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Artificially Intelligent Method (AIM) for STEM-based Electrical Engineering Education and Pedagogy Case Study: Microelectronics

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2017 ASEE Annual Conference & Exposition


Columbus, Ohio

Publication Date

June 24, 2017

Start Date

June 24, 2017

End Date

June 28, 2017

Conference Session

Electrical and Computer Division Technical Session 8

Tagged Division

Electrical and Computer

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Paper Authors


Faycal Saffih University of Waterloo

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Dr. Fayçal Saffih (IEEE, 2000) received B.Sc. (Best Honors) in Solid-State Physics from University of Sétif-1, Algeria, in 1996, M.Sc. degree in Bio-Physics from University of Malaya, Malaysia, in 1998, and Ph.D. degree in Electrical and Computer Engineering from the University of Waterloo, Canada, in 2005. In 2006, he joined the Communication Research Laboratory, McMaster University, Hamilton, ON, where he developed a versatile FPGA-based prototype for biomedical smart imaging application known as the wireless endoscopic capsule. Dr. Faycal Saffih joined Voxtel Inc., OR, USA, as Senior Analog Active Pixel Sensor engineer, designing imagers based on SOI-CMOS technology for high-energy physics particles detection, and electrons microscopy imaging. From 2009 until 2012, he joined KAUST as Research Fellow where incepted his invention on Smart Nano-photonic devices dedicated for imaging and solar energy harvesting. Dr. Saffih recently (March 2017) got certified from Renewables Academy (RENAC:, Germany, for developing Renewable Energy projects.
Driven by his interest on Intelligence-Harvesting and (Physical- and Bio-) Mimicry, Dr. Saffih has published various papers in Imaging and suggesting AI application in pedagogy and education starting with his paper at 142nd ASEE International Conference, Columbus, OH, USA, on June 2017.
To disseminate his research and teaching activities and findings, Dr. Saffih has launched his channel that can be accessed here:

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The teaching of microelectronic requires a multidisciplinary approach. This includes solid-state physics, microelectronics fabrication, electronic circuit analysis, Mathematics, and a good exposure on its applications. This is exactly what Science-Technology-Engineering-Math (STEM) curriculum is campaigning for to boost education and its impacts. These teaching dimensions, and intellectual faculties, are related to the nature of the subject itself which is just a one side of the “teaching coin” of the proposed Artificially-Intelligent Method (AIM) approach. The other side of this coin, which is common to all teaching disciplines, involves a good understanding of “learning psychology” of the students in addition to their socio-cultural conditions and realities. In the present paper, both facets of the AIM teaching coin are presented and more specifically how to use the associative nature of the student’s memory to enhance their revision and “in-class understanding moment” recall performance which in turns enhance their knowledge acquisition of the subject.

Saffih, F. (2017, June), Artificially Intelligent Method (AIM) for STEM-based Electrical Engineering Education and Pedagogy Case Study: Microelectronics Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. 10.18260/1-2--27614

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