This syllabus contains some experimental elements that are worth trying. However, experiments are allowed to fail and therefore the syllabus is subject to change based on how the class is learning.
Forms
Covid Precautions
Per the Duke Requirements, you must wear a mask if you are in-person in class and in office hours.
If you test positive, file a short term illness form.
Learning Sprints and Modules
The course is divided into a number of “learning sprints” that are typically two weeks long. They start on a Tuesday and end on a Monday. A module is about a week’s worth of work on a set of topics but does not span a week see below. We will typically release two modules per learning sprint. One module will often focus on programming and the other on statistics.
Modules
A module includes four components: Prepare, Group Worksheet, Practice, and Perform.
- Prepare. Will typically contain videos and/or readings to introduce new content, as well as a quiz to ensure comprehension. The quiz will be on Sakai and auto-graded. You can take the quiz up to three times to correct initial misunderstandings. A score of 80% on Prepare will result in full credit.
- Group Worksheet. Will typically happen during the first week of the Sprint in class. They are created based on the class’s performance on the Prepares so it focuses on what everyone is weakest on. They serve as a starting point to our discussion of the material. You will work in groups but must submit the worksheet individually. Your score is based on participation. You can miss 2 group worksheets with no penalty.
- Practice. Will typically consist of a set of coding/data analysis or statistics problems to complete in a Jupyter notebook and submit on Gradescope. We will typically work through several of these problems in class together. A score of 80% on a Practice will result in full credit.
- Perform. Will typically consist of some data science tasks to complete independently in a Jupyter notebook and submit on Gradescope. Will build on material from the Prepare and Practice. Graded for demonstration of mastery.
- Update as of 10/30/21: A score of 95% on a Perform will result in full credit due to the autograder still being new to the course.
Soft and Hard Deadlines & Late policy
To allow for the greatest amount of flexibility and to optimize learning with deliberate, spaced, and interleaved learning practice, our material will be released and due in the following manner. It is due at 11:59 PM ET on the day stated.
New deadlines starting 10/12 with Learning Sprint 5. Remember sprints start on Tuesdays and end on Mondays. Changes between the original and these deadlines has to do with the Prepares and Group Worksheets.
| Released | Soft Deadline | Hard Deadline | Late Deadline | Work Graded By | |
|---|---|---|---|---|---|
| Prepare | By beginning of Sprint | Module A: Tuesday of the first week of the Sprint Module B: Thursday of the first week of the Sprint | End of first week of Sprint | 1 day after first week of Sprint (only if no prior submission and only 1 submission allowed) | Autograded |
| Group Worksheet | Module A: Wednesday of the first week of the Sprint Module B: Friday of the first week of the Sprint | Day released | End of first week of Sprint | - | Autograded |
| Practice | By beginning of Sprint | - | End of Sprint | 1 week after Sprint | 1 week from the deadline it was submitted by |
| Perform | By 2nd week of the next Sprint | - | End of next Sprint | 1 week after next Sprint | As soon as we are able |
Old Deadlines that no longer apply
| Released | Soft Deadline | Hard Deadline | Late Deadline | Work Graded By | |
|---|---|---|---|---|---|
| Prepare | By beginning of Sprint | Module A: Tuesday of the first week of the Sprint Module B: Thursday of the first week of the Sprint | End of Sprint | 1 day after Sprint (only if no prior submission and only 1 submission allowed) | Autograded |
| Group Worksheet | Module A: Wednesday of the first week of the Sprint Module B: Friday of the first week of the Sprint | Day released | End of Sprint | - | Autograded |
| Practice | By beginning of Sprint | - | End of Sprint | 1 week after Sprint | 1 week from the deadline it was submitted by |
| Perform | By 2nd week of the next Sprint | - | End of next Sprint | 1 week after next Sprint | As soon as we are able |
Rationales and notes:
- There will be two instances of every Prepare. The first will be due about 24 hours before the class we will discuss that module. This is to give us time to create a Group Worksheet that focuses on what the class struggled with most on the material. The second will open immediately after the first is due/closed and will be clearly marked as after the soft deadline. The second instance of the Prepare will be due at the hard deadline.
- If you happen to submit to both the soft and hard deadline, we will take the max of the two in the gradebook.
- Practices and Performs can be submitted up to 1 week late and no points penalty will be applied. However, a late Practice means it may not be graded in time to use the feedback when filling out the Perform.
- There will be two instances of Practices and Performs. When it is due, Gradescope will close that assignment and open a new one that is clearly marked as late. This is so we can immediately start grading the assignments submitted on time.
- You can submit to only one instance or get the other submission NULLed. You can only submit to the late version of the assignment if you (1) did not submit to the original or (2) requested via the form your original submission be NULLed within 2 days of its closing. If you submit to the late version, but still have a submission on the original, the original will be counted and your late submission NULLed. This is to ensure the TAs are not grading more than once per student per assignment.
