Leading Undergraduate Students to Big Data Generation

TL;DR

This paper introduces a novel educational approach that combines network simulation and image processing tools to enhance undergraduate students' skills in Big Data analysis and manipulation, fostering practical and critical thinking abilities.

Contribution

The authors develop an innovative teaching method integrating network simulation and image processing to improve students' hands-on skills and understanding of Big Data concepts.

Findings

Improved student hands-on skills in Big Data analysis.

Enhanced critical thinking abilities among students.

Successful application of image-based rendering for virtual world generation.

Abstract

People are facing a flood of data today. Data are being collected at unprecedented scale in many areas, such as networking, image processing, virtualization, scientific computation, and algorithms. The huge data nowadays are called Big Data. Big data is an all encompassing term for any collection of data sets so large and complex that it becomes difficult to process them using traditional data processing applications. In this article, the authors present a unique way which uses network simulator and tools of image processing to train students abilities to learn, analyze, manipulate, and apply Big Data. Thus they develop students handson abilities on Big Data and their critical thinking abilities. The authors used novel image based rendering algorithm with user intervention to generate realistic 3D virtual world. The learning outcomes are significant.