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Luping Wang; Yun Hao; Shanshan Wang – Discover Education, 2025
In the traditional teaching mode, it is difficult for teachers to have a comprehensive understanding of each student's study, and it is also hard for them to provide targeted guidance and assistance. With the development of data collection and analysis technology, schools and educational institutions can make better use of big data technology to…
Descriptors: College Students, Predictor Variables, Scores, Academic Achievement
Kundi, Ghulam Muhammad – Journal of Educators Online, 2023
The objective of the study was to investigate the relationship between elearning and the academic achievement of research scholars in healthcare's higher education institutions using multimediators. The study used a theoretical network approach for the review of the literature and the Barron & Kenny model for mediation. The study employed a…
Descriptors: Health Services, Researchers, Scholarship, Higher Education
LiuJie Xu; Ling Chen; Yiran Chen – Education and Urban Society, 2024
The Expert-based Collective Advising Mechanism (ECAM) was embedded in the open online tutoring project to provide free tutoring for rural students and to help them improve their academic performance, and thus, to solve education inequity. Taking urban and rural students in Tongzhou District of Beijing as the objects, this study gathered data on…
Descriptors: Foreign Countries, Rural Education, Tutoring, Academic Advising
Sevim-Cirak, Nese; Erol, Osman; Baser-Gulsoy, Vesile Gul – Journal of Educational Technology and Online Learning, 2023
Students' readiness for e-learning is necessary in order to make the e-learning process more effective. Readiness for e-learning refers to the degree of having pre-knowledge and skills, and affective characteristics such as the necessary attitude and motivation to experience this process most effectively. Academic orientations of the students also…
Descriptors: College Students, Electronic Learning, Readiness, Goal Orientation
Sonia Muhammad Almwalad – ProQuest LLC, 2023
Problem: Online learning is a form of distance education that occurs via the Internet (Adams, 2004; Carliner, 1999). The success of online learning depends on student-related factors such as acceptance, willingness, and motivation (Almaiah et al., 2019; Almaiah et al., 2020). When online learning systems are not utilized, students cannot realize…
Descriptors: Undergraduate Students, Electronic Learning, Self Management, Achievement Need
Being Learners with Mental Resilience as Outcomes of Metacognitive Strategies in an Academic Context
Anthonysamy, Lilian – Cogent Education, 2023
The primary objective of this paper is twofold; firstly, to analyse the relationship between metacognitive strategies and learning performance. Secondly, a new mediator is proposed, namely digital literacy. Mental resilience is an omnitemporal skill that enables individuals to gain resilience thinking to successfully adapt to life tasks. Although…
Descriptors: Resilience (Psychology), Metacognition, Outcomes of Education, Academic Achievement
Wang, Qiang; Song, Xin; Hong, Jon-Chao; Li, Shuang; Zhang, Mengmeng; Yang, Xiantong – Education and Information Technologies, 2023
In response to the wide-ranging concern of online academic futility, the current study aimed to explore the independent variables and mediating variable from a novel perspective of parents during COVID-19. Based on the social comparison theory and the control-value theory of achievement emotions, social comparison and tutoring anxiety were…
Descriptors: Self Concept, Tutoring, Anxiety, Parent Attitudes
Nayak, Padmalaya; Vaheed, Sk.; Gupta, Surbhi; Mohan, Neeraj – Education and Information Technologies, 2023
Students' academic performance prediction is one of the most important applications of Educational Data Mining (EDM) that helps to improve the quality of the education process. The attainment of student outcomes in an Outcome-based Education (OBE) system adds invaluable rewards to facilitate corrective measures to the learning processes.…
Descriptors: Predictor Variables, Academic Achievement, Data Collection, Information Retrieval
Astatke, Melese; Weng, Cathy; Chen, Sufen – Interactive Learning Environments, 2023
Due to COVID-19 pandemic, schools all over the world have gone from full face-to-face to online lessons. This paper analyzed the influences of social networking sites (SNS) on secondary school students' academic achievement. The original studies were extracted from the Web of Science database, and the review of the 27 selected journal articles…
Descriptors: Literature Reviews, Social Networks, Secondary School Students, Academic Achievement
Analysis and Prediction of Students' Performance in a Computer-Based Course through Real-Time Events
Lucia Uguina-Gadella; Iria Estevez-Ayres; Jesus Arias Fisteus; Carlos Alario-Hoyos; Carlos Delgado Kloos – IEEE Transactions on Learning Technologies, 2024
Students learn not only directly from their teachers and books, but also by using their computers, tablets, and phones. Monitoring these learning environments creates new opportunities for teachers to track students' progress. In particular, this article is based on gathering real-time events as students interact with learning tools and materials…
Descriptors: Predictor Variables, Academic Achievement, Computer Assisted Instruction, Electronic Learning
Okan Bulut; Guher Gorgun; Seyma Nur Yildirim-Erbasli – Journal of Computer Assisted Learning, 2025
Background: Research shows that how formative assessments are operationalized plays a crucial role in shaping their engagement with formative assessments, thereby impacting their effectiveness in predicting academic achievement. Mandatory assessments can ensure consistent student participation, leading to better tracking of learning progress.…
Descriptors: Formative Evaluation, Academic Achievement, Student Participation, Learning Processes
Demir Kaymak, Zeliha; Horzum, Mehmet Baris – Turkish Online Journal of Distance Education, 2022
This research investigates the effects of online learning barriers on students' perceived learning and academic achievement. In this study, the barriers identified by Muilenburg and Berge in 2005 were used as online learning barriers. These are (1) administrative issues, (2) social interaction, (3) academic skills, (4) technical skills, (5)…
Descriptors: Barriers, Electronic Learning, Predictor Variables, Academic Achievement
Schmucker, Robin; Wang, Jingbo; Hu, Shijia; Mitchell, Tom M. – Journal of Educational Data Mining, 2022
We consider the problem of assessing the changing performance levels of individual students as they go through online courses. This student performance modeling problem is a critical step for building adaptive online teaching systems. Specifically, we conduct a study of how to utilize various types and large amounts of log data from earlier…
Descriptors: Academic Achievement, Electronic Learning, Artificial Intelligence, Predictor Variables
Alvin B. Barcelona; Sam Rhoy B. Dela Cruz – Journal of Educators Online, 2024
This explanatory sequential mixed-methods study explored the role of cognitive and noncognitive constructs, namely volitional competence, grit and metacognitive awareness in the academic achievement among online higher education learners in the Philippines. The first phase of the study involved the administration of the survey to 403 learners.…
Descriptors: Electronic Learning, Student Empowerment, Individual Power, Integrity
Khurshid, Shabana; Amin, Faseeh; Masoodi, Nayera; Khan, Mohammad Furqan – International Journal of Learning Technology, 2023
This work has investigated the relationship between SM use and its four antecedents, i.e., perceived interactivity, perceived usefulness, perceived ease of use and perceived enjoyment. Moreover, it has also examined the association of SM use with its outcome variables, i.e., active learning, creativity and collaborative learning, leading to…
Descriptors: Electronic Learning, Social Media, Interaction, Usability