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Gilboa, Nava; Dreyfus, Tommy; Kidron, Ivy – Educational Studies in Mathematics, 2023
The notion of definition is a central building block of mathematics. In addition to specific definitions, it is desirable that students learn about meta-mathematical aspects of definitions such as their role of classification, and about characteristics of definitions such as arbitrariness. We investigated how such meta-mathematical aspects emerge…
Descriptors: Mathematics Education, Definitions, Classification, Mathematical Concepts
Gee, Nick; Parrish, Abigail; Puttick, Steven – Teacher Development, 2023
Subject departments are an increasingly important unit of analysis for research on schools and beginning teachers' experiences. By analysing a practice-based typology of eight departmental types through an exploratory factor analysis of questionnaires completed by beginning teachers (n = 55), the authors refined the typology to four (hierarchical;…
Descriptors: Classification, Departments, Secondary Schools, Intellectual Disciplines
Qiwei He; Qingzhou Shi; Elizabeth L. Tighe – Grantee Submission, 2023
Increased use of computer-based assessments has facilitated data collection processes that capture both response product data (i.e., correct and incorrect) and response process data (e.g., time-stamped action sequences). Evidence suggests a strong relationship between respondents' correct/incorrect responses and their problem-solving proficiency…
Descriptors: Artificial Intelligence, Problem Solving, Classification, Data Use
He, Dan – ProQuest LLC, 2023
This dissertation examines the effectiveness of machine learning algorithms and feature engineering techniques for analyzing process data and predicting test performance. The study compares three classification approaches and identifies item-specific process features that are highly predictive of student performance. The findings suggest that…
Descriptors: Artificial Intelligence, Data Analysis, Algorithms, Classification
Gani, Mohammed Osman; Ayyasamy, Ramesh Kumar; Sangodiah, Anbuselvan; Fui, Yong Tien – Education and Information Technologies, 2023
The automated classification of examination questions based on Bloom's Taxonomy (BT) aims to assist the question setters so that high-quality question papers are produced. Most studies to automate this process adopted the machine learning approach, and only a few utilised the deep learning approach. The pre-trained contextual and non-contextual…
Descriptors: Models, Artificial Intelligence, Natural Language Processing, Writing (Composition)
Marta Marcilla-Jorda; Catarina Grande; Vera Coelho; César Rubio-Belmonte; Micaela Moro-Ipola – Journal of Autism and Developmental Disorders, 2025
Autism spectrum disorder (ASD) is characterized by impairments in many functional areas requiring long-term interventions to promote autonomy. This study aims to map The Sensory Profile™ 2 (SP-2), one of the most widely used assessment tools in children with ASD, with the International Classification of Functioning, Disability and Health for…
Descriptors: Sensory Experience, Profiles, Autism Spectrum Disorders, Classification
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
Peter Baldwin; Victoria Yaneva; Kai North; Le An Ha; Yiyun Zhou; Alex J. Mechaber; Brian E. Clauser – Journal of Educational Measurement, 2025
Recent developments in the use of large-language models have led to substantial improvements in the accuracy of content-based automated scoring of free-text responses. The reported accuracy levels suggest that automated systems could have widespread applicability in assessment. However, before they are used in operational testing, other aspects of…
Descriptors: Artificial Intelligence, Scoring, Computational Linguistics, Accuracy
Karly S. Ford; Megan Holland Iantosca; Leandra Cate – Educational Researcher, 2025
In scholarly research, racial categories are typically taken for granted. However, race categories vary over time and geography and reflect the social beliefs of the people who use them. Informed by quantitative critical race theory analysis, we interrogate how race categories align (or not) with 24,000 U.S. higher education students' responses to…
Descriptors: College Students, Self Concept, Racial Identification, Classification
Maneka Deanna Brooks – Education Policy Analysis Archives, 2025
This study, framed by dignity-focused language policy and intersectional anti-adultism, investigates how 74 adults misclassified as English learners (ELs) during U.S. K-12 education conceptualize essential knowledge for educating bilingual students. Through semi-structured interviews, participants stressed two key areas for schools that serve…
Descriptors: English Learners, Classification, Bilingual Students, Language Usage
Dubravka Svetina Valdivia; Shenghai Dai – Journal of Experimental Education, 2024
Applications of polytomous IRT models in applied fields (e.g., health, education, psychology) are abound. However, little is known about the impact of the number of categories and sample size requirements for precise parameter recovery. In a simulation study, we investigated the impact of the number of response categories and required sample size…
Descriptors: Item Response Theory, Sample Size, Models, Classification
Genshu Lu; Shuang Wen – Asia-Pacific Education Researcher, 2024
This study explored student engagement typology in Chinese universities and examined variations in the ability development across student types. Using data generated by a survey study covering 8461 undergraduate students at 53 Chinese universities, this research applied latent profile analysis to construct a Chinese student engagement typology. We…
Descriptors: Learner Engagement, Undergraduate Students, Foreign Countries, Classification
Lisa M. D. Archibald – Discover Education, 2024
The terms Language Disorder, Developmental Language Disorder (DLD), Language-based learning disabilities, Specific Learning Disorder, and Specific Learning Disability are commonly used to describe children struggling to learn at school. In this position paper, the definitions and distinctions between these terms are discussed, and key overlaps and…
Descriptors: Developmental Disabilities, Learning Disabilities, Language Impairments, Students with Disabilities
Anderson Pinheiro Cavalcanti; Rafael Ferreira Mello; Dragan Gaševic; Fred Freitas – International Journal of Artificial Intelligence in Education, 2024
Educational feedback is a crucial factor in the student's learning journey, as through it, students are able to identify their areas of deficiencies and improve self-regulation. However, the literature shows that this is an area of great dissatisfaction, especially in higher education. Providing effective feedback becomes an increasingly…
Descriptors: Prediction, Feedback (Response), Artificial Intelligence, Automation
Hlologelo Climant Khoza; Bob Maseko – Alberta Journal of Educational Research, 2024
Research in science education has established the significance of collaborative concept mapping as a powerful strategy in fostering conceptual learning. During such collaboration, students talk about concept map features (i.e., concepts to include, linking words, and cross-links) in constructing a joint map. The quality of the concept map produced…
Descriptors: Discourse Analysis, Concept Mapping, Audio Equipment, Biology