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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
Markus Gangl – Sociological Methods & Research, 2025
Rating scales are ubiquitous in the social sciences, yet may present practical difficulties when response formats change over time or vary across surveys. To allow researchers to pool rating data across alternative question formats, the article provides a generalization of the ordered logit model that accommodates multiple scale formats in the…
Descriptors: Rating Scales, Surveys, Responses, Models
Craig J. Cullen; Lawrence Ssebaggala; Amanda L. Cullen – Mathematics Teacher: Learning and Teaching PK-12, 2024
In this article, the authors share their favorite "Construct It!" activity, which focuses on rate of change and functions. The initial approach to instruction was procedural in nature and focused on making use of formulas. Specifically, after modeling how to find the slope of the line given two points and use it to solve for the…
Descriptors: Models, Mathematics Instruction, Teaching Methods, Generalization
Wong, Zi Yang; Liem, Gregory Arief D. – Educational Psychology Review, 2022
Notwithstanding its crucial role in facilitating desired outcomes of schooling, educational psychology researchers have recognized the conceptual haziness of student engagement as a multidimensional construct. With the main purpose of refining its conceptual definition, this paper aims to attain the following four goals. First, we seek to…
Descriptors: Learner Engagement, Definitions, Misconceptions, Theories
Hamzeh Ghasemzadeh; Robert E. Hillman; Daryush D. Mehta – Journal of Speech, Language, and Hearing Research, 2024
Purpose: Many studies using machine learning (ML) in speech, language, and hearing sciences rely upon cross-validations with single data splitting. This study's first purpose is to provide quantitative evidence that would incentivize researchers to instead use the more robust data splitting method of nested k-fold cross-validation. The second…
Descriptors: Artificial Intelligence, Speech Language Pathology, Statistical Analysis, Models
Andreas Lachner; Leonie Sibley; Salome Wagner – Educational Psychology Review, 2024
In educational research, there is the general trade-off that empirical evidence should be generalizable to be applicable across contexts; at the same time, empirical evidence should be as specific as possible to be localizable in subject-specific educational interventions to successfully transfer the empirical evidence to educational practice.…
Descriptors: Evidence Based Practice, Instructional Effectiveness, Science Instruction, Instructional Design
Justin L. Kern – Journal of Educational and Behavioral Statistics, 2024
Given the frequent presence of slipping and guessing in item responses, models for the inclusion of their effects are highly important. Unfortunately, the most common model for their inclusion, the four-parameter item response theory model, potentially has severe deficiencies related to its possible unidentifiability. With this issue in mind, the…
Descriptors: Item Response Theory, Models, Bayesian Statistics, Generalization
Patricio Erhard; Terry S. Falcomata; Molly Oshinski; Austin Sekula – Review Journal of Autism and Developmental Disorders, 2024
Adolescents and young adults with autism spectrum disorders (ASD) have persistent difficulty developing and generalizing social communication and interaction skills. Emerging research has demonstrated that people with ASD have benefited from strategies that embed multiple-exemplar training (MET) to increase generalization of social skills.…
Descriptors: Adolescents, Young Adults, Autism Spectrum Disorders, Generalization
Caitlin R. Bowman; Dagmar Zeithamova – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2023
A major question for the study of learning and memory is how to tailor learning experiences to promote knowledge that generalizes to new situations. In two experiments, we used category learning as a representative domain to test two factors thought to influence the acquisition of conceptual knowledge: the number of training examples (set size)…
Descriptors: Classification, Learning Processes, Generalization, Recognition (Psychology)
Shawn Hemelstrand; Tomohiro Inoue – Reading Research Quarterly, 2024
The unique orthographic complexities of Japanese, which utilizes multiple types of scripts (morphographic kanji and syllabic hiragana and katakana) for the same spoken language, place unique demands on early learners. Much research has centered on the average ability of Japanese readers, but given the varying challenges of these scripts, attention…
Descriptors: Japanese, Literacy, Contrastive Linguistics, Generalization
Terry A. Ackerman; Deborah L. Bandalos; Derek C. Briggs; Howard T. Everson; Andrew D. Ho; Susan M. Lottridge; Matthew J. Madison; Sandip Sinharay; Michael C. Rodriguez; Michael Russell; Alina A. Davier; Stefanie A. Wind – Educational Measurement: Issues and Practice, 2024
This article presents the consensus of an National Council on Measurement in Education Presidential Task Force on Foundational Competencies in Educational Measurement. Foundational competencies are those that support future development of additional professional and disciplinary competencies. The authors develop a framework for foundational…
Descriptors: Educational Assessment, Competence, Skill Development, Communication Skills
Hayes, Brett K.; Liew, Shi Xian; Desai, Saoirse Connor; Navarro, Danielle J.; Wen, Yuhang – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2023
The samples of evidence we use to make inferences in everyday and formal settings are often subject to selection biases. Two property induction experiments examined group and individual sensitivity to one type of selection bias: sampling frames - causal constraints that only allow certain types of instances to be sampled. Group data from both…
Descriptors: Logical Thinking, Inferences, Bias, Individual Differences
Pallotti, Gabriele – Second Language Research, 2022
Complex Dynamic Systems Theory (CDST) has received considerable attention over the last decades, inspiring a number of second language acquisition studies. This article examines the research from a critical epistemological point of view, starting from the Greek philosopher Cratylus, who concluded that remaining silent is the only way to be…
Descriptors: Systems Approach, Second Language Learning, Linguistic Theory, Epistemology
Condor, Aubrey; Litster, Max; Pardos, Zachary – International Educational Data Mining Society, 2021
We explore how different components of an Automatic Short Answer Grading (ASAG) model affect the model's ability to generalize to questions outside of those used for training. For supervised automatic grading models, human ratings are primarily used as ground truth labels. Producing such ratings can be resource heavy, as subject matter experts…
Descriptors: Automation, Grading, Test Items, Generalization
McEneaney, John; Morsink, Paul – Journal of Learning Analytics, 2022
Learning analytics (LA) provides tools to analyze historical data with the goal of better understanding how curricular structures and features have impacted student learning. Forward-looking curriculum design, however, frequently involves a degree of uncertainty. Historical data may be unavailable, a contemplated modification to curriculum may be…
Descriptors: Curriculum Design, Learning Analytics, Educational Change, Computer Software