Editing DS4UX (Spring 2016) (section)

== Administrative Notes ==

=== Attendance ===

Attendance in class is expected of all participants. This class is going to move very quickly and the things we learn will build on the things we've covered the week before. ''It will be extremely difficult to miss classes.'' If you need to miss class for any reason, please contact the instructor ahead of time (email is best). Multiple unexplained absences will likely result in a lower grade or (in extreme circumstances) a failing grade. In the event of an absence, you are responsible for obtaining class notes, handouts, assignments, etc.
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=== Office Hours ===

Because this is an evening degree program and I understand you have busy schedules that keep us away from campus during the day, I will not hold regular office hours. In general, I will be available to meet in person for brief discussions during the hour before class. 

Remote meetings, using Skype or Google Hangout, are always an option. Please contact me or Ray Hong on email to arrange a meeting.
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=== Disability Accommodations Statement ===

To request academic accommodations due to a disability please contact Disability Resources for Students, 448 Schmitz, 206-543-8924/V, 206-5430-8925/TTY. If you have a letter from Disability Resources for Students indicating that you have a disability that requires academic accommodations, please present the letter to me so we can discuss the accommodations that you might need for the class. I am happy to work with you to maximize your learning experience.
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=== Grades ===

Grades for individual components for this course (participation, coding challenges, final project deliverables) will be assigned based on the following criteria. For more information on grading policy, see the [http://www.hcde.washington.edu/myhcde/grading-policies HCDE grading policy] and the [http://depts.washington.edu/grading/conduct/grading.html UW Academic Conduct policy for grading]. 

To learn more about how I will evaluate your overall performance for the course, please see [https://mako.cc/teaching/assessment.html Professor Benjamin Mako Hill's assessment rubric].

{| class="wikitable"
!Assignment
!Percentage
|-
|Participation
|30%
|-
|Required Coding Challenges
|10%
|-
|Final Project Idea
|10%
|-
|Final Project Plan
|10%
|-
|Final Project Presentation
|10%
|-
|Final Project Report
|30%
|}
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==== Participation ====

You are not graded on whether you show up to class, or not. However, you ''are'' graded on your participation in class. Everyone misses class every once in a while. However, if you need to miss a class and you want to assure that your absence does not negatively impact your grade, follow the steps steps to demonstrate that you engaged with the material covered during that class session. 

'''IMPORTANT: For full participation credit on a day you are absent, you ''must'' contact the instructor or TA before 10pm the day after class via email with this information:'''
# you have reviewed any materials we covered in the class, including instructor slides, links, videos, etc. (check the wiki)
# you have attempted to perform any in-class exercises that we performed during class (if they're listed on the wiki). 
# you have turned in any assignments (graded coding challenges, project deliverables) due during the that week's class

'''In your email:''' please ask questions, what confused you, tell us how far you got on the coding challenges, and be honest about what you couldn't complete. I also highly recommend that you share your solutions or partial solutions in the email--sending me python files and/or pasting code into the body of an email is totally fine--this helps me and Ray understand your thought process and evaluate your effort and your progress.
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==== Coding Challenges ====

Only about half of the coding challenges will be graded (and I will be very clear which ones those are, so there is no confusion). Graded coding challenges are evaluated as ''complete/incomplete''. You gain a 'complete' for coding challenges by turning in the assignment (whether or not your answers are correct, or your code runs) via the submission channel I specified for that assignment.
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==== Final project deliverables ====

Grades for all final project deliverables (idea, proposal, presentation, and report) for this class are based on a rating scale.

Rating-scale grades are based on the faculty member's assessment of each assignment as opposed to a calculation from earned and possible points. The broad criteria for the ratings are given below. The ratings for some assignments may be multiplied by a constant (e.g. 2 or 3) so as to count more toward the final grade. The final grade is calculated as the average of all ratings.
 
;4.0 - 3.9: Excellent and exceptional work for a graduate student. Work at this level is extraordinarily thorough, well reasoned, methodologically sophisticated, and well written. Work is of good professional quality, shows an incisive understanding of data science-related issues and demonstrates clear recognition of appropriate analytical approaches to data science challenges and opportunities. ''Clients who received a deliverable of this quality would likely develop loyalty toward the vendor to the exclusion of other vendors.''
 
;3.8 - 3.7: Strong work for a graduate student. Work at this level shows some signs of creativity, is thorough and well-reasoned, indicates strong understanding of appropriate methodological or analytical approaches, and demonstrates clear recognition and good understanding of salient data science-related challenges and opportunities. ''Clients who received a deliverable of this quality would likely recommend this vendor to others and consider a longer-term engagement.''
 
;3.6 - 3.5: Competent and sound work for a graduate student; well reasoned and thorough, methodologically sound, but not especially creative or insightful or technically sophisticated; shows adequate understanding of data science-related challenges and opportunities, although that understanding may be somewhat incomplete. This is the graduate student grade that indicates neither unusual strength nor exceptional weakness. ''Clients who received a deliverable of this quality would likely agree to repeat business with this vendor.''
 
;3.3 - 3.4: Adequate work for a graduate student even though some weaknesses are evident. Moderately thorough and well reasoned, but some indication that understanding of the important issues is less than complete and perhaps inadequate in other respects as well. Methodological or analytical approaches used are generally adequate but have one or more weaknesses or limitations. ''Clients who received a deliverable of this quality would likely entertain competitor vendors.''
 
;3.0 - 3.2: Fair work for a graduate student; meets the minimal expectations for a graduate student in the course; understanding of salient issues is incomplete, methodological or analytical work performed in the course is minimally adequate. Overall performance, if consistent in graduate courses, would be in jeopardy of sustaining graduate status in "good standing." ''Clients who received a deliverable of this quality would likely pay the vendor in full but not seek further engagement.''
 
;2.7 - 2.9: Borderline work for a graduate student; barely meets the minimal expectations for a graduate student in the course. Work is inadequately developed, important issues are misunderstood, and in many cases assignments are late or incomplete. This is the minimum grade needed to pass the course. ''Clients who received a deliverable of this quality would likely delay payment until one or more criteria were met.''
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=== Plagiarism ===

;Writing:
Please don't use other people's writing as your own. It's easy to spot plagiarism of this type, and the consequences can be serious (see link below).

;Code:
Programmers routinely copy chunks of code from other people's programs into their own programs. This in itself does not constitute plagiarism--though when in doubt, it is best to inform your instructor that you copied/adapted some part of your code from another source. I encourage you to adapt code from our in-class demonstrations, exercises, and coding challenges to your final project if you think that code will work for you. However, please do NOT copy whole scripts or substantial parts of scripts from other sources and try to pass it off as your own. Again, this is easy to spot--experienced programmers have their own 'styles' and conventions and it generally contrasts with the style of less experienced programmers. Also, if you're copying code because you don't know how to reproduce it yourself, you're probably not learning very much, and that will come back to bite you later in the course, and maybe even in your professional life!

For more information, see [http://www.hcde.washington.edu/policies/plagiarism-and-academic-conduct the UW policy on plagiarism and academic conduct].


[[Category:DS4UX (Spring 2016)]]