Publication Date
In 2025 | 1 |
Since 2024 | 6 |
Since 2021 (last 5 years) | 8 |
Since 2016 (last 10 years) | 31 |
Since 2006 (last 20 years) | 158 |
Descriptor
Source
Educational Technology &… | 178 |
Author
Publication Type
Journal Articles | 178 |
Reports - Research | 103 |
Reports - Descriptive | 47 |
Reports - Evaluative | 25 |
Information Analyses | 3 |
Opinion Papers | 2 |
Tests/Questionnaires | 2 |
Education Level
Audience
Teachers | 3 |
Practitioners | 2 |
Researchers | 1 |
Location
Taiwan | 24 |
China | 7 |
Spain | 7 |
Malaysia | 6 |
Greece | 4 |
Canada | 3 |
Japan | 3 |
Turkey | 3 |
Australia | 2 |
Chile (Santiago) | 2 |
Estonia | 2 |
More ▼ |
Laws, Policies, & Programs
Assessments and Surveys
Cognitive Assessment System | 1 |
Embedded Figures Test | 1 |
Learning Style Inventory | 1 |
Motivated Strategies for… | 1 |
Myers Briggs Type Indicator | 1 |
Wechsler Intelligence Scale… | 1 |
What Works Clearinghouse Rating
Xieling Chen; Haoran Xie; Di Zou; Lingling Xu; Fu Lee Wang – Educational Technology & Society, 2025
In massive open online course (MOOC) environments, computer-based analysis of course reviews enables instructors and course designers to develop intervention strategies and improve instruction to support learners' learning. This study aimed to automatically and effectively identify learners' concerned topics within their written reviews. First, we…
Descriptors: Classification, MOOCs, Teaching Skills, Artificial Intelligence
Sandy C. Li; Jackie W. W. Chan; Andrew K. F. Lui; Ming Lui; Raymond W. P. Wong – Educational Technology & Society, 2024
While prior research has shown higher mindfulness is associated with lower problematic smartphone use (PSU), the contexts of these studies were not related to education or student performance. As such, whether and how mindfulness can reduce the adverse effects of PSU on academic self-efficacy remains unknown. This study proposed a model for…
Descriptors: Self Efficacy, Academic Achievement, Handheld Devices, Telecommunications
Chia-Yu Hsu; Izumi Horikoshi; Rwitajit Majumdar; Hiroaki Ogata – Educational Technology & Society, 2024
This study focuses on the problem that the process of building learning habits has not been clearly described. Therefore, we aim to extract the stages of learning habits from log data. We propose a data model to extract stages of learning habits based on the transtheoretical model and apply the model to the learning logs of self-directed extensive…
Descriptors: Habit Formation, Behavior Change, Learning Analytics, Data Interpretation
Lyons, Leilah; Mallavarapu, Aditi – Educational Technology & Society, 2021
In this paper we define the concept of collective usability, a complex systems perspective on usability that positions an entire group, not an individual, as the unit of analysis. Shared XR experiences have inherent temporal and spatial properties that produce emergent, collective impacts which can impede learners' engagement. Assembling large…
Descriptors: Computer Simulation, Usability, Educational Technology, Technology Uses in Education
Wen-Lung Huang; Liang-Yi Li; Jyh-Chong Liang – Educational Technology & Society, 2024
The purposes of this study were to explore students' learning performance, knowledge construction, and behavioral patterns in computer-supported collaborative learning (CSCL) online discussions with/without using Form+Theme+Context (FTC) model guidance scaffolding in visual imagery education. In the online learning activities, the control group…
Descriptors: Asynchronous Communication, Online Courses, Behavior Patterns, Discussion (Teaching Technique)
Rwitajit Majumdar; Huiyong Li; Yuanyuan Yang; Hiroaki Ogata – Educational Technology & Society, 2024
Self-direction skill (SDS) is an essential 21st-century skill that can help learners be independent and organized in their quest for knowledge acquisition. While some studies considered learners from higher education levels as the target audience, providing opportunities to start the SDS practice by K12 learners is still rare. Further, practicing…
Descriptors: 21st Century Skills, Skill Development, Electronic Learning, Physical Activity Level
Deliang Wang; Yaqian Zheng; Gaowei Chen – Educational Technology & Society, 2024
This study investigates the potential of ChatGPT, a cutting-edge large language model in generative artificial intelligence (AI), to support the teaching of dialogic pedagogy to preservice teachers. A workshop was conducted with 29 preservice teachers, wherein ChatGPT and another prominent AI model, Bert, were sequentially integrated to facilitate…
