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Teaching Data Analytics
Pedagogy and Program Design



ISBN 9781138744141
Published June 28, 2019 by Auerbach Publications
202 Pages 40 B/W Illustrations

 
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Book Description

The need for analytics skills is a source of the burgeoning growth in the number of analytics and decision science programs in higher education developed to feed the need for capable employees in this area. The very size and continuing growth of this need means that there is still space for new program development. Schools wishing to pursue business analytics programs intentionally assess the maturity level of their programs and take steps to close the gap.

Teaching Data Analytics: Pedagogy and Program Design is a reference for faculty and administrators seeking direction about adding or enhancing analytics offerings at their institutions. It provides guidance by examining best practices from the perspectives of faculty and practitioners. By emphasizing the connection of data analytics to organizational success, it reviews the position of analytics and decision science programs in higher education, and to review the critical connection between this area of study and career opportunities. The book features:

  • A variety of perspectives ranging from the scholarly theoretical to the practitioner applied
  • An in-depth look into a wide breadth of skills from closely technology-focused to robustly soft human connection skills
  • Resources for existing faculty to acquire and maintain additional analytics-relevant skills that can enrich their current course offerings.

Acknowledging the dichotomy between data analytics and data science, this book emphasizes data analytics rather than data science, although the book does touch upon the data science realm. Starting with industry perspectives, the book covers the applied world of data analytics, covering necessary skills and applications, as well as developing compelling visualizations. It then dives into pedagogical and program design approaches in data analytics education and concludes with ideas for program design tactics. This reference is a launching point for discussions about how to connect industry’s need for skilled data analysts to higher education’s need to design a rigorous curriculum that promotes student critical thinking, communication, and ethical skills. It also provides insight into adding new elements to existing data analytics courses and for taking the next step in adding data analytics offerings, whether it be incorporating additional analytics assignments into existing courses, offering one course designed for undergraduates, or an integrated program designed for graduate students.

Table of Contents

Preface: Teaching Data Analytics—A Primer for Higher Education

Acknowledgments

Editors

Contributors

Section I Industry Perspective

Chapter 1 It’s Not All About the Math

DOUG COGSWELL, ERIC CHO, AND MATEO MOLINA CORDERO

Chapter 2 A Two-Day Course Outline for Teaching Analytics to Fundraising Professionals: Lessons for Academia

MARIANNE M. PELLETIER

Chapter 3 Developing Professional Skills in a Data Analytics Classroom

KATHRYN S. BERKOW

Section II Curricular and Cocurricular

Assignment Design

Chapter 4 Formative and Summative Assessments in Teaching Association Rules

MATT NORTH

Chapter 5 The Necessity of Teaching Computer Simulation within Data Analytics Programs

VIRGINIA M. MIORI

Chapter 6 Using Games to Create a Common Experience for Students

STEPHEN PENN

Chapter 7 Student Competitions: Extending Student Experience Outside of the Classroom

YELENA BYTENSKAYA, KATHERINE LEAMING GOLDBERG, AND ELENA GORTCHEVA

Section III Program Design Tactics

Chapter 8 Competencies for the Design, Implementation, and Adoption of the Analytics Process

EDUARDO RODRIGUEZ, JOHN S. EDWARDS, AND GERMÁN A. RAMÍREZ

Chapter 9 Business Analytics: A Course Design

KATHERINE LEAMING GOLDBERG

Chapter 10 Building a Ranked Data Analytics Program

VIRGINIA M. MIORI, NICOLLE T. CLEMENTS, AND KATHLEEN CAMPBELL-GARWOOD

Index

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Author(s)

Biography

Dr. Susan A. Vowels is the Constance F. and Carl W. Ferris associate professor and Chair of the Department of Business Management at Washington College. In 2002, she launched the business program’s management information systems curriculum, subsequently developing courses in management information systems, enterprise resource planning systems, business intelligence, and business analytics. She is a cofounder and codirector of the College’s Information Systems Minor and provided the impetus for Washington College to join the SAP University Alliance, serving as faculty coordinator since 2003. Most recently, along with Dr. Austin Lobo, she co-founded the Data Analytics Minor at Washington College and will serve as program director beginning Fall 2019. Her broad research interests have included attention to how technology can serve strategic corporate goals, methods for infusing ethics into management information systems pedagogy, and how the examination of end user well-being can help us better understand ethical considerations in information systems implementations. Her broad research interests are informed by a liberal arts degree from St. John’s College in Annapolis, Maryland; an MBA with a specialization in international business from the University of Delaware; and a DBA from Wilmington University as well as a successful career in industry. Her service in industry included stints as a systems engineer with IBM; as a programmer for firms supporting the advertising and travel industries; and as a consultant supporting an SAP implementation, along with a successful career with a wholesale millwork firm, moving from functional responsibility for information systems to serving as vice president and a member of the board of directors. She sees data analytics as a unifier of disparate information and an essential tool for organizational decision-making.

Katherine Leaming Goldberg serves two roles at Washington College in Chestertown, Maryland. She is the Lecturer of Business Analytics in the Department of Business Management at Washington College. She is also the Director of Advancement Services, helping the college fundraise by applying data analytic approaches. Her research interests include methods of using predictive text and cluster analytics to increase fundraising at nonprofit organizations. Her love for data started with her undergraduate degree when she designed her own major in Mathematical Biology at Randolph- Macon Woman’s College in Lynchburg, Virginia. She holds a certificate in Fundraising Operations from the Susan B. Glasscock School of Continuing Studies at Rice University. She completed her Masters of Data Analytics from University of Maryland University College (UMUC) and was inducted as a member of Phi Kappa Phi. She is an instructor in the Fundraising Operations program at Rice University, where she recently created an on-demand course to teach nonprofit professionals about gift processing. She is also a Teaching Assistant in the Masters of Data Analytics program at UMUC.