Course Policies for English 146 (W 2022)
Data Stories: Theory and Practice of Data-driven Narratives in the Digital Age
Attendance & Course Completion Requirements
Since there no exams in this course, regular attendance and participation is a must. To pass the course students must be in class the majority of the time. (Students are allowed a maximum of two absences without needing to ask for permission in advance, with the count starting after the first week of classes.)
All assignments must be completed to pass the course.
Solo Assignments & Participation Grade (60% of final grade)
Solo Assignments (50% of final grade): Besides team work, each student has solo assignments that are individually graded. These include the following (for assignment details, see Schedule page):
- An analysis of a narrative due in Class 4 (10% of final grade).
- A pair of spreadsheets of data due in Class 8 (10% of final grade)
- A “datasheet” reporting on a dataset due in Class 11 (10% of final grade)
- A final 3-page essay due by 11:59 pm on March 14th, 2022 (20% of final grade)
Assignments 1-3 above are due no later than the time of class on each specified date (because we will often be using or referring to them during the class). Assignment 4 above is due after classes end by 11:59 pm on March 14th.
Grading system: The instructors will grade each assignment numerically through the course GauchoSpace site on a 100-point scale, with scores corresponding conceptually to letter grades on the following scale, taking the B grades as an example:
- “B-” = 81-82
- “B” = 83-87
- “B+” = 88-89
Late assignment policy: Late assignments for which an extension was not approved in advance will decay by 3 pts out of 100 pts for each day they are late. So, for example, an 88-pt paper (equivalent to a B+ letter grade) that is turned in one day late becomes an 85-pt paper (equivalent to a B letter grade).
Participation (10% of final grade): Students are also graded individually for participation in their team project and in class discussion. The instructors will base this grade on their assessment of a student’s participation throughout the course in their team project (as witnessed in visible contributions to the final project or background contributions in a team’s shared drive) as well as in class discussion. Any student who participates equally with their teammates in the team project and also speaks up during class discussion should be able to earn the full 10% of this grade.
Team Project Grade (40% of final grade)
Students will group into teams of 3 to 4 members each to create a data narrative due by the last class of the course. (For details and project-building activities, see Schedule page.) 40% of the final grade of each student will be based on the team-wide grade for their project.
Academic Integrity
As with all student work at UCSB, student assignments in this course are governed by campus-enforced standards of academic integrity and respect for the intellectual property of others. See this course’s Intellectual Property and Academic Integrity Guidelines page for definitions and policies regarding copyright (and “fair use”), plagiarism, collusion, and cheating.
