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Improving Technical Writing Skills Through the Judicious Use of Infographics

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2015 ASEE Annual Conference & Exposition


Seattle, Washington

Publication Date

June 14, 2015

Start Date

June 14, 2015

End Date

June 17, 2015





Conference Session


Tagged Division

Computing & Information Technology

Page Count


Page Numbers

26.929.1 - 26.929.11



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Paper Authors


Joseph Alan Nygate Rochester Institute of Technology (CAST)

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Current position
Associate Professor, College of Applied Science and Technology, RIT

Previous employment
10 years as Vice President of Technology and Architecture, Amdocs
6 years as Director of Architecture and Business Development, Nortel Networks
10 years, MTS Research and Development, AT&T Bell Labs

PhD Computer Engineering, 1994, Case Western Reserve University, USA - AT&T Bell Labs, PhD Scholar
MSc Computer Science, 1985, Weizmann Institute of Science, Israel
MSc Applied Mathematics, 1985, Weizmann Institute of Science, Israel
BSc Computer Science and Mathematics, 1982, Ben-Gurion University, Israel

Big Data Applications in Telecommunications
Software Defined Networks – operations, management and orchestration
Artificial Intelligence – expert systems, intelligent agents, reinforcement learning
Self-Organizing Networks
Number Theory

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Richard Cliver Rochester Institute of Technology (CAST)

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Richard C. Cliver is an Associate Professor in the department of Electrical, Computer and Telecommunications Engineering Technology at RIT where he teaches a wide variety of courses both analog and digital, from the freshman to senior level. Richard also works for the Eastman Kodak Company as a Senior Design Engineer. Richard has received two teaching awards while at RIT. He was the recipient of the 1998 Adjunct Excellence in Teaching Award and the recipient of the 2002 Provost’s Excellence in Teaching Award. Richard is a contributing volunteer in both ABET and IEEE.

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Improving Technical Writing Skills through the Judicious Use of InfographicsEffective composition of technical documentation requires both strongwriting skills and clear visualization of data using techniques such ascharts, scatterplots and histograms.While many schools provide intensive programs that focus on improvingthe written aspect of documentation, students receive very little guidanceon methods that can be used to present their data in well-structured,coherent graphs. During engineering classes it became apparent thatstudents lack this important skill. They knew about line charts, bar chartsand scatterplots but did not know of: • The existence of many other types of infographics such as histograms, control charts and sparklines • The strengths and weaknesses of each graph type • How to use colors and fonts effectively • How to choose which metric and what scaling factor should be used on each axis • How to connect the text with the graph and how they complement each otherThis paper shares the process, experience and outcomes of teaching datavisualization techniques within an existing telecommunications networkplanning and design class.The principles and methods that were taught were based on EdwardTufte’s classical work - “The Visual Display of QuantitativeInformation”.These techniques and best practices opened the student’s eyes to a wholenew perspective that was hitherto unknown to them. Surprisingly, themore they learned, the more they enjoyed and the more they invested.Students learned that graphical excellence • Induces thinking • Groups data into coherent sets • Reveals data at several levels • Conveys graphical integrity • Maximizes the value of ink • Leverages the use of colors, shapes, fonts and sizesMost importantly, the students realized that text, together with graphics,are much more than the sum of their parts. While the text providescontext and explains how the diagram is constructed it is the graphics thatpresent the information so we can detect patterns and trends, drawconclusions or make predictions.This paper describes the progress students made in drawing graphs andtables, and the impact it had on the quality of their work.We will describe the visualization techniques that were found to be mostuseful, how were able to teach these techniques within the currentengineering curriculum and how were able to get the students involvedand excited.These techniques are valuable across any field that requires datavisualization. Big data technologies, cluster analysis, correlation andprediction, pattern and anomaly detection, are common to almost all areasof research. Being able to present the information clearly and efficientlyare key to being able to analyze and reason about the data. While thismaterial was taught in the context of a specific class, the lessons learnedwill be valuable to all.

Nygate, J. A., & Cliver, R. (2015, June), Improving Technical Writing Skills Through the Judicious Use of Infographics Paper presented at 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.24266

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