Evidence-based and student-centered instructional methods hold the promise of transforming undergraduate STEM education and simultaneously solving the dual challenge of STEM workforce needs and inequities within STEM. The Learning Assistant (LA) Model was created to reform curriculum, recruit teachers, and inform discipline-based education…

Data--their collection, analysis and use--have always been part of education, used to inform policy, strategy, operations, resource allocation, and, in the past, teaching and learning. Recently, with the emergence of learning analytics, the collection, measurement, analysis and use of student data have become an increasingly important research…

As the body of scientific evidence about effective policies and practices grows, so does the need to effectively communicate that evidence to policy-makers and practitioners. Clearinghouses have emerged to facilitate the evidence-based decision-making process for education practitioners. While the results and methods for developing and analyzing…

As the body of scientific evidence about effective policies and practices grows, so does the need to effectively communicate that evidence to policy-makers and practitioners. Clearinghouses have emerged to facilitate the evidence-based decision-making process for education practitioners. While the results and methods for developing and analyzing…

Implementing systematic diversity transformation requires embracing all aspects of diversity--gender, sexual orientation, disability, gender identification, and other salient characteristics of difference--as well as race and ethnicity. This book lays out a framework for systematic and sustained diversity process that first recognizes that too…

Education Leadership Data Analytics (ELDA) is an emerging domain that is centered at the intersection of education leadership, the use of evidence-based improvement cycles in schools to promote instructional improvement, and education data science. ELDA practitioners work collaboratively with school and district leaders and teachers to analyze,…

Large-scale, robust implementation of teacher data-driven decision making (DDDM) is a challenging endeavor, impeded by numerous organizational, and teacher, factors. One well-documented barrier to teacher DDDM is underdevelopment of teacher data literacy. This study examines common errors made by pre-service elementary teachers in the formulation…

This chapter provides an example of how one university's institutional research office played an active role in using data from institutional studies to guide the university toward courses ripe for change, faculty toward successful teaching strategies, students toward successful learning behaviors, and the university toward assessing the impact of…

Analysis of student-level data to inform policy and promote student success is a core function of executive higher education agencies. Postsecondary data systems have expanded their collection of data elements for use by policymakers, institutional staff and the general public. State coordinating and governing boards use these data systems for…

This chapter details the process the University of Michigan developed to build institutional capacity for learning analytics. A symposium series, faculty task force, fellows program, research grants, and other initiatives are discussed, with lessons learned for future efforts and how other institutions might adapt such efforts to spur cultural…

Responsible Operations is intended to help chart library community engagement with data science, machine learning, and artificial intelligence (AI) and was developed in partnership with an advisory group and a landscape group comprised of more than 70 librarians and professionals from universities, libraries, museums, archives, and other…

There is an urgent need to develop an evidence-based framework for learning analytics whereby stakeholders can manage, evaluate, and make decisions about which types of interventions work well and under which conditions. In this article, we will work towards developing a foundation of an Analytics4Action Evaluation Framework (A4AEF) that is…

This article outlines the design and development of a bespoke "Research Training Support Framework," targeting the professional development needs of higher degree research (HDR) supervisors and their students, which was achieved by implementing Patton's (2011; 2012) utilisation-focused evaluation methodology (UFE). The primary research…

The purpose of this research is to propose how we can encourage non-computing major first-generation-college-bound students to be actively involved in learning data analytics. Non-computing major students have limited opportunities to take a data analytics related course. The computing major programs have the resource limit for offering none-major…

The purpose of the study is the learning using research as a base. To strengthen the skills of classroom research Emphasizing Data Analysis and Result and to study the development of research skills in the class Emphasizing Data Analysis and Result of SSRU' Students by learning using research base. The target group are students in the 2nd semester…