RES-ECON 303: Writing in Resource Economics

Example syllabus only – exact content subject to change. Please see your instructor’s syllabus for the current term for your specific course’s guidelines

3 credits, in-person

Section 1: MW 2:30–3:45
Section 2: TTh 2:30–3:45
Section 3: TTh 1:00–2:15

Classroom: 301 Stockbridge Hall

Instructor Information

Instructor: Luke Bloomfield
Office: 309B Stockbridge Hall
Office Hours: MW 11:00–12:00, or by appointment

Overview

RES-ECON 303 is the Junior Year Writing course for students in the Department of Resource Economics. The purpose of this course is to improve writing and research skills through analytical, critical, and reflective thinking. The course modalities include theoretical inquiry, practical application, and reflection:

• Theory will give us relevant frameworks for understanding goals.
• Practice will build confidence and competency.
• Reflection will ensure we retain what we’ve learned.

Technology—and its influence on the economy, society, the environment, and the self—will be a thematic component of this course.We will give some but not all of our attention to a few of the dominant forms of AI (predictive, generative, and algorithmic) and its impact—direct and indirect—on our ability to write. This means that we will allocate portions of our time to explore, discuss, write about, and analyze current pervasive technologies that have emerged and made claims to presenting “solutions” to the “problems” of writing and learning.

This course is structured around three graded assignments:

1. Personal Inquiry Essay
2. Executive Summary
3. Business Case Study (group project)

Each assignment will go through multiple stages: brainstorming, freewriting, drafting, review, and revision. You will receive feedback from myself and your peers during this process. You will receive feedback from the instructor and your peers during this process.

By the end of the course, you should have the necessary tools to write with authority in a range of contexts (academic, professional, personal).

In addition, you should be able to:

1. Apply your Resource Economics background to help audiences understand contemporary issues.
2. Collaborate with your peers to build research and analytical skills.
3. Engage in ethical and strategic reflection through writing.

Grading

Grading Weights

Grade Scale

Schedule (subject to minor modifications)

• Weeks 1–3: Foundations and Personal Inquiry
• Weeks 4–7: Executive Summary Skills
• Weeks 8–14: Business Case Study

RES-ECON 303 Student Learning Objectives

This course contributes to the following student learning objectives (SLO) for undergraduate students in the Department of Resource Economics:

Experiential Goals

Late Work Policy

If you need extra time to complete an assignment, you must request an extension more than 12 hours before the deadline. Late work submitted without a granted extension will incur a one-point penalty per day until it is submitted.

Course Material and Supplies

• All readings will be available for free through Canvas and as hard copies.
• You will need to bring a personal writing notebook to every class. You will use this notebook to free-write, take notes, jot down ideas, outline, and doodle. You can purchase notebooks at the University shop in the Campus Center, at Amherst Books in downtown Amherst, at another brick-and-mortar retailer, or online.
• You will also need to bring a writing instrument, such as ballpoint pen, gel pen, rollerball pen, fountain pen, calligraphy pen, mechanical pencil, or traditional wood-cased graphite pencil.

Technology Policy

Phones:

Use of mobile phones during class is strictly prohibited. Mobile phones should not be visible at any time during the class period. When class begins, phones must be stored in a bag or backpack. If I observe use of a mobile phone during class, I will issue one reminder of the policy. If you observe repeated violations of the policy, an absence will be marked for that class.

Laptops and tablets:

Unless otherwise instructed by me, laptops and tablets (anything with a screen that connects to the internet) should remain in your bag or backpack during class. Occasionally I will invite you to use your laptop for a class activity, such as exploring academic resources. Otherwise, the only objects on your small desk during class should be your notebook and writing instrument. Water bottle optional (if there’s space).

The purpose of this strict technology policy is to enhance engagement and be present together during class time. It has become an inescapable truth, empirically proven, that personal-use technology has had the twofold effect of fragmenting our attention and downgrading the value of experiences IRL. In this class we will strive to unify and sustain attention while seeking opportunities to increase the possibilities of locating value in intellectual engagement and discovery.

Attendance and Participation

You are expected to attend and participate in class. Excluding any of the standard excused reasons for being absent (sickness, personal emergency, religious observance), >2 absences and/or a noticeable lack of participation will count against your final grade, which I will assess fairly and judiciously on a case-by-case basis. Participation boils down to coming to class, actively engaging with the class, actively engaging in small groups, promptly replying to emails from me and your peers, giving thoughtful responses and feedback to peers, not doing non-class related things on your electronic device during class time. An absence may only be excused if you notify me before the class that you will miss.

AI Statement

Terms

Artificial Intelligence (AI) refers to a general category of technology based on machine learning.

Generative AI (gen AI) refers to a category of AI that produces content (visual, audio, textual) by making accurate predictions based on massive amounts of training data scraped from the internet, often without crediting—nor compensating—the originators of the data.

Large Language Models (LLMs) refer to a category of gen AI that produces text by next-token language prediction from massive amounts of training data scraped from the internet, often without crediting—nor compensating—the originators of the data.

