Most existing solutions to the current replication crisis in science address only the factors stemming from specific poor research practices. We introduce a novel mechanism that leverages the experts' predictive abilities to analyze the root causes of replication failures. It is backed by the principle that the most accurate predictor is the most…

We propose new ways of robustifying goodness-of-fit tests for structural equation modeling under non-normality. These test statistics have limit distributions characterized by eigenvalues whose estimates are highly unstable and biased in known directions. To take this into account, we design model-based trend predictions to approximate the…

In recent years, knowledge tracing (KT) within intelligent tutoring systems (ITSs) has seen rapid development. KT aims to assess a student's knowledge state based on past performance and predict the correctness of the next question. Traditional KT often treats questions with different difficulty levels of the same concept as identical…

Education is inherently entangled with the future. This argumentative review examines this entanglement and proposes a framework differentiating between four educational orientations towards the future. The orientation 'Futures of education' examines how education changes in the future: From rhetorical to visionary, these futures are concerned…

This study examines the relationship between L2 vocabulary knowledge, self-rating of word knowledge, self-perceptions of four language skills (listening, reading, speaking, and writing), and students' academic achievement. An objective measure of lexical knowledge and questionnaire on self-perception and self-rating of vocabulary knowledge were…

This paper aims to showcase the value of implementing a Bayesian framework to analyze and report results from international large-scale assessments and provide guidance to users who want to analyse ILSA data using this approach. The motivation for this paper stems from the recognition that Bayesian statistical inference is fast becoming a popular…

Recent decades have seen a global shift in educational policy and practice towards various forms of "joining-up," through partnerships and networks. These networks have differing aims but are broadly geared towards increasing quality and/or innovation in educational provision, although many prove messy and problematic. Policy makers in…

In the present study, we examined how the perceived attainability and relatability of moral exemplars predicted moral elevation and pleasantness among both adult and college student participants. Data collected from two experiments were analyzed with Bayesian multilevel modeling to explore which factors significantly predicted outcome variables at…

Metacognition is important for successful goal-directed behavior. It consists of two main elements: metacognitive knowledge and online awareness. Online awareness consists of monitoring and self-regulation. Metacognitive sensitivity is the extent to which someone can accurately distinguish their own correct from incorrect responses and is an…

The latest technologies in natural language processing provide creative, knowledge retrieval, and question-answering technologies in the design of intelligent education, which can provide learners with personalized feedback and expert guidance. Entrepreneurship education aims to cultivate and develop the innovative thinking and entrepreneurial…

Algorithms may be better at prediction than humans in a variety of contexts, but they are not perfect. A deeper understanding of the ways in which educators use and question algorithmic advice within their professional domain is needed. Educators are a particularly unique professional group, in comparison with the other groups studied in the…

Maternal sensitivity during an observed mother-child clean-up task at 18 months and maternal sensitivity during an observed mother-child free-play task at 18 months were tested as independent predictors of child internalizing symptoms, externalizing symptoms, social competence, and language development at 24 months. Participants (n = 292 mothers)…

This study aimed to develop and validate machine learning models to predict intensities in children and adolescents with cystic fibrosis (CF) across different accelerometry brands and placements. Thirty-five children and adolescents with CF (11.6 ± 2.8 yrs; 15 girls) and 28 healthy youth (12.2 ± 2.7 yrs; 16 girls) performed six activities whilst…

Foundations of statistics research aims to establish fundamental principles guiding inference about populations under uncertainty. It is concerned with the process of learning from observations, notions of uncertainty and induction, and satisfying inferential objectives. The growing interest in predictive methods in high-stakes fields like…

Misinformation can profoundly impact an individual's attitudes--sometimes even after the misinformation has been corrected. In two preregistered experiments (N[subscript 1] = 355, N[subscript 2] = 725), we investigated whether individual differences in the ability and motivation to process information thoroughly influence the impact of…