Analytical Learning through Robotics and the Internet

By Jumie Yuventi.

Published by Ubiquitous Learning: An International Journal

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Article: Print $US10.00
Article: Electronic $US5.00

Learning computer programming or migrating to a new programming language is often perceived as being difficult. This is partially because the traditional methods of teaching focus more on the memorization of syntax rather than understanding and developing algorithms. Additionally, the traditional tools used to teach programming do little to retain students’ attention or increase confidence in their skills. Building upon previous attempts at innovative computer programming strategies to create an environment that engages the student, this paper presents a method of learning programming through the use of robotics and the Internet. The concept revolves around separating language and function, focusing on the application of analytical thinking toward creating algorithms. The Internet is used to provide ubiquity in learning; creating an easily accessible platform that potentially reduces the cost of learning. This method can provide students with a greater understanding of the logic involved in programming than other approaches. This understanding should make it easier to develop unique/complex software or transition to a new programming language. The direction taken in this paper is governed by the notion that programming helps to develop analytical thinking. The method introduced is not meant solely for computer science students, but also the greater technical audience.

Keywords: Analytics, Learning, Algorithms, Robotics, Internet, Computer Programming, Programming Languages, Cloud Computing, Server-side Processing, Multi-architecture Web Design

Ubiquitous Learning: An International Journal, Volume 4, Issue 1, pp.29-42. Article: Print (Spiral Bound). Article: Electronic (PDF File; 1.420MB).

Jumie Yuventi

PhD Student, Electrical Engineering, Construction Engineering Management in Civil and Environmental Engineering, Stanford University, Palo Alto, CA, USA

Jumie is a doctoral candidate at Stanford University. He has a Bachelors in Electrical Engineering from The City College of New York and a Masters in the same field from Stanford University. He is interested in research, employment, and entrepreneurship opportunities involving the application of technology and optimization strategies to increase productivity and address challenges in Engineering and Finance.