2026-09-30:From Learning to Performance: Exploring Maritime Workforce Innovation Through Hands-On Experience — Field Trip Report

VDMC and Q.E.D. Systems teams at the Q.E.D. Center for Training and Development.

How do we really know when someone has learned a skilled trade? Is completing a task enough, or should we also understand how the person performed it, where they struggled, what demanded their attention, and how their performance changed as they gained experience?

These questions came to life during a recent hands-on maritime workforce visit to Q.E.D. Systems, Inc., by members of the Virginia Digital Maritime Center (VDMC) Workforce Innovation team. For the day, we stepped away from the roles we normally hold as researchers, developers, and workforce professionals and became novice maritime trainees. Instead of only discussing workforce training and performance from the outside, we experienced parts of the learning process firsthand.

The experience gave us an opportunity to learn several maritime skilled trades firsthand while also observing how skills are introduced, practiced, coached, and ultimately assessed. Combining hands-on participation with observation made the visit especially valuable for understanding both training and performance.

From the Learning Lab to the Maritime Olympics

VDMC Team 1 and Team 2 relay teams during the Maritime Olympics Challenge.

The day began in the Learning Lab, where we rotated through hands-on activities involving marine electrical work, rigging, welding, and fall protection. We quickly realized that learning a skilled trade is very different from simply watching someone perform it. We listened carefully to instructions, observed demonstrations, handled unfamiliar tools, attempted new tasks, made mistakes, received feedback, adjusted techniques, and tried again.

One important takeaway was realizing how much is involved in performing even a seemingly simple task well. We had to pay close attention to instructions, coordinate our movements, remember each step, make judgments as we worked, and continuously check whether the task was being performed correctly.

Later in the day, the Learning Lab became an Assessment Lab through Q.E.D.'s Maritime Olympics. The skills introduced earlier were no longer just something we had learned or practiced; we now had to put them to the test through a series of performance challenges and demonstrate what we could do.

Experiencing the Challenge as Learners

VDMC team member Lawrence Obiuwevwi is practicing welding during the hands-on training

Another activity that stood out to us was welding. It is easy to observe an experienced welder and focus only on the finished result. As we took on the role of learners, we began noticing everything that happens before that final result: where attention is directed, how the hands are positioned, whether the correct movement is maintained, how quickly an error is recognized, and how performance changes after feedback.

That experience raised an important question for us: How do we move someone from being introduced to a skill to being able to perform that skill reliably in a real working environment? And perhaps more importantly, how do we know when that transition has actually happened?

Looking Beyond Task Completion

Traditional workforce assessment can focus on whether the trainee completed the task, how long it took, how many errors occurred, and whether the final product met the required standard. Those measures are important, but participating in the activities reinforced that they tell only part of the story.

Two people may successfully complete the same task while going through very different processes. One person may move confidently and efficiently, while another may hesitate, repeatedly correct mistakes, require more guidance, or experience much greater cognitive demand. If we look only at the final product, much of that difference can remain invisible.

Within VDMC's Maritime Human Performance Science effort, led by Dr. Jessica M. Johnson at the Neuroergonomics and Simulation lab, we are interested in how multimodal technologies can help explain what happens during skilled performance, not simply what the final outcome looks like.

As we moved through the activities at Q.E.D., we began thinking about the kinds of questions that could be investigated using eye tracking, physiological sensing, neurophysiological measurement, behavioral observations, and performance measures. Where does a trainee look during a critical step? When does a task begin demanding more attention? Where do hesitation and uncertainty appear? How does a learner respond after an instructor provides feedback? And what begins to change as the learner becomes more proficient?

Those are the kinds of questions that move us beyond simply asking, “Did the trainee complete the task?” toward understanding how skill is actually acquired. This is where the field-trip experience connected directly with the research being pursued at VDMC.

Toward a Process-Level Understanding of Skilled Work

From a research perspective, skilled work is especially interesting because many different kinds of information are generated at the same time. Eye tracking can tell us something about visual attention. Physiological sensing can help us examine changes associated with workload and arousal. Neurophysiological measures can add another perspective on cognitive processes, while task-performance data provide the context needed to understand what was happening at a particular moment.

The challenge is not simply collecting all of these data. The important question is how we synchronize, organize, analyze, and model them in a way that produces information instructors and trainees can actually use.

The long-term goal is not to add more sensors simply because the technology exists, but to use these measurements to better understand how trainees learn, where difficulties emerge, and how proficiency develops over time.

