Collection

ASEE-NE 2022

Authors

Joshua Luckens, Wentworth; Afsaneh Ghanavati, Wentworth Institute of Technology

development asdesign thinkers visible to themselves, empowering them to enunciate their evolving skills ascreative problem solvers. In the process, they develop both essential professional writing skillsand the ability to recognize and eloquently communicate their thought processes. Both steps–theawareness of one's cognitive processes and the ability to eloquently explain one's thinking toothers–are skills that will serve our students well as they start their professional career paths.Another fundamental skill that the engineering notebook reinforces is systems thinking. Throughreflective writing, first-year students draw explicit connections between their lived experiencesand the fundamentals of engineering, reinforcing the training in systems

Collection

ASEE-NE 2022

Authors

Grace Remillard, University of Massachusetts Lowell; Sarah Kamal, University of Massachusetts, Lowell; Justin An, University of the District of Columbia; Charles Thompson PhD, University of Massachusetts Lowell; Kavitha Chandra, University of Massachusetts Lowell

Technology Today; American Men and Women of Science, West Babylon Alumni Hall of Fame; He is a Fellow of the Acoustical Society of America and cited for his fundamental contributions to theoretical and computational acoustics. He is senior member of IEEE, and a member of the American Physical Society and Sigma Xi. He has published reesearch in acoustics, control theory, fluid mechanics, heat transfer, linear and nonlinear systems, and telecommunications.Prof. Kavitha Chandra, University of Massachusetts Lowell Kavitha Chandra is the Associate Dean for Undergraduate Programs and Professor of Electrical and Com- puter Engineering in the Francis College of Engineering at the University of Massachusetts Lowell. She

Collection

ASEE-NE 2022

Authors

Cuong H Pham, Wentworth Institute of Technology

exploration, data cleaning, data analysis, and data visualization followedby live coding sections and hands on labs. Fig. 1. Data Exploration with Pandas in Jupyter NotebookLabs are developed in Pandas and Jupyter Notebook. Pandas is a data analysis and manipulationtool built on top of the Python programming language and has been one of the most commonlyused tools for Data Science and Machine learning to handle data. The main advantages of Pandasover Java are its simplicity and ease of use. Jupyter Notebook on the other hand is an open-source web-based notebook environment that allows you to write code, view it, and execute itwithin a single user interface, thus making it easy to make changes on the go and immediatelysee the impact

Collection

ASEE-NE 2022

Authors

Savita Vitthalrao Kendre, Worcester Polytechnic Institute; Gus Taylor Teran; Lauryn Whiteside, Worcester polytechnic ; Tyler C Looney; Ryley Ian Wheelock; Surya Sebastian Ghai, University of Maryland; Markus Nemitz

tocreate an object by layer-wise controlled deposition through software. There are different types of3D printers and printing protocols, which allow increasingly complex designs. Wallin et al. discusscommon 3D printing techniques for soft robots including fused deposition modeling (FDM),stereolithography (SLA), direct ink writing (DIW), and selective laser sintering (SLS), amongothers [10]. These techniques use filaments, inks, powders, or resins as printing materials.FDM printing is the most common 3D printing fabrication technique; it uses the melting of afilament to construct an object in successive layers [10]. For FDM printing soft devices, first, thedesign of components is created in CAD software, then it is printed using flexible filaments

Collection

ASEE-NE 2022

Authors

Filip Cuckov, Wentworth Institute of Technology; Marisha Rawlins, Wentworth Institute of Technology; Pilin Junsangsri, Wentworth Institute of Technology; Wayne Bynoe, Wentworth Institute of Technology; James R McCusker PhD, Wentworth Institute of Technology; José R. Sánchez, Wentworth Institute of Technology

addressedthe challenges of Industry 4.0 and (re)imagined and (re)designed our engineering curricula [1].Since then, innovations such as distributed computing and robotics, the Internet of things, multi-agent systems, semantic web, complex adaptive systems, artificial intelligence and machinelearning, and self-organizing business processes; have emerged and accelerated the transitionfrom Industry 4.0 to Industry 5.0 [2]. The overarching problem is that the industry careerspresented to our current graduates have changed fundamentally [3], and our present curricula areincreasingly becoming less fit to prepare our students to fill the needs of their prospectiveemployers. Also, our instructional methodologies are rapidly becoming obsolete because they