UT Tyler College of Engineering

MSEL 5396 — Engineering Leadership Project

The University of Texas at Tyler • College of Engineering
Syllabus • Spring 2025 • Subject to change

Instructor

Dr. Mayzan Isied
Office: Ratliff Building South (RBS) 1009
Phone: (903) 565‑5872
Email: misied@uttyler.edu

Modality & Times

100% Online (Canvas LMS)
Asynchronous – individual Zoom consultations as needed.

Office Hours

By appointment (schedule via email).

Grading Basis

Credit / No‑Credit (Pass/Fail) — total of 1,000 points across milestones.

Course Overview

MSEL 5396 Engineering Leadership Project is the culminating capstone project for the Master of Science in Engineering Leadership program. This one‑on‑one, fully online course provides an opportunity for students to independently design and execute a leadership‑focused project tied to a real‑world work context or a realistic simulated professional role. Under instructor supervision, each student will identify a unique leadership challenge or research question in an engineering or technical environment and carry out a project to address it. Projects may take various forms – for example, an experimental study, a modeling or simulation‑based analysis, a human‑subjects research project, or an organizational leadership initiative – but all will require applying engineering leadership principles in a practical way.

All course activities are conducted through Canvas and remote communication. Students will propose 3–5 potential project topics and submit a recorded presentation early in the semester to outline their ideas. After a review and discussion with the instructor (via Zoom), one topic will be selected and developed into a formal project plan. The chosen project is then executed over the semester with bi‑weekly progress updates (written reports and/or short presentations submitted via Canvas) to track development. The course emphasizes professional communication and strict adherence to writing and formatting guidelines: students must prepare a final leadership project report in a format similar to National Science Foundation (NSF) research reports/proposals, as provided in the course resources. By the end of the term, students will produce a polished project report and a final recorded presentation that communicates their project results and leadership learnings. This capstone is graded on a Pass/Fail basis, with successful completion requiring timely submission of all milestones and high‑quality deliverables that demonstrate mastery of engineering leadership skills.

Student Learning Outcomes

  • Propose and plan an engineering leadership project that addresses a complex problem or opportunity in a real or simulated organizational context, clearly defining project objectives, scope, and methodology.
  • Apply research methods and leadership principles to execute the project, including data collection, analysis, and project management techniques appropriate to the chosen topic.
  • Integrate knowledge from engineering, management, and leadership literature by conducting a relevant literature review and incorporating best practices and theoretical frameworks into the project design and execution.
  • Demonstrate professional communication skills through the creation of well‑organized project proposals, comprehensive written reports (following NSF‑style formatting guidelines), and effective oral presentations (recorded for remote delivery).
  • Evaluate project outcomes and leadership effectiveness by analyzing data or results, assessing the impact of leadership interventions or decisions, and reflecting on lessons learned to provide recommendations for future improvement.
  • Observe ethical and professional standards throughout the project, including responsible conduct of research (e.g., obtaining IRB approval for human‑subject studies if applicable) and integrity in data reporting and collaboration.

Prerequisite

Enrollment is restricted to MSEL students in their final semester of the program. It is recommended that students have completed the core MSEL coursework (27 credit hours) or obtain department approval before enrolling in MSEL 5396. Instructor permission is required.

Required Textbooks and Readings

No required textbook. Students are expected to perform an independent literature review relevant to their chosen project. The instructor will provide guidance and recommend resources as needed (research articles, case studies, leadership frameworks, methodology references) via Canvas. All necessary materials for research methodology and report format (including an NSF‑style report template and example) will be available through Canvas. Use the UT Tyler library and online databases for scholarly and professional literature related to your topic.

Milestones & Deliverables

All submissions via Canvas by 11:59 PM on the due date (tentative schedule).

WeekMilestoneDeliverable
Week 1Orientation & PlanningIntroductory meeting (Zoom); review course expectations and project guidelines; begin brainstorming topics.
Week 2Project Topic ProposalsSubmit 3–5 topic ideas + ~5‑minute recorded pitch introducing proposed topics/objectives.
Week 3Topic Review & SelectionOne‑on‑one Zoom; finalize topic; begin preliminary work (background research, refining questions).
Week 4Formal Project ProposalNSF‑style written proposal: background, problem, objectives, methodology/approach, expected outcomes, plan/timeline.
Weeks 5–13Bi‑Weekly Progress UpdatesFour updates (due ~Weeks 6, 8, 10, 12): short written reports and/or brief recorded presentations.
Week 8 (Mid‑Semester)Midpoint Check‑InLive progress review (Zoom) to evaluate progress and troubleshoot issues.
Week 14Full Draft DueComplete draft of NSF‑style report for review and revisions.
Week 15Final DeliverablesPolished final report; recorded presentation (15–20 min); verification of external submission to intended stakeholder.
Week 16Final AssessmentShort reflective quiz in Canvas.