One example is our ongoing pipefitting research in the lab, where we use a holographic training environment to study skilled-task performance. By combining task-performance measures with multimodal sensing, including eye tracking, physiological signals, and neurophysiological measures, we can examine how trainees respond to instructions, move through different task steps, encounter and correct errors, and adapt with practice. These insights can help inform better simulations, training approaches, and instructor feedback.

Sample trainee interaction with the Proto holographic pipefitting training environment.

Learning Maritime Skills Firsthand

The rope-knotting activity was another good example of why being physically present matters. Watching an instructor demonstrate a knot and actually trying to reproduce it are two completely different experiences. Reproducing the knot requires translating what was just observed into coordinated hand movements, while instructor feedback becomes part of the learning process.
Experiences like this reminded us that it is difficult to fully understand skilled work from a laboratory alone. By taking the position of novice trainees—receiving instructions, using unfamiliar tools, making mistakes, correcting them, and later being assessed, we gained a different perspective on the complexity behind skilled performance.

VDMC team learning maritime rope knotting at the Q.E.D. Center for Training and Development.

Connecting Research, Training, and Workforce Readiness

One of the biggest takeaways from the visit was how closely workforce practice and workforce research can inform one another. We begin by identifying real workforce challenges, translating them into relevant research questions, collecting evidence, and using what we learn to improve training, assessment, and ultimately workforce readiness.
For us at the Virginia Digital Maritime Center (VDMC), this is especially important because modern training environments can generate large and diverse streams of human-performance data. Our research increasingly focuses on understanding the process of skill acquisition, not only whether a trainee succeeds or fails at a task, but also how cognitive, physiological, behavioral, and performance patterns change as that trainee progresses toward proficiency.

This leads to an important research question: How can we move beyond measuring task completion and better understand the processes through which skilled competency develops? Answering that question requires collaboration across computer science, human-performance research, training, simulation, workforce development, and industry, with skilled workers and trainees at the center of the research.

We are grateful to Q.E.D. Systems, Inc. for opening its doors to us and allowing us to experience maritime training from the perspective of learners. We also appreciate the support of the Submarine Industrial Base Program Office and the broader maritime community working to strengthen workforce development and innovation.

We arrived at Q.E.D. as a workforce innovation team interested in training and human performance, but for part of the day we also became trainees. That shift in perspective was valuable because some research questions become much clearer when we step outside the laboratory, put on the safety equipment, pick up the tools, make mistakes, receive feedback, and experience the learning process firsthand.

Special Thanks and Acknowledgments

I would like to express sincere gratitude to Dr. Jessica M. Johnson, Director of the NeuroErgonomics & Simulation Lab and a leader of VDMC's Workforce Innovation efforts, for continued mentorship, guidance, and opportunities to participate in meaningful research at the intersection of human performance, workforce development, and innovation. We are equally grateful to Q.E.D. Systems, Inc. for sharing the expertise of its workforce and instructors and giving us the opportunity to learn by doing.

I also sincerely appreciate Dr. Sampath Jayarathna, Associate Professor of Computer Science at Old Dominion University and a member of the Web Science and Digital Libraries (WS-DL) Research Group and NIRDS Lab, for continued research guidance and support connecting field experiences with broader academic research.

I also acknowledge the contributions of the broader Virginia Digital Maritime Center Workforce Innovation team, including Jennifer Renne, Danielle Joyner, Devon Nelson, Paige Rainey, Ashley Buczkowski, John Snell, Jason Dudley, and Jannah Elmousalami, across K–12 education and career exploration, industry workforce and training innovation, simulation, assessment, and

maritime human-performance research. We are grateful as well to the Virginia Digital Maritime Center, the Web Science and Digital Libraries Research Group, NIRDS Lab, and the broader Old Dominion University research community for fostering the interdisciplinary environment that makes this work possible.

About the Author

Lawrence Obiuwevwi is a Ph.D. student in the Department of Computer Science at Old Dominion University, a graduate research assistant with the Virginia Digital Maritime Center, and a student member of the Web Science and Digital Libraries (WS-DL) Research Group and NIRDS Lab. His work focuses on multimodal human-performance computing, affective computing, neuroergonomics, and workforce development and innovation, with particular interest in understanding how people learn, adapt, and develop proficiency in skilled training environments.

Lawrence Obiuwevwi
Graduate Research Assistant | Virginia Digital Maritime Center
Department of Computer Science | Old Dominion University
Norfolk, VA 23529
Email: lobiu001@odu.edu 

Web: lawobiu.com