IUCEE Workshop on Algorithms

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Instructor  Richard Anderson Course Resources  CSE 421 Autumn 2005  CSE 421 Autumn 2006  CSE 321 Winter 2008 Lecture Slides  Workshop slides  Algorithms  Discrete Math  Data Structures

Algorithms, Data Structures, and Discrete Mathematics are key parts of any Computer Science program. These courses provide students with important background for further study, as well as foundations for professional work in the computing field. This workshop will focus on two aspects of teaching these courses: how to introduce an active learning methodology into the classes to improve student engagement and learning outcomes, and how to keep these courses current in a rapidly changing field. It is well known that students perform better when they are actively engaged in classes. There are many pedagogical techniques, generally referred to as "active learning", where students build on knowledge in class and provide feedback to the instructor and other students. A variety of techniques, including Classroom Assessments, Peer Instruction, and Student Activities will be introduced and illustrated in the context of Algorithms, Data Structures and Discrete Mathematics. These are all techniques that the instructor has developed and refined in his courses in over twenty years of teaching these subjects. Although Algorithms, Data Structures, and Discrete Mathematics provide an important foundation for work in computing, it is essential that the material of the courses be kept up to date, so that it remains relevant to current computing practices. These subjects all need to be tied to current problems and technologies. We will discuss different connections between these subjects and the broader field of computing. Preliminary Schedule Monday, June 30, Active learning and instructional goals Welcome and Overview (1 hr) Teaching Principles, Leadership Training (2 hrs) Introductory Activity (1 hr). Determine background of participants Active learning and instructional goals (1hr) in Discrete Math, Data Structrues, Algorithms. Overview of theory instruction (1 hr) Group Work (2 hrs). Development of activities/goals from participant's classes. Content lectures (Great Ideas in Computing): (1 hr) Problem mapping Tuesday, July 1, Discrete Mathematics Discrete Mathematics Teaching (2 hrs) Accessing content (2hrs). Campus Connect and other Open Educational Resources Activities in Discrete Mathematics (1 hr) Group work and presentations (2 hrs) Content Lecture: (1 hr) Complexity Theory Wednesday, July 2, Data Structures Data Structures Teaching (2hrs) Outcome Assessment (1 hr) Data Structure Activities (1 hr) Group work and presentations (2 hrs) Content Lecture: (1hr) Average Case Analysis Thursday, July 3, Algorithms Algorithms Teaching (2 hrs) Interaction with Industry (3hrs) Algorithms Activities (1 hr) Group work and presentations (1 hr) Content Lecture: (1 hr) Solving Real Problems Friday, July 4, Educational Technology and Socially Relevant Computing Lecture (1.5 hrs) Educational Technology Lecture (1.5 hrs) Socially relevant computing Followup and faculty presentations (5 hrs)

	Computer Science & Engineering University of Washington Box 352350 Seattle, WA  98195-2350 (206) 543-1695 voice, (206) 543-2969 FAX [comments to anderson]