The "LFK" index has been promoted as an improved method to detect bias in meta-analysis. Putatively, its performance does not depend on the number of studies in the meta-analysis. We conducted a simulation study, comparing the "LFK" index test to three standard tests for funnel plot asymmetry in settings with smaller or larger…

Past research has demonstrated that children prefer to learn from confident rather than hesitant informants. It is frequently assumed that they do so because they believe confidence to predict a person's knowledge and future accuracy; however, this assumption has not previously been tested. The present investigation therefore explored how 3- to…

As computer-based testing becomes more prevalent, the attention paid to response time (RT) in assessment practice and psychometric research correspondingly increases. This study explores the rate of Type I error in detecting preknowledge cheating behaviors, the power of the Kullback-Leibler (KL) divergence measure, and the L person fit statistic…

This study introduces an approach to estimate the uncertainty in bibliometric indicator values that is caused by data errors. This approach utilizes Bayesian regression models, estimated from empirical data samples, which are used to predict error-free data. Through direct Monte Carlo simulation--drawing many replicates of predicted data from the…

Datasets are critical for emotion analysis in the machine learning field. This study aims to explore emotion analysis datasets and related benchmarks in online learning, since, currently, there are very few studies that explore the same. We have scientifically labeled the topic and nine-category emotion of 4715 comment texts in online learning…

Difficulties in academic achievement have been linked to adverse outcomes such as increased problem behavior and delays in development (Hinshaw, 1992). Early education should include training to self-monitor, as self-monitoring can improve academic performance and has a wide range of uses (Harris et al., 2005). Previous literature typically uses…

In classroom assessments, examinees can often answer test items multiple times, resulting in sequential multiple-attempt data. Sequential diagnostic classification models (DCMs) have been developed for such data. As student learning processes may be aligned with a hierarchy of measured traits, this study aimed to develop a sequential hierarchical…

In classroom assessments, examinees can often answer test items multiple times, resulting in sequential multiple-attempt data. Sequential diagnostic classification models (DCMs) have been developed for such data. As student learning processes may be aligned with a hierarchy of measured traits, this study aimed to develop a sequential hierarchical…

The response time concealed information test (RT-CIT) can reveal that a person recognizes a relevant item (probe) among other, irrelevant items, based on slower responding to the probe compared to the irrelevant items. Thereby, if this person is concealing knowledge about the relevance of this item (e.g., recognizing it as a murder weapon), this…

We evaluated the detailed, behavioral properties of face matching performance in two specialist groups: forensic facial examiners and super-recognizers. Both groups compare faces to determine identity with high accuracy and outperform the general population. Typically, facial examiners are highly trained; super-recognizers rely on natural ability.…

Small sample sizes pose a severe threat to convergence and accuracy of between-group level parameter estimates in multilevel structural equation modeling (SEM). However, in certain situations, such as pilot studies or when populations are inherently small, increasing samples sizes is not feasible. As a remedy, we propose a two-stage regularized…

Predicting student performance has been a critical focus of educational research. With an effective predictive model, schools can identify potentially at-risk students and implement timely interventions to support student success. Recent developments in educational data mining (EDM) have introduced several machine learning techniques that can…

Child protection social workers in England are required to make many decisions in their day-to-day work, including whether to accept a referral, undertake a child protection investigation, pursue care proceedings, or close the case. Many of these decisions involve implicit or explicit predictions about the likelihood of future actions, events, and…

Purpose: The goal of the current study was to conduct a substantive validity review of four autism knowledge assessments with prior psychometric support (Gillespie-Lynch in J Autism and Dev Disord 45(8):2553-2566, 2015; Harrison in J Autism and Dev Disord 47(10):3281-3295, 2017; McClain in J Autism and Dev Disord 50(3):998-1006, 2020; McMahon…

Metacognitive reasoning is central to decision-making. For every decision, we can also judge our trust in that decision, or our level of "confidence." The mechanisms and representations underlying reasoning about confidence remain debated. We test whether children rely on "processing fluency" to infer their own confidence: do…