LRES 575: Professional Paper
Credits: 3
Semester: Spring and Fall
Location: Online
The professional paper is intended to give you an in-depth experience in the design, implementation, and completion of a rigorous, original project. It is a scholarly assessment, and novel analysis of a clearly formulated problem. It is not a term paper. Like a thesis, the outcome of a professional paper is a paper of publishable quality like that of a peer-reviewed journal paper. As such, approximate guidelines for the length of the paper are 25-45 double spaced pages (including figures, tables, references, etc.). In addition, you are expected to orally present (via webinar) your professional paper at a symposium to your graduate committee and other interested faculty and students.
The professional paper requirement is flexible to your needs and interests and tailored to your topic of study and/or research. Professional papers should draw from and build on course work completed throughout the program. You are also encouraged to draw upon ongoing work-place relationships, collaborations, and research interests in designing and implementing a professional paper. The topic of your professional paper should align with the background or experience of your professional paper instructor to ensure quality mentoring. Although the professional paper is a rigorous analytical exercise, primary data collection is not required. Professional papers can be based on either primary or secondary data analyses. Although not preferred, and with instructor approval, it can be based on a novel, synthetic analysis of existing literature provided you conduct a clearly unique academic study. The abstract must clearly indicate your contribution and report results from the analysis.
Learning Outcomes:
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Develop a rigorous research project that addresses a key issue in the environmental sciences.
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Read, analyze, and synthesize the relevant literature on the topic of interest.
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Develop and carry out a methodological approach to the problem.
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Write a detailed, thorough, original, and rigorous professional paper in first-person voice.
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Present a rehearsed oral presentation overview of the professional paper to a public audience within the allotted timeframe.
Your professional paper is a two-semester process, not a two-semester course. The first semester is focused on proposal development and project initiation (You will NOT register for professional paper credits during this semester). The second semester is focused on project and paper completion (You WILL register for 3 credits of professional paper during this semester). Ideally, these are the final two semesters of your program. The proposal development semester begins with required participation in several online modules that detail the overall professional paper process. From there, you will begin to identify a topic and write a short proposal (< 1 page), followed by a full proposal and literature review (approximately 3-5 pages). The proposal must be approved by an instructor and your graduate committee the semester before registering for the 3-credit professional paper course. During the two semesters that you are working on your proposal and professional paper, you will work closely with your professional paper instructor to carry out the proposed project. Regular meetings are strongly advised so that you stay on schedule.
Deadlines for proposals are as follows:
- For fall term professional paper enrollment:
- Short proposal: due March 1
- Full proposal: due May 1
- For spring term professional paper enrollment:
- Short proposal: due October 1
- Full proposal: due December 1
Semester 1: Proposal development and project initiation:
The goal of the proposal development semester is to help you articulate the problem, goals, and potential methods for your research and to help you identify a faculty member to work with on your project. The first step of proposal development is to write a short proposal (< 1 page) that addresses the following key questions:
Short proposal questions/prompts:
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What is the working title of your project?
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What is the primary question(s) your project seeks to answer?
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How does this project address a knowledge gap in your field of study?
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Briefly describe data sets and analysis methods that are required for this project.
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Do you anticipate a need for statistical consulting services?
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Suggest one or more faculty members with whom you might work with on this project.
Please submit your short proposal to your academic advisor, Dr. Bob Peterson (bpeterson@montana.edu).Once you have submitted a short proposal, your graduate committee will review your responses, provide feedback, and help you identify an appropriate faculty instructor. The remainder of the proposal development semester will then be devoted to working on your full proposal (3-5 pages) that addresses the following key questions:
Full proposal questions/prompts:
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What is the working title of your project?
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What is the primary question(s) your project seeks to answer?
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How does this project address a knowledge gap in your field of study?
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What are your specific project objectives?
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What are your proposed methods?
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What are your expected results and why might they be significant?
Note: You are encouraged to begin working on your project concurrent to developing the full proposal.
Please submit your full proposal to Bob Peterson (bpeterson@montana.edu)and your faculty instructor (TBD).
Semester 2: Project and paper completion:
To ensure that you complete your project, you must strictly adhere to a rigid timeline for the professional paper during the project completion semester. Suggested guidelines, at a minimum, are as follows:
- Three months before symposium: Submit a complete, detailed OUTLINE of your professional paper to your instructor. Use the next three months to write drafts and receive timely feedback from your instructor (generally within 2-3 days of receipt).
- One month before symposium: Submit the first COMPLETE DRAFT of your professional paper to your instructor. If you cannot meet this deadline, you MUST withdraw from LRES 575 and retake it another semester. Your draft should be a nearly complete representation of the entirety of the project. Your professional paper instructor will read the draft and provide comments back to you that must be addressed in subsequent drafts.
- One week before symposium: Submit FINAL DRAFT of your professional paper to your graduate committee (Bob Peterson, Scott Powell, and Tim Covino). Please put your name in the file name and the e-mail subject line. If you cannot meet this deadline, you cannot present your professional paper at the symposium, and you will need to retake LRES 575 another semester. Your final draft should be a complete and high-quality draft. The full committee will read your draft and provide comments back to you that must be addressed in your final paper.
- Professional paper symposium (dates/times TBD; typically, finals week): You will work with your professional paper instructor on the content, structure, and rehearsal of the presentation. You must attend all the professional paper presentations, unless extraordinary circumstances prevent you from doing so. Following the presentation, you will be informed of any additional changes that must be incorporated into your final paper.
- Final week of term: Submit final paper and a PDF of your presentation to your instructor, advisor and Marni Rolston (mrolston@montana.edu). Your instructor will grade the course with a letter grade (A-F).
