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Ayça Fidan; Yasemin Koçak Usluel – Education and Information Technologies, 2024
It is pointed out that one of the main problems of online learning environments is determining whether students engage or not. As engagement is a complex and multifaceted concept, researchers have stated that engagement is effected by many factors (environmental conditions and learner characteristics) and changes according to the context. Among…
Descriptors: Online Courses, Electronic Learning, Metacognition, Emotional Response
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
Lars de Vreugd; Anouschka van Leeuwen; Marieke van der Schaaf – Journal of Computer Assisted Learning, 2025
Background: University students need to self-regulate but are sometimes incapable of doing so. Learning Analytics Dashboards (LADs) can support students' appraisal of study behaviour, from which goals can be set and performed. However, it is unclear how goal-setting and self-motivation within self-regulated learning elicits behaviour when using an…
Descriptors: Learning Analytics, Educational Technology, Goal Orientation, Learning Motivation
Kheira Ouassif; Benameur Ziani – Education and Information Technologies, 2025
The integration of educational data mining and deep neural networks, along with the adoption of the Apriori algorithm for generating association rules, focuses to resolve the problem of misdirection of students in the university, leading to their failure and dropout. This is reached through the development of an intelligent model that predicts the…
Descriptors: Predictor Variables, College Students, Majors (Students), Decision Making
Jovanka, Della Raymena; Habibi, Akhmad; Mailizar, Mailizar; Yaqin, Lalu Nurul; Kusmawan, Udan; Yaakob, Mohd Faiz Mohd; Tanu Wijaya, Tommy – Cogent Education, 2023
The Internet has been massively utilized for educational purposes during the last ten years with many platforms, including e-Learning Services (e-LS). This survey study aimed to report factors affecting the intention to use e-LS in the Indonesian Open University (OU) context. The original technology acceptance model (TAM) was extended, involving…
Descriptors: Foreign Countries, Electronic Learning, College Students, Student Attitudes
Altinpulluk, Hakan; Kilinc, Hakan; Alptekin, Gokhan; Yildirim, Yusuf; Yumurtaci, Onur – Open Praxis, 2023
The aim of this study was to determine the relationship between the intrinsic motivation levels and self-directed learning levels of learners within a massive open online course environment. In addition, the relationship between these variables and the technology competences/average daily use times of technology were also studied. This study was…
Descriptors: MOOCs, Independent Study, Student Motivation, Correlation
Oronzo Mazzeo; Lucia Monacis; Paolo Contini – Turkish Online Journal of Distance Education, 2025
The study aimed to analyze the influence of such factors, as cognitive engagement, learning strategies and social support on academic success and student satisfaction in online learning environments. Data were collected in a cross-sectional survey carried out in the Winter semester of 2023. Participants were 523 students recruited from…
Descriptors: Success, Student Satisfaction, Online Courses, College Students
María García de Blanes Sebastián; José Ramón Sarmiento Guede; Alberto Azuara Grande; Antonio Ferrao Filipe – Education and Information Technologies, 2025
During COVID-19 pandemic, Mobile learning (M-learning) was implemented in many universities to continue teaching. Consequently, its use has increased drastically, facing new challenges and benefits. The main aim of this research is to adopt the Unified Theory of Acceptance and Use of Extended Technology (UTAUT-2) to determine the intention of…
Descriptors: Telecommunications, Handheld Devices, Educational Technology, Technology Uses in Education
Sointu, Erkko; Hyypiä, Mareena; Lambert, Matthew C.; Hirsto, Laura; Saarelainen, Markku; Valtonen, Teemu – Higher Education: The International Journal of Higher Education Research, 2023
Flipped classrooms have become widely adopted in educational settings (e.g., in higher education) worldwide. However, there is a need for more precise understanding of the ingredients for student satisfaction in a flipped setting. The aim of this paper was to investigate university students' experiences of the factors that create a successful…
Descriptors: Flipped Classroom, Educational Technology, Student Satisfaction, College Students
Xiao, Jun; Jiang, Zhujun – International Journal of Mobile and Blended Learning, 2023
Mobile learning provides more flexibility and holds considerable promise for improving the learning process and promoting lifelong learning. In order to reduce the sense of isolation felt by the learners, this research integrates mobile learning in the blended synchronous learning environment (BSLE). This study proposed a mobile learning model in…
Descriptors: Telecommunications, Handheld Devices, Blended Learning, Synchronous Communication
Hong, Jon-Chao; Cao, Wei; Liu, Xiaohong; Tai, Kai-Hsin; Zhao, Li – Journal of Research on Technology in Education, 2023
Due to COVID-19, the primary teaching method has changed from traditional face-to-face teaching to online teaching. The present study explored the correlates between two personality traits, Neuroticism and Extraversion, and two types of self-efficacy, Internet self-efficacy and academic self-efficacy, on practical performance anxiety. Data from…
Descriptors: Personality Traits, Predictor Variables, Internet, Self Efficacy
Hui-Tzu Hsu; Chih-Cheng Lin – Journal of Computer Assisted Learning, 2024
Background: Behavioural intention (BI) has been predicted using other variables by adopting the technology acceptance model (TAM). However, few studies have examined whether BI can predict learning performance. Objectives: The present study used an extended TAM to investigate whether students' BI is a predictor of their listening learning…
Descriptors: Intention, Vocabulary Development, Handheld Devices, College Students
Zacharis, Georgios; Nikolopoulou, Kleopatra – Education and Information Technologies, 2022
The use of eLearning platforms has made it possible to continue the learning process in universities, and other educational institutions, during the COVID pandemic. Students' acceptance of eLearning is important because it is associated with their engagement in the online teaching--learning environment. This study used the Unified Theory of…
Descriptors: Predictor Variables, College Students, Student Attitudes, Intention
Bag, Sudin; Aich, Payel; Islam, Md. Aminul – Journal of Applied Research in Higher Education, 2022
Purpose: The aim of the study is to examine the intention of students toward the online education system with emphasis on online examination in higher education. The study investigated different constructs that have an influence on the use of the online platform for learning to the specific domain that mitigates the personal needs of the learners…
Descriptors: Intention, Student Attitudes, College Students, Online Courses
Hakami, Tahani Ali; Al-Shargabi, Bassam; Sabri, Omar; Khan, Syed Md Faisal Ali – Journal of Educators Online, 2023
The information revolution has transformed higher education. After the COVID-19 pandemic, teachers and instructors were encouraged to improve technology-enhanced teaching methods. Furthermore, various factors influenced the adoption of internet and digital-based technologies as an aspect of teaching methodology, including its usefulness, ease of…
Descriptors: Foreign Countries, Educational Technology, Technology Integration, Electronic Learning