Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 5 |
| Since 2017 (last 10 years) | 11 |
| Since 2007 (last 20 years) | 32 |
Descriptor
| Educational Environment | 52 |
| Models | 52 |
| Computer Simulation | 35 |
| Simulation | 17 |
| Computer Assisted Instruction | 16 |
| Instructional Design | 12 |
| Problem Solving | 11 |
| Teaching Methods | 11 |
| Educational Technology | 10 |
| Electronic Learning | 10 |
| Foreign Countries | 10 |
| More ▼ | |
Source
Author
Publication Type
Education Level
Audience
| Policymakers | 1 |
Location
| Spain | 4 |
| Netherlands | 3 |
| Australia | 2 |
| China | 2 |
| Pennsylvania | 2 |
| United Kingdom | 2 |
| Asia | 1 |
| Brazil | 1 |
| Connecticut | 1 |
| Costa Rica | 1 |
| Croatia | 1 |
| More ▼ | |
Laws, Policies, & Programs
Assessments and Surveys
| Program for International… | 1 |
| Rosenberg Self Esteem Scale | 1 |
What Works Clearinghouse Rating
Bahar Radmehr; Adish Singla; Tanja Käser – International Educational Data Mining Society, 2024
There has been a growing interest in developing learner models to enhance learning and teaching experiences in educational environments. However, existing works have primarily focused on structured environments relying on meticulously crafted representations of tasks, thereby limiting the agent's ability to generalize skills across tasks. In this…
Descriptors: Reinforcement, Artificial Intelligence, Educational Environment, Natural Language Processing
Nan Zhang; Hongkai Wang; Tianqi Huang; Xinran Zhang; Hongen Liao – IEEE Transactions on Learning Technologies, 2024
Trunk anatomy education is critical in the training of the surgeon. Most trunk anatomy education systems use a personal or synthetic anatomical model. It remains difficult to obtain appropriate population anatomy information and create individualized anatomy customization based on a quantity of diverse data. Furthermore, the naked-eye virtual…
Descriptors: Computer Simulation, Simulated Environment, Human Body, Anatomy
Tracy Bobko; Mikiko Corsette; Minjuan Wang; Erin Springer – IEEE Transactions on Learning Technologies, 2024
This article discusses the transformative impact of technology on knowledge acquisition and sharing, focusing on the emergence of the metaverse as a virtual community with vast potential for virtual learning. Learning in the metaverse is found to enhance engagement, motivation, and retention, while fostering 21st-century skills. It also offers…
Descriptors: Educational Innovation, Computer Simulation, Technology Uses in Education, Models
Zoran Sevarac; Jelena Jovanovic; Vladan Devedzic; Bojan Tomic – Interactive Learning Environments, 2023
The paper proposes EXPLODE, a new model of exploratory learning environment for teaching and learning neural networks. The EXPLODE model is about pedagogically instrumenting a software development environment to transform it into an exploratory learning environment for neural networks. Such an environment is particularly aimed for students who are…
Descriptors: Models, Discovery Learning, Artificial Intelligence, Computer Simulation
Nadav Aridan; Michal Bernstein-Eliav; Dana Gamzo; Maya Schmeidler; Niv Tik; Ido Tavor – Anatomical Sciences Education, 2024
Anatomy studies are an essential part of medical training. The study of neuroanatomy in particular presents students with a unique challenge of three-dimensional spatial understanding. Virtual Reality (VR) has been suggested to address this challenge, yet the majority of previous reports have implemented computer-generated or imaging-based models…
Descriptors: Anatomy, Neurology, Electronic Learning, Computer Simulation
Chu, Kar-Hai; Shensa, Ariel; Colditz, Jason B.; Sidani, Jaime E.; Hoffman, Beth L.; Sinclair, David; Krauland, Mary G.; Primack, Brian A. – Health Education & Behavior, 2020
Background: The use of electronic cigarettes (e-cigarette) offers potential to facilitate cigarette smoking cessation, yet potentially increases risk of cigarette smoking initiation. This relationship has been primarily modeled in mathematical ways that often do not represent real-world complexities, which could inform decisions regarding local…
Descriptors: Smoking, Electronic Equipment, Risk, Health Behavior
Goksu, Idris; Islam Bolat, Yusuf – Review of Education, 2021
In this meta-analysis, the aim is to determine the overall effect of the ARCS (attention, relevance, confidence, satisfaction) model of motivation on students' academic achievement, motivation, attention, relevance, confidence and satisfaction. Additionally, the effect of the model is analysed according to the learning environment in which the…
