Publication Date
In 2025 | 3 |
Since 2024 | 6 |
Since 2021 (last 5 years) | 11 |
Since 2016 (last 10 years) | 24 |
Since 2006 (last 20 years) | 28 |
Descriptor
Source
Journal of Educational… | 41 |
Author
Acharya, Anal | 1 |
Aguilar, Jose | 1 |
Aimeur, Esma | 1 |
Allen, Laura K. | 1 |
Aslan, Sinem | 1 |
Azevedo, Roger | 1 |
Basa, Roselle S. | 1 |
Baylor, Amy | 1 |
Baylor, Amy L. | 1 |
Beck, Joseph E. | 1 |
Bengu, Golgen | 1 |
More ▼ |
Publication Type
Journal Articles | 41 |
Reports - Research | 32 |
Reports - Descriptive | 7 |
Reports - Evaluative | 3 |
Tests/Questionnaires | 3 |
Information Analyses | 1 |
Education Level
Higher Education | 10 |
Postsecondary Education | 6 |
Secondary Education | 6 |
High Schools | 4 |
Middle Schools | 4 |
Elementary Education | 3 |
Grade 5 | 3 |
Intermediate Grades | 3 |
Grade 4 | 2 |
Junior High Schools | 2 |
Early Childhood Education | 1 |
More ▼ |
Audience
Location
Taiwan | 2 |
Canada | 1 |
China | 1 |
China (Shanghai) | 1 |
Malaysia | 1 |
Netherlands | 1 |
Pakistan | 1 |
Philippines (Manila) | 1 |
Spain (Madrid) | 1 |
Laws, Policies, & Programs
Assessments and Surveys
Gates MacGinitie Reading Tests | 2 |
Flesch Reading Ease Formula | 1 |
Learning Style Inventory | 1 |
Woodcock Reading Mastery Test | 1 |
What Works Clearinghouse Rating
Noah L. Schroeder; Robert O. Davis; Eunbyul Yang – Journal of Educational Computing Research, 2025
Pedagogical agents are virtual characters that instructional designers include in learning environments to help students learn. Research in the area has flourished for thirty years, yet there are still critical questions about the efficacy of pedagogical agents for influencing learning and affect. As such, we conducted an umbrella review to…
Descriptors: Educational Technology, Technology Uses in Education, Artificial Intelligence, Intelligent Tutoring Systems
Yueru Lang; Shaoying Gong; Xiangen Hu; Boyuan Xiao; Yanqing Wang; Tiantian Jiang – Journal of Educational Computing Research, 2024
The present research conducted two experiments with an intelligent tutoring system to investigate the overall and dynamic impact of emotional support from a pedagogical agent (PA). In Experiment 1, a single factor intergroup design was used to explore the impact of PA's emotional support (supportive vs. non-supportive) on learners' emotions,…
Descriptors: Psychological Patterns, Learning Strategies, Multimedia Instruction, Multimedia Materials
Peng, Tzu-Hsiang; Wang, Tzu-Hua – Journal of Educational Computing Research, 2022
Pedagogical agents (PAs) are a crucial aspect of the e-learning environment. A PA is defined as a virtual character presented on an interface, and they are designed to promote student learning. PAs have been widely discussed in academic papers. However, an appropriate analysis framework has not been proposed because of the diversity and complexity…
Descriptors: Electronic Learning, Instructional Effectiveness, Intelligent Tutoring Systems, Evaluation Methods
Wu, Ting-Ting; Lee, Hsin-Yu; Li, Pin-Hui; Huang, Chia-Nan; Huang, Yueh-Min – Journal of Educational Computing Research, 2024
This study combines ChatGPT, Apple's Shortcuts, and LINE to create the ChatGPT-based Intelligent Learning Aid (CILA), aiming to enhance self-regulation progress and knowledge construction in blended learning. CILA offers real-time, convergent information to learners' inquiries, as opposed to traditional Google search engine that provide divergent…
Descriptors: Independent Study, Learning Processes, Blended Learning, Artificial Intelligence
Lei Shi – Journal of Educational Computing Research, 2025
This study explores the integration of advanced AI technologies, including emotion detection and adaptive learning systems, to enhance second language acquisition among 274 English as a Foreign Language (EFL) learners. Utilizing a pretest-posttest randomized control trial, the research evaluates the effects of AI-enhanced interventions on…
Descriptors: Artificial Intelligence, Technology Uses in Education, Emotional Response, Intelligent Tutoring Systems
Yang, Chunsheng; Chiang, Feng-Kuang; Cheng, Qiangqiang; Ji, Jun – Journal of Educational Computing Research, 2021
Machine learning-based modeling technology has recently become a powerful technique and tool for developing models for explaining, predicting, and describing system/human behaviors. In developing intelligent education systems or technologies, some research has focused on applying unique machine learning algorithms to build the ad-hoc student…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Data Use, Models
Personalized Recommendation in the Adaptive Learning System: The Role of Adaptive Testing Technology
Dai, Jing; Gu, Xiaoqing; Zhu, Jiawen – Journal of Educational Computing Research, 2023
