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Direct linkJean-Paul Fox – Journal of Educational and Behavioral Statistics, 2025
Popular item response theory (IRT) models are considered complex, mainly due to the inclusion of a random factor variable (latent variable). The random factor variable represents the incidental parameter problem since the number of parameters increases when including data of new persons. Therefore, IRT models require a specific estimation method…
Descriptors: Sample Size, Item Response Theory, Accuracy, Bayesian Statistics
Download full textKylie L. Anglin – Annenberg Institute for School Reform at Brown University, 2025
Since 2018, institutions of higher education have been aware of the "enrollment cliff" which refers to expected declines in future enrollment. This paper attempts to describe how prepared institutions in Ohio are for this future by looking at trends leading up to the anticipated decline. Using IPEDS data from 2012-2022, we analyze trends…
Descriptors: Validity, Artificial Intelligence, Models, Best Practices
Deise Monquelate Arndt; Ramon Mayor Martins; Jean Carlo Rossa Hauck – Informatics in Education, 2025
Critical thinking is a fundamental skill for 21st-century citizens, and it should be promoted from elementary school and developed in computing education. However, assessing the development of critical thinking in educational contexts presents unique challenges. In this study, a systematic mapping was carried out to investigate how to assess the…
Descriptors: Critical Thinking, Elementary Secondary Education, Computer Science Education, 21st Century Skills
Shabnam Ara S. J.; Tanuja Ramachandriah; Manjula S. Haladappa – Online Learning, 2025
Predicting learner performance with precision is critical within educational systems, offering a basis for tailored interventions and instruction. The advent of big data analytics presents an opportunity to employ Machine Learning (ML) techniques to this end. Real-world data availability is often hampered by privacy concerns, prompting a shift…
Descriptors: Learning Analytics, Privacy, Artificial Intelligence, Regression (Statistics)
Yuan Cui; Xiao-Xi Xiao; Zhi-Li Zhan; Guo-Liang Yang – Research Evaluation, 2025
In the current higher education landscape, universities are facing expanding requirements beyond teaching and research. Evaluation methods must evolve accordingly to prevent universities from facing development dilemmas. Current mainstream evaluation methods primarily emphasize the research domain, often failing to holistically capture a…
Descriptors: Universities, Diversity, Equal Education, Evaluation Methods
Yunus Kökver; Hüseyin Miraç Pektas; Harun Çelik – Education and Information Technologies, 2025
This study aims to determine the misconceptions of teacher candidates about the greenhouse effect concept by using Artificial Intelligence (AI) algorithm instead of human experts. The Knowledge Discovery from Data (KDD) process model was preferred in the study where the Analyse, Design, Develop, Implement, Evaluate (ADDIE) instructional design…
Descriptors: Artificial Intelligence, Misconceptions, Preservice Teachers, Natural Language Processing
