NotesFAQContact Us
Collection
Advanced
Search Tips
Source
Journal of Computer Assisted…29
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Showing 1 to 15 of 29 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Min Young Doo; Meina Zhu – Journal of Computer Assisted Learning, 2024
Background: Online learning has become more prevalent over the past three decades, especially during the COVID-19 pandemic. Educators and scholars have increasingly emphasized the significance of self-directed learning (SDL) on successful learning outcomes in online learning environments. Objectives: The purpose of this study was to synthesize the…
Descriptors: Electronic Learning, Independent Study, Virtual Classrooms, Academic Achievement
Peer reviewed Peer reviewed
Direct linkDirect link
Yuhui Jing; Chengliang Wang; Zhaoyi Chen; Shusheng Shen; Rustam Shadiev – Journal of Computer Assisted Learning, 2024
Background Study: Technology-supported learning environments, act as significant observational and enabling indicators for evaluating and encouraging the digital revolution of education, are of vital importance in current educational research. Keeping track of the dynamics of technology-supported learning environment research allows for the…
Descriptors: Educational Technology, Technology Uses in Education, Educational Environment, Educational Research
Peer reviewed Peer reviewed
Direct linkDirect link
Guo, Liming; Du, Junlei; Zheng, Qinhua – Journal of Computer Assisted Learning, 2023
Background: There is a strong association between interactions and cognitive engagement, which is crucial for constructing new cognition and knowledge. Although interactions and cognitive engagement have attracted extensive attention in online learning environments, few studies have revealed the evolution of cognitive engagement with interaction…
Descriptors: Cognitive Ability, Learner Engagement, Electronic Learning, Technology Uses in Education
Peer reviewed Peer reviewed
Direct linkDirect link
Lanqin Zheng; Zichen Huang; Lei Gao; Yunchao Fan – Journal of Computer Assisted Learning, 2025
Background: Online collaborative learning has been broadly applied in the field of higher education. Nevertheless, not all types of collaborative learning can produce the desired learning results. Objectives: To facilitate online collaborative learning, the present study proposed an innovative artificial intelligence-enabled group cognitive…
Descriptors: Artificial Intelligence, Technology Uses in Education, Electronic Learning, Online Courses
Peer reviewed Peer reviewed
Direct linkDirect link
Chen, Xiuyu; Feng, Shihui – Journal of Computer Assisted Learning, 2023
Background: Video-based learning (VBL) is the learning process of acquiring defined knowledge, competence, and skills with the systematic use of video resources. Currently, the relationship between teaching presence and social presence in VBL is underexamined. Objectives: This study examined the relationships between social presence and teaching…
Descriptors: Teacher Student Relationship, Social Behavior, Electronic Learning, Video Technology
Peer reviewed Peer reviewed
Direct linkDirect link
Zhihao Cui; Oi-Lam Ng; Morris Siu-yung Jong; Xiaojing Weng – Journal of Computer Assisted Learning, 2025
Background: Amidst the increasing application of online education in the post-COVID era, new challenges in student engagement have emerged. However, most studies on online engagement have adopted macro-level approaches and relied on self-report measures of retrospective engagement. Few have examined micro-level engagement in terms of real-time and…
Descriptors: Middle School Students, Learner Engagement, Attention, Synchronous Communication
Peer reviewed Peer reviewed
Direct linkDirect link
Sule Biyik Bayram; Gamze Özener; Nilay Çakici; Handan Eren; Sinan Aydogan; Deniz Öztürk; Emel Gülnar; Nurcan Çaliskan – Journal of Computer Assisted Learning, 2024
Background: There are deficiencies in ensuring the permanence of some theoretical information taught in nursing education and transferring it to practice environment. Mobile-assisted teaching can be useful to eliminate deficiencies. The aim of this study was to determine the effect of mobile-assisted teaching on nursing students' learning…
Descriptors: Foreign Countries, Nursing Students, Human Body, Electronic Learning
Peer reviewed Peer reviewed
Direct linkDirect link
Hui Shi; Nuodi Zhang; Secil Caskurlu; Hunhui Na – Journal of Computer Assisted Learning, 2025
