Publication Date
In 2025 | 65 |
Since 2024 | 214 |
Since 2021 (last 5 years) | 570 |
Since 2016 (last 10 years) | 1160 |
Since 2006 (last 20 years) | 1827 |
Descriptor
Source
Author
Publication Type
Education Level
Location
Taiwan | 48 |
China | 41 |
United Kingdom | 29 |
Pennsylvania | 27 |
Germany | 23 |
Turkey | 23 |
Canada | 22 |
Spain | 22 |
Massachusetts | 21 |
California | 15 |
India | 15 |
More ▼ |
Laws, Policies, & Programs
Every Student Succeeds Act… | 3 |
Elementary and Secondary… | 2 |
American Rescue Plan Act 2021 | 1 |
No Child Left Behind Act 2001 | 1 |
Assessments and Surveys
What Works Clearinghouse Rating
Meets WWC Standards without Reservations | 4 |
Meets WWC Standards with or without Reservations | 6 |
Does not meet standards | 2 |
Juan Zheng; Shan Li; Tingting Wang; Susanne P. Lajoie – International Journal of Educational Technology in Higher Education, 2024
Emotions play a crucial role in the learning process, yet there is a scarcity of studies examining emotion dynamics in problem-solving with fine-grained data and advanced tools. This study addresses this gap by investigating the emotional trajectories during self-regulated learning (SRL) phases (i.e., forethought, performance, and self-reflection)…
Descriptors: Medical Students, Problem Solving, Intelligent Tutoring Systems, Nonverbal Communication
Valentina Grion; Juliana Raffaghelli; Beatrice Doria; Anna Serbati – Educational Research and Evaluation, 2024
Feedback is crucial for improving student learning. In this regard, overcoming the transmissive conception of feedback in favour of its dialogic function introduces new reflections concerning the internal generative feedback process. In this regard, Nicol [(2020). The power of internal feedback: Exploiting natural comparator processes.…
Descriptors: Student Attitudes, Self Evaluation (Individuals), Feedback (Response), Individual Differences
Sajja, Ramteja; Sermet, Yusuf; Cwiertny, David; Demir, Ibrahim – International Journal of Educational Technology in Higher Education, 2023
Miscommunication between instructors and students is a significant obstacle to post-secondary learning. Students may skip office hours due to insecurities or scheduling conflicts, which can lead to missed opportunities for questions. To support self-paced learning and encourage creative thinking skills, academic institutions must redefine their…
Descriptors: College Students, Artificial Intelligence, Teaching Assistants, Intelligent Tutoring Systems
Scruggs, Richard; Baker, Ryan S.; Pavlik, Philip I., Jr.; McLaren, Bruce M.; Liu, Ziyang – Educational Technology Research and Development, 2023
Despite considerable advances in knowledge tracing algorithms, educational technologies that use this technology typically continue to use older algorithms, such as Bayesian Knowledge Tracing. One key reason for this is that contemporary knowledge tracing algorithms primarily infer next-problem correctness in the learning system, but do not…
Descriptors: Algorithms, Prediction, Knowledge Level, Video Games
Huang, Yun; Brusilovsky, Peter; Guerra, Julio; Koedinger, Kenneth; Schunn, Christian – Journal of Computer Assisted Learning, 2023
Background: Skill integration is vital in students' mastery development and is especially prominent in developing code tracing skills which are foundational to programming, an increasingly important area in the current STEM education. However, instructional design to support skill integration in learning technologies has been limited. Objectives:…
Descriptors: Intelligent Tutoring Systems, Coding, Programming, Skill Development
Wang, Tingting; Li, Shan; Huang, Xiaoshan; Pan, Zexuan; Lajoie, Susanne P. – Education and Information Technologies, 2023
Students process qualitatively and quantitatively different information during the dynamic self-regulated learning (SRL) process, and thus they may experience varying cognitive load in different SRL behaviors. However, there is limited research on the role of cognitive load in SRL. This study examined students' cognitive load in micro-level SRL…
Descriptors: Cognitive Processes, Difficulty Level, Learning Strategies, Self Efficacy
Essa, Eman Khaled – International Journal of Research in Education and Science, 2023
With the escalation of the COVID-19 crisis, many educational institutions have turned to distance education, especially universities and higher education institutions, which may affect the quality of learning outcomes especially those related to deeper learning and academic mindfulness. The present study aimed at investigating the effectiveness of…
Descriptors: College Students, Blended Learning, Metacognition, Instructional Effectiveness
Jantakun, Thiti; Jantakun, Kitsadaporn; Jantakoon, Thada – Online Submission, 2023
Advances in augmented and virtual reality (AVR) technology have allowed for the development of AVR interactive learning environments (AVR-ILEs) with increasing fidelity. When paired with a suitably capable computer tutor agent, such environments can permit adaptive and self-directed learning of procedural skills in some cases. We undertook a…
Descriptors: Virtual Classrooms, Computer Simulation, Intelligent Tutoring Systems, Skill Development
Assim S. Alrajhi – Education and Information Technologies, 2025
Motivated by the proliferation of artificial intelligence that has the potential to promote self-access learning, this study utilizes a sequential explanatory quasi-experimental mixed methods design to investigate the efficacy of Google Assistant (GA) in facilitating second language (L2) vocabulary learning compared to online dictionaries. A…
Descriptors: English (Second Language), Second Language Learning, Artificial Intelligence, Vocabulary Development
William T. Faranda – Marketing Education Review, 2025
Students' approaches to learning, including "deep," "surface," or "strategic" methods, significantly impact their academic success and skill development. This study investigates the transition in learning approach preferences among marketing majors, comparing junior-level students beginning their upper-division…
Descriptors: Business Education, Marketing, Capstone Experiences, Academic Achievement
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
Zhou, Guojing; Azizsoltani, Hamoon; Ausin, Markel Sanz; Barnes, Tiffany; Chi, Min – International Journal of Artificial Intelligence in Education, 2022
In interactive e-learning environments such as Intelligent Tutoring Systems, pedagogical decisions can be made at different levels of granularity. In this work, we focus on making decisions at "two levels": whole problems vs. single steps and explore three types of granularity: "problem-level only" ("Prob-Only"),…
Descriptors: Electronic Learning, Intelligent Tutoring Systems, Decision Making, Problem Solving
Laine, Joakim; Lindqvist, Timo; Korhonen, Tiina; Hakkarainen, Kai – International Journal of Technology in Education and Science, 2022
Advances in immersive virtual reality (I-VR) technology have allowed for the development of I-VR learning environments (I-VRLEs) with increasing fidelity. When coupled with a sufficiently advanced computer tutor agent, such environments can facilitate asynchronous and self-regulated approaches to learning procedural skills in industrial settings.…
Descriptors: Intelligent Tutoring Systems, Computer Simulation, Industry, Job Skills
Shakya, Anup; Rus, Vasile; Venugopal, Deepak – International Educational Data Mining Society, 2021
Predicting student problem-solving strategies is a complex problem but one that can significantly impact automated instruction systems since they can adapt or personalize the system to suit the learner. While for small datasets, learning experts may be able to manually analyze data to infer student strategies, for large datasets, this approach is…
Descriptors: Prediction, Problem Solving, Intelligent Tutoring Systems, Learning Strategies
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