Teaching Artificial Intelligence and Robotics to Undergraduate Systems Engineering Students

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Author(s)

Luis Emilio Alvarez-Dionisi 1,* Mitali Mittra 2 Rosbelia Balza 1

1. Polytechnic University Institute “Santiago Mariño,” Barinas, Venezuela

2. Russian Presidential Academy of National Economy and Public Administration (RANEPA), Kingston/RANEPA MBA Program, Moscow, Russian Federation

* Corresponding author.

DOI: https://doi.org/10.5815/ijmecs.2019.07.06

Received: 22 Apr. 2017 / Revised: 10 Jun. 2017 / Accepted: 13 Sep. 2017 / Published: 8 Jul. 2019

Index Terms

Artificial Intelligence, Robotics, Big Data, Case Study, Universal Robots

Abstract

The skills of artificial intelligence (AI) and robotics provide a wide window of job opportunities for the following professionals: computer scientists, mechanical engineers, system engineers, computer engineers, biomedical engineers, and electrical engineers. Additionally, other professionals benefiting from AI and robotics’ job opportunities are information technologists, informatic engineers, electronic engineers, data scientists, industrial engineers, big data engineers, and related specialists in the dynamic field of engineering robotics. Therefore, the purpose of this research was to study the effort of teaching AI and robotics to undergraduate systems engineering students at the Polytechnic University Institute “Santiago Mariño” in Barinas, Venezuela. Consequently, the methodology used in this academic research was the case study approach, which included three phases, namely Initiation Phase, Fieldwork Phase, and Closing Phase. In that sense, the design of research adopted in this study was based on the development of an exploratory single case study method. As a result, the Theoretical Framework created as a cornerstone of this research highlighted the following three research variables: (1) Robotic Applications, (2) Mechanics of Robotic Manipulation and Computer Vision, and (3) Object-oriented Analysis and Design (OOAD) and Object-oriented (OO) High-level Programming Languages. In conclusion, two nondirectional null hypotheses were tested, leading to the positive answers of the following research questions: (1) “Can undergraduate systems engineering students apply OOAD and OO High-level Programming Languages to analyze, design, and develop Robotic Applications?” and (2) “Can undergraduate systems engineering students use Mechanics of Robotic Manipulation and Computer Vision to analyze, design, and develop Robotic Applications?” as stated in this case study.

Cite This Paper

Luis Emilio Alvarez-Dionisi, Mitali Mittra, Rosbelia Balza, "Teaching Artificial Intelligence and Robotics to Undergraduate Systems Engineering Students", International Journal of Modern Education and Computer Science(IJMECS), Vol.11, No.7, pp. 54-63, 2019.DOI: 10.5815/ijmecs.2019.07.06

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