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E. Gothai; S. Saravanan; C. Thirumalai Selvan; Ravi Kumar – Education and Information Technologies, 2024
In recent years, online education has been given more and more attention with the widespread use of the internet. The teaching procedure divides space and makes time for online learning; though teachers cannot control the learners accurately, the state of education calculates learners' learning situation. This paper explains that the discourse…
Descriptors: Artificial Intelligence, Discourse Analysis, Classification, Comparative Analysis
Mohammed Jebbari; Bouchaib Cherradi; Soufiane Hamida; Abdelhadi Raihani – Education and Information Technologies, 2024
With the advancements in technology and the growing demand for online education, Virtual Learning Environments (VLEs) have experienced rapid development in recent years. This demand was especially evident during the COVID-19 pandemic. The incorporation of new technologies in VLEs provides new opportunities to better understand the behaviors of…
Descriptors: MOOCs, Algorithms, Computer Simulation, COVID-19
Jelena Andelkovic Labrovic; Nikola Petrovic; Jelena Andelkovic; Marija Meršnik – Journal of Computing in Higher Education, 2025
The focus of this study was on identifying patterns of student behavior to support data-informed decision-making which would then improve the learning experience and learning outcomes of online English language courses. Learning analytics approach (or more specifically cluster analysis) was used to identify engagement patterns in online learning.…
Descriptors: Electronic Learning, Online Courses, Behavior Patterns, Student Behavior
Jiang, Bo; Zhao, Wei; Zhang, Nuan; Qiu, Feiyue – Interactive Learning Environments, 2022
Block-based programing languages (BBPL) provide effective scaffolding for K-12 students to learn computational thinking. However, the output-based assessment in BBPL learning is insufficient as we can not understand how students learn and what mistakes they have had. This study aims to propose a data-driven method that provides insight into…
Descriptors: Programming Languages, Computer Science Education, Problem Solving, Game Based Learning
Roshelle Laticia Lemon-Howard – ProQuest LLC, 2022
Academic dishonesty remains a pervasive, multi-discipline dilemma which has been reported as having the propensity of resulting in longstanding consequences beyond academic settings. Previous research has suggested that students who participate in dishonest behaviors while attending institutions of higher education have greater tendencies to…
Descriptors: Decision Making, Ethics, Integrity, Community College Students
Kaliisa, Rogers; Dolonen, Jan Arild – Technology, Knowledge and Learning, 2023
Despite the potential of learning analytics (LA) to support teachers' everyday practice, its adoption has not been fully embraced due to the limited involvement of teachers as co-designers of LA systems and interventions. This is the focus of the study described in this paper. Following a design-based research (DBR) approach and guided by concepts…
Descriptors: College Faculty, Student Participation, Discourse Analysis, Behavior Patterns
Liu, Yan; Deng, Lisa; Lin, Lin; Gu, Xiaoqing – Interactive Learning Environments, 2023
With the rapid development of mobile devices and web-based technologies, it becomes common for students to switch between different tasks during study time. However, it remains unclear how the transition between on-task and off-task states happens and how digital devices affect the process. This study examines college students' independent study…
Descriptors: Independent Study, Student Behavior, Behavior Patterns, Time on Task
Tong Li; Chris Kirk; Leticia Oseguera – Journal of College Student Development, 2023
Academic achievement, often measured by GPA, has been extensively studied in the literature of science, technology, engineering, and mathematics (STEM) education, including its impact on student persistence and success in college (Rask, 2010). However, most research has only looked at students' performance at a single point in time, such as their…
Descriptors: STEM Education, Intention, College Students, Longitudinal Studies
Chu-Yang Chang; Hsu-Chan Kuo – Journal of Creative Behavior, 2024
Parents and teachers are significant authority figures that substantially impact adolescents' psychological and cognitive development, including their creativity. The current study investigated the relationship between adolescents' attitudes toward authority (parents and teachers) and innovative behavior and examined the mediating effects of…
Descriptors: Foreign Countries, Adolescent Attitudes, Secondary School Students, Student Attitudes
Antonio A. Morgan-López; Lissette M. Saavedra; Heather L. McDaniel; Stephen G. West; Nicholas S. Ialongo; Catherine P. Bradshaw; Alexandra T. Tonigan; Barrett W. Montgomery; Nicole P. Powell; Lixin Qu; Anna C. Yaros; John E. Lochman – Grantee Submission, 2024
Coping Power (CP) is a preventive intervention that focuses on reducing child externalizing problems. Although it is typically delivered in a group format (GCP), individually-delivered CP (ICP) has produced greater mean reductions in externalizing problems. However, standard analysis of randomized trials loses individual-level information…
Descriptors: Coping, Prevention, Intervention, Child Behavior
Jing Liu; Megan Kuhfeld; Monica Lee – Annenberg Institute for School Reform at Brown University, 2023
Noncognitive constructs such as self-efficacy, social awareness, and academic engagement are widely acknowledged as critical components of human capital, but systematic data collection on such skills in school systems is complicated by conceptual ambiguities, measurement challenges and resource constraints. This study addresses this issue by…
Descriptors: Student Behavior, Predictor Variables, Predictive Validity, Academic Achievement
Milat, Iness Nedji; Seridi, Hassina; Moudjari, Abdelkader – International Journal of Distance Education Technologies, 2020
Recently, discovering learner behaviour has taken more attention in the field of e-learning. It aims to gain useful insights into the learning process of students despite the absence of direct interaction with teachers. In fact, the only available source of information in such environments is the log file that represents all possible interactions…
Descriptors: Student Behavior, Behavior Patterns, Electronic Learning, Learning Analytics
Dermy, Oriane; Brun, Armelle – International Educational Data Mining Society, 2020
Analyzing students' activities in their learning process is an issue that has received significant attention in the educational data mining research field. Many approaches have been proposed, including the popular sequential pattern mining. However, the vast majority of the works do not focus on the time of occurrence of the events within the…
Descriptors: Learning Analytics, Time, College Freshmen, Intervals
Iustina Alexandra Groza; Marius Ciprian Ceobanu; Cristina Maria Tofan – European Journal of Psychology of Education, 2024
Academic procrastination has been a subject of particular interest in research due to its frequent association with heightened levels of anxiety, stress, and the long-term risk of emotional and behavioural vulnerability (Hoge et al., 2013). Our study tests the correlation between motivational persistence as a trait and academic procrastination, as…
Descriptors: Study Habits, Females, Foreign Countries, Student Motivation
Mohd Fazil; Angelica Rísquez; Claire Halpin – Journal of Learning Analytics, 2024
Technology-enhanced learning supported by virtual learning environments (VLEs) facilitates tutors and students. VLE platforms contain a wealth of information that can be used to mine insight regarding students' learning behaviour and relationships between behaviour and academic performance, as well as to model data-driven decision-making. This…
Descriptors: Learning Analytics, Learning Management Systems, Learning Processes, Decision Making

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