Wolfram Computation Meets Knowledge

Wolfram Summer School

Alumni

Vladimir Portnykh

Educational Technology

Class of 2019

Bio

Dr. Vladimir Portnykh is a mathematician who specializes in Functional Analysis and Active System Theory. Mathematics Genealogy Project contains his personal record. In 1998 Vladimir received an MS in Mathematics with highest honors from Voronezh State University (VSU). V. Portnykh’s academic advisor, professor Boris Sadovskij, was a student and co-author of a famous mathematician: Mark Krasnoselskij. While in Russia Vladimir has published 15 research papers in various academic journals and three scientific monographs. In 2001 Vladimir’s thesis was defended before the Dissertation Council of V. A. Trapeznikov Institute of Control Sciences also known as The Institute of Automatics and Telemechanics of the Russian Academy of Sciences. Vladimir’s strength lies in his ability to combine theory with its practical applications with a particular focus on using modern computer technologies. As an inventor of a number of internationally patented ideas in the field of digital media, Vladimir knows that research is an integral part of commercial success. Dr V. Portnykh is a very passionate teacher and mentor, who truly enjoys teaching mathematics. He is a keen supporter of constructivist teaching and learning in math, who has experience and expertise in promoting and supporting the development of computational thinking of students.

Project: Data presentation and interpretation

Goal

Despite Mathematica’s powerful features for data analysis, it remains seldom used in education. The aim of my project is to provide “how to” examples, and by doing this, this project presents Mathematica as a flexible and powerful tool for data analysis. The efforts, like the presentation notebook, could be important in allowing students and faculty to realize that they have at their disposal an incredibly powerful tool for data analysis.

Summary of Results

This computational experience will equip students with the range of skills important to analyze and present data. The data may be discrete or continuous, grouped or ungrouped. Specifically, they should be able to calculate measures of location, mean, median and mode and variation, standard deviation, variance, range and interpercentile range. They should also be able to interpret and draw inferences from summary statistics. These calculations should be recapped from GCSE; however, the focus now is on students using Mathematica.

Future Work

The natural next step would be to use the Wolfram Problem Generator. This is incredibly powerful and useful functionality for many teachers, but it remains a clear underdog in the Wolfram family. The quiz style, i.e. where four possible answers are given to chose from, is obsolete and mix-and-match questions have proven to be a far better alternative. It will help to promote Mathematica and open more opportunities for empowering users.

Wolfram Summer School | Champaign, IL, USA | July 3 29–July 22, 2022

APPLY NOW