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…

How researchers use statistical analyses shapes their research toward or away from an anti-racist agenda. In this article, we demonstrate how developmental scientists can use the QuantCrit framework to critically examine the process of conducting quantitative analyses. In particular, we focus on mixture modeling to clearly demonstrate how the…

Making sense of data is fundamental to science. Yet, the form in which data are represented can make their interpretation challenging for students. We introduce an activity that transformed a data table into an embodied artifact. The activity helped 8th grade students interpret the data to find that cold water warmed "fast-then-slow," in…

Student wellbeing has been foregrounded during the recent Covid-19 pandemic but this is broad brush and contested with different models being followed across the sector. One aspect of concern is the extent to which access to the technology institutions require students to use contributes to additional stress. A student survey (n=30) in one UK HEI…

As many studies focus on improving scientific literacy skills in students, there are still many gaps, thus an appropriate learning innovations are needed to get maximum results. This study aimed to evaluate the implementation of project-based blended learning in enhancing students' scientific literacy skills at the university. The experimental…

How do people reason with data to make sense of the world? What implications might everyday practices hold for data literacy education? We leverage the unique context of the COVID-19 pandemic to shed light on these questions. COVID-19 has engendered a complex, multimodal ecology of information resources, with which people engage in high-stakes…

Although an increasing number of ethical data science and AI courses is available, with many focusing specifically on technology and computer ethics, pedagogical approaches employed in these courses rely exclusively on texts rather than on algorithmic development or data analysis. In this paper we recount a recent experience in developing and…

In this teaching case, we describe an experiential learning project that allows students to perform sentiment analysis on a set of tweets (posts made on the social media platform, Twitter) by collecting and analyzing posts that include key words selected by the students. Sentiment analysis refers to the process of identifying and categorizing…

College-educated white women across social classes support and uphold racism. Using narrative methods in a secondary analysis, we, as two white women, explored how white non-trans women make meaning of social class using the revised model of multiple dimensions of identity (RMMDI; Abes et al., 2007) as positioned within the context of white…

Background: The current study aimed to validate the utility of previously established validity indicators derived from MOXO-d-CPT's continuous performance test. Method: Healthy simulators feigned impairment after searching online for relevant information, an ecologically valid coaching condition (n = 39). They were compared to ADHD patients (n =…

My dissertation comprises three studies designed to explore nuances of data use in education that presently confound the relationship between variation in teachers' practice of data use and student outcomes: (1) the relationships between different data sources within and across instructional practices; (2) the dimensionality of teachers' practice…

Students' emotions in the classroom are highly dynamic and thus typically strongly vary from one moment to the next. Methodologies like experience sampling and daily diaries have been increasingly used to capture these momentary emotional states and its fluctuations. A recurring question is to what extent aggregated state ratings of emotions over…

Data collected in many biology laboratory classes are on ratio or interval scales where the size interval between adjacent units on the scale is constant, which is a critical requirement for analysis with parametric statistics such as t-tests or analysis of variance. In other cases, such as ratings of disease or behavior, data are collected on…

Background: New technology and increased collaboration have revolutionized how scientists work with data. This creates a need to identify new aspects of working with scientific data that are important for K-12 students to learn. Purpose: To address this need, we conducted a study with practicing scientists and K-12 science teachers. The purpose of…

Is public engagement with science deliberative and evidence-based? The public is often perceived as underprepared to use data and susceptible to partisan and emotional manipulation. Consequently, educational efforts focus on the ability to identify reliable information. We posit that effective engagement with science goes beyond this and hinges on…