Correct specifications of hierarchical attribute structures in analyses using diagnostic classification models (DCMs) are pivotal because misspecifications can lead to biased parameter estimations and inaccurate classification profiles. This research is aimed to demonstrate DCM analyses with various hierarchical attribute structures via Bayesian…

This study explored certain popular educational apps' vital characteristics and potential profiles (n1 = 50) for kindergarten kids. The profile analysis involved a categorization ascended from an evaluation process conducted by pre-service early childhood teachers' (n2 = 295) at the University of Crete, Greece, using a new instrument, validated in…

This study focuses on how teachers' pedagogical content knowledge (PCK) of mathematics may differ depending on teacher interactions in an online teacher community of practice (CoP). The study utilizes data from 26,857 posts collected from the South Korean self-generated online teacher CoP, 'Indischool'. This data was then analyzed using natural…

We present two types of validity evidence to support inferences and decisions about use of easyCBMs in relation to state testing programs. The first type involves the use of Benchmarks in reading to use in making predictions of performance on the Smarter Balanced (SB) test. These predictions can be made both well in advance (several months) or…

This report sets out the findings of the technical development work completed as part of the Use Cases for Generative AI in Education project, commissioned by the Department for Education (DfE) in September 2023. It has been published alongside the User Research Report, which sets out the findings from the ongoing user engagement activity…

Background/Context: Chronic absenteeism is a serious problem that has been linked to lower academic achievement, diminished socioemotional skills, and an increased likelihood of high school dropout (Allensworth et al., 2021; Gottfried, 2014). As a result, many schools have begun to embrace early warning systems (EWS) as a tool to identify and flag…

In this study, it was aimed to compare the predictions of the academic achievement of the artificial neural networks (ANN) run in MATLAB and SPSS software and to determine the factors related to their academic achievement. Sample consisted of 465 students who were studying at Grade 4 in primary schools in the Central Anatolian Region of Turkey in…

This research synthesizes studies that used a Digitalized Interactive Component (DIC) to assess K-12 student mathematics performance during Computer-based-Assessments (CBAs) in mathematics. A systematic search identified ten studies that categorized existing DICs according to the tools that provided language assistance to students and tools that…

Due to benefits for teaching and learning, an increasing number of studies have focused on classroom dialogue and how to make it productive. Coding, in which the transcribed conversation is allocated to a set of features, is commonly employed to deal with the textual data arising from this dialogue. This is generally done manually and cannot…

Virtual reality (VR) is an emerging technology that is gaining traction in K12 education. Whereas well-designed and engaging VR experiences may be considered educational, teacher educators with content-area expertise are uniquely positioned to analyze the actual content provided by those experiences when determining VR's educational value.…

The purpose of this mixed methods study was to employ the International Society for Technology in Education (ISTE) Standards for Students as taxonomy to classify educational mobile application (app) software into seven categories and empirically examine the influence on students' technology literacy. A purposeful sample of fifth grade core subject…

This study analyzes Achieve3000, Lexia Core 5, and Imagine Learning software programs designed to increase student literacy levels in a six-week summer school program. The Brainology program was also used with 4th to 6th grade students to determine if there was an increase in growth mindset. Three elementary schools with the highest percentages of…

The purpose of this study was to develop a framework for analyzing and evaluating student-constructed models of physical phenomena and monitoring the progress of these models. Moreover, we aimed to examine whether this framework could capture differences between models created using different computer-based modeling tools; namely, computer-based…

We present an inference algorithm for perturbation models based on Poisson regression. The algorithm is designed to handle unclassified input with multiple errors described by independent mal-rules. This knowledge representation provides an intelligent tutoring system with local and global information about a student, such as error classification…

This paper reports on an ESRC-funded project that investigated the use of corpus-based activities in a primary-school context, with children aged 8-10 years. The study explored the contributions that could be made by a corpus--comprising language written for a child audience--and a modified version of the associated software, in helping these…