Indianapolis, Indiana, is one of the six sites selected to participate in the "New Skills ready network." This five-year initiative, launched by JPMorgan Chase & Co. in 2020, aims to improve student completion of high-quality career pathways. In the first year of the initiative, the Indianapolis, Indiana, "New Skills ready…

Data collected from across the child care and early education (CCEE) field, both during and prior to COVID-19, have been critical for identifying and scaling public resources to meet the increasing needs of children, families, early educators, and providers. Much of the data collected throughout the global health crisis demonstrated how the…

Since 2016, the Advanced Distributed Learning (ADL) Initiative has been developing the Total Learning Architecture (TLA), a 4-pillar data strategy for managing lifelong learning. Each pillar describes a type of learning-related data that needs to be captured, managed, and shared across an organization. Each data pillar is built on a set of…

In this commentary on Van Leeuwen (2015, this issue), I explore the relation between theory and practice in learning analytics. Specifically, I caution against adhering to one specific theoretical doctrine while ignoring others, suggest deeper applications of cognitive load theory to understanding teaching with analytics tools, and comment on…

The POGIL-PCL project implements the principles of process-oriented, guided-inquiry learning (POGIL) in order to improve student learning in the physical chemistry laboratory (PCL) course. The inquiry-based physical chemistry experiments being developed emphasize modeling of chemical phenomena. In each experiment, students work through at least…

The role and impact of diversity in higher education has permeated conversations about student access and achievement for many years. Language articulated by various courts suggests that higher education policies should reflect a broad conceptualisation of diversity beyond that of the magnitude and proportion of race and ethnicity, yet…

Schools have long collected information about students, from basic emergency contact details to daily attendance statistics. But only recently have schools used education technology to collect solid, reliable information (or data) about how students learn--as well as details about their strengths, challenges, and individual traits that impact…

In this paper, I describe preliminary work on a new research project in learning analytics at Arizona State University. In conjunction with an innovative remedial mathematics course using Khan Academy and student coaches, this study seeks to measure the effectiveness of visualized data in assisting student coaches as they help remedial math…

Academic analytics and learning analytics have been increasingly adopted by academic institutions of higher learning for improving student performance and retention. While several studies have reported the implementation details and the successes of specific analytics initiatives, relatively fewer studies exist in literature that describe the…

The paper gives a brief overview of the main activities for the development of the emerging field of learning analytics led by the Society for Learning Analytics Research (SoLAR). The place of the "Journal of Learning Analytics" is identified. Analytics is the most significant new initiative of SoLAR.

Students recognise and analyse data and draw inferences. They represent, summarise and interpret data and undertake purposeful investigations involving the collection and interpretation of data… They develop an increasingly sophisticated ability to critically evaluate chance and data concepts and make reasoned judgments and decisions, as well as…

Purpose: This study examines conceptions of instructional leadership in the institutional environment. We know that principals' practices affect student learning and that principals are influenced by ideas in the broader environment. This article examines and defines the multiple conceptions of what it means for principals to be instructional…

The primary objective of this study was to examine the effect of missing data on goodness of fit statistics in confirmatory factor analysis (CFA). For this aim, four missing data handling methods; listwise deletion, full information maximum likelihood, regression imputation and expectation maximization (EM) imputation were examined in terms of…

This paper discusses the fundamental question of how data-intensive e-research methods could contribute to the development of learning theories. Using methodological developments in research on self-regulated learning as an example, it argues that current applications of data-driven analytical techniques, such as educational data mining and its…

Despite our best efforts as evaluators, program implementation failures abound. A wide variety of valuable methodologies have been adopted to explain and evaluate the "why" of these failures. Yet, typically these methodologies have been employed concurrently (e.g., project monitoring) or to the post-hoc assessment of program activities.…