Publication Date
| In 2026 | 0 |
| Since 2025 | 1 |
| Since 2022 (last 5 years) | 2 |
| Since 2017 (last 10 years) | 3 |
| Since 2007 (last 20 years) | 5 |
Descriptor
Source
| British Journal of… | 5 |
Author
| Bryant, Lauren H. | 1 |
| Chittum, Jessica R. | 1 |
| Daryn A. Dever | 1 |
| Doolittle, Peter E. | 1 |
| Dragan Gaševic | 1 |
| Huixiao Le | 1 |
| Kejie Shen | 1 |
| Li, Kai | 1 |
| Liao, Hung-Chang | 1 |
| Luzhen Tang | 1 |
| Megan D. Wiedbusch | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 5 |
| Reports - Research | 4 |
| Reports - Descriptive | 1 |
Education Level
| Higher Education | 3 |
| Postsecondary Education | 3 |
Audience
Location
| China | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Daryn A. Dever; Megan D. Wiedbusch; Sarah M. Romero; Roger Azevedo – British Journal of Educational Technology, 2024
Intelligent tutoring systems (ITSs) incorporate pedagogical agents (PAs) to scaffold learners' self-regulated learning (SRL) via prompts and feedback to promote learners' monitoring and regulation of their cognitive, affective, metacognitive and motivational processes to achieve their (sub)goals. This study examines PAs' effectiveness in…
Descriptors: Intelligent Tutoring Systems, Scaffolding (Teaching Technique), Independent Study, Prompting
Yizhou Fan; Luzhen Tang; Huixiao Le; Kejie Shen; Shufang Tan; Yueying Zhao; Yuan Shen; Xinyu Li; Dragan Gaševic – British Journal of Educational Technology, 2025
With the continuous development of technological and educational innovation, learners nowadays can obtain a variety of supports from agents such as teachers, peers, education technologies, and recently, generative artificial intelligence such as ChatGPT. In particular, there has been a surge of academic interest in human-AI collaboration and…
Descriptors: College Students, Writing Achievement, Writing Exercises, Artificial Intelligence
Qin, Fen; Li, Kai; Yan, Jianyuan – British Journal of Educational Technology, 2020
Artificial Intelligence (AI) has penetrated the field of education. Trust has long been regarded as a driver for the acceptance of technology. Netnography and interviews were used to investigate trust in AI-based educational systems from the perspective of users. We identified the factors influencing trust in AI-based educational systems and…
Descriptors: Trust (Psychology), Artificial Intelligence, Classification, Context Effect
Doolittle, Peter E.; Bryant, Lauren H.; Chittum, Jessica R. – British Journal of Educational Technology, 2015
The construction of asynchronous learning environments often involves the creation of self-paced multimedia instructional episodes that provide the learner with control over the pacing of instruction (segmentation); however, does the amount of segmentation impact learning? This study explored the effects of the degree of segmentation on recall and…
Descriptors: Multimedia Instruction, Asynchronous Communication, Pacing, Learner Controlled Instruction
Wang, Ya-huei; Liao, Hung-Chang – British Journal of Educational Technology, 2011
In the conventional English as a Second Language (ESL) class-based learning environment, teachers use a fixed learning sequence and content for all students without considering the diverse needs of each individual. There is a great deal of diversity within and between classes. Hence, if students' learning outcomes are to be maximised, it is…
Descriptors: Cognitive Style, Learning Motivation, Learning Processes, Individualized Instruction

Peer reviewed
Direct link
