Cognitive diagnosis models (CDMs) are the assessment tools that provide valuable formative feedback about skill mastery at both the individual and population level. Recent work has explored the performance of CDMs with small sample sizes but has focused solely on the estimates of individual profiles. The current research focuses on obtaining…

The present study investigates the influence of multidimensionality on linking and equating in a unidimensional IRT. Two hypothetical multidimensional scenarios are explored under a nonequivalent group common-item equating design. The first scenario examines test forms designed to measure multiple constructs, while the second scenario examines a…

The revised Speech Learning Model (SLM-r) postulates that learners with more precisely defined categories in their native language (L1) exhibit greater proficiency in acquiring sounds in a second language (L2). Despite its recent emergence, empirical studies validating this hypothesis remain scarce. This study aims to investigate the predictive…

Purpose: This systematic review and multilevel meta-analysis examines the accuracy of sentence repetition (SR) tasks in distinguishing between typically developing (TD) children and children with developmental language disorder (DLD). It explores variation in the way that SR tasks are administered and/or evaluated and examines whether variability…

The current educational system relies heavily on manual grading, posing challenges such as delayed feedback and grading inaccuracies. Automated grading tools (AGTs) offer solutions but come with limitations. To address this, "GRAD-AI" is introduced, an advanced AGT that combines automation with teacher involvement for precise grading,…

The purpose of this explanatory sequential mixed methods study was to examine faculty perceptions of distance course quality review feedback at a small healthcare-focused college in the United States. The Examining the Evaluator Feedback Survey tool was adapted and used to determine faculty perceptions (N=16) of five key aspects of reviewer…

This study investigates the use of Large Language Models (LLMs) by undergraduates majoring in Instrumentation and Control Engineering (ICE) at University of Shanghai for Science and Technology. We conducted a questionnaire survey to assess the awareness and usage habits of these LLMs among ICE undergraduates in ICE courses, focusing on the model…

The objective of question generation from knowledge graphs (KGQG) is to create coherent and answerable questions from a given subgraph and a specified answer entity. KGQG has garnered significant attention due to its pivotal role in enhancing online education. Encoder-decoder architectures have advanced traditional KGQG approaches. However, these…

Mathematics teachers have been documented as thinking of precision as a black-and-white issue that should be judged based on external expectations (Otten et al., 2019), suggesting that matters of precision align primarily with approaches to mathematics instruction that prioritize accuracy and speed. How can teachers who also value creativity and…

Background/purpose: This study aimed to reveal the accuracy of estimation of multiple-choice test items parameters following the models of the item-response theory in measurement. Materials/methods: The researchers depended on the measurement accuracy indicators, which express the absolute difference between the estimated and actual values of the…

Although it is commonly believed that automation aids human decision-making, conflicting evidence raises questions about whether individuals would gain greater advantages from automation in difficult tasks. Our study examines the combined influence of task difficulty and automation reliability on aided decision-making. We assessed decision…

Statewide longitudinal data systems (SLDSs) often rely on personal identifiers to securely link individual-level data across early childhood, K-12, higher education, and the workforce. However, different sectors use different types of personal identifiers which can make accurately connecting records difficult. Driver's license data offers a single…

Over the past decade, social scientists have adapted computational methods for qualitative text analysis, with the hope that they can match the accuracy and reliability of hand coding. The emergence of GPT and open-source generative large language models (LLMs) has transformed this process by shifting from programming to engaging with models using…

Artificial intelligence companies and researchers are currently working to create Artificial Superintelligence (ASI): AI systems that significantly exceed human problem-solving speed, power, and precision across the full range of human solvable problems. Some have claimed that achieving ASI -- for better or worse -- would be the most significant…

The increasing rate of permanent school closures in U.S. public school districts presents unprecedented challenges for administrators and communities alike. This study develops an early-warning indicator model to predict mass closure events -- defined as a district closing at least 10% of its schools -- five years in advance. Leveraging…