Although extensive research has focused on the perceptual abilities of second language (L2) learners, a significant gap persists in understanding how cognitive functions like phonological short-term memory (PSTM) and nonverbal intelligence (IQ) impact L2 speech perception. This study sets out to investigate the discrimination of L2 English…

The Every Student Succeeds Act of 2015 requires states to use a variety of indicators, including standardized tests and attendance records, to designate schools for support and improvement based on schoolwide performance and the performance of groups of students within schools. Schoolwide and group-level performance indicators are also…

This study explored the use of stealth assessments within a digital game to assess second language (L2) Chinese learners' reading comprehension. Log data tracking learners' in-game behaviors from a game designed for Chinese dual language immersion classrooms (Poole et al., 2022) were used to construct Bayesian Belief Networks to model reading…

The What Works Clearinghouse (WWC) released a report that applies two methodological approaches new to the WWC that together aim to improve researchers' understanding of how early literacy interventions may work to improve outcomes for students in grades K-3. First, this report pilots a new taxonomy developed by early literacy experts and…

This article presents a latent class model for multilevel data to identify latent subgroups and estimate heterogeneous treatment effects. Unlike sequential approaches that partition data first and then estimate average treatment effects (ATEs) within classes, we employ a Bayesian procedure to jointly estimate mixing probability, selection, and…

Infant language learners are faced with the difficult inductive problem of determining how new words map to novel or known objects in their environment. Bayesian inference models have been successful at using the sparse information available in natural child-directed speech to build candidate lexicons and infer speakers' referential intentions. We…

This contribution shows a simple implementation of Monte Carlo simulation method when presenting Bayes' rule. The implementation is carried out in the environment of Microsoft Excel spreadsheets by means of a generator of random numbers. The empiric results gained by simulation serve to confirm the correctness of the chosen procedures in…

Multilevel modeling is a statistical approach to analyze hierarchical data, which consist of individual observations nested within clusters. Bayesian methods is a well-known, sometimes better, alternative of Maximum likelihood methods for fitting multilevel models. Lack of user-friendly and computationally efficient software packages or programs…

The Schwarz or Bayesian information criterion (BIC) is one of the most widely used tools for model comparison in social science research. The BIC, however, is not suitable for evaluating models with order constraints on the parameters of interest. This article explores two extensions of the BIC for evaluating order-constrained models, one where a…

Background: Performance monitoring plays a key role in self-regulated learning, but is difficult, especially for complex visual tasks such as navigational map reading. Gaze displays (i.e. visualizations of participants' eye movements during a task) might serve as feedback to improve students' performance monitoring. Objectives: We hypothesized…

This paper explores how student performance across the full set of multiple modular assessments of individual standards, which we refer to as mini-assessments, from a large scale, operational program of interim assessment can be summarized using Bayesian networks. We follow a completely data-driven approach in which no constraints are imposed to…

The MUSIC (eMpowerment, Usefulness, Success, Interest, Caring) Model of Academic motivation was developed to help instructors promote student motivation in the classroom. This study examines relationships among student perceptions of motivation and effort compared with their performance in undergraduate business analytics courses. Specifically,…

Although some previous studies have investigated the relationship between moral foundations and moral judgment development, the methods used have not been able to fully explore the relationship. In the present study, we used Bayesian Model Averaging (BMA) in order to address the limitations in traditional regression methods that have been used…

The purpose of this research was to determine classification accuracy of the factors affecting the success of students' reading skills based on PISA 2018 data by using Artificial Neural Networks, Decision Trees, K-Nearest Neighbor, and Naive Bayes data mining classification methods and to examine the general characteristics of success groups. In…

Early school leaving has profound implications at a socio-economic level and planning effective prevention programs within school is crucial for contrasting it. Based on the hypothesis that the dropout is the last step of a process that ends in the student's decision to leave school, we studied the interplay between multiple risk factors of school…