INSTRUCTORS
Professor James W. Harrington
serves as the lead instructor. His office is 408 Smith Hall;
telephone 206-616-3821; electronic mail jwh@u.washington.edu.
His website is http://faculty.washington.edu/jwh
.
Fred Dent
serves as the lab instructor. His office is 417 Smith Hall;
electronic mail dent@u.washington.edu.
The website for the course labs is http://staff.washington.edu/dent/geog367/
.
TIMES AND PLACES
The class meets as a whole from 2:30 - 4:20 p.m. on Mondays
and Wednesdays in 415 Smith Hall (the Geography Collaboratory). Lab
sections meet once a week (1:30 - 2:20 on Mondays (AA) or Wednesdays
(AB)), in 401 Smith Hall (a.k.a. the Sherman Lab).
Professor Harrington's office hours (498 Smith Hall) are Fridays,
1:00 - 2:20 p.m. and by appointment: e-mail jwh@u.washington.edu.
Mr. Dent's office hours are Mondays and Wednesdays, 12:30 -
1:20 p.m., in the Sherman Lab.
OBJECTIVES AND REQUIREMENTS
Learning objectives. We have organized this course with
nine learning objectives. From the readings, lectures, labs, cases,
project, and tests, please try to:
Readings. We will be using an assortment of readings, accessible through a variety of means, and timed as noted below. Most materials are available at Rams Copy Center, 4144 University Way NE, 206-632-6630. Some readings are available on-line, linked to this syllabus (see the URL for this syllabus in the upper right-hand corner). Copies of Getting to Know ArcView GIS are available (under Geography 461 -- extra copies were ordered) at University Bookstore (on University Way) and on reserve at OUGL.
Lab assignments. The course is organized into five units:
an introduction to the subject matter and the software, three hands-on
cases, and student-led (team) projects. The lab sections will focus
on these assignments, which will require additional student work (outside
of classes and labs) on computers that are fitted with ArcView and the
relevant extensions. (In other words, you will need to find 3-5 hours
each week to come to the Geography department labs). Each of the
cases will have a set of “deliverables”: screen shots, answers to
specific questions, and (much more importantly) a well-written report to
your hypothetical supervisor or client (what was the problem at hand, how
did you approach it, what did you find, and what concerns do you have about
your findings).
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Tests. There will be two in-class tests (each with short-answer and short-essay components) on concepts, principles, and lab experiences.
Project. Students should form teams of 3-4 to develop and
produce a project, using data on the City of Seattle to develop a case
similar to any of the three lab cases. We will discuss this assignment
in class and section; students should individually propose projects
by Friday 8 February, and propose team assignments (and identify
likely data sources) by Friday 22 February. The time that
the University has scheduled for a final exam (plus 40 minutes: 2:30
- 5:00 p.m. Tuesday 19 March) will be devoted to team presentations.
The project (worth 15 of the 100 points for the course) will be graded
on the basis of: the group presentation; a team-written report (what
was the case scenario, the research question, what data were available,
what overall approach, what techniques, what findings); and individual
self-assessments.
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GRADING
Grades on tests and assignments. Each test and assignment
will be graded on a percentage basis. Content, clarity, and format
all count in the grading of the assignments. Be especially careful
about plagiarism: more than three words in the order you read them
somewhere else (including on the WWW, including the instructors' lecture
notes) must be set off in quotation marks and given a full citation.
Final grades. The final grade for the course will be calculated
as follows. Each graded item (participation, three tests and three
assignments) can contribute up to a specified number of points toward the
quarter’s total that can equal up to 100 points. Each student’s final
grade reflects the number of these 100 points the student has earned during
the quarter.
| 3 cases, 10 points each |
30 points
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| 2 tests, 15 points each |
30 points
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| small lab assignments and lab participation |
10 points
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| participation in class meetings |
10 points
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| student project |
20 points
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| TOTAL |
100 points
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| 85 - 100 points |
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| 70 - 84 points |
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| 55 - 74 points |
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| 45 - 55 points |
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| 0 - 44 points |
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Late assignments. Tests must be taken on the scheduled day, except by prior arrangement with the instructor or ex post written communication with the instructor based on illness (in this latter circumstance, the instructor will need documentation of your illness or that of someone in your care; this will be handled on a case-by-case basis). Assignments received after 5:00 on the due date will be penalized by 20 percentage points (e.g., a two-day-late assignment that is judged to be 85% successful would receive 65% credit); assignments 7 or more days after the due date will be penalized by 40 percentage points. Because of the deadlines for grading, the instructors cannot accept any material after 5:00 p.m. Tuesday 19 March.
Incomplete work. [From the University Registrar's website] A grade of “I” (Incomplete) is given only when the student has been in attendance and has done satisfactory work until within two weeks of the end of the quarter and has furnished proof satisfactory to the instructor that the work cannot be completed because of illness or other circumstances beyond the student's control. To obtain credit for the course, an undergraduate student must convert an Incomplete into a passing grade no later than the last day of the next quarter. The student should never reregister for the course as a means of removing the Incomplete. An Incomplete grade not made up by the end of the next quarter is converted to the grade of 0.0 by the Registrar unless the instructor has indicated, when assigning the Incomplete grade, that a grade other than 0.0 should be recorded if the incomplete work is not completed. The original Incomplete grade is not removed from the permanent record.
7-14 January: Introduction to economic uses of geographic data (see notes)