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Yujie Han; Sumin Hong; Zhenyan Li; Cheolil Lim – TechTrends: Linking Research and Practice to Improve Learning, 2025
This scoping review investigates the roles of intelligent learning companion systems (LCS) within educational settings, as well as the presences artificial intelligence (AI) embodies within these roles, and their application in education. Employing the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for…
Descriptors: Artificial Intelligence, Definitions, Classification, Technology Uses in Education
Chee-Kit Looi; Fenglin Jia – Education and Information Technologies, 2025
Since the advent of chatbots enabled by Generative AI such as ChatGPT, their application in the domain of education has been linked to promises of personalizing learning (PL). Through a study of conversational interactions of graduate students with such chatbots, this paper provides an empirical study of how current ChatGPT technologies can enable…
Descriptors: Individualized Instruction, Artificial Intelligence, Technology Uses in Education, Educational Technology
Peer reviewedHa Tien Nguyen; Conrad Borchers; Meng Xia; Vincent Aleven – Grantee Submission, 2024
Intelligent tutoring systems (ITS) can help students learn successfully, yet little work has explored the role of caregivers in shaping that success. Past interventions to support caregivers in supporting their child's homework have been largely disjunct from educational technology. The paper presents prototyping design research with nine middle…
Descriptors: Middle School Mathematics, Intelligent Tutoring Systems, Caregivers, Caregiver Attitudes
Xiaoyan Chu; Minjuan Wang; Jonathan Michael Spector; Nian-Shing Chen; Ching Sing Chai; Gwo-Jen Hwang; Xuesong Zhai – Educational Technology Research and Development, 2025
The Flipped Classroom Model (FCM) has gained widespread acceptance in higher education as an effective pedagogical strategy. Despite its success, the FCM still faces persistent concerns, including a lack of personalized interaction, limited application to introductory courses, and insufficient analysis of the learning process. The integration of…
Descriptors: Flipped Classroom, Artificial Intelligence, Technology Uses in Education, Educational Technology
Tawfik, Andrew A.; Gatewood, Jessica; Gish-Lieberman, Jaclyn J.; Hampton, Andrew J. – Technology, Knowledge and Learning, 2022
Various theories and models have implicitly discussed the role of interaction when using learning technologies. Indeed, interaction is described as being important as it relates to technology adoption, cognitive load, and usability. While each of these perspectives describe elements of interaction, they fail to comprehensively detail how educators…
Descriptors: Definitions, Learning Experience, Interaction, Usability
Ju, Song; Zhou, Guojing; Barnes, Tiffany; Chi, Min – International Educational Data Mining Society, 2020
Identifying critical decisions is one of the most challenging decision-making problems in real-world applications. In this work, we propose a novel Reinforcement Learning (RL) based Long-Short Term Rewards (LSTR) framework for critical decisions identification. RL is a machine learning area concerning with inducing effective decision-making…
Descriptors: Decision Making, Reinforcement, Artificial Intelligence, Man Machine Systems
Lippert, Anne; Shubeck, Keith; Morgan, Brent; Hampton, Andrew; Graesser, Arthur – Technology, Knowledge and Learning, 2020
This article describes designs that use multiple conversational agents within the framework of intelligent tutoring systems. Agents in this case are computerized talking heads or embodied animated avatars that help students learn by performing actions and holding conversations with them in natural language. The earliest conversational intelligent…
Descriptors: Intelligent Tutoring Systems, Man Machine Systems, Natural Language Processing, Educational Technology
Lippert, Anne; Shubeck, Keith; Morgan, Brent; Hampton, Andrew; Graesser, Arthur – Grantee Submission, 2020
This article describes designs that use multiple conversational agents within the framework of intelligent tutoring systems. Agents in this case are computerized talking heads or embodied animated avatars that help students learn by performing actions and holding conversations with them in natural language. The earliest conversational intelligent…
Descriptors: Intelligent Tutoring Systems, Man Machine Systems, Natural Language Processing, Educational Technology
Castro, Robin – Education and Information Technologies, 2019
Education is a complex system that requires multiple perspectives and levels of analysis to understand its contexts, dynamics, and actors' interactions, particularly concerning technological innovations. This paper aims to identify some of the most promising trends in blended learning implementations in higher education, the capabilities provided…
Descriptors: Blended Learning, Educational Technology, Technology Uses in Education, Higher Education
Yuan, Chia-Ching; Li, Cheng-Hsuan; Peng, Chin-Cheng – Interactive Learning Environments, 2023
Fighter jets are a critical national asset. Because of the high cost of their manufacture and that of their related equipment, both pilots and maintenance personnel must complete intensive training before coming into contact with a jet. Due to gradual military downsizing, one-on-one training is often impracticable, and the level of familiarization…
Descriptors: Artificial Intelligence, Man Machine Systems, Technology Uses in Education, Educational Technology
Holstein, Kenneth; McLaren, Bruce M.; Aleven, Vincent – Grantee Submission, 2019
As artificial intelligence (AI) increasingly enters K-12 classrooms, what do teachers and students see as the roles of human versus AI instruction, and how might educational AI (AIED) systems best be designed to support these complementary roles? We explore these questions through participatory design and needs validation studies with K12 teachers…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Instructional Design, Elementary Secondary Education
Song, Donggil – Contemporary Educational Technology, 2017
Learning-by-teaching has been identified as one of the more effective approaches to learning. Recently, educational researchers have investigated virtual environments in order to utilize the learning-by-teaching pedagogy. In a face-to-face learning-by-teaching situation, the role of the learners is to teach their peers or instructors. In virtual…
Descriptors: Intelligent Tutoring Systems, Concept Mapping, Man Machine Systems, Interaction
Bull, Susan; Kay, Judy – International Journal of Artificial Intelligence in Education, 2016
The SMILI? (Student Models that Invite the Learner In) Open Learner Model Framework was created to provide a coherent picture of the many and diverse forms of Open Learner Models (OLMs). The aim was for SMILI? to provide researchers with a systematic way to describe, compare and critique OLMs. We expected it to highlight those areas where there…
Descriptors: Educational Research, Data Collection, Data Analysis, Intelligent Tutoring Systems
Jordan, Pamela W.; Albacete, Patricia L.; Katz, Sandra – Grantee Submission, 2015
Tutorial dialogue systems often simulate tactics used by experienced human tutors such as restating students' dialogue input. We investigated whether the amount of tutor restatement that supports student inference interacts with students' incoming knowledge level in predicting how much students learn from a system. We found that students with…
Descriptors: Intelligent Tutoring Systems, Man Machine Systems, Interaction, Student Reaction
Letting Artificial Intelligence in Education out of the Box: Educational Cobots and Smart Classrooms
Timms, Michael J. – International Journal of Artificial Intelligence in Education, 2016
This paper proposes that the field of AIED is now mature enough to break away from being delivered mainly through computers and pads so that it can engage with students in new ways and help teachers to teach more effectively. Mostly, the intelligent systems that AIED has delivered so far have used computers and other devices that were essentially…
Descriptors: Artificial Intelligence, Educational Technology, Robotics, Intelligent Tutoring Systems
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