645.662.8VL - Introduction to Systems Engineering

Course Structure

The course materials are divided into 12 modules which can be accessed by clicking modules on the menu on the course Canvas page. A module will have several sections including the overview, content, reading assignment, article review summary, and assignment. You are encouraged to preview all sections of the module before starting. Most modules run for a period of seven (7) days, exceptions are noted on the Course Outline page (also accessed from the Syllabus & Course Information link on the left). You should regularly check the Calendar and Announcements for assignment due dates.

Course Topics

Topics include defining Systems, the System Development Life Cycle and the Systems Engineering Method. These primary topics are decomposed into Requirements Analysis, Functional Design, Physical Design, Design Validation, Concept Development, Engineering Development and Post Development. In addition, the tools and methods at the Systems Engineer’s disposal are also covered. These include Risk Analysis, Configuration Management, Design Trade Offs, Modeling & Simulation, Interface Management, and how these subjects are linked to Systems Program Management activities.

Course Goals

To identify, describe and practice the methods and principles of systems engineering - and then apply that knowledge to develop a system concept.

Course Learning Outcomes (CLOs)

• Define what a system is, as well as the various levels that comprise a System's hierarchy.
• Describe the Systems Engineering (SE) activities, which include Requirements Analysis, Functional Definition, Physical Definition, and Design Validation.
• Identify and describe the technical management tools used to assist the systems engineer, which include the Systems Engineering Management Plan (SEMP), Risk & Configuration Management, Model Based Systems Engineering (MBSE), Trade Studies, Modeling & Simulation and the Work Breakdown Structure (WBS).
• Define the System Development Life Cycle (SDLC) and how the SE process is applied across the SDLC.
• Describe the alternative life cycle models and how to choose among them.
• Identify and describe the relationship between specialist engineering, project management and specialist engineering areas.
• Differentiate between the types of requirements and apply techniques for writing good requirements.
• Identify and create the functional and physical domains of a system concept.
• Identify, analyze, assess, and write risks and their mitigations.
• Identify and differentiate among the types of trade studies and demonstrate performing a formal trade study using the Analytical Hierarchy Process (AHP) method.
• Describe the application of the SE process for a complex system development effort.
• Define a system concept and capture that concept in the form of a partial, preliminary conceptual architecture.

Textbooks

Required Textbook

There are two required textbooks for this course:

1. INCOSE (2023). Systems Engineering Handbook (5th edition). Hoboken, NJ: John Wiley & Sons, Inc. ISBN: 978-1119814290
2. Kossiakoff, A., et al. (2020). Systems Engineering Principles and Practice (3rd ed.). Hoboken, NJ: John Wiley & Sons, Inc. zyBook edition. See Textbook Information Page on Canvas for access code to zyBook.
   

Other Materials & Online Resources

Vitech CORE or Vitech Genesys or Catia Magic Enterprise Architect

Our JHU Systems Engineering Program has setup a community site on Canvas to give you access to Systems Engineering and Project Management tools.  These tools can be used in your courses throughout the program. To access this site, follow this link. 
Be sure to follow the instructions exactly. Most issues students have trace back to not following instructions exactly.
For Catia Magic users: you'll be required to launch the Ivanti VPN and copy/paste the server name and port every time you want to open the app. 

Student Coursework Requirements

It is expected that each module will take approximately 6-15 hours per week to complete. Here is an approximate breakdown:

• Reading assignments: approximately 1–3 hours per week.
• Watching lecture videos: approximately 2-4 hours per week.
• INCOSE Quizzes or Discussion Forums: 1 hour per week.
• Homework assignment: approximately 2-4 hours per week.

This course will consist of five basic student requirements:

Individual Assignments (40% of final grade calculation)

There will be individual homework assignments for modules 1 through 6 in this course (in addition to the problems in the zyBook).

1. These assignments are made available in each module folder. Through the first half of the course, homework assignments are completed individually. In the latter half of the course (module 7 onward), the assignments are completed as a group (see #4 below).
2. Assignments are individual work—although any non-human source is available to you.
3. Some problems may require additional research outside of class lectures and the zyBook. All research for this class, however, can be accomplished via the Internet. Be sure to credit your sources.
4. The assignments are due by the due date (provided on the course calendar on Canvas). If you are going to be late with an assignment, please let your instructor know (via email). See late policy below in “grading” for late submissions.
5. Please see the grading rubric for grading methodology and assignment expectations for each assignment. Don’t forget to submit your assignment as a PDF (don’t submit as .pptx or .docx, etc).

