Syllabus and Overview of PHY 415#
In designing this course, we plan to emphasize more independent learning on your part and greater agency for you in determining what you learn and how you demonstrate you have learned. So you should expect:
to read a variety of pieces of information to coordinate information
to present your ideas publicly and to discuss them
to learn new approaches and novel techniques on your own
to become more expert than me in the areas of your interest
to learn more about scientists that you have not learned about
This is not to say that you are on your own. Here’s what you can expect from us:
resources, information, and tools to help you learn
support and scaffolding to move you towards more independence in your learning
timely and detailed feedback to help you along
a commitment to an inclusive classroom
Statement on the use of Generative AI tools
Contact Information#
Web page#
Web page for this class: https://dannycab.github.io/phy415fall23/content/intro
Instructor#
Prof. Danny Caballero (he/him/his)
Class Meetings: Tuesdays and Thursdays 10:20am-12:10pm (Location: 1300 BPS)
Email: caball14@msu.edu, office: 1310-A BPS
Office hrs: 4:00pm-5:00pm Wednesdays & Thursdays in the Strosacker Help Room (or zoom). If I’m not in Stroscaker, I’m in 1310 BPS; just come in. I also have an “open door” policy (find a time). I enjoy visiting and talking with you about physics.
Teaching Assistant/Grader#
Ian Neuhart (he/him/his)
Email: neuharti@msu.edu; office: 4214 BPS
Office hrs: 1:30pm-2:30pm Tuesdays, or by appointment
Learning Assistant#
Alia Valentine (she/her/hers)
Email: valen176@msu.edu
Office hrs: 3:00pm-5:00pm Fridays in the Strosacker Help Room. If I’m not in Stroscaker, I’m in 1310 BPS; just come in. Feel free to email me if you want to set up a time. I too enjoy visiting and talking with you about math and physics.
Grading#
Details about course activities are here and information regarding assessment is here. Your grade will be comprised of completing weekly discussion questions, seven of eight worked problems, and three of four projects that you will complete in the form of a Jupyter notebook (a “computational essay”, which we will discuss later).
Your grade is comprised of the following:
Activity |
Percent of Grade |
---|---|
Weekly Reading Questions (completion) |
5% |
Seven of Eight Worked Problems (5% each) |
35% |
Three of Four Projects (see below) |
60% |
Total |
100% |
Your grade on each project is split between completion (50%) and quality (50%). We will collectively define “quality” in class, but we have provided a preliminary rubric for us to work from for the first project. Your final grade will be scaled based on your best performances; there will be slightly more projects than what comprises your grade. The intent here is to to allow you space to explore a model or project that you really enjoy, and to reward you for doing that. How your project grade is calculated appears below.
Activity |
Percent of Grade |
---|---|
Best Project Grade |
25% |
2nd Best Project Grade |
20% |
3rd Best Project Grade |
15% |
While attendance is not required, you are unlikely to succeed with your projects without regular attendance and engagement.
“Extra” Credit#
We get that you might want to do more of the projects or maybe you fell a little behind during the semester. If you complete 8 of the 8 worked problems, you can earn up to another 5%. If you complete four projects, then your lowest scoring project will be included up to an additional 10%. These have to be completed within the usual due dates for the worked problems and projects; not at the end of the semester.