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…

The recent commentary by Beaujean and Farmer (2020) on the original paper by Dixon et al. (2019) serves a cautionary tale of selective p-values, the law of small N sizes, and the type-II error. We believe these authors have crafted a somewhat questionable argument in which only 57% of the original Dixon et al. data were re-analyzed, based on a…

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…

In this position paper, the authors lay out the imperative for equitable artificial intelligence (AI), highlighting the essential role of access-oriented institutions and calling on technology companies (both large and small), foundations, and local, state, and federal regulators to consult with the newly convened Complete College America Council…

This paper responds to some recent discussions in the Journal about how interview data can be used. While recognising the value of detailed analysis of the discourse employed in interviews to identify its formal features, it is argued that such analysis is not essential for all the purposes for which interview data can be employed in social…

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…

A gap exists between the ability to gauge the success of institutions by deploying a relatively simple set of measures typically based upon the federal cohort, versus the ability to monitor the successful (or unsuccessful) progression of the varied students who move through them. Daniel Regan questions which matters more. To gauge the health of an…

This is an editorial for a special issue "Innovations in Exploring Sequential Process Data" in the journal Zeitschrift für Psychologie. Process data refer to log files generated by human-computer interactive items. They document the entire process, including keystrokes, mouse clicks as well as the associated time stamps, performed by a…

Teaching students to reason with data is not a totally new enterprise. A small but insistent statistics education community has been studying the process for decades. This commentary provides an introduction to some major themes of that research, in order to provide common ground for conversations between learning sciences researchers and those…

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…

Virtual learning environments (VLEs) are increasingly used at-scale in educational contexts to facilitate teaching and promote learning, and the data they produce can be used for educational research purposes. Meanwhile, the U.S. Department of Education's Office of Educational Technology has repeatedly emphasized the importance of using evidence…

Virtual learning environments (VLE) are increasingly used at-scale in educational contexts to facilitate teaching and promote learning, and the data they produce can be used for educational research purposes. Meanwhile, the U.S. Department of Education's Office of Educational Technology has repeatedly emphasized the importance of using evidence to…

Meta-analysis and structural equation modeling (SEM) are 2 of the most prominent statistical techniques employed in the behavioral, medical, and social sciences. They each have their own well-established research communities, terminologies, statistical models, software packages, and journals ("Research Synthesis Methods" and…

The goal of this special issue is to examine the use of self-report measures in the study of motivation and strategy use. This commentary reviews the articles contained in this special issue to address the primary objective of determining if and when self-report measures contribute to understanding these major constructs involved in self-regulated…