This study evaluated the validity of the Michigan English Test (MET) Listening Section by investigating its underlying factor structure and the replicability of its factor structure across multiple test forms. Data from 3255 test takers across four forms of the MET Listening Section were used. To investigate the factor structure, each form was…

Learning data analytics improves the learning field in higher education using educational data for extracting useful patterns and making better decisions. Identifying potential at-risk students may help instructors and academic guidance to improve the students' performance and the achievement of learning outcomes. The aim of this research study is…

Network meta-analysis is a popular method to synthesize the information obtained in a systematic review of studies (e.g., randomized clinical trials) involving subsets of multiple treatments of interest. The dominant method of analysis employs within-study information on treatment contrasts and integrates this over a network of studies. One…

This article illustrates the Bayesian approximate measurement invariance (MI) approach in Mplus with longitudinal data and small sample size. Approximate MI incorporates zero-mean small variance prior distributions on the differences between parameter estimates over time. Contrary to traditional invariance testing methods, where exact invariance…

One crucial function of a classroom, and a school more generally, is to prepare students for future learning. Students should have the capacity to learn new information and to acquire new skills. This ability to "learn" is a core competency in our rapidly changing world. But how do we measure ability to learn? And how can we measure how…

Contribution: This study applies supervised and unsupervised machine learning (ML) techniques to discover which significant attributes that a successful learner often demonstrated in a computer course. Background: Students often experienced difficulties in learning an introduction to computers course. This research attempts to investigate how…

This mixed research aims to design and implement the Web Application on Bayes' Theorem (WABT) in the Statistical Instrumentation for Business subject. WABT presents the procedure to calculate the probability of Bayes' Theorem through the simulation of data about the supply of products. Technology Acceptance Model (TAM), machine learning and data…

Awareness of students' learning status, and maintaining students' focus and attention during class are important issues in classroom management. Several observation instruments have been designed for human observers to document students' engagement in class, but the processes are time-consuming and laborious. Recently, with the development of…

Bayesian knowledge tracing model (BKT) is a typical student knowledge assessment method. It is widely used in intelligent tutoring systems. In the standard BKT model, all knowledge and skills are independent of each other. However, in the process of student learning, they have a very close relation. A student may understand knowledge B better when…

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…