This special issue's editors invited discussion of three broad questions. Slightly rephrased, they are: How well do self-report data represent theoretical constructs? How should analyses of data be conditioned by properties of self report data? In what ways do interpretations of self-report data shape interpretations of a study's findings? To…

This article conceptualizes the notion of magic(al)ing in relation to post-pandemic ways of thinking about data production and analyses. Revisiting old data produced pre-COVID-19 and engaging with new data produced during COVID-19, we consider the possibilities and potential of magic(al)ing as a theoretical concept. We think with several ideas…

The objective of this paper is to comment on the think-aloud methods presented in the three papers included in this special issue. The commentary offered stems from the author's own psychological investigations of unobservable information processes and the conditions under which the most defensible claims can be advanced. The structure of this…

When writing about transformation in higher education (HE) in South Africa, it is quite popular to mention the fall of apartheid, and perhaps also 1994, as a starting point for significant change. I, myself, have made this mistake (see Bernard, 2015). However, the recent #FeesMustFall protests highlighted that many approaches to transformation…

Commonly used machine learning applications seem to relate to big data. This article provides a gentle review of machine learning and shows why machine learning can be applied to small data too. An example of applying machine learning to screen irregularity reports is presented. In the example, the support vector machine and multinomial naïve…

James J. Cochran is Professor of Applied Statistics, Rogers-Spivey Faculty Fellow, and Associate Dean for Research in the Culverhouse College of Commerce at the University of Alabama. He is a Fellow of the American Statistical Association and of Institute for Operations Research and Management Sciences. He is also a recipient of the INFORMS Prize…

The development of a student's ability to make data-driven decisions has become a focus in higher education (Schield 1999; Stephenson and Caravello 2007). Data literacy, the ability to understand and use data to effectively inform decisions, is a fundamental component of information competence (Mandinach and Gummer 2013; Stephenson and Caravello,…

In this policy forum commentary, we call for improved national and state-level data collection and access relevant to the principal pipeline. We focus specifically on how access to quality data can inform, has informed, and is critical to policy and practice across three segments of the principal pipeline--principal preparation, licensure, and…

Brian Kotz is Professor of Mathematics and Statistics at Montgomery College. He is a former member of the American Statistical Association/American Mathematical Association of Two-Year Colleges (ASA)/(AMATYC) Joint Committee and the current chair of the AMATYC Data Science Subcommittee. This interview took place via email on November 23,…

This commentary elaborates on the role of "grounding" as a focal theoretical concept and aims to contextualize the claims formulated by Schneider and Pea (2015, this issue) in previous CSCL discussions. It provides fingerposts for enriching and refining the concept of grounding from a pedagogical point of view. It also suggests using the…

This article reflects on the tensions I encountered as an insider researcher during a qualitative study exploring academics' integration of educational technology in a South African higher education institution. While critical qualitative approaches acknowledge research participants' vulnerability to the researcher's interpretation and…

In 1995, the National Council of Teachers of English (NCTE) issued the Resolution on Electronic Online Services in support of making online resources available to students. In 1998, NCTE issued the Resolution on Testing and Equitable Treatment of Students in support of students' well-being in assessment development and administration. In light of…

The article, "Distributed Revisiting: An Analytic for Retention of Coherent Science Learning" is an interesting study that operates at the intersection of learning theory and learning analytics. The authors observe that the relationship between learning theory and research in the learning analytics field is constrained by several…

Despite abundant data and increasing data availability brought by technological advances, there has been very limited education policy studies that have capitalized on big data--characterized by large volume, wide variety, and high velocity. Drawing on the recent progress of using big data in public policy and computational social science…

Chronic absenteeism, commonly defined as missing 10% or more of school days for any reason (excused or unexcused), detracts from learning and is a proven early warning sign of academic risk and school dropout. It is the position of the National Association of School Nurses (NASN) that the registered professional school nurse is an integral member…