NotesFAQContact Us
Collection
Advanced
Search Tips
Showing 1,216 to 1,230 of 29,616 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Arif Hasan; Sandeep Raghuwanshi; Hiren Harsora; Prabhat Kumar; Vivek Gupta; Ardhendu Shekhar Singh – Discover Education, 2025
Purpose: The present research is interested in evaluating the Unified Theory of Acceptance and Use of Technology (UTAUT) model and its extra predictors to examine those factors which determine the millennials and elearning issue. The relationship between behaviour intentions (BI) and further process of adopting elearning is the result on which the…
Descriptors: Electronic Learning, Age Groups, Intention, Technology Uses in Education
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Tunggul Sihombing; Katarina Triana Tinambunan – Educational Process: International Journal, 2025
Background/purpose: The growing environmental issues in Medan City, particularly regarding plastic use and its detrimental effects, have prompted the Indonesian Forum for the Environment (WALHI) to launch the Green Student Movement (GSM) program. This program aims to raise awareness and involve youth in tackling environmental and humanitarian…
Descriptors: Foreign Countries, Environmental Education, Consciousness Raising, Student Behavior
Peer reviewed Peer reviewed
Direct linkDirect link
Toshna Pandey; Alexa Budavari; Catherine P. Bradshaw – Society for Research on Educational Effectiveness, 2025
Background/Context: Student behavior problems are a significant concern for educators; if unaddressed, these problems can result in major disruptions in the educational experience for many students. Moreover, these challenges can also cause significant frustration for teachers, leading to burnout, stress, and in some cases teacher turnover…
Descriptors: Coaching (Performance), Classroom Techniques, Evidence Based Practice, Fidelity
Peer reviewed Peer reviewed
Direct linkDirect link
Xiaohong Ji; Xin Liu; Xin Chen; Rong Li – Education and Information Technologies, 2025
Students classroom behaviours are complex and variable, involving multiple aspects such as students personality traits, learning attitudes, thinking styles and learning abilities, but traditional classroom behavioural assessment cannot comprehensively and reasonably assess students classroom learning status. The study adopts the improved Yolov5…
Descriptors: Student Behavior, Classroom Techniques, Artificial Intelligence, Identification
Peer reviewed Peer reviewed
Direct linkDirect link
Hong Thi Nguyen; Lan Thi Pham; Viet Anh Nguyen; Kien Trung Do – International Journal of Information and Learning Technology, 2025
Purpose: Predicting learner outcomes in blended learning (BL) is a new problem with many challenges, as learner data must be collected in both face-to-face and online environments. The purpose of this article is to identify the best method for building a model to predict student performance in BL and to determine the appropriate time for early…
Descriptors: Blended Learning, Student Behavior, In Person Learning, Artificial Intelligence
Peer reviewed Peer reviewed
Direct linkDirect link
Yavuz Dinc; Sarah Malone; Verena Ruf; Steffen Steinert; Stefan Küchemann; Jochen Kuhn – Physical Review Physics Education Research, 2025
Prior research has demonstrated that students' performance on physics test items can be accurately predicted using machine learning algorithms based on their gaze behavior. These gaze data are typically recorded during item completion and capture students' visual attention to both the verbal item stem and accompanying visual representations, such…
Descriptors: Artificial Intelligence, Computer Uses in Education, Eye Movements, Test Items
Peer reviewed Peer reviewed
Direct linkDirect link
Eduardo Real; Edson Pimentel – Technology, Knowledge and Learning, 2025
In Virtual Learning Environments (VLEs), teachers usually organize the sequence of course contents and activities according to their didactic-pedagogical strategies, expecting to guide each student in his learning path. However, usually, each student follows a specific path based on his actions. VLEs typically record student interaction with…
Descriptors: Models, Electronic Learning, Interaction, Student Behavior
Peer reviewed Peer reviewed
Direct linkDirect link
Bueckmann-Diegoli, Rafaela; García de los Salmones Sánchez, María del Mar; San Martín Gutiérrez, Héctor – Education & Training, 2021
