Course Syllabus

Contact Information

This table includes information about how to contact your instructor and other important details about your class

Office Hours: By appointment and odd week Tuesdays when we don't have class, 7pm

Email: nathanial.d.wiggins-1@ou.edu

Live Session:  Tuesday, Weeks 2, 4, 6, 8

7:00 - 8:30 pm  (Central) Zoom link

Meeting ID: 912 388 3023

 

Professor Nate Wiggins

Assistant Professor of Engineering

Director of Engineering and Leadership Program

Gallogly College of Engineering

Course Details

For a list of course activities, scroll to the bottom of this page.

Course Format

This 8-week course is multi-modal with asynchronous and synchronous work and meetings. You will have asynchronous online work using Canvas. We meet once every other week, with a synchronous meeting, or Live Session, for an hour and a half using Zoom.  The Live Sessions are not graded. 

Course Materials

Course materials are provided by the department and integrated into Canvas. The primary textbook used in the class is the NASA Cost Estimating Handbook (CEH):

Program Learning Outcomes (PLO)

Program Learning Outcomes for ELM & ISE programs
Engineering Leadership & Management Industrial & Systems Engineering
  1. Design, develop, and use various techniques and models to facilitate data-informed decision-making regarding technologies, the environment, and demand, considering factors such as risk, uncertainties, and other constraints.
  2. Effectively establish, lead, and manage multidisciplinary teams to efficiency to solve complex real-world problems and promote innovation with a range of technologies.
  3. Effectively plan and manage costs, schedules, scope of work, logistics, and quality systems.
  4. Explain the legal, safety, regulatory, professional and ethical implications of management decisions and outline the responsibilities of the organization, team or individual.
  5. Communicate clearly and concisely, both orally and in writing to a variety of audiences, from specialists to non-specialists.
  1. Employ tools and techniques for successful implementation of the systems engineering process.
  2. Provide decision quality for systems design value trade-offs.
  3. Analyze system performance for any part of the life cycle of a system through application of operations research, cost analysis, and predictive analytics techniques
  4. Collaborate with and effectively lead multifunctional teams to achieve project management objectives.

Course Learning Outcomes (CLO) Alignment

Course Learning Outcomes
CLO Description PLO
A Synthesize and apply engineering economics concepts and applications.

ELM:  1

ISE: 1

B Apply cost engineering methods.

ELM: 3

ISE: 1, 2, 3

C Apply cost management techniques.

ELM:  3

ISE: 1, 2, 3

D Form strategies for the management of cost issues in interdisciplinary project environments.

ELM: 3 

ISE: 1, 2, 3

E Apply modern software packages to conduct analysis of real-world data.

ELM:  2

ISE: 1

F Communicate results of a cost engineering analysis.

ELM:  5

ISE: 1, 4


Grades

Breakdown

Course activities and grades listed for each activity
Activity Description Points/Percentage
Assignments Weekly homework assignments with concept review and application of techniques. 60%
Labs Labs designed to enhance your cost engineering skills 10%
Cost Engineering Project Proposal Project Proposal  5%
Cost Engineering Poster Project

Application of Cost Engineering Analysis to a structured, multi-criteria, real-world problem. 

  • Cost Engineering Poster (20%)
  • Peer Feedback (5%) 
25%
Total  100%

Scale

Grade Scale
Percentage Letter Grade
90–100% A
80–89% B
70–79% C
60–69% D
Below 60% F

Course Components

Assignments

Homework Assignments are integrated into Canvas. The platform has integrated resources with PDF readings, hints, and examples. The assignments review definitions and concepts presented in the lectures and readings. There are problem questions for applying the economic skills of the week. 

Labs

Labs are designed to enhance skills related to particular lessons with hands-on practice with real-world problems.

Cost Engineering Poster Project

You will work throughout the course on real-world project solving a problem related to cost engineering. You will follow the process of economic decision analysis and create a poster.

Project Presentation

In this poster presentation, you don't get to post a video - your poster must stand on its own and you will review each other's posters, based on the poster alone. You will provide peer feedback on your classmates' posters.


Course Policies

Communication 

I'm available often, even on weekends and evenings. Contact me via email if you need anything and if you don't hear back within 24-48 hours, contact me again. 

Feedback 

I aim to complete grading within a week. 

Late Policy

  • Course Project: No late submissions for the course project are accepted.  
  • Assignments: You have available a Late Pass for up to five homework assignments. Each assignment has a Late Pass button which can automatically communicate to me that the assignment will be late.  If you take a Late Pass, you have 72 hours to submit the homework assignment.

Generative AI Policy

Generative AI can be very useful as you plan your strategy for how to approach an assignment in this class and begin to gather the information you’ll need to be successful. Here is how you can use Generative AI in this class: · Planning: Goblin.tools has a “Magic ToDo”, which can help you break down more complicated tasks into smaller action items. This can help you in the planning stage of any assignment.

Brainstorming and Outlining: You may use Generative AI to help you in the initial stages of your assignments, but you must ensure that your work goes beyond the Generative AI output. This starts with effective prompts. For example, brainstorming means thinking with Generative AI, rather than having Generative AI think for you. Instead of a prompt that says: “I have to do an assignment on a topic. What topic should I do?”, you should provide more context in your prompt, share your interests, your ideas, what questions you have, and ask it to help you make a decision or to learn about topics you might be interested in given what you shared. Similarly with outlining, you should include in a prompt your initial ideas based on what you are learning in the course and can then use AI to help you order those ideas effectively.

AI Research tools: We will explore ResearchRabbit, SemanticScholar, AI research assistants in e-books, and other appropriate AI research tools to explore how AI can help you find additional sources that you can use in your exploration of our course topics.

To ensure everyone has access to the same resources, you may only use free Generative AI tools, or those that are provided to you through the university such as Copilot and AI tools with Adobe Creative Cloud (available in campus computer labs).

To implement this policy, we will have ongoing discussions in class about effective use of Generative AI and how you are using it. You’ll be asked to reflect frequently about AI usage both in-class and as part of your assignment submission (see assignment instructions for specifics), where you’ll also be asked to share your prompts, screenshots of your chats with Generative AI tools, and how you ensure your ideas and voice remain central in your assignment. In this class, it is important that you take the time to fully develop your own ideas and, therefore, you should not use AI to draft or revise your writing.

It is important to follow the guidelines for each assignment carefully. There may be times, such as in-class quizzes, midterms, or finals, where Generative AI usage is prohibited. I will clearly state this on any relevant assignment. Any use of Generative AI in those cases will be considered a violation of the academic integrity policy.

If you have any questions about this policy, please talk with me.

Consequences for Violating the Generative AI Usage Policy: Per our usage policy, you will be responsible for the accuracy of anything you submit, including appropriately citing and summarizing any articles you find through AI research tools, and thus must read the material you are citing. Submitting data or research that is not real (a risk when overly relying on Generative AI) may result in an academic integrity violation for falsifying information.

My Use of Generative AI: I will model appropriate Generative AI usage by clearly disclosing when I use it and why. Expected use cases include: using my notes and previous PowerPoints to improve the structure of my lectures so that they are clearer to you all as students and using AI research tools to find current articles to update our course readings. I will never use Generative AI to grade your work or to communicate with you.

Plagiarism 

Models and work should be your own. Any dishonest actions are ethics violations. If you are using another source, make sure to cite it properly. 

For more information about plagiarism, watch the OU Libraries Plagiarism Tutorial video and take the short Avoiding Plagiarism Tutorial Canvas course offered by University Libraries. 


University Academic Policies and Student Support

Access the University Academic Policies Document.

 


Course Summary:

Course Summary
Date Details Due