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Download full textSaida Ulfa; Ence Surahman; Izzul Fatawi; Hirashima Tsukasa – Electronic Journal of e-Learning, 2024
The purpose of this study was to evaluate the factors that influence behavioural intention (BI) to use the Online Summary-with Automated Feedback (OSAF) in a MOOCs platform. Task-Technology Fit (TTF) was the main framework used to analyse the match between task requirements and technology characteristics, predictng the utilisation of the…
Descriptors: MOOCs, Intention, Automation, Feedback (Response)
Kraisila Kanont; Pawarit Pingmuang; Thewawuth Simasathien; Suchaya Wisnuwong; Benz Wiwatsiripong; Kanitta Poonpirome; Noawanit Songkram; Jintavee Khlaisang – Electronic Journal of e-Learning, 2024
This study investigates the factors influencing the adoption of Generative-AI tools amongst Thai university students, employing the Technology Acceptance Model (TAM) as a theoretical framework. Data from 911 higher education students from 10 different Thai Universities Health Sciences, Sciences and Technology, Social Sciences and Humanities, and…
Descriptors: Artificial Intelligence, College Students, Student Attitudes, Educational Technology
Hanadi Aldreabi; Nisreen Kareem Salama Dahdoul; Mohammad Alhur; Nidal Alzboun; Najeh Rajeh Alsalhi – Electronic Journal of e-Learning, 2025
The examination of the impact of Generative AI (GenAI) on higher education, especially from the viewpoint of students, is gaining significance. Although prior research has underscored GenAI's potential advantages in higher education, there exists a discernible research gap concerning the determinants that affect its adoption. In the present study,…
Descriptors: Student Behavior, Artificial Intelligence, Natural Language Processing, Technology Uses in Education
Tri Lathif Mardi Suryanto; Aji Prasetya Wibawa; Hariyono; Andrew Nafalski; Hechmi Shili – Electronic Journal of e-Learning, 2025
This study delves into the adoption of chatbot technology in higher education, with a focus on Indonesian online learning environments. Recognizing the potential of AI-driven tools to address academic support gaps, particularly in developing regions, the research explores how performance expectancy, effort expectancy, and facilitating conditions…
Descriptors: Foreign Countries, Artificial Intelligence, Technology Uses in Education, Higher Education
