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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)
Mayssa Hayeen-Halloun; Michal Ayalon – Journal of Mathematics Teacher Education, 2025
This paper aims to characterize critical events noticed by novice mathematics teacher-educators (NMTEs) while they facilitate teacher education sessions. Twenty-four NMTEs enrolled in a university course on teaching teachers were asked to facilitate a series of three sessions with preservice teachers, identify critical events from those sessions…
Descriptors: Beginning Teachers, Mathematics Teachers, Teacher Educators, Observation
Charity N. Watson; Pablo Duran; Adam Castillo; Edgar Fuller; Geoff Potvin; Laird Kramer – International Journal of Mathematical Education in Science and Technology, 2025
College calculus plays an important role in STEM students' degree and career aspirations. One of the key factors considered in assessing a student's ability to be successful in calculus is their proficiency in topics from prior mathematics courses such as algebra and precalculus. This study set out to examine the impact of students' precalculus…
Descriptors: Active Learning, Calculus, Mathematics Instruction, Teaching Methods
Ke-Hai Yuan; Zhiyong Zhang – Grantee Submission, 2025
Most methods for structural equation modeling (SEM) focused on the analysis of covariance matrices. However, "Historically, interesting psychological theories have been phrased in terms of correlation coefficients." This might be because data in social and behavioral sciences typically do not have predefined metrics. While proper methods…
Descriptors: Correlation, Statistical Analysis, Models, Tests
Anna Garrido; Digna Couso – Journal of Research in Science Teaching, 2025
The importance of models and modeling in science education is well-recognized, yet there exists significant polysemy among these terms within the literature. This ambiguity often leads to confusion, particularly regarding whether modeling represents an expected student performance, an instructional strategy to promote such performance, or both.…
Descriptors: Science Education, Learner Engagement, Models, Educational Practices
Safa Ridha Albo Abdullah; Ahmed Al-Azawei – International Review of Research in Open and Distributed Learning, 2025
This systematic review sheds light on the role of ontologies in predicting achievement among online learners, in order to promote their academic success. In particular, it looks at the available literature on predicting online learners' performance through ontological machine-learning techniques and, using a systematic approach, identifies the…
Descriptors: Electronic Learning, Academic Achievement, Grade Prediction, Data Analysis
Juhaina Awawdeh Shahbari – International Journal of Science and Mathematics Education, 2025
The modeling approach is used to prepare students to become responsible citizens and face the challenges and demands of modern times, mainly when they engage in modeling activities using digital tools. This study investigates the features of digital tools used in modeling processes among prospective teachers. Thirty-two prospective mathematics…
Descriptors: Models, Technology, Preservice Teachers, Mathematics Teachers
Jean-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
Kangkang Li; Chengyang Qian; Xianmin Yang – Education and Information Technologies, 2025
In learnersourcing, automatic evaluation of student-generated content (SGC) is significant as it streamlines the evaluation process, provides timely feedback, and enhances the objectivity of grading, ultimately supporting more effective and efficient learning outcomes. However, the methods of aggregating students' evaluations of SGC face the…
Descriptors: Student Developed Materials, Educational Quality, Automation, Artificial Intelligence
Sohee Kim; Ki Lynn Cole – International Journal of Testing, 2025
This study conducted a comprehensive comparison of Item Response Theory (IRT) linking methods applied to a bifactor model, examining their performance on both multiple choice (MC) and mixed format tests within the common item nonequivalent group design framework. Four distinct multidimensional IRT linking approaches were explored, consisting of…
Descriptors: Item Response Theory, Comparative Analysis, Models, Item Analysis
Kylie 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
Zhengjun Li; Huayang Kang – International Journal of Web-Based Learning and Teaching Technologies, 2025
The rapid development of higher education in China has significantly advanced physical education within universities, contributing to students' comprehensive development and national health improvement. However, the expansion of university enrollment has introduced challenges such as a decrease in per capita sports resources and declines in…
Descriptors: Physical Education Teachers, Teacher Effectiveness, Physical Education, Evaluation Methods
Reese Butterfuss; Harold Doran – Educational Measurement: Issues and Practice, 2025
Large language models are increasingly used in educational and psychological measurement activities. Their rapidly evolving sophistication and ability to detect language semantics make them viable tools to supplement subject matter experts and their reviews of large amounts of text statements, such as educational content standards. This paper…
Descriptors: Alignment (Education), Academic Standards, Content Analysis, Concept Mapping
Greta Goetz – Educational Philosophy and Theory, 2025
"Applications" of knowledge symbolically and structurally "codify" thinking, often displacing the human who is relegated to passive, routine reproduction of operations and left with no space or time to understand or question the relations underlying the processes. This is both mirrored and augmented by the schematic narrowing…
Descriptors: Educational Philosophy, Critical Theory, Teaching Methods, Phenomenology
Lauren A. Mason; Abigail Miller; Gregory Hughes; Holly A. Taylor – Cognitive Research: Principles and Implications, 2025
False alarming, or detecting an error when there is not one, is a pervasive problem across numerous industries. The present study investigated the role of elaboration, or additional information about non-error differences in complex visual displays, for mitigating false error responding. In Experiment 1, learners studied errors and non-error…
Descriptors: Error Correction, Error Patterns, Evaluation Methods, Visual Aids