- A given sprint may involve 4 modules at once. It includes the Prepare and Practice of the current Sprint and the Performs of the prior Sprint. This is to help make your learning stickier because it gives you spaced and interleaved practice on the material. It also lets you react to the feedback when you work on Performs. However, not all Sprints will be like this. Some modules will be replaced with a Project work module.
- The goal for this class is your grade reflects your mastery of the material, not when you mastered it or whether you submitted work on time. However, to keep the class moving forward and to not overload the grading at any given time, we need to impose these time restrictions.
- This is an experiment. We will reassess after a few sprints if this is working to enable flexibility while also keeping everyone on track.
Regrades
Students wishing to have a grade changed must make a written request through the regrade request feature on Gradescope no later than one week from the day the assignment is returned. Regrade requests should explain specifically why the student believes a different grade is more appropriate, not just ask for more partial credit without any reason. Please note that grade changes (apart from clear grader errors) are rare.
Projects
Instead of a final exam, this course has an open-ended collaborative project. In groups of four or five, you will choose a research topic that can be explored through data science. You will formulate research questions, acquire data, and perform your own data processing, analysis, and modeling to answer your research questions. The projects have three stages of deliverables.
- Proposal. 1-2 page (single space) document that highlights a topic, data source(s), research questions, and a collaboration plan.
- Prototype. 3-4 page (single space) document that highlights methods, preliminary results, and an updated collaboration plan.
- Final Report and Presentation. 6-8 page (single space) document that provides a complete description of the topic, research questions, methods, results, and conclusions, along with a 15-20 minute recorded presentation involving all group members.
More details will be provided about each deliverable closer to their due dates, including a simple criterion-based rubric for grading. Project Deliverables will be graded for satisfying the necessary criteria, i.e., satisfying the basic requirements will result in full credit. This is intended to encourage creativity to allow project groups to explore widely in terms of topics, research questions, and methods without fear of a grade penalty. We will also provide constructive written feedback on project deliverables separate from the criterion grading in order to help teams make progress.
Grades
The final course grade, as a percentage, will be calculated as the following weighted average:
- Prepare 8%
- Group Worksheet 2%
- Practice 15%
- Project 35%, broken down by deliverables:
- Proposal 3%
- Prototype 6%
- Presentation 6%
- Final Report 20%
- Perform 40%
Final numerical grades will be converted to letter grades as follows. Letter grades of A+ are awarded only for students with a grade of A and exceptional course projects as determined by the instructor.
- [90, 94) = A-, [94, 100] = A
- [80, 83) = B-, [83, 87) = B, [87, 90) = B+
- [70, 73) = C-, [73, 77) = C, [77, 80) = C+
- [60, 63) = D-, [63, 67) = D, [67, 70) = D+
Course Policies
Collaboration
You are welcome and encouraged to collaborate on Prepare and Practice assignments. You can search for study partners in class or in the discussion forum. However, you should not “split up” the work and only look at a portion of the material, as this will deprive you and your partner of valuable learning opportunities. Instead, we encourage that you work together actively or each attempt portions independently and then come together to discuss. Also, You should not share your solutions with anyone you do not actually study/work with.
You must complete the Perform assignments independently. You should not discuss the Perform assignments with any other classmates until after grades have been returned. You may not show your solutions to other students and should not view other solutions. Doing so will be considered in violation of the Duke Community Standard.
The group projects will be completed in groups of four or five, and while some group members may focus on different aspects of the project, all group members should be actively engaged in the overall project, each doing a fair share of work, and regularly communicating with group members.
Academic Integrity
All participants in this course are expected to uphold the Duke Community Standard; that is, to agree that “…I will not lie, cheat, or steal in my academic endeavors; I will conduct myself honorably in all my endeavors; and I will act if the Standard is compromised.” In all cases, failure to uphold this standard will result in referral to Office of Student Conduct. Any work that copies, paraphrases, or in any other way uses materials not your own without citation will be considered in violation.
Disability Accommodation
Duke University is committed to providing equal access to students with documented disabilities. Students with disabilities may contact the Student Disability Access Office (SDAO) to ensure your access to this course and to the program. There you can engage in a confidential conversation about the process for requesting reasonable accommodations both in the classroom and in clinical settings. Students are encouraged to register with the SDAO as soon as they begin the program. Please note that accommodations are not provided retroactively. More information can be found online at access.duke.edu or by contacting SDAO at 919-668-1267, SDAO@duke.edu.
Long Term Health Issues
If you have or develop a chronic health issue that will interfere with your participation in this course, please contact your academic dean to seek accommodations as directed by Trinity College.
Personal Distress or Emergencies
If a situation of extreme personal distress or an emergency interferes with your participation in this course, please contact your academic dean to seek accommodations as directed by Trinity College.
