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Valentine Joseph Owan; Ibrahim Abba Mohammed; Ahmed Bello; Tajudeen Ahmed Shittu – Contemporary Educational Technology, 2025
Despite the increasing interest in artificial intelligence technologies in education, there is a gap in understanding the factors influencing the adoption of ChatGPT among Nigerian higher education students. Research has not comprehensively explored these factors in the Nigerian context, leaving a significant gap in understanding technology…
Descriptors: Student Behavior, Foreign Countries, Artificial Intelligence, Natural Language Processing
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Taneja, Mohit; Kiran, Ravi; Bose, S. C. – Studies in Higher Education, 2024
This work investigates the impact of entrepreneurial experiential learning (EL) on students' entrepreneurial intention (EI), through the lens of entrepreneurial self-efficacy (ESE). To provide a comprehensive viewpoint, the direct impact of entrepreneurial attitude (EA) on entrepreneurial intention has also been looked at. This study, has adopted…
Descriptors: Entrepreneurship, Intention, Experiential Learning, Self Efficacy
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Megan E. Douglas; Heidemarie Blumenthal; Charles A. Guarnaccia – Journal of American College Health, 2024
Objective: The transition to college is marked by poorer eating behaviors, making emerging adulthood a particularly salient intervention point for improving lifelong health. The present study aims to better understand what psychosocial factors predict eating behaviors of college students using the Theory of Planned Behavior (TPB). Participants…
Descriptors: College Students, Eating Habits, Predictor Variables, Food
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Tiana P. Johnson-Clements; Guy J. Curtis; Joseph Clare – Journal of Academic Ethics, 2025
Concerns over students engaging in various forms of academic misconduct persist, especially with the post-COVID-19 rise in online learning and assessment. Research has demonstrated a clear role of the personality trait psychopathy in cheating, yet little is known about why this relationship exists. Building on the research by Curtis et al.…
Descriptors: Pandemics, COVID-19, Cheating, Electronic Learning
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Montathar Faraon; Kari Rönkkö; Marcelo Milrad; Eric Tsui – Education and Information Technologies, 2025
This study explored factors influencing ChatGPT adoption among higher education students in five Nordic countries (Sweden, Finland, Denmark, Norway, and Iceland) and the USA. The unified theory of acceptance and use of technology 2 (UTAUT2) framework was employed and extended to incorporate personal innovativeness. Data was collected from 586…
Descriptors: Artificial Intelligence, Technology Uses in Education, Higher Education, College Students
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Hermann Kurthen; Anna Hammersmith – Frontiers: The Interdisciplinary Journal of Study Abroad, 2024
Although more students study abroad today than in decades prior, participation still lags behind national goals put forth by the Lincoln Commission. Many students plan to study abroad, yet this often does not correspond with actual participation. This gap suggests there are barriers that prevent study abroad intentions from evolving into program…
Descriptors: Study Abroad, Barriers, Intention, Student Participation
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Miftah Arifin; Anas Ma'ruf Annizar; Moh. Khusnuridlo; Abd. Halim Soebahar; Agus Yudiawan – Journal of Education and e-Learning Research, 2025
This study examines a level and model for technology acceptability and use in online learning inside universities. The unified theory of UTAUT is used as an analysis tool. An associative quantitative method is used with a sample of 392 students. Data were collected by distributing questionnaires through a specially designed Google Form. The data…
Descriptors: Educational Technology, Electronic Learning, Technology Uses in Education, College Students
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Ana M. Gallardo-Guerrero; María J. Maciá-Andreu; Noelia González-Gálvez; Raquel Vaquero-Cristóbal; Marta García-Tascón – Education and Information Technologies, 2025
The main objectives of this research were to analyze the impact of the use of augmented reality (AR) for analyzing the safety of sport equipment, on the motivational climate, behavior, and intention to use, and to validate a theoretical model for predicting continuance intention to use AR among students. The sample consisted of 254 university…
Descriptors: Simulated Environment, Safety, Athletics, Equipment
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Amy M. Kemp; Gabriella Norton; Madison Neese; Yalian Pei; Katy H. O'Brien – Journal of American College Health, 2025
Objective: This mixed method study examined how psychosocial factors from the Theory of Planned Behavior and Reasoned Action (TPB/RA) influence health-seeking behaviors after concussion, expanding from student-athlete TPB/RA research to assess the influence of psychosocial factors within a general college population. Participants: Two hundred and…
Descriptors: Health Behavior, Head Injuries, Brain, Student Athletes
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Moon-Heum Cho; Eunjung Grace Oh; Yunjeong Chang; Seokwon Hwang – Distance Education, 2025
The purpose of this study was to examine the relationships among MOOC learners' personal goal achievement, instructor goal achievement, learning experiences measured with perceived learning and course satisfaction, and their continuance intention in a MOOC offered by a research university in the United States. A total of 203 MOOC learners…
Descriptors: MOOCs, Goal Orientation, Technology Uses in Education, Intention
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Chinelo Orji; Carolyn M. Brown; Jamie Barner; Leticia Moczygemba; Daisy Morales-Campos – Journal of American College Health, 2025
Purpose: To determine college students' intentions to be Human Papillomavirus (HPV) vaccinated. Methods: The study was comprised of college students aged 18-45 years. A survey was developed based on the Theory of Planned Behavior (TPB). The significance of the TPB constructs--attitude, subjective norms, and perceived behavioral control--and an…
Descriptors: Immunization Programs, Sexually Transmitted Diseases, Intention, College Students
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Hüseyin Gokal; Cem Ufuk Baytar – Turkish Online Journal of Educational Technology - TOJET, 2025
This study aims to examine university students' intentions to use artificial intelligence (AI) applications in their educational processes within the context of job characteristics (JC), technology characteristics (TC), task-technology fit (TTF), and self-efficacy (SE). The research was conducted with 965 students enrolled in Information…
Descriptors: College Students, Intention, Technology Uses in Education, Artificial Intelligence
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Humida, Thasnim; Al Mamun, Md Habib; Keikhosrokiani, Pantea – Education and Information Technologies, 2022
Digital transformation and emerging technologies open a horizon to a new method of teaching and learning and revolutionizes the e-learning industry. The goal of this study is to scrutinize a proposed research model for predicting factors that influence student's behavioral intention to use e-learning system at Begum Rokeya University, Bangladesh.…
Descriptors: Student Behavior, Intention, Electronic Learning, College Students
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Clara Mumme; Laura M. Leipert; Regina Vollmeyer – Discover Education, 2025
This study investigates the predictive influences of expectancies and values that may sustain students' dropout intentions in physics as well as gender differences in students' motivation and intention. Eccles's expectancy-value model was used to frame the study. The academic self-concept (expectancy component) and value components focusing on…
Descriptors: Foreign Countries, Expectation, Values, Dropout Attitudes
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Meng Na; Mazzlida Mat Deli; Ummu Ajirah Abdul Rauf – SAGE Open, 2025
Understanding the decision-making process behind international student mobility requires an integrated analysis of both external and internal drivers. This study examines the pivotal role of self-efficacy--a student's belief in their ability to succeed--in shaping the intention of Chinese students to study in Malaysia, a rising education…
Descriptors: Foreign Countries, Self Efficacy, Student Attitudes, Foreign Students
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