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Engineering pedagogical content knowledge for undergraduate engineering and technology programs: Accelerating graduates’ preparedness for the 4IR geospatial industry

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Conference

2023 ASEE Annual Conference & Exposition

Location

Baltimore , Maryland

Publication Date

June 25, 2023

Start Date

June 25, 2023

End Date

June 28, 2023

Conference Session

Experimentation and Laboratory-Oriented Studies Division (DELOS) Technical Session 4: Bring Your Own Experiments +

Tagged Division

Experimentation and Laboratory-Oriented Studies Division (DELOS)

Page Count

11

DOI

10.18260/1-2--43339

Permanent URL

https://strategy.asee.org/43339

Download Count

128

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Paper Authors

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Huiran Jin New Jersey Institute of Technology

biography

Laramie Potts New Jersey Institute of Technology

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Dr. Laramie Potts’ is an associate professor of Engineering Technology at NJIT and serves as the program coordinator of the Surveying Engineering Technology (SET) program at NJIT. He has been working as an educator, consultant, and researcher in geoinfo

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Abstract

Surveying engineering technology (SET) and Geomatics (S/G) programs have significantly been impacted by advances of three-dimensional (3D) geospatial data acquisition technologies coupled with innovation in computational infrastructure over the past decade. Today, large-volume 3D data in the form of point clouds, meshes, or other representations, are frequently collected by sensors such as Light Detection and Ranging (LiDAR) and depth cameras for both industrial purposes and scientific investigations. Traditional surveying techniques are more often integrated with the emerging state-of-the-art geospatial technology and 3D data analytics. Evolving geospatial industry labor markets are challenging the traditional skillsets developed at conventional S/G programs at colleges. Yet, higher education graduates may still lack decision making and project application skills, and most importantly, the ability to apply the body of knowledge from their academic training in college courses to solve real-world problems and meet the skill challenges of the Fourth Industrial Revolution (4IR).

To bridge the gap between theory and application of these relevant technologies for industry-ready graduates, hands-on exercises are developed and incorporated in a 300-level photogrammetry course for SET and Civil Engineering majors. This case study describes the project-based learning exercise that requires students to process point cloud data acquired by a depth camera mounted on a remote-controlled wheeled vehicle. Point cloud processing experience ramps up critical geospatial skills through using Open3D, an open-source library that supports rapid visualization and processing of 3D data, and Open3D-ML, an extension of Open3D for 3D machine learning tasks. With a few lines of Python code, students are presented with complete workflows such as surface registration, scene reconstruction, semantic point cloud segmentation, and object detection, thus gaining a better insight into these complex topics and how they are translated into easy-to-follow operations and applied on real 3D data. Our efforts to combine theory, real-world applications, hands-on exercises, and publicly available resources largely enable students to immerse themselves in the learning, promote their intrinsic motivation to master S/G curricula, and empower them to become active data users and analysts in their professional career. We assess the impact of our project-based learning on improving student learning outcomes of fundamentals and applications of photogrammetry.

Jin, H., & Potts, L. (2023, June), Engineering pedagogical content knowledge for undergraduate engineering and technology programs: Accelerating graduates’ preparedness for the 4IR geospatial industry Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--43339

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