Personalized recommendation plays an important role on content selection during the adaptive learning process. It is always a challenge on how to recommend effective items to improve learning performance. The aim of this study was to examine the feasibility of applying adaptive testing technology for personalized recommendation. We proposed the…
Descriptors: Individualized Instruction, Intelligent Tutoring Systems, Evaluation Methods, Tests
Reese Butterfuss; Rod D. Roscoe; Laura K. Allen; Kathryn S. McCarthy; Danielle S. McNamara – Journal of Educational Computing Research, 2022
The present study examined the extent to which adaptive feedback and just-in-time writing strategy instruction improved the quality of high school students' persuasive essays in the context of the Writing Pal (W-Pal). W-Pal is a technology-based writing tool that integrates automated writing evaluation into an intelligent tutoring system. Students…
Descriptors: High School Students, Writing Evaluation, Writing Instruction, Feedback (Response)
Wang, Yue; Eysink, Tessa H. S.; Qu, Zhili; Yang, Zhijiao; Shan, Huaming; Zhang, Nan; Zhang, Hai; Wang, Yining – Journal of Educational Computing Research, 2022
This research used a comparative quasi-experimental design to investigate the impacts of an IRS in the ILE on students' academic performance, cognitive load, and satisfaction with the lesson. A total of 31 middle school students were divided into the experimental group and the control group. Mann-Whitney U tests yielded three major results. (1)…
Descriptors: Intelligent Tutoring Systems, Active Learning, Academic Achievement, Cognitive Processes
Sheehan, Kathleen M.; Napolitano, Diane – Journal of Educational Computing Research, 2020
Personalized learning technologies such as automated reading tutors have been proposed as a way to help struggling readers acquire needed skills while simultaneously encouraging engaged, sustained reading of entire books. This article investigates a key step in the development of such technologies: translating an entire novel into a sequence of…
Descriptors: Feedback (Response), Intelligent Tutoring Systems, Reading Instruction, Reliability
Lijuan Feng – Journal of Educational Computing Research, 2025
This study investigates the impact of AI-assisted language learning (AIAL) strategies on cognitive load and learning outcomes in the context of language acquisition. Specifically, the study explores three distinct AIAL strategies: personalized feedback and adaptive learning, interactive exercises with speech recognition, and intelligent tutoring…
Descriptors: Artificial Intelligence, Computer Assisted Instruction, Second Language Learning, Second Language Instruction
Borracci, Giuliana; Gauthier, Erica; Jennings, Jay; Sale, Kyle; Muldner, Kasia – Journal of Educational Computing Research, 2020
We investigated the impact of assistance on learning and affect during problem-solving activities with a computer tutor we built using the Cognitive Tutor Authoring Tools framework. The tutor delivered its primary form of assistance in the form of worked-out examples. We manipulated the level of assistance the examples in the tutor provided, by…
Descriptors: Intelligent Tutoring Systems, Mathematics Instruction, Mathematics Education, Algebra
Zhu, Xin-Hua; Wu, Tian-Jun; Chen, Hong-Chao – Journal of Educational Computing Research, 2018
Based on the sharable content object concept of advanced distributed learning, an ontology-based intelligent content object (ICO) that can automatically reason and be reused is proposed. Then, by extending the advanced distributed learning or sharable content object reference model (SCORM) specification, an interoperable model for the ICO is…
Descriptors: Models, Intelligent Tutoring Systems, Computer Software, Multimedia Instruction
Roscoe, Rod D.; Allen, Laura K.; McNamara, Danielle S. – Journal of Educational Computing Research, 2019
A critical challenge for computer-based writing instruction is providing appropriate and adaptive practice. The current study examined three modes of computer-based writing practice with the goal of identifying those with the greatest learning and motivational value. High school students learned about writing strategies by studying lessons within…
Descriptors: High School Students, Writing Instruction, Computer Assisted Instruction, Writing Strategies
Chen-Chung Liu; Wan-Jun Chen; Fang-ying Lo; Chia-Hui Chang; Hung-Ming Lin – Journal of Educational Computing Research, 2024
Reading requires appropriate strategies to spark initial interest and sustain engagement. One promising strategy is the pedagogical approach of learning-by-teaching, transforming learners into active participants. Integrating this approach into digitalized and individualized reading contexts has the potential to foster the development of young…
Descriptors: Reading Interests, Active Learning, Intelligent Tutoring Systems, Artificial Intelligence