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Yongtian Cheng; K. V. Petrides – Educational and Psychological Measurement, 2025
Psychologists are emphasizing the importance of predictive conclusions. Machine learning methods, such as supervised neural networks, have been used in psychological studies as they naturally fit prediction tasks. However, we are concerned about whether neural networks fitted with random datasets (i.e., datasets where there is no relationship…
Descriptors: Psychological Studies, Artificial Intelligence, Cognitive Processes, Predictive Validity
Ilhan Çiçek; Mete Sipahioglu; Ümit Dilekçi – Psychology in the Schools, 2026
This study aims to examine the mediating roles of resilience and occupational self-efficacy in the relationship between occupational stress and subjective well-being and to adapt the Teacher Occupational Self-Efficacy-Short Form (OSS-SF) to Turkish culture. Using a cross-sectional design, convenience sampling was employed to collect the data. The…
Descriptors: Self Efficacy, Stress Variables, Teaching (Occupation), Resilience (Psychology)
Ali Geris; Taibe Kulaksiz – Research in Learning Technology, 2025
This study aims to investigate the factors influencing teachers' intentions to integrate Virtual Reality (VR) technology into their educational practices, utilising the Unified Theory of Acceptance and Use of Technology (UTAUT-2) framework. The research involved adapting and validating the 'Acceptance of Mobile Immersive Virtual Reality in…
Descriptors: Technology Integration, Computer Simulation, Teacher Attitudes, Intention
Katherine E. Castellano; Daniel F. McCaffrey; Joseph A. Martineau – Educational Measurement: Issues and Practice, 2025
Growth-to-standard models evaluate student growth against the growth needed to reach a future standard or target of interest, such as proficiency. A common growth-to-standard model involves comparing the popular Student Growth Percentile (SGP) to Adequate Growth Percentiles (AGPs). AGPs follow from an involved process based on fitting a series of…
Descriptors: Student Evaluation, Growth Models, Student Educational Objectives, Educational Indicators
Caroline F. Rowland; Amy Bidgood; Gary Jones; Andrew Jessop; Paula Stinson; Julian M. Pine; Samantha Durrant; Michelle S. Peter – Language Learning, 2025
A strong predictor of children's language is performance on non-word repetition (NWR) tasks. However, the basis of this relationship remains unknown. Some suggest that NWR tasks measure phonological working memory, which then affects language growth. Others argue that children's knowledge of language/language experience affects NWR performance. A…
Descriptors: Vocabulary Development, Comparative Analysis, Computational Linguistics, Language Skills
Anders Holm; Anders Hjorth-Trolle; Robert Andersen – Sociological Methods & Research, 2025
Lagged dependent variables (LDVs) are often used as predictors in ordinary least squares (OLS) models in the social sciences. Although several estimators are commonly employed, little is known about their relative merits in the presence of classical measurement error and different longitudinal processes. We assess the performance of four commonly…
Descriptors: Elementary Education, Scores, Error of Measurement, Predictor Variables
Paul T. von Hippel; Brendan A. Schuetze – Annenberg Institute for School Reform at Brown University, 2025
Researchers across many fields have called for greater attention to heterogeneity of treatment effects--shifting focus from the average effect to variation in effects between different treatments, studies, or subgroups. True heterogeneity is important, but many reports of heterogeneity have proved to be false, non-replicable, or exaggerated. In…
Descriptors: Educational Research, Replication (Evaluation), Generalizability Theory, Inferences
Casey J. Metoyer; Katherine Sullivan; Lee J. Winchester; Mark T. Richardson; Michael R. Esco; Michael V. Fedewa – Measurement in Physical Education and Exercise Science, 2025
Relative adiposity (%Fat) was measured using a smartphone-based application in a convenience sample of adults aged 20-52 years (n = 32, 68.7% female, 84.3% White/Caucasian, 26.7 ± 3.5 kg/m2) across different body positions (Anterior versus Posterior) on consecutive days (Day 1 versus Day 2). A reference photo was obtained from the posterior view…
Descriptors: Adults, Body Composition, Handheld Devices, Computer Assisted Instruction
Carey Bernini Dowling; C. Veronica Smith; Yue Yin; Jeffrey M. Williams – Journal of the Scholarship of Teaching and Learning, 2025
People view many attributes, including intelligence, through implicit theories (or mindsets). Entity mindsets position the attribute as unchangeable or static, whereas incremental mindsets see the attribute as malleable or capable of being changed/improved (Dweck & Leggett, 1988). The present studies examined a new questionnaire designed to…
Descriptors: Grade Point Average, Undergraduate Students, Study Habits, Intelligence
Bahar Bahtiyar-Saygan – Infant Mental Health Journal: Infancy and Early Childhood, 2025
The crucial importance of parenting for human development is well known, yet there has been little investigation, particularly regarding infancy parenting. This study investigates mother- and infant-related characteristics affecting parenting styles in the first year after birth. Additionally, adapting an Infancy Parenting Styles Questionnaire…
Descriptors: Foreign Countries, Infants, Parenting Styles, Questionnaires
Madina Bekturova; Saule Tulepova; Altnay Zhaitapova – Education and Information Technologies, 2025
The advancement of technologies has resulted in the boost of a popular chatbot software -- ChatGPT. It is ripe with potential, yet has introduced various challenges, especially in the world of education. This paper aims to explore how TEFL (Teaching English as a foreign language) students perceive the usefulness and ease of using ChatGPT in regard…
Descriptors: Foreign Countries, Predictor Variables, Second Language Learning, English (Second Language)
Liwei Hsu – European Journal of Education, 2025
As generative artificial intelligence (GenAI) increasingly penetrates language education, understanding learners' continued intention to use this technology becomes crucial. This study examines EFL learners' continuance intention to use GenAI for language learning through PLS-SEM and fsQCA methodologies. Participants were undergraduate EFL…
Descriptors: Second Language Learning, English (Second Language), Artificial Intelligence, Student Attitudes
Min Pan; Wei-Ting Hsu – Measurement in Physical Education and Exercise Science, 2025
Constraints-led approach (CLA) is widely used in physical education (PE). This four-phased study aimed to develop a self-report measurement of students' perceived constraints support in PE. The relationships among students' perceived constraints support, competence and novelty need satisfaction, motivation, effort, and engagement in PE were also…
Descriptors: Physical Education, Student Attitudes, Test Construction, Test Validity
Dina Fitria Murad; Meta Amalya Dewi; Arbaiah Inn; Silvia Ayunda Murad; Noor Udin; Taufik Darwis – Journal of Educators Online, 2025
This study aims to produce a more personalized recommendation system for online learning using multicriteria in collaborative filtering and data from the Binus Online Learning repository as a knowledge base. The study uses forecasting (regression) and consists of three stages: (1) collecting data on the results of the learning process; (2) adding…
Descriptors: Electronic Learning, Data Collection, Context Effect, Learning Processes
Thao-Trang Huynh-Cam; Long-Sheng Chen; Tzu-Chuen Lu – Journal of Applied Research in Higher Education, 2025
Purpose: This study aimed to use enrollment information including demographic, family background and financial status, which can be gathered before the first semester starts, to construct early prediction models (EPMs) and extract crucial factors associated with first-year student dropout probability. Design/methodology/approach: The real-world…
Descriptors: Foreign Countries, Undergraduate Students, At Risk Students, Dropout Characteristics

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