 12:00-2:00 Sieg 427

Course Book

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

 

© 2017 David W. McDonald