Journal article
Pedagogy of diversity and data analytics: Theory to practice
Computer applications in engineering education, v 27(5), pp 1277-1285
01 Sep 2019
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
A course in probability is a requirement in Baccalaureate Programs in Electrical and Computer Engineering. Students view this course as conceptual with little connection to real world problems. Efforts have been undertaken to mitigate this issue and connect the conceptual topics to data analytics to make the course relevant. Data analytics based exercises are now integral to the course. Several demos were created to link statistical concepts with practice through analysis of data. In this study, a demo created to illustrate the concept of diversity to improve the performance of a machine vision system is described. It incorporates concepts of Bayes' rule, single and multiple random variables, goodness fit tests, random number simulation and data analytics to illustrate the pedagogy of diversity and associated data processing. Student survey results suggest that these demos enhance that the learning experience in the engineering probability course.
Metrics
Details
- Title
- Pedagogy of diversity and data analytics: Theory to practice
- Creators
- P. Mohana Shankar - Drexel University
- Publication Details
- Computer applications in engineering education, v 27(5), pp 1277-1285
- Publisher
- Wiley
- Number of pages
- 9
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000480046300001
- Scopus ID
- 2-s2.0-85070073037
- Other Identifier
- 991019167793304721
UN Sustainable Development Goals (SDGs)
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Interdisciplinary Applications
- Education, Scientific Disciplines
- Engineering, Multidisciplinary