Context-aware mobile learning applications provide learning materials to suit the needs of individual learners. Despite several applications developed, there is a lack of architectural support for developing these applications. This has resulted in a number of challenges; lack of standardization, poor quality of developed applications, and…

RobotReviewer is a tool for automatically assessing the risk of bias in randomized controlled trials, but there is limited evidence of its reliability. We evaluated the agreement between RobotReviewer and humans regarding the risk of bias assessment based on 1955 randomized controlled trials. The risk of bias in these trials was assessed via two…

Conventional approaches to assessment involve teachers and examiners judging the quality of learners work by reference to lists of criteria or other 'outcome' statements. This paper explores a quite different method of assessment using 'Adaptive Comparative Judgement' (ACJ) that was developed within a research project at Goldsmiths University of…

Automated Essay Scoring (AES) tools aim to improve the efficiency and consistency of essay scoring by using machine learning algorithms. In the existing research work on this topic, most researchers agree that human-automated score agreement remains the benchmark for assessing the accuracy of machine-generated scores. To measure the performance of…

Purpose: Artificial intelligence (AI) is more capable and accessible than ever before. But what does this mean for clinical practice? How can speech-language clinicians evaluate the efficacy, validity, and reliability of AI and machine learning tools for automating assessment and treatment? How can speech-language clinicians ethically use these…

Artificial Intelligence (AI) has rapidly become a pivotal force in education, offering personalized learning pathways and dynamic solutions to longstanding instructional challenges. In English as a Foreign Language (EFL) contexts, idiomatic competence remains a challenging aspect of language development, often eluding effective coverage through…

More than three decades after their introduction, diagnostic classification models (DCM) do not seem to have been implemented in educational systems for the purposes they were devised. Most DCM research is either methodological for model development and refinement or retrofitting to existing nondiagnostic tests and, in the latter case, basically…

Evidence-based decision-making is predicated on the ability of users to find and comprehend results from systematic review. Evidence producers have an obligation to support evidence users in this process. The Agency for Healthcare Research and Quality (AHRQ) Evidence-based Practice Center (EPC) program--a producer of rigorous and comprehensive…

The literature provides multiple measures of diversity along a single demographic dimension, but when it comes to studying the interaction of multiple diversity types (e.g. age, gender, and race), the field of useable measures diminishes. We present the use of decision trees as a machine learning technique to automatically identify the…

This paper argues that key findings from computer-assisted language learning (CALL) research need to be replicated to permit the construction of a valid and reliable evidence-base which can inform the design of future CALL software and activities, together with language teachers' decisions about their adoption. Through the critical examination of…

Calls for replication studies are becoming more frequent, and Computer Assisted Language Learning (CALL) has now reached sufficient maturity to offer numerous studies that lend themselves to replication. Realistic and successful replications rely on transparency in terms of data, results, and methodology. Two published studies in the area of…

Houston's experience with the Educational Value-Added Assessment System (R) (EVAAS) raises questions that other districts should consider before buying the software and using it for high-stakes decisions. Researchers found that teachers in Houston, all of whom were under the EVAAS gun, but who taught relatively more racial minority students,…

The focus of assessment in statistics has gradually shifted from traditional assessment towards alternative assessment where more attention has been paid to the core statistical concepts such as center, variability, and distribution. In spite of this, there are comparatively few assessments that combine the significant three types of statistical…

Our study examines the efficacy of Computer Assisted Scoring (CAS) of open-response text relative to expert human scoring within the complex domain of evolutionary biology. Specifically, we explored whether CAS can diagnose the explanatory elements (or Key Concepts) that comprise undergraduate students' explanatory models of natural selection with…

Among the many methods currently available for estimating latent variable interactions, the unconstrained approach is attractive to applied researchers because of its relatively easy implementation with any structural equation modeling (SEM) software. Using a Monte Carlo simulation study, we extended and evaluated the unconstrained approach to…