TUM Library

"An Auerbach book."

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

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.

Includes index.

OCLC-licensed vendor bibliographic record.