Descriptors: Artificial Intelligence, Preservice Teachers, Models, Teaching Methods
Gibson, David; Broadley, Tania; Downie, Jill; Wallet, Peter – Educational Technology & Society, 2018
The UNESCO Institute for Statistics (UIS) has been measuring ICT in education since 2009, but with such rapid change in technology and its use in education, it is important now to revise the collection mechanisms to focus on how technology is being used to enhance learning and teaching. Sustainable development goal (SDG) 4, for example, moves…
Descriptors: Models, Information Technology, Data Collection, Statistics
Findik-Coskunçay, Duygu; Alkis, Nurcan; Özkan-Yildirim, Sevgi – Educational Technology & Society, 2018
With the recent advances in information technologies, Learning Management Systems have taken on a significant role in providing educational resources. The successful use of these systems in higher education is important for the implementation, management and continuous improvement of e-learning services to increase the quality of learning. This…
Descriptors: Integrated Learning Systems, Foreign Countries, Technology Uses in Education, Structural Equation Models
Li, Fengying; He, Yifeng; Xue, Qingshui – Educational Technology & Society, 2021
With the deep application of artificial intelligence and big data in education, adaptive learning has become a new research hotspot in online education. Based on the systematic review of the connotation and research progress of adaptive learning, a new definition of adaptive learning is given. By literature analysis, this paper points out the…
Descriptors: Educational Technology, Artificial Intelligence, Student Needs, Individualized Instruction
Liu, I-Fan; Chen, Ruey-Shin; Lu, Hao-Chun – Educational Technology & Society, 2015
With the rapid development of the Internet and information technology, the issues related to online exams have become the concern of an increasing number of researchers. At present, the biggest challenges for the integration of web communication technology into online exams are the ability to detect cheating behaviors during the exam, and the…
Descriptors: Foreign Countries, Computer Assisted Testing, Cheating, Identification
Wu, Pengfei; Yu, Shengquan; Wang, Dan – Educational Technology & Society, 2018
The present study uses a text data mining approach to automatically discover learner interests in open learning environments. We propose a method to construct learner interests automatically from the combination of learner generated content and their dynamic interactions with other learning resources. We develop a learner-topic model to discover…
Descriptors: Data Collection, Data Analysis, Educational Technology, Technology Uses in Education
Bey, Anis; Jermann, Patrick; Dillenbourg, Pierre – Educational Technology & Society, 2018
Computer-graders have been in regular use in the context of MOOCs (Massive Open Online Courses). The automatic grading of programs presents an opportunity to assess and provide tailored feedback to large classes, while featuring at the same time a number of benefits like: immediate feedback, unlimited submissions, as well as low cost of feedback.…
Descriptors: Comparative Analysis, Online Courses, Feedback (Response), Foreign Countries
Poitras, Eric G.; Lajoie, Susanne P.; Doleck, Tenzin; Jarrell, Amanda – Educational Technology & Society, 2016
Learner modeling, a challenging and complex endeavor, is an important and oft-studied research theme in computer-supported education. From this perspective, Educational Data Mining (EDM) research has focused on modeling and comprehending various dimensions of learning in computer-based learning environments (CBLE). Researchers and designers are…
Descriptors: Intelligent Tutoring Systems, Data, Data Analysis, Medical Evaluation
Challco, Geiser C.; Andrade, Fernando R. H.; Borges, Simone S.; Bittencourt, Ig I.; Isotani, Seiji – Educational Technology & Society, 2016
Flow is the affective state in which a learner is so engaged and involved in an activity that nothing else seems to matter. In this sense, to help students in the skill development and knowledge acquisition (referred to as learners' growth process) under optimal conditions, the instructional designers should create learning scenarios that favor…
Descriptors: Instructional Design, Models, Learning Theories, Student Development