Grading Policy

This course is graded on a Credit/No‑Credit (Pass/Fail) basis. To earn a Pass, you must satisfactorily complete all required deliverables and meet expectations for quality and timeliness. There are no traditional exams or letter grades; evaluation is based on cumulative performance on milestones and final outputs.

Evaluation Components (Points)

Project Topic Proposal & Presentation — 100 pts (10%)

Clarity and thoughtfulness of initial topic ideas and presentation.

Formal Project Proposal — 100 pts (10%)

Quality of written project plan (problem definition, objectives, methodology).

Bi‑Weekly Progress Updates (4 × 50) — 200 pts (20%)

Consistent progress and quality of updates across the term.

Final Project Report (NSF‑style) — 300 pts (30%)

Depth of analysis, quality of writing, adherence to format.

Final Project Presentation — 200 pts (20%)

Effectiveness of oral presentation and visual communication.

Final Quiz (Project & Leadership Knowledge) — 100 pts (10%)

Understanding of project outcomes and key leadership lessons.

Total: 1,000 points (100%). A minimum of 70% (700 points) is generally required to receive Credit. Completion of all major deliverables (proposal, updates, final report, final presentation, quiz) is mandatory.

Late Work / Assignment Policy

Professionals are not late. If you will miss a deadline, contact the instructor before the due date to discuss.

How lateDeduction
0–24 hours lateUp to −25% of earned grade
24–48 hours lateUp to −50% of earned grade
48–72 hours lateUp to −75% of earned grade
> 72 hours lateNo credit (assignment must still be submitted)

Unapproved late submissions may receive a zero. Technology issues are not an excuse—submit early.

Sample Leadership Project Topics (Examples)

Civil Engineering Project Manager (City Public Works)

Data: Infrastructure condition surveys, maintenance records, and budget data

Objectives: Develop and lead a pavement management plan for city roads; prioritize maintenance, optimize limited budgets, coordinate schedules; demonstrate leadership across departments.

Construction Site Safety Officer

Data: Safety incident reports, compliance audit data, and worker feedback surveys

Objectives: Design and execute a safety‑culture initiative (training + incentives); measure reduction in incidents and improved compliance.

Manufacturing Process Improvement Lead (Mechanical Engineering)

Data: Production output metrics, defect rates, and process simulation results

Objectives: Increase line efficiency with Lean Six Sigma + simulation; boost throughput, reduce defects; train operators on updated procedures.

Quality Assurance Team Leader (Aerospace)

Data: Quality inspection results, testing data, and rework statistics

Objectives: Lead root‑cause analysis; implement revised QC protocol and training; reduce defect rates; build a culture of quality.

Electrical Engineering R&D Project Lead

Data: Laboratory experiment data, prototype performance metrics, and project timelines

Objectives: Coordinate sensor development from concept to prototype; manage iterations; deliver working prototype and documented process.

IoT Systems Deployment Manager (E/CE)

Data: Sensor readings, network performance logs, and analytics

Objectives: Deploy predictive‑maintenance IoT; integrate dashboard; reduce downtime; train maintenance staff for adoption.

Power Systems Operations Supervisor

Data: Grid load data, outage frequency records, simulation models

Objectives: Integrate smart‑grid upgrade; coordinate implementation; manage risks; communicate reliability improvements.

Engineering Team Training Coordinator

Data: Skills assessments, training feedback, and performance KPIs

Objectives: Design and evaluate a leadership/project‑management training program; measure impacts on team performance.

Process Automation Project Manager (Chemical/Mechanical)

Data: Process flow data, production rate statistics, and safety logs

Objectives: Automate a manual process; improve safety and efficiency; manage change and operator readiness.

Organizational Change Analyst (Engineering Firm)

Data: Employee surveys, productivity metrics, interviews

Objectives: Study communication bottlenecks; pilot new protocols/tools; evaluate outcomes with follow‑up measures.

Human Factors Researcher (Leadership Study)

Data: Behavioral observations, experiment results, and questionnaires

Objectives: Experimental/case study on leadership style vs. team performance; analyze output/creativity/morale; recommend practices.