Purpose: The main goal of this work is to argue the theoretical validity of two competitive models that integrate entrepreneurial alertness in the Theory of Planned Behavior (TPB), and also to propose an explanation for the conceptual approach with a higher explicative ability. Design/Methodology/Approach: A total of 281 undergraduate students…
Descriptors: Entrepreneurship, Undergraduate Students, Behavior Theories, Models
Kahan, Sara Kaweblum; Fairchild, Lyndsay A.; Womack, Tyler A.; Fallon, Lindsay; Dart, Evan – Communique, 2021
Functional assessments, while considered the "gold standard" for behavioral assessments, are not often implemented in school settings due the extensive amount of time, resources, and expertise required. The interview-informed synthesized contingency analysis (IISCA), is a timely, comprehensive, and accurate method for conducting such…
Descriptors: Functional Behavioral Assessment, Interviews, Evaluation Methods, Student Behavior
Peer reviewed Peer reviewed
PDF on ERIC Download full text
marbley, aretha faye; Lertora, Ian; Back, Arlette; Abbott, Paula; Dunn, Patrice; Crews, Charles – Multicultural Education, 2021
The authors assert that the American School Counselor Association (ASCA) model and its companion documents provide school counselors with a comprehensive framework for intervening to prevent violence. This article is a brief overview of the model, the competencies, and the standards, which are used as theoretical lenses for addressing gun violence…
Descriptors: Counselors, School Safety, Models, Student Attitudes
Mei Fong Zhang – ProQuest LLC, 2021
The purpose of this study was to examine the effect of stress on alcohol consumption and other avoidant coping strategies among college students. Two affective variables that may serve as risk factors underlying problem drinking and other avoidant coping styles are distress tolerance (DT) and anxiety sensitivity (AS). Additionally, two…
Descriptors: Anxiety, Stress Variables, Student Behavior, College Students
Peer reviewed Peer reviewed
Direct linkDirect link
Lopes, João M.; Laurett, Rozélia; Ferreira, João J.; Silveira, Paulo; Oliveira, José; Farinha, Luís – Industry and Higher Education, 2023
This study analyzes the predictive factors influencing the entrepreneurial intentions of students at higher education institutions (HEIs) in a peripheral European region. The study includes a sample of 594 students and uses structural equation models for data analysis. The results show that the attitude to behavior and perceived behavioral control…
Descriptors: Foreign Countries, College Students, Entrepreneurship, Intention
Peer reviewed Peer reviewed
Direct linkDirect link
Kälin, Sonja; Roebers, Claudia M.; Oeri, Niamh – Early Education and Development, 2023
Research Findings: The goal of this longitudinal study was to examine persistence development during the transition to school. The sample consisted of N = 88 children from Caucasian, middle-class families (51% female). Participants were recruited through advertisement in public kindergartens and were tested twice, in kindergarten (mean…
Descriptors: Academic Persistence, Student Adjustment, Profiles, Kindergarten
Peer reviewed Peer reviewed
Direct linkDirect link
Ledford, Jennifer R.; Zimmerman, Kathleen N. – Remedial and Special Education, 2023
A number of resources are available for evaluating the rigor of single-case designs, including the commonly used multiple baseline design. In this article, we discuss two characteristics commonly cited as necessary for the highest rigor in multiple baseline designs--concurrence and response-guided baseline condition duration. We suggest that both…
Descriptors: Research Methodology, Research Design, Behavior Change, Intervention
Peer reviewed Peer reviewed
Direct linkDirect link
Lu, Chun; Yang, Wei; Wu, Longkai; Yang, Xiao – Journal of Science Education and Technology, 2023
Understanding factors that influence k-12 students' Science, Technology, Engineering, and Mathematics (STEM) performance is essential to improving their problem-solving ability. Most studies have focused on the relationship between students' psychological factors and STEM performance and have paid little attention to the relationship between…
Descriptors: Student Behavior, Psychological Patterns, STEM Education, Elementary Secondary Education
Pages: 1  |  ...  |  78  |  79  |  80  |  81  |  82  |  83  |  84  |  85  |  86  |  ...  |  1975