INCOSE Quizzes (5% of final grade calculation)

1. INCOSE quizzes take place periodically throughout the semester.
2. Completion of these quizzes in conjunction with the other assignments is equivalent to taking the INCOSE Knowledge Exam, as this course has academic equivalency for the INCOSE knowledge exam.
3. These INCOSE quiz questions pull information solely from the INCOSE SE Handbook 5th Edition.

zyBook Participation Activities (5% of final grade calculation)

1. The zyBook contains Participation Activities (PAs) throughout each chapter.
2. You have unlimited attempts to answer the PAs.
3. Ensure you access the zyBook from the Canvas link to gain credit for the PAs – otherwise Canvas will not register your responses and you won’t get credit for the PAs. In other words, don’t sign in through zyBooks.com. Instead, click the link to the zyBook from Canvas.
4. Be aware that incomplete PAs will often register in Canvas as “F”, “D”, “C” etc. until the chapter is complete, where it should then register as an “A”.

Discussion Forum (15% of Final Grade Calculation)

1. The discussion forum focuses on using large language models (LLMs) and artificial intelligence (AI) in domain systems engineering.
2. You will engage in discussions related to the course material, contributing original posts and responding substantively to your classmates.
3. Engage with the forums, making at least one original post and responding to at least one classmates' post with substantive feedback.
4. Provide thoughtful and well-researched posts relevant to the discussion topic.

Team Project (25% of Final Grade Calculation)

1. Individual homework assignments are replaced by team assignments in Module 7.
2. Students are assigned to teams toward the beginning of the semester and may begin working on team assignments together.
3. Teams are not expected to begin the team project until Module 7 begins.
4. Project materials are provided in the Modules section of Canvas.
5. The project artifact(s) should be turned in by a single individual from the group at the end of each module. There is no need for each member in the group to turn in each artifact.
6. Project artifacts are assigned in each module in the latter half of the course starting at Module 7; however, the artifacts are cumulatively ‘due’ at the end of the semester.
7. Teams will progressively add more material and refine their artifacts as they progress from team assignment to the next.
8. When teams submit their artifacts, the section instructor will review and provide comments so the team may make improvements to their artifacts.
9. No grades are awarded until the final report and presentation are provided during Module 12.
10. Grading is by team, with everyone receiving the same grade.
11. No separate grade is given for the report and the presentation, and in general the project report will dominate the grading.
12. Please see the grading rubric for grading methodology and assignment expectations.

Team Member Performance Assessment (10% of final grade calculation)

As a part of the development of the group project, students will be required to assess their teammate’s contributions and performance throughout the development of the project. Assessments will be turned in using the same manner as assignments in the same week the project is turned in. Assessments are anonymous and will not be shared among individuals. Performance assessments will be factored with the overall team assignment grade for each individual. Thus, students may receive different grades for the same team project depending on their individual contributions. If a student's individual contributions lacked to a greater extent, the instructor may further modify their team assignment grade.

Grading Policy

EP uses a +/- grading system (see “Grading System”, Graduate Programs catalog, p. 10).

Late assignments will be deducted 5% for every day they are late. If you know that you will be late, either attempt to submit the assignment prior to the due date or request permission from your section instructor for an extension with justification. The instructor may grant an extension at their discretion.

Instructors generally do not directly grade spelling and grammar. However, egregious violations of the rules of the English language will be noted without comment. Consistently poor performance in either spelling or grammar is taken as an indication of poor written communication ability that may detract from your grade.

A grade of A indicates achievement of consistent excellence and distinction throughout the course—that is, conspicuous excellence in all aspects of assignments and discussion in every week.

A grade of B indicates work that meets all course requirements on a level appropriate for graduate academic work.

Course Evaluation

Course Evaluations are provided near the Mid Term and again near the end of the semester.

Course Policies

Due dates

Assignments are due according to the dates in the calendar and assignments items in the corresponding modules. Instructors will post grades typically within two weeks after assignment due dates.

Using AI (ChatGPT) as a tool to aid/guide.

Students are permitted to use Generative AI tools such as ChatGPT to help them where needed, but there are precautions that must be taken into account.

While AI can be a useful tool, it is not infallible and may provide partially or wholly incorrect responses. Some limitations of using AI may include:

• AI may not fully understand the context of the problem, leading to inaccurate or incomplete responses. Even when prompted with context, it has been discovered that AI will 'make things up' and present its response as facts. When prompted to provide sources for its responses, it has been found to 'make things up' here as well.
• AI cannot follow links to websites and does not 'read' books when prompted. It may act like it can and does but understand that it does not. AI relies on the data that it has 'scraped' from the internet, and without proper and accurate prompting, will make holistic 'guesses' from a wide range of data and present its response as fact. If using Generative AI, it would benefit you to understand how it works. Here is a list of courses that can get you up to speed (sign in with your @jhu.edu email for free access).
• AI is biased based on the data it has been trained on, leading to results that are not entirely objective. Since AI pulls from existing data it has 'scraped' from the internet, it will carry the same biases as the data that was scraped. In many cases, during development, AI has been instructed to ignore specific sites or files that do not align with the biases of the programmers or their organizations. This does not impact the hard sciences as much as the soft sciences, but it is still somewhat present. Thus, AI may not have access to all the relevant information necessary to provide a complete or accurate response.
• AI follows the same GIGO (garbage in, garbage out) principles as standard search engines or other database queries. Proper and accurate prompts will achieve more accurate and higher quality results. If you'd like to enhance your prompt engineering skills, check out LinkedIn Learning's Prompt Engineering course and others like it .

