Teaching Artificial Intelligence using Project Based Learning

EasyChair Preprint 4789

Abstract

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.

Keyphrases: Artificial Intelligence, Artificial Neural Network, image recognition, machine vision, project engineering

@booklet{EasyChair:4789,
  author    = {Marc Dahmen and Luis Quezada and Miguel Alfaro and Guillermo Fuertes and Claudio Aballay and Manuel Vargas},
  title     = {Teaching Artificial Intelligence using Project Based Learning},
  howpublished = {EasyChair Preprint 4789},
  year      = {EasyChair, 2020}}