Descriptors: Models, Student Motivation, Academic Achievement, Attention
Pan, Xu-Wei; Ding, Ling; Zhu, Xi-Yong; Yang, Zhao-Xiang – EURASIA Journal of Mathematics, Science & Technology Education, 2017
In m-learning environments, context-awareness is for wide use where learners' situations are varied, dynamic and unpredictable. We are facing the challenge of requirements of both generality and depth in generating and processing high-level context. In this paper, we present a social approach which exploits social dynamics and social computing for…
Descriptors: Electronic Learning, Social Media, Educational Environment, Models
Fratamico, Lauren; Conati, Cristina; Kardan, Samad; Roll, Ido – International Journal of Artificial Intelligence in Education, 2017
Interactive simulations can facilitate inquiry learning. However, similarly to other Exploratory Learning Environments, students may not always learn effectively in these unstructured environments. Thus, providing adaptive support has great potential to help improve student learning with these rich activities. Providing adaptive support requires a…
Descriptors: Computer Simulation, Models, Educational Environment, Comparative Analysis
An Evaluation of the Alignment Method for Detecting Measurement Noninvariance in Noncognitive Scales
Jessica Kay Flake – ProQuest LLC, 2015
In recent years a new methodology, the alignment method (Asparouhov & Muthen, 2014), has surfaced for estimating measurement models and detecting measurement noninvariance (i.e., DIF) across many groups. The purpose of the current study was to investigate the alignment method for use with non-cognitive scales across groups of students from…
Descriptors: Measures (Individuals), Methods, Measurement, Models
Cocea, Mihaela; Magoulas, George D. – IEEE Transactions on Learning Technologies, 2017
Exploratory learning environments (ELEs) promote a view of learning that encourages students to construct and/or explore models and observe the effects of modifying their parameters. The freedom given to learners in this exploration context leads to a variety of learner approaches for constructing models and makes modelling of learner behavior a…
Descriptors: Generalization, Mathematics Instruction, Computer Simulation, Discovery Learning
Orhan, Sevil; Karaman, M. Kemal – International Association for Development of the Information Society, 2014
Specifically Second Life (SL) among virtual worlds draws attention of researchers to form collaborative learning environments (Sutcliffe & Alrayes, 2012) since it could be used as a rich platform to simulate a real environment containing many collaborative learning characteristics and interaction tools within itself. Five Stage Model (FSM)…
Descriptors: Computer Simulation, Simulated Environment, Cooperative Learning, Educational Environment
Chickerur, Satyadhyan; Joshi, Kartik – British Journal of Educational Technology, 2015
Emotion detection using facial images is a technique that researchers have been using for the last two decades to try to analyze a person's emotional state given his/her image. Detection of various kinds of emotion using facial expressions of students in educational environment is useful in providing insight into the effectiveness of tutoring…
Descriptors: Nonverbal Communication, Psychological Patterns, Recognition (Psychology), Computer Simulation
Lamb, Richard L. – Journal of Science Education and Technology, 2016
Within the last 10 years, new tools for assisting in the teaching and learning of academic skills and content within the context of science have arisen. These new tools include multiple types of computer software and hardware to include (video) games. The purpose of this study was to examine and compare the effect of computer learning games in the…
Descriptors: Cognitive Processes, Computation, Models, Science Laboratories
Andrade, Alejandro; Danish, Joshua A.; Maltese, Adam V. – Journal of Learning Analytics, 2017
Interactive learning environments with body-centric technologies lie at the intersection of the design of embodied learning activities and multimodal learning analytics. Sensing technologies can generate large amounts of fine-grained data automatically captured from student movements. Researchers can use these fine-grained data to create a…
Descriptors: Measurement, Interaction, Models, Educational Environment

Peer reviewed
Direct link