To provide an example, if a student queries ChatGPT for a 3-tier system hierarchy for an automobile, the response misses important details and provides incomplete information. It will present tier 3 and 4 elements at tier 2, and the number of elements will fall far short of the 'actual' 3 tier automobile physical hierarchy.

It is important for students to always double-check AI responses against the course material and principles taught in the lesson material. While AI can be a useful tool, it should not be relied upon as the sole source of information. We Encourage students to critically evaluate AI responses and to seek help from the instructor or other resources if they have any doubts or questions.

Academic Policies

Deadlines for Adding, Dropping and Withdrawing from Courses

Students may add a course up to one week after the start of the term for that particular course. Students may drop courses according to the drop deadlines outlined in the EP academic calendar (https://ep.jhu.edu/student-services/academic-calendar/). Between the 6th week of the class and prior to the final withdrawal deadline, a student may withdraw from a course with a W on their academic record. A record of the course will remain on the academic record with a W appearing in the grade column to indicate that the student registered and withdrew from the course.

Academic Misconduct Policy

All students are required to read, know, and comply with the Johns Hopkins University Krieger School of Arts and Sciences (KSAS) / Whiting School of Engineering (WSE) Procedures for Handling Allegations of Misconduct by Full-Time and Part-Time Graduate Students.

This policy prohibits academic misconduct, including but not limited to the following: cheating or facilitating cheating; plagiarism; reuse of assignments; unauthorized collaboration; alteration of graded assignments; and unfair competition. Course materials (old assignments, texts, or examinations, etc.) should not be shared unless authorized by the course instructor. Any questions related to this policy should be directed to EP’s academic integrity officer at ep-academic-integrity@jhu.edu.

Students with Disabilities - Accommodations and Accessibility

Johns Hopkins University values diversity and inclusion. We are committed to providing welcoming, equitable, and accessible educational experiences for all students. Students with disabilities (including those with psychological conditions, medical conditions and temporary disabilities) can request accommodations for this course by providing an Accommodation Letter issued by Student Disability Services (SDS). Please request accommodations for this course as early as possible to provide time for effective communication and arrangements.

For further information or to start the process of requesting accommodations, please contact Student Disability Services at Engineering for Professionals, ep-disability-svcs@jhu.edu.

Student Conduct Code

The fundamental purpose of the JHU regulation of student conduct is to promote and to protect the health, safety, welfare, property, and rights of all members of the University community as well as to promote the orderly operation of the University and to safeguard its property and facilities. As members of the University community, students accept certain responsibilities which support the educational mission and create an environment in which all students are afforded the same opportunity to succeed academically. 

For a full description of the code please visit the following website: https://studentaffairs.jhu.edu/policies-guidelines/student-code/

Classroom Climate

JHU is committed to creating a classroom environment that values the diversity of experiences and perspectives that all students bring. Everyone has the right to be treated with dignity and respect. Fostering an inclusive climate is important. Research and experience show that students who interact with peers who are different from themselves learn new things and experience tangible educational outcomes. At no time in this learning process should someone be singled out or treated unequally on the basis of any seen or unseen part of their identity. 
 
If you have concerns in this course about harassment, discrimination, or any unequal treatment, or if you seek accommodations or resources, please reach out to the course instructor directly. Reporting will never impact your course grade. You may also share concerns with your program chair, the Assistant Dean for Diversity and Inclusion, or the Office of Institutional Equity. In handling reports, people will protect your privacy as much as possible, but faculty and staff are required to officially report information for some cases (e.g. sexual harassment).

Course Auditing

When a student enrolls in an EP course with “audit” status, the student must reach an understanding with the instructor as to what is required to earn the “audit.” If the student does not meet those expectations, the instructor must notify the EP Registration Team [EP-Registration@exchange.johnshopkins.edu] in order for the student to be retroactively dropped or withdrawn from the course (depending on when the "audit" was requested and in accordance with EP registration deadlines). All lecture content will remain accessible to auditing students, but access to all other course material is left to the discretion of the instructor.