Course Syllabus

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Course Description:

AM/ECON 11B is a second course in mathematical tools and reasoning with applications in economics. Topics are drawn from multivariable differential calculus and single variable integral calculus, and include partial derivatives, linear and quadratic approximation, optimization with and without constraints, Lagrange multipliers, definite and indefinite integrals, and elementary differential equations. 

Student Learning Outcomes:

Upon successful completion of the course, students will be able to:

  • Integrate Functions: Students will evaluate definite and indefinite integrals and apply them to problems in economics.
  • Analyze and Approximate Behavior of Functions: Students will use linear and quadratic approximations, to approximate nonlinear functions and interpret the implications in economic modeling.
  • Solve and Interpret Elementary Differential Equations: Students will solve basic first-order differential equations and apply them to dynamic models in economics.
  • Apply Multivariable Calculus to Economic Models: Students will be able to compute and interpret partial derivatives to analyze functions of several variables in economic contexts, such as utility, cost, and production functions.
  • Use Optimization Techniques with and without Constraints: Students will demonstrate proficiency in solving unconstrained and constrained optimization problems, with applications in economic decision-making scenarios.

Textbook:

Great news: your textbooks for this class are free (Open Educational Resources)!

This course will rely on sections from free OpenStax Calculus textbooks: Volume 1, Volume 2, and Volume 3. These sections can be found embedded in our Canvas course and are also available directly through the website mathgpt.ai, where our homework assignments will also be found, once you create a free student account with your ucsc.edu Google credentials. You can buy a print version of the textbook (or download a pdf) at these links: Volume 1, Volume 2, and Volume 3. 

Please also plan on bringing a smartphone or other internet-enabled device to class. If for some reason you lose your device or it is out of batteries, you will be able to log your participation in activities with TAs.

You have several other options to view this book, without AI tools and homework integration:

 

Assignments & Grading

Homework: Homework is assigned weekly online through mathgpt.ai. No late homework is accepted after that 24 hours.

25%

Participation and Attendance: You must attend and participate in 80% of course meetings to get full credit for this component of the course (so 20% of absences or low participation will be forgiven). Any illnesses or unforeseen circumstances do not need to be reported to your instructional team and count towards that 20% forgiveness policy.

15%

Lecture Quizzes: in Lecture, every other Wednesday. Lowest one will be dropped. Any illnesses or unforeseen circumstances that prevent you from taking a lecture quiz do not need to be reported to your instructional team and the missed lecture quiz will be your dropped score. 

30%

Mini-Quizzes: in Discussion Section every week except for weeks with holidays. Lowest two will be dropped. Any illnesses or unforeseen circumstances that prevent you from taking a mini-quiz do not need to be reported to your instructional team and the missed mini-quiz will be one of your 2 dropped scores. 

10%

Final Exam: You must take the final exam to pass the course.

20%

SETS Bonus: At the end of the quarter, if our class has a 80% completion rate or higher for the Student Evaluations of Teaching Sruvey (SETS), you will all get +1%.

+

 

Student Hours for Course:

This is a 5-unit course, which means that this course should take approximately 15 hours of your time each week: 3.25 hours of lecture, 1.25 hours of discussion section, and 10.5 hours of work outside of class (time spent doing homework, tutoring, studying with a group, etc.) on average. If this course ever starts to seem like more work than this, please talk to us!

Student Feedback:

We want to hear from you! We will be asking you a variety of feedback questions during the quarter to get a feel for how you are doing and how we can support your success. At the end of the quarter you will be asked to complete an anonymous Student Experience of Teaching (SET) survey for this course. This is an opportunity for you to give constructive feedback that helps us improve the course for future students to learn more effectively. But feel free to email or come chat with us about any concerns you may have.

 

Course Schedule:

Week Dates Topics Deliverables

1

1/5 - 1/11

Summation and Definite Integration

Sign up for MathGPT

AI Consent Form

HW01

Mini-Quiz 0

2

1/12 - 1/18

FTC, Average Value, and Properties of Integrals

HW02

Mini-Quiz 1

Lecture Quiz 1

3

1/19 - 1/25

(No class on 1/19 MLK JR Day)

Substitution and Area Between Curves

HW03

Mini-Quiz 2

4

1/26 - 2/1

Gini Coefficient, Surpluses, and Other Techniques of Integration

HW04

Mini-Quiz 3

Lecture Quiz 2

5

 2/2 - 2/8

Money Flows and Differential Equations

HW05

Mini-Quiz 4

6

2/9 - 2/15

Logistic Growth and Functions of Several Variables

HW06

Mini-Quiz 5

Lecture Quiz 3

7

2/16 - 2/22 

(No class on 2/16 Presidents’ Day)