Background: The growth of online education has provided flexibility and access to a wide range of courses. However, the self-paced and often isolated nature of these courses has been associated with increased dropout and failure rates. Researchers employed machine learning approaches to identify at-risk students, but multiple issues have not been…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, At Risk Students
Peer reviewed Peer reviewed
Direct linkDirect link
Zhe Wang; Sara Abercrombie; Rachel Wong; Yuxin Ren; Shiting Dai – Journal of Computer Assisted Learning, 2024
Background: There are two major types of pictures that have been the focus of multimedia learning research, namely, seductive and interpretational pictures. Despite an increasing body of literature documenting the effects of either seductive or interpretational pictures added to text-based materials, there is a paucity of research explicitly…
Descriptors: Electronic Learning, Computers, Computer Assisted Instruction, Visual Aids
Peer reviewed Peer reviewed
Direct linkDirect link
Gerti Pishtari; María Jesús Rodríguez-Triana; Luis P. Prieto; Adolfo Ruiz-Calleja; Terje Väljataga – Journal of Computer Assisted Learning, 2024
Background: In the field of Learning Design, it is common that researchers analyse manually design artefacts created by practitioners, using pedagogically-grounded approaches (e.g., Bloom's Taxonomy), both to understand and later to support practitioners' design practices. Automatizing these high-level pedagogically-grounded analyses would enable…
Descriptors: Electronic Learning, Instructional Design, Active Learning, Inquiry
Peer reviewed Peer reviewed
Direct linkDirect link
Joshua Weidlich; Aron Fink; Ioana Jivet; Jane Yau; Tornike Giorgashvili; Hendrik Drachsler; Andreas Frey – Journal of Computer Assisted Learning, 2024
Background: Developments in educational technology and learning analytics make it possible to automatically formulate and deploy personalized formative feedback to learners at scale. However, to be effective, the motivational and emotional impacts of such automated and personalized feedback need to be considered. The literature on feedback…
Descriptors: Emotional Response, Student Motivation, Feedback (Response), Automation
Peer reviewed Peer reviewed
Direct linkDirect link
Mugur V. Geana; Dan Cernusca; Pan Liu – Journal of Computer Assisted Learning, 2024
Background: Education is, after gaming, the second largest sector embracing augmented reality (AR) at an accelerated pace, yet studies on AR's potential as an efficient learning environment had mixed results. Objectives: This study's primary objective is to test students' interaction with graphical 3D elements in AR and its impact on information…
Descriptors: Learner Engagement, Computer Simulation, Technology Uses in Education, Information Dissemination
Peer reviewed Peer reviewed
Direct linkDirect link
John L. Nietfeld; Kristin F. Hoffmann – Journal of Computer Assisted Learning, 2024
Background: Goal setting has been established in the literature as a critical component of self-regulated learning and for effective problem-solving. Yet, surprisingly little attention has been focused on goal-directed behaviour in digital game-based learning environments (GBLEs) despite their expanding use in educational contexts. Objectives: The…
Descriptors: Game Based Learning, Educational Environment, Goal Orientation, Electronic Learning
Peer reviewed Peer reviewed
Direct linkDirect link
Weipeng Yang; Xinyun Hu; Ibrahim H. Yeter; Jiahong Su; Yuqin Yang; John Chi-Kin Lee – Journal of Computer Assisted Learning, 2024
Background: Artificial Intelligence (AI) literacy is a crucial part of digital literacy that all individuals should possess in today's technologically advanced world. Despite the potential benefits that AI education offers, little research has been done on how to teach AI literacy to children. Objectives: This study aimed to fill that gap by…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Technology, Digital Literacy
Peer reviewed Peer reviewed
Direct linkDirect link
Lahza, Hatim; Khosravi, Hassan; Demartini, Gianluca – Journal of Computer Assisted Learning, 2023
Background: The use of crowdsourcing in a pedagogically supported form to partner with learners in developing novel content is emerging as a viable approach for engaging students in higher-order learning at scale. However, how students behave in this form of crowdsourcing, referred to as learnersourcing, is still insufficiently explored.…
Descriptors: Learning Analytics, Learning Strategies, Electronic Learning, Independent Study
Previous Page | Next Page »
Pages: 1  |  2