The purpose of this monograph is to give readers a practical and theoretical foundation in learning analytics in higher education, including an understanding of the challenges and incentives that are present in the institution, in the individual, and in the technologies themselves. Among questions that are explored and answered are: (1) What are the current trends in higher education that are driving a need for learning analytics tools?; (2) What role do institutional context, technological capacity, and individual beliefs play in promoting or constraining adoption and integration of learning analytics technologies in higher education?; (3) What are the ethical considerations related to use of learning analytics or other predictive data and associated interventions?; and (4) What are the practical implications and future research recommendations associated with learning analytics? This monograph draws from several areas of research--organizational theory, technology adoption, faculty beliefs and behaviors, and ethics and privacy--in a comprehensive model of learning analytics in higher education. This monograph is intended to serve as an introduction to learning analytics for those practitioners and researchers who are interested in learning more about the development, implementation, and promise of harnessing educational big data with predictive methods. Contents of this monograph include: (1) Executive Summary; (2) Acknowledgements; (3) Foreword; (4) Introduction to Learning Analytics and Educational Technology Tools in Higher Education; (5) How Organizational Context and Capacity and Technological Alignment Affect Learning Analytics Adoption; (6) Faculty, Advisor, and Student Decision Making Related to Use of Learning Analytics Data and Tools; (7) Ethical and Privacy Concepts and Considerations; and (8) Recommendations for Moving Forward: Considerations of Organizational Complexity, Data Fidelity, and Future Research.