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…

The purpose of this study was to validate a novel reading comprehension assessment for college students named MOCCA-College. A random sample of college students (N = 63, average age of 22.5) were recruited from various education programs (e.g., first-year courses, TRIO, SONA) and completed MOCCA-College Online and were later recruited to complete…

Background: Analyzing student short-answer written justifications to conceptually challenging questions has proven helpful to understand student thinking and improve conceptual understanding. However, qualitative analyses are limited by the burden of analyzing large amounts of text. Purpose: We apply dense and sparse Large Language Models (LLMs)…

This study evaluates the performance of three leading AI chatbots--OpenAI's ChatGPT, Google's Gemini, and Microsoft Bing Copilot--in answering multiple choice questions (MCQs) from the UGC-NET Education paper. Using 150 randomly selected questions from examination cycles between June 2019 and December 2023, the chatbots' accuracy was assessed…

This study examines the effectiveness of Lesson Study (LS) in enhancing the writing accuracy of EFL learners. A group of 63 intermediate male EFL learners from Gofteman Language Institute in Ardebil, Iran, divided into two experimental groups and one control group, participated in the research. After taking a grammar pre-test on the target…

We implemented tact matrix training to teach tacts of spatial locations to four children (male, 4-7 years of age) on the autism spectrum in China. The experimental design involved a multiple-probe design across participants with pre- and postinstruction probes on untaught tacts and listener responses. Learning outcomes included taught tacts of…