Revising Computer Science Networking Hands-On Courses in the Context of the Future Internet

Bibliographic Data

ID20297741
AuthorsJuan A Fraire (0000-0001-9816-6989, Consejo Nacional de Investigaciones Científicas y Técnicas), Juan E Duran (0000-0003-1900-096X, Universidad Nacional de Córdoba)
Year2021
Volume64
Issue2
Pages133-138
Publication date2021-05-01
Open AccessYes
TypeARTICLE
VenueIEEE Transactions on Education (JOURNAL)
Journal identifiersISSN: 0018-9359 • E-ISSN: 1557-9638
PublisherInstitute of Electrical and Electronics Engineers (IEEE) (PUBLISHER)
DOI10.1109/te.2020.3015673
OpenAlexW3083551129
LanguageEN
References cited19

Contribution: In a context where hands-on courses are biased toward specific technologies, a novel creativity-provoking instructional approach for networking undergraduate courses is successfully applied following action research principles and active and creative learning techniques. Background: Extensive engineering-oriented networking courses have been proposed with a strong focus on specific protocol solutions. At the same time, the amount and complexity of techniques is notably increasing with the advent of the Future Internet. As a result, the curricula looses focus on the fundamentals of networking algorithms. Intended Outcomes: We address algorithmic learning in networking for computer sciences, where students are expected to 1) create; 2) develop; 3) analyze; and 4) compare algorithms and processes regardless of protocol-specific technologies. At least 70% of the students are expected to meet this goal while enhancing their engagement and motivation in a time-constrained course schedule. Application Design: To achieve 1) and 2), we instrument an active experimental strategy, while objectives 3) and 4) are tackled with creative learning techniques, both applied in an action research framework. The approach is supported by state-of-the-art networking application interfaces and simulators. Furthermore, a blended and game learning component favors the engagement via comparison and competition of students' project metrics. Findings: The experiment is carried out by professors of the Computer Science Bachelor's degree taught in FAMAF. Results show that the applied methodology met the intended outcomes, and improved by 7% in a two-year cycle. Furthermore, the approach was very well received based on student's feedback

Active learning (machine learning) · Bachelor · Context (archaeology) · Creativity · Curriculum · Multimedia · Pedagogy · The Internet · World Wide Web · Artificial Intelligence · Cloud Computing and Resource Management · Computer Science · IoT and Edge/Fog Computing · Software-Defined Networks and 5G

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