Contents -- List of Illustrations -- Foreword: Building a Smarter University: Big Data, Innovation, and Ingenuity -- Note -- Reference -- Preface -- Acknowledgments -- Part I. Overview -- Chapter 1: Fostering Smarter Colleges and Universities: Data, Big Data, and Analytics -- Abstract -- Unpacking Big Data -- Data Analytics, Data Mining, and Machine Learning -- Big Data and Student Success -- Big Data and Research -- Big Data and Education: Creating Data Scientists -- Higher Education Systems: Taking Data Analytics to Scale -- The Cautionary Side -- The Way Forward -- Notes -- References -- Chapter 2: Legal Issues Associated with Big Data in Higher Education: Ethical Considerations and Cautionary Tales -- Abstract -- Privacy and Education Records -- Intellectual Property -- Security -- Recomendations -- Conclusion -- Notes -- References -- Chapter 3: Education and . . . Big Data versus Big-But-Buried Data -- Abstract -- Data , Information, and Knowledge -- Big Data Simpliciter (BD) Versusus Big-But -Buried Data (B3D) -- Two Anticipated Questions, Two Answers -- The Example of Calculus -- The Paradox of the Arrow -- The Future -- Next Steps -- Notes -- References -- Part II: Access, Completion, Success -- Chapter 4: Big Data's Impact on College Admission Practices and Recruitment Strategies -- Abstract -- Introduction -- Defining Big Data in the College Admissions and Enrollment Management Context: Extreme Information Management to Improve Student Access and Success -- Ethics and Standards are a First Priority of any Student Data Endeavor -- Strong Enrollment Management has Always Been Data Driven -- Sem: Recruitment and Retention are two Sides of the Same Coin -- Small Data Exposing Student Choice Factors: Curent Enrollment Trends Emerging from Deep Data Sharing and Analytics -- Curent Trends in Traditional Student Enrollments and College Choice.

Big Data's Potential to more Clearly Segment Student Populations and Identify Early Needs -- Big Data's Potential to Build Stronger Relationships and Improve Student-Institution Match -- Using Big Data to Discover "Why": An Eharmony Model to Improve Student Recruitment? -- Using Efm to Embrace Big Data in Admissions and Enrollment Management -- Efm Aproach to Improve Admissions and Enrollment Management Services? -- Getting Started: Preparing to Use Big Data in Admissions and Enrollment Management -- Conclusion -- References -- Chapter 5: Who is the Big Data Student? -- Abstract -- It's Big Data Time for Education -- Finding One Student Among Thousands: A Heideggerian Perspective -- Understanding the Student as Dasein -- Big Data in Education -- What is so Different About Big Data? -- Big Human Data -- Taking the Analysis of Big Data from the Ontic to the Ontological: Finding Dasein Among Das Man -- Big Data Implications for the Design of Education -- Conclusion: Giving Students the Posibility of an Authentic Course -- Notes -- References -- Chapter 6: Nudge Nation: A New Way to Use Data to Prod Students into and through College -- Abstract -- Cooling "Summer Melt" -- Choosing the Right Courses -- Getting the Academic Green Light -- Coping in Class and Life -- Counseling by Phone -- Building Policies for Success -- Notes -- References -- Chapter 7: Unanticipated Data-Driven Innovation in Higher Education Systems: From Student Success to Course Equivalencies -- Abstract -- Strategic Policies and Administrative Capacity: The Relationship Between Policy and Data -- Analytic Method and Data -- Degreeworks: From Student Success to Course Equivalencies -- Phase I: Student-Driven Strategy -- Phase II: Data-Driven Innovation -- Phase III: System Integration -- Discussion -- Conclusion.

Apendix 1: Glosary of Suny Strategic Policies and Administrative Capacities -- Strategic Policies (in chronological order) -- Administrative Capacities (in alphabetical order) -- Notes -- References -- Part III: Policy Development and Institutional Decision Making -- Chapter 8: Integrating Data Analytics in Higher Education Organizations: Improving Organizational and Student Success -- Abstract -- The Need for a Data-Driven Culture -- Data Analytics as an Organizational Innovation -- Adopting Data Analytics in Colleges and Universities -- Factors That Influence an Academic Leader's Choice of Adoption and Use of Data Analytics -- Organizational and Individual Use of Data Analytics -- A Model of Individual Adoption of Data Analytics -- Conclusion -- Notes -- References -- Chapter 9: The Opportunities, Challenges, and Strategies Associated with the Use of Operations-Oriented (Big) Data to Support Decision Making within Universities -- Abstract -- Introduction -- Operational Goals, Research Goals, and Institutional Data -- The Accuracy of Operations-Oriented Data -- Principles and Strategies for Examining Operations-Oriented Data -- Past Research into Instructional Productivity and Costs -- Discussion and Conclusion -- Notes -- References -- Chapter 10: Measuring the Internationalization of Higher Education: Data, Big Data, and Analytics -- Abstract -- Why Measure Internationalization? -- Measuring International Aspects of Higher Education: Sources and Methods -- Cautionary Considerations -- What Does the Future Hold? -- Notes -- References -- Chapter 11: Big Data and Human Capital Development and Mobility -- Abstract -- Demand for Linked Longitudinal Data -- Borders can Hinder Data Flow -- The Wiche Multistate Data Exchange Pilot -- Considerations in Making Apropriate and Effective Use of Linked Longitudinal Data -- Conclusion -- Notes -- References.

Contributors -- Index.