Overview

LLMs have become a ubiquitous topic. Contemporary writing courses cannot effectively teach writing without at least addressing LLMs. To that point, we will read about it, discuss it, and possibly perform a few experiments of our own. We will not depend on it, nor will we fear it. One of our objectives is to explore the possibility that there might be a practical use for LLMs that enhances our ability and potential to think and write. I’m not saying that we will definitely discover a use, but we will look for one in good faith using the three modalities mentioned at the beginning of this syllabus.

LLM Policy

In this course, the LLM-use policy is as follows. While working on a graded assignment, you are allowed—but not required—to use an LLM in the following ways:

• Summarize a text that you have already read
• Suggest improvements for clarity and structure of writing you produced
• Summarize complex concepts of which you have prior familiarity
• Check for logical consistency and argument strength in writing you produced
• Solicit source recommendations
• Translate and rewriting for clarity

The following are non-allowed ways to use LLMs

• Produce fully formed sentences that you pass off as your own
• Generate ideas that you pass off as your own (this might be construed as “brainstorming,” however, since an LLM has no brain, this is an inaccurate misnomer; which is to say, you may not get “ideas” from an LLM, as that would require you to attribute those ideas to the LLM, which is problematic and currently a violation of the Academic Integrity Policy (see next bullet). (You are, of course, always welcome to incorporate ideas that were generated by experts in the field you’re researching and cite those ideas in your writing—this is considered the typicalwork of a student in academia)).
• As a citation source/source of information

Disclosure:

If you choose to employ an LLM as an assistant, you must show me how you used it by submitting the complete transcript of your chat as an addendum to your submission. To do this, you must be logged-in, otherwise the application will not store any information, and I will be unable to assess your use of gen AI. It is not sufficient to merely state that you used an LLM. I must see it.

Further, if you choose to employ an LLM, you are still responsible for the content of the assignment. If the LLM produces incorrect, incomplete, inaccurate, or otherwise inadequate information, and you do not catch it, the consequence will be on you and reflected in your grade.

If I determine that an LLM was used, but you did not submit a disclosure, or that it was used in a non-allowed way, I reserve the right to give zero credit to the assignment.

Note: I accept that Grammarly predates LLMs and many students have been using it for nearly as long as they’ve been writing. To avoid confusion, if you use Grammarly, you must disclose this too. Further, also note that Grammarly has its own LLM function that can produce language from user prompts. If you use this tool, you must show how you used it like any other LLM.

Additional Comments

By now you should be aware of the limits of LLM as a writing tool, notably its propensity to present falsehoods—hallucinations, mirages, phantasmagoria, what-have-you—as though they were truth. Therefore, as a general caution, you should assume all information provided by LLMs is wrong unless it can be verified elsewhere.

You should also be aware that LLMs’ language constructions are bland, formulaic, monotonous, and absent of original thought. I have had little problem picking out LLM-generated text among assignments since its introduction into our lives near the end of 2022 because of the repetitive quality of the language, lack of consistent meaningful insight, and a level of mechanical competence of which most high school students are expected to be capable. The standard of writing expected of you in this course goes beyond what an LLM can do on its own.

If it quacks like a duck…

There are many AI programs that claim to detect LLM-generated text, but none of them can do so with 100% accuracy. However, where AI falls short, human intuition prevails. What I simply mean to say is, I know when a student has submitted LLM-generated text. This is because I have been reading student writing since long before LLMs came onto the scene. I have accumulated an adequately large sample size of student writing over the years that when non-student writing appears in front of me it is so embarrassingly conspicuous that it may as well have been presented in a different language. Thus, if it quacks like a duck and walks like a duck…it’s probably an LLM.

So, to repeat, I will know.

*NO LLM WAS USED TO WRITE THIS STATEMENT

Academic Integrity

Accommodation

The University of Massachusetts Amherst is committed to providing an equal educational opportunity for all students. If you have a documented physical, psychological, or learning disability on file with Disability Services (DS), you may be eligible for reasonable academic accommodations to help you succeed in this course. If you have a documented disability that requires an accommodation, please notify the instructor within the first two weeks of the semester so that appropriate arrangements can be made.

For further information, please visit Disability Services:
https://www.umass.edu/disability/

Academic Alerts

I have partnered with Student Success and your academic advisors to assist you on your path to success. Throughout the semester, I will communicate with Student Success and academic advisors regarding your progress in the course. If you are contacted, please consider scheduling appointments such as tutoring or academic advising and with the instructor. Referrals are not punitive and are meant to assist you in connecting with resources at UMass.

Please email [email protected] if you have any questions or need assistance connecting with resources.

Title IX Statement

In accordance with Title IX of the Education Amendments of 1972 that prohibits gender-based discrimination in educational settings that receive federal funds, the University of Massachusetts Amherst is committed to providing a safe learning environment for all students, free from all forms of discrimination, including sexual assault, sexual harassment, domestic violence, dating violence, stalking, and retaliation. This includes interactions in person or online through digital platforms and social media. Title IX also protects against discrimination on the basis of pregnancy, childbirth, false pregnancy, miscarriage, abortion, or related conditions, including recovery. There are resources here on campus to support you. A summary of the available Title IX resources (confidential and non-confidential) can be found at: https://www.umass.edu/titleix/resources

You do not need to make a formal report to access them. If you need immediate support, you are not alone. Free and confidential support is available 24 hours a day / 7 days a week / 365 days a year at the SASA Hotline: 413-545-0800