TY - JOUR
T1 - A project based learning approach for teaching artificial intelligence to undergraduate students
AU - Vargas, Manuel
AU - Nuñez, Tabita
AU - Alfaro, Miguel
AU - Fuertes, Guillermo
AU - Gutierrez, Sebastian
AU - Ternero, Rodrigo
AU - Sabattin, Jorge
AU - Banguera, Leonardo
AU - Duran, Claudia
AU - Peralta, Maria Alejandra
N1 - Funding Information:
Acknowledgments – This research was supported by CIES (Research Center for Higher Education) of the San Sebastián University (USS).
Publisher Copyright:
© 2020 TEMPUS Publications.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020
Y1 - 2020
N2 - This work presents an active learning methodology called Project-based learning (PBL) for developing artificial intelligence (AI) in a computer vision course of an undergraduate engineering degree. The objective of the course was to develop image recognition capabilities using Deep Learning (DL)/Machine Learning (ML) technics in real-world problems. The PBL learning methodology helped students search for real-world problems, develop complex solutions, and generate synergy among team members. The main role of the professor was to advise, guide and motivate the students throughout the course. The pedagogic innovation with active learning methodologies offered the professor the opportunity to create a dynamic motivating learning environment based on experiences. Each undergraduate engineering student had the opportunity to develop the skills and techniques of their profession: teamwork, proactivity, innovation, and leadership. The results obtained by the student teams showed problem-solving, including the use of automatic navigation equipment with AI, detection of the malaria parasite, recognition of non-human individuals to control vehicular traffic.
AB - This work presents an active learning methodology called Project-based learning (PBL) for developing artificial intelligence (AI) in a computer vision course of an undergraduate engineering degree. The objective of the course was to develop image recognition capabilities using Deep Learning (DL)/Machine Learning (ML) technics in real-world problems. The PBL learning methodology helped students search for real-world problems, develop complex solutions, and generate synergy among team members. The main role of the professor was to advise, guide and motivate the students throughout the course. The pedagogic innovation with active learning methodologies offered the professor the opportunity to create a dynamic motivating learning environment based on experiences. Each undergraduate engineering student had the opportunity to develop the skills and techniques of their profession: teamwork, proactivity, innovation, and leadership. The results obtained by the student teams showed problem-solving, including the use of automatic navigation equipment with AI, detection of the malaria parasite, recognition of non-human individuals to control vehicular traffic.
KW - Artificial intelligence
KW - Artificial neural network
KW - Image recognition
KW - Machine vision
KW - Project engineering
UR - http://www.scopus.com/inward/record.url?scp=85096032928&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:85096032928
SN - 0949-149X
VL - 36
SP - 1773
EP - 1782
JO - International Journal of Engineering Education
JF - International Journal of Engineering Education
IS - 6
ER -