BASIE is a framework for interpreting impact estimates from evaluations. It is an alternative to null hypothesis significance testing. This guide walks researchers through the key steps of applying BASIE, including selecting prior evidence, reporting impact estimates, interpreting impact estimates, and conducting sensitivity analyses. The guide…

Computing education has growing inclusion and equity challenges (e.g. exclusionary online learning experiences, biased assessments, inadequate student feedback mechanisms). Many groups experience minoritization in computing education, including students who are Black, Indigenous, and people of color (BIPOC), women, non-binary students, transfer…

Clustering, a prevalent class of machine learning (ML) algorithms used in data mining and pattern-finding--has increasingly helped engineering education researchers and educators see and understand assessment patterns at scale. However, a challenge remains to make ML-enabled educational inferences that are useful and reliable for research or…

This article discusses how each of the papers in this special issue explored some combination of subject, audience, and data scientist perspectives with an eye toward helping students situate their relationship to data. Specifically, within the data scientist perspective, the papers examined a variety of ways in which students can relate to data…

Most White people have learned to ignore the way that the social construct of race benefits them or harms people of Color, myself included. In this way, people take for granted that race is not real, but rather the invention of White supremacists. Moreover, researchers who are responsible for generating knowledge far too often depend on…

Assessing scientific argumentation is one of main challenges in science education. Constructed-response (CR) items can be used to measure the coherence of student ideas and inform science instruction on argumentation. Published research on automated scoring of CR items has been conducted mostly in English writing, rarely in other languages. The…

A shifting policy landscape in Australian teacher education has led to the introduction of teaching performance assessment tasks in initial teacher education degrees, foregrounding data literacy practices. The aim of this research was to explore pre-service teachers' uses of data to inform and evaluate their teaching practice as demonstrated in…

Nowadays, the assessment of student performance has become increasingly technology-based, a trend that can also be observed in the evaluation of scientific reasoning, with more and more of the formerly paper-based assessment tools moving into the digital space. The study aimed to examine the reliability and validity of the paper-based and…

The global COVID-19 health pandemic caused major interruptions to educational assessment systems, partially due to shifts to remote learning environments, entering the post-COVID educational world into one that is more open to heterogeneity in instructional and assessment modes for secondary students. In addition, in 2020, educational inequities…

Despite the growing popularity of cyclic voltammetry, many students do not receive formalized training in this technique as part of their coursework. Confronted with self-instruction, students can be left wondering where to start. Here, a short introduction to cyclic voltammetry is provided to help the reader with data acquisition and…

The COVID-19 pandemic has necessitated the need to reliably detect the presence of viral genomes in human clinical samples. The most accurate viral tests involve the use of qPCR. Thus, it is important for students to understand the mechanism to detect viral genomes by qPCR including critical qPCR controls and how to properly interpret qPCR data.…

Meaning-making in teaching-learning mathematical processes is a relevant issue analysed through different philosophical and educational frames. In particular, the use of digital tools in mathematics education affects the meaning-making processes. This paper discusses meaning-making from a phenomenological standpoint, in which interpretative…

A data party is an engaging way to involve stakeholders in program evaluation. We explain the use of a data party for engaging 4-H program stakeholders (e.g., staff and volunteers) in data interpretation and helping them understand, embrace, and use program evaluation information to make data-driven decisions about their programs. We present two…

Systems thinking involves attempts to understand and improve complex systems, examines systems holistically, and focuses on the way that a system's constituent parts interrelate. This essay provides examples of how systems thinking can enable principals to demonstrate instructional leadership and nurture learning-focused schools in the current era…

In undergraduate research settings, students are likely to encounter anomalous data, that is, data that do not meet their expectations. Most of the research that directly or indirectly captures the role of anomalous data in research settings uses post-hoc reflective interviews or surveys. These data collection approaches focus on recall of past…