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Data Science for All: A University-Wide Course in Data Analytics

Incorporating data literacy into a curriculum is an opportunity for higher education to make an impact on students as they prepare to enter the workforce. This presentation describes the design and structure of “Data Science,” a new, unique undergraduate elective course in Temple University’s General Education curriculum.

In this 45-minute webinar, you’ll hear how the course:

  • Encourages students to adopt an “evidence-based” mindset
  • Gives students the skills to identify and use data relevant to their field of study and the world around them
  • Uses Tableau to introduce analytics and data literacy to a broad, non-technical audience
The webinar will highlight several aspects of Tableau that make it a useful tool for teaching undergraduate students the power of data. David Schuff will demonstrate several hands-on exercises used in the course using publicly available data to create visualizations, interactive dashboards, and simple analytics.

발표자 소개

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David Schuff

Professor of Management Information Systems, Fox School of Business, Temple University

David Schuff teaches courses in data analytics, information systems strategy, process design and improvement, and application development. He has led several analytics initiatives at Temple University, including the Temple Analytics Challenge, a University-wide data visualization contest that awards $10,000 in prizes annually, and the design and implementation of a University-wide General Education course in Data Science.

David received the MIS Department’s teaching award twelve times, most recently in 2015. He received Fox School of Business’ Musser Award for Excellence in Teaching (2014), Temple University’s Lindback Award for Distinguished Teaching (2013), and the Fox MBA Faculty of the Year award (2007). In 2015, David received the Teradata University Network (TUN) Teaching Innovation Award for his Data Science course.

He has published over 35 refereed journal articles, book chapters, and conference proceedings. His research interests include the application of information visualization to decision support systems, data warehousing, and the impact of user-generated content on organizations and society. David’s work has appeared in numerous academic journals, including Management Information Systems Quarterly, Decision Sciences, Decision Support Systems, Communications of the ACM, IEEE Computer, AIS Transactions on Human-Computer Interaction, and Information Systems Journal.

David holds a BA in Economics from the University of Pittsburgh, an MBA from Villanova University, an MS in Information Management from Arizona State University, and a Ph.D. in Business Administration from Arizona State University.

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