2025 ASEE Annual Conference & Exposition

Work in Progress: Delivering Flexible, Relevant, and Demonstrably Effective Online Education to Working Professionals

Presented at Graduate Education, Artificial Intelligence

Many professional engineers are being called upon to incorporate the latest technologies and associated skill sets into their work (e.g., artificial intelligence). But they have little time or opportunity to obtain such knowledge and skill at the depth required for real-world application. The challenge for continuing education providers is: How to create learning experiences that are both rigorous enough to address working engineers’ practical needs and flexible enough to fit into their busy lives? Furthermore, when online education is the chosen modality, how can we create learning opportunities that are equivalent to in-person – in terms of quality, outcomes, and experience – and that work for cutting-edge technologies requiring physical interaction (e.g., additive manufacturing)?

Our team is focused on one piece of the solution: applying our signature approach, called Learning Engineering, to build online, graduate-level certificates that are targeted to industry needs, efficient and flexible for professional learners, and (most importantly) demonstrably effective and applicable. Learning Engineering has three key elements: (1) leverage learning science research to design effective, engaging instruction; (2) align educational technologies to the needs of the teaching/learning context; and (3) systematically collect learning data to guide ongoing improvement. The resulting online courses are much more than just video with a discussion board or “Zoom in the room;” they enable students to authentically interact with the material, the instructional team, and each other.

In this paper, we illustrate the elements of Learning Engineering in the context of two online courses drawn from different graduate programs and engineering disciplines:
* In biomedical engineering, students learn to modify an off-the-shelf 3D printer, making it 3D-bioprinting-enabled, and propose a novel application of 3D printing – from selecting a material, modifying it to better suit their biomedical application, testing it, and preparing it for FDA approval.
* In mechanical engineering, students use tools of the trade to complete homework and learn-by-doing practice activities where they (a) apply machine learning strategies to real-world problems and (b) implement fundamental machine learning algorithms in Python. We prioritized integrating the programming environment into our Learning Management System, so students can focus on learning the key skills rather than navigating technology hurdles, thereby easing their cognitive load.

In addition to discussing how we apply Learning Engineering in each case, we describe the multi-faceted assessment strategy we are using to compare the outcomes and experience of our online learners to those of matched in-person students. As of now, we have several data sources showing similar quality between online and in-person performance. This is an important part of the work given that each of our graduate certificates is an official university credential and that learners may “stack” a particular sequence of online certificates together to earn a Master’s degree.

Authors

Dr. Marsha Lovett Carnegie Mellon University [biography]

Dr. Marsha Lovett is Vice Provost for Teaching and Learning Innovation at Carnegie Mellon University. She has published research on learning and instruction, conducted in a variety of educational settings. A theme running throughout Lovett’s work is leveraging data – from past research and present course-based activities – to enhance teaching and learning. Aligned with that theme, her favorite phrase is "data-informed iterative improvement!"
Levent Burak Kara Carnegie Mellon University [biography]

Prof. Kara works at the intersection of machine learning, engineering design, and manufacturing. At CMU, he teaches graduate and undergraduate courses in the space of AI / Machine learning, design, dynamic systems, and linear algebra.
Prof. Rachelle Palchesko Carnegie Mellon University [biography]

Rachelle Palchesko is an Assistant Teaching Professor in the Biomedical Engineering Department at Carnegie Mellon University. She joined CMU in 2011 as a Post-Doc in Professor Adam Feinberg's lab and was promoted to Special Faculty in 2016. She began teaching courses in 2019 and was promoted to Assistant Teaching Professor in 2022. She has taught courses in topics such as biomaterials, bioprinting and biofabrication, biomechanics, and tissue engineering just to name a few. She is interested in integrating cutting edge education tools and hands on activities into her courses and teaching laboratory courses.
Zachary Mineroff http://orcid.org/0000-0001-8806-9069 Carnegie Mellon University [biography]

As Assistant Director of Learning Engineering at CMU, Zach supports the design, development, and implementation of innovative educational technologies and learning experiences. He supervises a team of learning engineers that supports instructors through consultations, course design projects, and fellowship programs. He is a graduate of the Masters of Educational Technology and Applied Learning Science (METALS) program at CMU.
Judy Brooks Carnegie Mellon University
Avi Chawla Carnegie Mellon University [biography]

As a Senior Learning Engineer at CMU, Avi works with instructors and the team at Eberly to design, develop and implement courses for online programs utilizing learning science principles. His main focus of work is on developing learning experiences which align learning goals, assessments and instruction using evidence based design principles and data analysis.
Mr. Martin van Velsen Carnegie Mellon University [biography]

Martin is a senior system’s architect with experience designing large scale production and research architectures. He has worked on research projects of a wildly varied nature, some which are: neurosurgery simulations, large scale artificial intelligence architectures, virtual humans and cognitive training simulations. Martin serves as technical adviser to many leading specialists in the field of serious games, simulations, and digital entertainment. Martin has been a speaker and panel host for various entertainment technology gatherings. Most recently he took part as a panelist at the PAX East gaming convention, but he has also organized such scientific forums as a panel on Authoring Interactive Narrative at the Stanford Spring Symposium. Over the last 18 years Martin has been responsible for shepherding open-ended research projects towards viable products that can be deployed by such organizations as DARPA, Army Research Labs (ARL), Air Force Research Labs (AFRL) and the Office of Naval Research (ONR). Finally Martin is an award winning artist, published fiction author, engineer, and a researcher in the field of interactive narrative.

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