Jaime Lester is Associate Professor of Higher Education at George Mason University, USA.Carrie Klein is a PhD Candidate and Research and Teaching Assistant in the Higher Education Program at George Mason University, USA.Aditya Johri is Associate Professor of Information Sciences and Technology at George Mason University, USA.Huzefa Rangwala is Associate Professor of Computer Science at George Mason. University, USA.

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• ContentsList of TablesList of FiguresPrefaceAcknowledgmentsChapter 1: Absorptive capacity and routines: Understanding barriers to learning analytics adoption in higher educationAditya JohriChapter 2. Analytics in the field: Why locally grown continuous improvement systems are essential for effective data driven decision-makingMatthew T. HoraChapter 3: Big data, small data, and data shepherdsJennifer DeBoer and Lori BreslowChapter 4: Evaluating scholarly teaching: A model and call for an evidence-based approachDaniel L. Reinholz, Joel C. Corbo, Daniel J. Bernstein, and Noah D. FinkelsteinChapter 5: Discipline-focused learning analytics approaches with users instead of for usersDavid B. Knight, Cory Brozina, Timothy J. Kinoshita, Brian J. Novoselich, Glenda D. Young, and Jacob R. GrohsChapter 6: Student consent in learning analytics: The devil in the details?Paul Prinsloo and Sharon SladeChapter 7: Using learning analytics to improve student learning outcomes assessment in higher education: Potential, constraint, & possibilityCarrie Klein, and Richard M. HessChapter 8: Data, data everywhere: Implications and considerationsMatthew D. PistilliContributor Bios

Jaime Lester is Associate Professor of Higher Education at George Mason University, USA.Carrie Klein is a PhD Candidate and Research and Teaching Assistant in the Higher Education Program at George Mason University, USA.Aditya Johri is Associate Professor of Information Sciences and Technology at George Mason University, USA.Huzefa Rangwala is Associate Professor of Computer Science at George Mason. University, USA.

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• ContentsList of TablesList of FiguresPrefaceAcknowledgmentsChapter 1: Absorptive capacity and routines: Understanding barriers to learning analytics adoption in higher educationAditya JohriChapter 2. Analytics in the field: Why locally grown continuous improvement systems are essential for effective data driven decision-makingMatthew T. HoraChapter 3: Big data, small data, and data shepherdsJennifer DeBoer and Lori BreslowChapter 4: Evaluating scholarly teaching: A model and call for an evidence-based approachDaniel L. Reinholz, Joel C. Corbo, Daniel J. Bernstein, and Noah D. FinkelsteinChapter 5: Discipline-focused learning analytics approaches with users instead of for usersDavid B. Knight, Cory Brozina, Timothy J. Kinoshita, Brian J. Novoselich, Glenda D. Young, and Jacob R. GrohsChapter 6: Student consent in learning analytics: The devil in the details?Paul Prinsloo and Sharon SladeChapter 7: Using learning analytics to improve student learning outcomes assessment in higher education: Potential, constraint, & possibilityCarrie Klein, and Richard M. HessChapter 8: Data, data everywhere: Implications and considerationsMatthew D. PistilliContributor Bios

Jaime Lester is Associate Professor of Higher Education at George Mason University, USA.Carrie Klein is a PhD Candidate and Research and Teaching Assistant in the Higher Education Program at George Mason University, USA.Aditya Johri is Associate Professor of Information Sciences and Technology at George Mason University, USA.Huzefa Rangwala is Associate Professor of Computer Science at George Mason. University, USA.

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• ContentsList of TablesList of FiguresPrefaceAcknowledgmentsChapter 1: Absorptive capacity and routines: Understanding barriers to learning analytics adoption in higher educationAditya JohriChapter 2. Analytics in the field: Why locally grown continuous improvement systems are essential for effective data driven decision-makingMatthew T. HoraChapter 3: Big data, small data, and data shepherdsJennifer DeBoer and Lori BreslowChapter 4: Evaluating scholarly teaching: A model and call for an evidence-based approachDaniel L. Reinholz, Joel C. Corbo, Daniel J. Bernstein, and Noah D. FinkelsteinChapter 5: Discipline-focused learning analytics approaches with users instead of for usersDavid B. Knight, Cory Brozina, Timothy J. Kinoshita, Brian J. Novoselich, Glenda D. Young, and Jacob R. GrohsChapter 6: Student consent in learning analytics: The devil in the details?Paul Prinsloo and Sharon SladeChapter 7: Using learning analytics to improve student learning outcomes assessment in higher education: Potential, constraint, & possibilityCarrie Klein, and Richard M. HessChapter 8: Data, data everywhere: Implications and considerationsMatthew D. PistilliContributor Bios