Oral Presentation:
You are required to orally present your rehearsed, instructor-approved professional paper during a live, public symposium via webinar. The symposium will be the only scheduled event for the course. A headset works best for audio and is strongly recommended. In addition, it is strongly recommended that you are plugged into an internet cable (as opposed to wireless), or that you are in a building with a robust internet connection (e.g., at work, at school, or in a public library). Marni Rolston will conduct a test with you one week before the symposium to ensure that you have the proper software and equipment and that everything is running smoothly.
You will be allotted 15 minutes for the presentation, and 3-5 minutes for questions and answers. Presentation graphics (e.g., PowerPoint) are expected.
The following are requirements for an effective presentation:
- Share your draft slides with your instructor, well before your presentation. Practice your presentation with your instructor. Remember, 25% of your grade is based on the presentation.
- Practice! Give your talk to friends and co-workers, etc. Get feedback about your presentation before you present.
- Keep text to a minimum.
- Use images and graphics to convey your points.
- Do NOT read text verbatim on your slides or from notes. For example, convey a key point with the text, but then give more background and details that are not on the slide.
- Use large, legible fonts.
- Avoid complex figures and graphics that you cannot easily explain.
- Always label your graph axes and be able to explain your main point(s) briefly.
- If you include graphics or figures that you did not create, cite the sources.
- If necessary, please use a headset for remote presentations.
- Avoid the need to tell the audience every detail from your professional paper, especially background information. Keep it brief and cover the main points of your analysis to stay within the time limits.
- Have fun with this presentation and tell us a good story!
Statistical consulting:
Statistical consulting MAY be available on request from the Statistical Resources group (https://www.montana.edu/statisticalconsulting/) or the HELPS Lab (Helps Lab - HELPSLab | Montana State University), in situations where you are collecting your own primary data and need advice on study design, or your instructor is unsure of appropriate statistical approaches, or you have limited statistical experience.
Professional Paper Format:
Use of an active and first-person voice throughout the paper is required, unless extraordinary circumstances or your instructor dictate otherwise.
The format for the written professional paper must follow closely the standard preparation guidelines established by The Graduate School (Please find the link in your Canvas “LRES Online Advising” course. Please let Marni know if you can’t find this template). It is very important you read through it BEFORE starting on your professional paper.
Please note, however, that professional papers will NOT be submitted directly to the Graduate School for formatting (even if you do receive an e-mail from The Graduate School about this).
Citation Format:
Use standard citation format for ecological journals (e.g., Ecology) – Author(s). Year. Article title. Journal name volume: pages.
For example:
Coral reefs provide an interesting case in which to consider these issues, because they have been studied for centuries, with the last few decades underscoring the large changes that have occurred relative to the 1960s (and earlier) (Cramer et al., 2021).
Cramer, K. L., M. K. Donovan, J. B. Jackson, B. J. Greenstein, C. A. Korpanty, G. M. Cook, and J. M. Pandolfi. 2021. “The Transformation of Caribbean Coral Communities since Humans.” Ecology and Evolution 11: 10098–118.
Please also look at the Canvas “LRES Online Advising” course for additional information about the professional paper, including an archive of past professional papers. Each project is unique, of course, but these should give you some idea of the expected format and rigor of the projects.
Note: Professional papers will be archived in the MSU ScholarWorks database (https://scholarworks.montana.edu/). If you have a proprietary conflict, please let us know.
Grading:
The professional paper course is graded with a letter grade, as with any other course. Your professional paper instructor is the ultimate arbiter of the final grade, and they may solicit input from your graduate committee if desired. The course will be graded based on the learning outcomes and the following breakdown:
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Final paper: 75%
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Presentation: 25%
After your presentation, you will have approximately one week to incorporate any additional feedback into your final paper.
**Note for instructors: Please send the final grade, prior to the end of the term, to Bob Peterson (bpeterson@montana.edu), who will enter the grade for you.
AI Policy:
Students should learn how to use AI tools to enhance rather than detract from their developing abilities as writers, coders, communicators, and thinkers. Instructors should ensure fair grading for both those who do and do not use AI tools. This policy stresses transparency and fairness and adopts some commonsense expectations and limitations on the use of AI tools. As such, students in the professional paper class are required to:
- Give credit to AI tools whenever used, even if only to generate ideas rather than usable text or illustrations.
- When using AI tools, add an appendix showing (a) the entire exchange, highlighting the most relevant sections; (b) a description of precisely which AI tools were used (e.g. ChatGPT private subscription version or DALL-E free version), (c) an explanation of how the AI tools were used (e.g. to generate ideas, turns of phrase, elements of text, long stretches of text, lines of argument, pieces of evidence, maps of conceptual territory, illustrations of key concepts, etc.); (d) an account of why AI tools were used (e.g. to save time, to surmount writer’s block, to stimulate thinking, to handle mounting stress, to clarify prose, to translate text, to experiment for fun, etc.).
- Use AI tools wisely and intelligently, aiming to deepen understanding of subject matter and to support learning.
In return, we, as your instructors, pledge that we will:
- Seek to understand how AI tools work, including their strengths and weaknesses, to optimize their value for student learning.
- Treat work by students who declare no use of AI tools as the baseline for grading.
- Use a lower baseline for students who declare use of AI tools, depending on how extensive the usage, while rewarding creativity, critical nuance, and the correction of inaccuracies or superficial interpretations in response to suggestions made by AI tools.
- Employ AI detection tools to evaluate the degree to which AI tools have likely been employed.
- Impose a significant penalty for low-energy or unreflective reuse of material generated by AI tools.
