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Shuanghong Shen; Qi Liu; Zhenya Huang; Yonghe Zheng; Minghao Yin; Minjuan Wang; Enhong Chen – IEEE Transactions on Learning Technologies, 2024
Modern online education has the capacity to provide intelligent educational services by automatically analyzing substantial amounts of student behavioral data. Knowledge tracing (KT) is one of the fundamental tasks for student behavioral data analysis, aiming to monitor students' evolving knowledge state during their problem-solving process. In…
Descriptors: Student Behavior, Electronic Learning, Data Analysis, Models
Önder, Asuman; Akçapinar, Gökhan – Education and Information Technologies, 2023
The effective use of self-regulation strategies has been considered significant in online learning environments. It is known that learners must be supported in this context. Academic help-seeking (AHS), as one of the main self-regulated learning strategies, is associated with academic success. However, learners may avoid seeking help for…
Descriptors: Students, Help Seeking, Student Behavior, Learning Analytics
McIntosh, Kent; von Ravensberg, Heidi; Santiago-Rosario, María Reina; Chaparro, Erin – Center on Positive Behavioral Interventions and Supports, 2022
Removing students from the classroom and placing them in remote instruction for their behavior is an emerging form of discipline (Jones, 2020). The purpose of this brief is to describe this form of discipline, examine its implications and potential negative impacts, and provide guiding principles for improving behavior through evidence-based…
Descriptors: Student Behavior, Suspension, Distance Education, Discipline Policy
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
Orchard, Ryan K. – Journal of Educational Technology Systems, 2019
Learning management systems (LMS) allow for a variety of ways in which online multiple-choice assessments ("tests") can be configured, including the ability to allow for multiple attempts and options for which of and how the attempts will count. These options are usually chosen according to the instinct of the instructor; however, LMS…
Descriptors: Integrated Learning Systems, Data Use, Electronic Learning, Assignments
Halaweh, Mohanad – TechTrends: Linking Research and Practice to Improve Learning, 2017
Smartphones are developing rapidly and continually with new features that make them widely used in many contexts. This paper is to reflect on students' behaviours of using smartphones spontaneously (unplanned use) in the classroom, in a university in Dubai city in UAE. This reflection shall address the following questions: How can the instructors…
Descriptors: Teaching Experience, Foreign Countries, Technology Uses in Education, Technology Integration
Veselá, Katerina Gajdácová – ICTE Journal, 2018
This paper shows that the flexibility of time as a potential of Computer Assisted Language Learning (CALL) proves the sustainability of its latest stage -- Ubiquitous CALL. Firstly, the ideas of the Third Millennium Pedagogy are combined with the ethical and philosophical principles of sustainable education. One of the descriptors of the…
Descriptors: Computer Assisted Instruction, Sustainability, Electronic Learning, Blended Learning
Moten, James, Jr.; Fitterer, Alex; Brazier, Elise; Leonard, Jonathan; Brown, Avis – Electronic Journal of e-Learning, 2013
Academic dishonesty in the online cheating environment of distance education learning has gained traction in the past decade. By a few simple keystrokes, students' can find a wide array of online services for hire to write research papers, complete homework assignments, or enroll on behalf of the student on record to take the entire online…
Descriptors: Distance Education, Cheating, Online Courses, Electronic Learning
Graf, S.; Liu, T.-C.; Kinshuk, – Journal of Computer Assisted Learning, 2010
Providing adaptive features and personalized support by considering students' learning styles in computer-assisted learning systems has high potential in making learning easier for students in terms of reducing their efforts or increasing their performance. In this study, the navigational behaviour of students in an online course within a learning…
Descriptors: Cognitive Style, Management Systems, Online Courses, Computer Assisted Instruction
Farisi, Mohammad Imam – Turkish Online Journal of Distance Education, 2013
Today, in the era of open access to digital-based information and communication, one of the biggest challenges in higher education to realize moral education and to build academic culture and integrity is the emergence of academic dishonesty behaviors among academic members. The paper describes academic dishonesty behaviors in Distance Higher…
Descriptors: Ethics, Distance Education, Higher Education, Models
Lowdermilk, John; Martinez, Deborah; Pecina, Julie; Beccera, Lisa; Lowdermilk, Carey – TechTrends: Linking Research and Practice to Improve Learning, 2012
This article examines the use of a focused educational game. The game, "Behavior Breakthroughs"[TM], was created to teach people that work with children with autism, appropriate behavior management techniques. A group of undergraduate, teacher education students played the game and provided feedback on their experiences.
Descriptors: Autism, Student Behavior, Classroom Techniques, Special Education
Lee, Chung-Ping; Lou, Shi-Jer; Shih, Ru-Chu; Tseng, Kuo-Hung – Turkish Online Journal of Educational Technology - TOJET, 2011
This study uses the analytical hierarchy process (AHP) to quantify important knowledge management behaviors and to analyze the weight scores of elementary school students' behaviors in knowledge transfer, sharing, and creation. Based on the analysis of Expert Choice and tests for validity and reliability, this study identified the weight scores of…
Descriptors: Knowledge Management, Elementary School Students, Student Behavior, Evaluation Methods
Hussain, Fehmida – International Association for Development of the Information Society, 2012
Web 3.0, termed as the semantic web or the web of data is the transformed version of Web 2.0 with technologies and functionalities such as intelligent collaborative filtering, cloud computing, big data, linked data, openness, interoperability and smart mobility. If Web 2.0 is about social networking and mass collaboration between the creator and…
Descriptors: Foreign Countries, Electronic Learning, Learning Theories, Data
Peters, Vanessa L.; Hewitt, Jim – Computers & Education, 2010
This study investigated the online practices of students enrolled in graduate-level distance education courses. Using interviews and a questionnaire as data sources, the study sought to: (a) identify common practices that students adopt in asynchronous discussions, and (b) gain an understanding of why students adopt them. An analysis of the data…
Descriptors: Distance Education, Coping, Educational Technology, Student Behavior
Hillman, Richard – US Government Accountability Office, 2011
Once comprised of local, sole-proprietor ownership, the nation's for-profit institutions now range from small, privately owned schools to publicly traded corporations. Enrollment in such colleges has grown far faster than in traditional higher-education institutions. Moreover, during the 2009-2010 school year, for-profit colleges received almost…
Descriptors: Student Experience, Student Financial Aid, Educational Policy, Research Reports
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