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Clutterbuck, Jennifer; Hardy, Ian; Creagh, Sue – Journal of Education Policy, 2023
In this article, we reveal the nature and effects of data infrastructures on the authorisation of data that represent students and educational practitioners, including how such data can misrepresent and govern educational policy and practices in sometimes problematic ways. To better understand the governance capacities of data infrastructures, we…
Descriptors: Data Analysis, Governance, Educational Policy, Educational Practices
Gray, Pennie L. – Teacher Education Quarterly, 2021
An analysis of data collected through series of semiscripted interviews with 16 first-year teachers reveals the types of classroom management systems implemented by early-career teachers at the start of the school year. The findings of this study indicate that the first-year teachers adopted a hybrid approach to classroom management. Eleven of 16…
Descriptors: Mentors, Beginning Teachers, Classroom Techniques, Teacher Attitudes
Teo, Timothy; Zhou, Mingming; Fan, Andy Chun Wai; Huang, Fang – Educational Technology Research and Development, 2019
Moodle is widely used in higher education institutions in this digital age. With the growing popularity of Moodle use in education, this study aimed to research on the factors that influence student users' intentions to adopt Moodle for learning purposes in Macau. A total of 564 students from nine departments at the University of Macau responded…
Descriptors: College Students, Student Attitudes, Management Systems, Intention
Yakubu, Mohammed Nasiru; Dasuki, Salihu Ibrahim; Abubakar, A. Mohammed; Kah, Muhammadou M. O. – Education and Information Technologies, 2020
Research has shown that technology, when used prudently, has the potential to improve instruction and learning both in and out of the classroom. Only a handful of African tertiary institutions have fully deployed learning management systems (LMS) and the literature is devoid of research examining the factors that foster the adoption of LMS. To…
Descriptors: Management Systems, Instructional Improvement, Student Surveys, Intention
Rodrigues, Rodrigo Lins; Ramos, Jorge Luis Cavalcanti; Silva, João Carlos Sedraz; Dourado, Raphael A.; Gomes, Alex Sandro – International Journal of Distance Education Technologies, 2019
The increasing use of the Learning Management Systems (LMSs) is making available an ever-growing, volume of data from interactions between teachers and students. This study aimed to develop a model capable of predicting students' academic performance based on indicators of their self-regulated behavior in LMSs. To accomplish this goal, the authors…
Descriptors: Management Systems, Teacher Student Relationship, Distance Education, College Students
Al-Hatem, Ahmed Isam; Masood, Mona; Al-Samarraie, Hosam – Journal of Information Technology Education: Research, 2018
Aim/Purpose: This study investigated the potential use of Second Life (SL) to facilitate nursing students' confidence and motivation, as well as its impact on their self-regulated learning development. Background: The current emphasis on nursing education in general has resulted in more consideration of different virtual learning environments as a…
Descriptors: Metacognition, Nursing Education, Student Motivation, Self Esteem
Ramirez-Arellano, Aldo; Bory-Reyes, Juan; Hernández-Simón, Luis Manuel – Journal of Educational Computing Research, 2019
Several studies have focused on identifying the significant behavioral predictors of learning performances in web-based courses by examining the log data variables of learning management systems, including time spent on lectures, the number of assignments submitted, and so forth. However, such studies fail to quantify the impact of emotional,…
Descriptors: Predictor Variables, Correlation, Student Motivation, Metacognition
Brennan, Amelia; Sharma, Akshay; Munguia, Pablo – Journal of Learning Analytics, 2019
A common use of technology in higher education is the provision of online course materials, invoking an investigation of the ways in which students engage with online course content, and how their participation changes over time. This is particularly necessary in the context of high absenteeism from lectures, where online access may be the only…
Descriptors: Attendance, Lecture Method, Technology Uses in Education, Higher Education
van Halema, Nicolette; van Klaveren, Chris; Drachsler, Hendrik; Schmitz, Marcel; Cornelisz, Ilja – Frontline Learning Research, 2020
For decades, self-report instruments -- which rely heavily on students' perceptions and beliefs -- have been the dominant way of measuring motivation and strategy use. Event-based measures based on online trace data arguably has the potential to remove analytical restrictions of self-report measures. The purpose of this study is therefore to…
Descriptors: Independent Study, Learning Motivation, Learning Strategies, Student Behavior
Edwards, Roger; Holguín-Barrera, María Daniela; Ortiz, Ana Cristina; Pérez, Mariela – Latin American Journal of Content and Language Integrated Learning, 2019
This action research was undertaken at a university language center in Ambato, Ecuador, as a result of concerns over the high level of teacher dependence among learners of English as a Second Language (EFL). The project aimed at assessing the development of autonomous learning behavior and the motivational impact of student collaboration on…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Management Systems
Jo, Il-Hyun; Park, Yeonjeong; Yoon, Meehyun; Sung, Hanall – International Review of Research in Open and Distributed Learning, 2016
The purpose of this study was to identify the relationship between the psychological variables and online behavioral patterns of students, collected through a learning management system (LMS). As the psychological variable, time and study environment management (TSEM), one of the sub-constructs of MSLQ, was chosen to verify a set of time-related…
Descriptors: Online Courses, Time Management, Correlation, Behavior Patterns
Kai, Shimin; Andres, Juan Miguel L.; Paquette, Luc; Baker, Ryan S.; Molnar, Kati; Watkins, Harriet; Moore, Michael – International Educational Data Mining Society, 2017
As higher education institutions develop fully online course programs to provide better access for the non-traditional learner, there is increasing interest in identifying students who may be at risk of attrition and poor performance in these online course programs. In our study, we investigate the effectiveness of an online orientation course in…
Descriptors: Online Courses, Student Behavior, Prediction, Models
Lowes, Susan; Lin, Peiyi; Kinghorn, Brian R. C. – Online Learning, 2016
Prior research has suggested that there may be differences in the ways that male and female students approach their online courses. Using data for 802 high school students enrolled in 14 online courses, this study explored gender differences in the interrelationships among online behaviors and course performance. The findings show that females…
Descriptors: Gender Differences, High School Students, Online Courses, Grades (Scholastic)
Rubio, Fernando; Thomas, Jonathan M.; Li, Qin – Computer Assisted Language Learning, 2018
This chapter describes a study of a blended language course that combines face-to-face (F2F) instructional time with an online component. The purpose of the study is to understand how teachers and students exploit the complementarity of the two delivery formats to improve the learning experience. The study first examines how the presence of an…
Descriptors: Student Participation, Blended Learning, Second Language Learning, Second Language Instruction
Firat, Mehmet – Journal of Information Technology Education: Research, 2016
Two of the most important outcomes of learning analytics are predicting students' learning and providing effective feedback. Learning Management Systems (LMS), which are widely used to support online and face-to-face learning, provide extensive research opportunities with detailed records of background data regarding users' behaviors. The purpose…
Descriptors: Academic Achievement, Integrated Learning Systems, Electronic Learning, Management Systems
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