The evaluation of hypotheses, and the ability to learn from critical reflection on experimental and theoretical tests of those hypotheses, is central to an authentic practice of physics. A large part of physics education therefore seeks to help students understand the significance of this kind of reflective practice and to develop the strategies…

Skill prerequisite information is useful for tutoring systems that assess student knowledge or that provide remediation. These systems often encode prerequisites as graphs designed by subject matter experts in a costly and time-consuming process. In this paper, we introduce "Combined student Modeling and prerequisite Discovery"…

This teaching note gives a real-life example of Bayesian thinking. It discusses how credible accusations are that the outcome of the draw for the quarter-finals in the 2013 European Champions League Football was manipulated.

Promoting self-determination is essential to effective transition services and supports. The Goal Setting Challenge App (GSC App) was developed to deliver self-determination instruction via technology, building on the evidence-based Self-Determined Learning Model of Instruction (SDLMI). This paper presents data on goal attainment outcomes for…

In this research, we aimed to investigate the visual-cognitive behaviours of a sample of 106 children in Year 3 (8.8 ± 0.3 years) while completing a mathematics bar-graph task. Eye movements were recorded while children completed the task and the patterns of eye movements were explored using machine learning approaches. Two different techniques of…

An innovative mixed-methods approach to exploratory focus group design is presented using a case study conducted with smallholder rice farmers in Vietnam. Understanding human decision-making under the uncertainties of a complex and changing social and environmental context requires a flexible yet structured and theoretically grounded approach.…

The appendices accompany the full report "Using Bayesian Meta-Analysis to Explore the Components of Early Literacy Interventions. WWC 2023-008," (ED630495), which pilots a new taxonomy developed by early literacy experts and intervention developers as part of a larger effort to develop standard nomenclature for the components of literacy…

Purpose: This study reexamines the claim that difficulty forming memories of words comprising uncommon sound sequences (i.e., low phonological neighborhood density words) is a determinant of delayed expressive vocabulary development (e.g., Stokes, 2014). Method: We modeled communicative development inventory data from (N = 442) 18-month-old…

How do we teach and learn with our students about data literacy, at the same time as Biesta (2015) calls for an emphasis on 'subjectification' i.e. 'the coming into presence of unique individual beings'? (Good Education in an Age of Measurement: Ethics, Politics, Democracy. Routledge) Our response to these challenges and the datafication of higher…

Network meta-analysis (NMA) combines direct and indirect evidence from trials to calculate and rank treatment estimates. While modelling approaches for continuous and binary outcomes are relatively well developed, less work has been done with time-to-event outcomes. Such outcomes are usually analysed using Cox proportional hazard (PH) models.…

Humans' face ability develops and matures with extensive experience in perceiving, recognizing, and interacting with faces that move most of the time. However, how facial movements affect 1 core aspect of face ability--holistic face processing--remains unclear. Here we investigated the influence of rigid facial motion on holistic and part-based…

In this paper, we investigate two purported problems with Bayesian Knowledge Tracing (BKT), a popular statistical model of student learning: "identifiability" and "semantic model degeneracy." In 2007, Beck and Chang stated that BKT is susceptible to an "identifiability problem"--various models with different…

BKT and other classical student models are designed for binary environments where actions are either correct or incorrect. These models face limitations in open-ended and data-driven environments where actions may be correct but non-ideal or where there may even be degrees of error. In this paper we present BKT-SR and RKT-SR: extensions of the…

In Bayesian structural equation modeling (BSEM), prior settings may affect model fit, parameter estimation, and model comparison. This simulation study was to investigate how the priors impact evaluation of relative fit across competing models. The design factors for data generation included sample sizes, factor structures, data distributions, and…

This article proposes a flexible extension of the Fay--Herriot model for making inferences from coarsened, group-level achievement data, for example, school-level data consisting of numbers of students falling into various ordinal performance categories. The model builds on the heteroskedastic ordered probit (HETOP) framework advocated by Reardon,…