Partial Derivatives

HW07

Mini-Quiz 6

8

2/23 - 3/1

Linear and Quadratic Approximation

HW08

Mini-Quiz 7

Lecture Quiz 4

9

3/2 - 3/8

Optimization in Several Variables

HW09

Mini-Quiz 8

10

3/9 - 3/15

Constrained Optimization

HW10

Mini-Quiz 9

Lecture Quiz A*

3/19

8 - 11 am

Final Exam is cumulative

Location: same as lecture

Final Exam

*Note: Lecture Quiz A refers to an alternate lecture quiz timeslot, to allow for flexibility in case of campus or other unforeseen disruptions. There will only be 4 total lecture quizzes.

Accessibility:

UC Santa Cruz is committed to creating an academic environment that supports its diverse student body. If you are a student with a disability who requires accommodations to achieve equal access in this course, please affiliate with the DRC. I encourage all students to benefit from learning more about DRC services to contact DRC by phone at 831-459-2089 or by email at drc@ucsc.edu. For students already affiliated, make sure that you have requested Academic Access Letters, where you intend to use accommodations. You can also request to meet privately with me during my office hours or by appointment, as soon as possible. I would like us to discuss how we can implement your accommodations in this course to ensure your access and full engagement in this course.

 

Academic Integrity and Artificial Intelligence (AI^2):

This course is a collaborative learning experience focused on your academic growth and our shared goals. You're welcome to use external resources, but ensure they help you learn, not just find answers. Our aim is to build your understanding of the process, not just the outcome. We might even explore using AI tools in class! 

However, some assignments like quizzes or the final exam may be individual assignments and/or may require that you do not use any notes or external tools (including calculators). We will be sure to communicate these rules to you as we go, but just know that it’s good not to be too dependent on anything but a pen and paper and your beautiful brain.

All members of the UCSC community benefit from an environment of trust, honesty, fairness, respect, and responsibility. You are expected to present your own work and acknowledge the work of others in order to preserve the integrity of scholarship. 

Academic integrity includes:

  • Following exam rules
  • Using only permitted materials during an exam
  • Viewing exam materials only when permitted by your instructor 
  • Keeping what you know about an exam to yourself
  • Incorporating proper citation of all sources of information
  • Submitting your own original work 

 

Academic misconduct includes, but is not limited to, the following:

  • Disclosing exam content during or after you have taken an exam
  • Accessing exam materials without permission
  • Copying/purchasing any material from another student, or from another source, that is submitted for grading as your own
  • Plagiarism, including use of Internet material without proper citation
  • Submitting work that was produced by artificial intelligence (e.g., ChatGPT)
  • Using cell phones or other electronics to obtain outside information during an exam without explicit permission from the instructor
  • Submitting your own work in one class that was completed for another class (self-plagiarism) without prior permission from the instructor.
  • Violations of the Academic Integrity policy can result in dismissal from the university and a permanent notation on a student’s transcript. For the full policy and disciplinary procedures on academic dishonesty, students and instructors should refer to the Academic Misconduct page at the Division of Undergraduate Education.

 

AI Policy

 

Generative artificial intelligence tools—software that creates new text, images, computer code, audio, video, and other content—have become widely available. Well-known examples include ChatGPT for text and DALL•E for images. This policy governs all such tools, including those released during our semester together. You may use generative AI tools on assignments in this course on assignments outside of class sessions and when we explicitly permit you to do so in class sessions. Otherwise, you should refrain from using such tools. If you do use generative AI tools on assignments in this class, please be prepared to explain how you used the tool. If you choose to use generative AI tools, please remember that they are typically trained on limited datasets that may be out of date. Additionally, generative AI datasets are trained on pre-existing material, including copyrighted material; therefore, relying on a generative AI tool may result in plagiarism or copyright violations. Finally, keep in mind that the goal of generative AI tools is to produce content that seems to have been produced by a human, not to produce accurate or reliable content; therefore, relying on a generative AI tool may result in your submission of inaccurate content. It is your responsibility—not the tool’s—to assure the quality, integrity, and accuracy of work you submit in any college course. If you use generative AI tools to complete assignments in this course, in ways that we have not explicitly authorized, we will apply the UCSC Academic Integrity policies as appropriate to your specific case. Please act with integrity, for the sake of both your personal character and your academic record. If you have questions about AI use, please come ask me! 

Course Summary:

Course Summary
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