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Kajal Mahawar; Punam Rattan – Education and Information Technologies, 2025
Higher education institutions have consistently strived to provide students with top-notch education. To achieve better outcomes, machine learning (ML) algorithms greatly simplify the prediction process. ML can be utilized by academicians to obtain insight into student data and mine data for forecasting the performance. In this paper, the authors…
Descriptors: Electronic Learning, Artificial Intelligence, Academic Achievement, Prediction
Uk Hyun Cho – ProQuest LLC, 2024
The present study investigates the influence of multidimensionality on linking and equating in a unidimensional IRT. Two hypothetical multidimensional scenarios are explored under a nonequivalent group common-item equating design. The first scenario examines test forms designed to measure multiple constructs, while the second scenario examines a…
Descriptors: Item Response Theory, Classification, Correlation, Test Format
Khaleel Asyraaf Mat Sanusi; Deniz Iren; Nardie Fanchamps; Mai Geisen; Roland Klemke – Educational Technology Research and Development, 2025
Psychomotor skill training has traditionally relied on the physical presence of both teacher and learner for effective demonstrations and feedback, posing challenges for remote and self-directed learning. Technological advancements have given rise to immersive learning environments (ILEs), offering novel solutions for interactive and multimodal…
Descriptors: Psychomotor Skills, Skill Development, Computer Simulation, Electronic Learning
Mehmet Can Demir; Kübra Atalay-Kabasakal; Murat Dogan Sahin – Turkish Journal of Education, 2024
Previous researchers have identified socioeconomic status as a significant predictor of achievement/literacy. However, it is important to recognize that the influence of socioeconomic status on literacy may vary at different levels of socioeconomic status. Thus, this study analyzes the relationship between socioeconomic status and literacy scores…
Descriptors: Socioeconomic Status, Scores, Correlation, Classification
Francesco Innocenti; Math J. J. M. Candel; Frans E. S. Tan; Gerard J. P. van Breukelen – Journal of Educational and Behavioral Statistics, 2024
Normative studies are needed to obtain norms for comparing individuals with the reference population on relevant clinical or educational measures. Norms can be obtained in an efficient way by regressing the test score on relevant predictors, such as age and sex. When several measures are normed with the same sample, a multivariate regression-based…
Descriptors: Sample Size, Multivariate Analysis, Error of Measurement, Regression (Statistics)
George Kinnear – Research in Mathematics Education, 2024
Prompting learners to generate examples has been proposed as an effective way of developing understanding of a new concept. However, empirical support for this approach is lacking. This article presents two empirical studies on the use of example-generation tasks in an online course in introductory university mathematics. The first study compares…
Descriptors: Comparative Analysis, Classification, Task Analysis, Mathematics Instruction
Jehanzeb Rashid Cheema – Journal of Education in Muslim Societies, 2024
This study explores the relationship between the Spiral Dynamics and the 3H (head, heart, hands) models of human growth and development, using constructs such as empathy, moral reasoning, forgiveness, and community mindedness that have been shown to have implications for education. The specific research question is, "Can a combination of…
Descriptors: Correlation, Factor Analysis, Computer Software, Moral Values
Kalender Arikan – Journal of Baltic Science Education, 2025
Learning style (LS), either visual or verbal, has become debatable in the f ield of education vis-à-vis its relation to student success. However, it remains a valuable research theme for improving learning activities in the teaching of highly visual science fields, including biology, physics, and chemistry. Previous studies have primarily focused…
Descriptors: Cognitive Style, Biology, Retention (Psychology), Science Education
Laura del Hoyo Soriano; Audra Sterling; Jamie Edgin; Debra R. Hamilton; Elizabeth Berry-Kravis; Amanda Dimachkie Nunnally; Angela John Thurman; Leonard Abbeduto – Journal of Autism and Developmental Disorders, 2024
This study explores sex-differences in (a) rates and profiles of autism symptoms as well as in (b) the contribution of intellectual quotient (IQ) to autism symptom presentation in Down syndrome (DS). Participants were 40 males and 38 females with DS, aged 6 to 23 years. Autism symptoms were rated through the Autism Diagnostic Observation…
Descriptors: Correlation, Gender Differences, Autism Spectrum Disorders, Observation
Andrew R. Thompson – Advances in Physiology Education, 2024
The revised two-factor Study Process Questionnaire and the Approaches and Study Skills Inventory for Students are two instruments commonly used to measure student learning approach. Although they are designed to measure similar constructs, it is unclear whether the metrics they provide differ in terms of their real-world classification of learning…
Descriptors: Comparative Analysis, Anatomy, Classification, Cognitive Style
Yuanfang Liu; Mark H. C. Lai; Ben Kelcey – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Measurement invariance holds when a latent construct is measured in the same way across different levels of background variables (continuous or categorical) while controlling for the true value of that construct. Using Monte Carlo simulation, this paper compares the multiple indicators, multiple causes (MIMIC) model and MIMIC-interaction to a…
Descriptors: Classification, Accuracy, Error of Measurement, Correlation
E. Gothai; S. Saravanan; C. Thirumalai Selvan; Ravi Kumar – Education and Information Technologies, 2024
In recent years, online education has been given more and more attention with the widespread use of the internet. The teaching procedure divides space and makes time for online learning; though teachers cannot control the learners accurately, the state of education calculates learners' learning situation. This paper explains that the discourse…
Descriptors: Artificial Intelligence, Discourse Analysis, Classification, Comparative Analysis
Sedat Sen; Allan S. Cohen – Educational and Psychological Measurement, 2024
A Monte Carlo simulation study was conducted to compare fit indices used for detecting the correct latent class in three dichotomous mixture item response theory (IRT) models. Ten indices were considered: Akaike's information criterion (AIC), the corrected AIC (AICc), Bayesian information criterion (BIC), consistent AIC (CAIC), Draper's…
Descriptors: Goodness of Fit, Item Response Theory, Sample Size, Classification
Christine M. White; Christopher Schatschneider – Contemporary School Psychology, 2024
Universal screening to predict students' risk for reading problems is a foundational component of the Multi-Tiered Systems of Support framework and is required by law in many US states. School or district administrators are tasked with selecting screening assessments that are both technically adequate and feasible given the resources of their…
Descriptors: Screening Tests, Reading Tests, Reading Difficulties, Classification
Anikó Fehérvári; Krisztián Széll – Intercultural Education, 2024
The present paper explores approaches to the classification of ethnic identity. In the framework of research on comparative classifications, we analyse the contextual factors that influence classification in Hungarian education. We compared the number of students who self-reported as Roma with the respective number reported by the school heads (as…
Descriptors: Minority Groups, Minority Group Students, Classification, Self Concept
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