Introduction In the section “Data Analytics in Education,” we begin with some examples of how analytics is being used in education to support learners. Just as telescopes and microscopes extend our vision of the natural world, new analytic instruments can reveal learning patterns and trajectories not ordinarily visible to the casual observer or even to the expert practitioner. Understanding these hidden patterns is a prelude to developing new models to support learners, and it includes the ability to detect and correct systematic distortions and inequities that affect at-risk students but also impede the progress of advanced students. In “Grand Challenges in Education” we describe three interrelated grand challenges in higher education: college readiness, college success, and career readiness. A great deal has been written about the challenges students face while they are in college, but a more holistic view of student success requires that we examine the complete college pipeline as a continuous experience, beginning before students enter college, continuing while they are in college, and positioning them to succeed with careers upon graduation. At the beginning of the college pipeline, millions of students enroll each year in open-access colleges and universities, underprepared for college level work and therefore they require some form of remediation. Despite investments of tens of billions of dollars, the problem of developmental education at scale in higher education remains unsolved. In college, students face numerous challenges as they try to navigate their way through a variety of obstacles on their way to graduation. At the end of the college pipeline, the vast majority of students who earn either a degree or a credential at open-access institutions enter the workforce underprepared and therefore are unable to occupy middle-skill or high-skill jobs. In “Mastery Learning” we narrow our focus to instruction and describe novel uses of data in the “learning moment.” Mastery learning is a specific pedagogical theory formulated by the educational psychologist Benjamin S. Bloom. Mastery learning has a rich history, going back to the pioneering work of Carleton Washburne (1922) and his Winnetka Plan, Henry C. Morrison (1926) and his University of Chicago Laboratory School experiments, and John Carroll (1963) and his Model of School Learning. We argue that Bloom’s theory of mastery learning offers the richest theoretical and empirical framework for improving learning outcomes.
