Publication Date
| In 2025 | 0 |
| Since 2024 | 2 |
| Since 2021 (last 5 years) | 5 |
| Since 2016 (last 10 years) | 9 |
| Since 2006 (last 20 years) | 13 |
Descriptor
Source
| International Educational… | 5 |
| Education and Information… | 2 |
| Journal of Educational Data… | 2 |
| Grantee Submission | 1 |
| Interactive Learning… | 1 |
| International Working Group… | 1 |
| Science Insights Education… | 1 |
Author
Publication Type
| Reports - Research | 8 |
| Journal Articles | 6 |
| Collected Works - Proceedings | 5 |
| Speeches/Meeting Papers | 1 |
Education Level
| Middle Schools | 13 |
| Junior High Schools | 12 |
| Secondary Education | 12 |
| Elementary Education | 9 |
| Higher Education | 6 |
| Postsecondary Education | 6 |
| Grade 8 | 5 |
| High Schools | 5 |
| Grade 7 | 3 |
| Elementary Secondary Education | 2 |
| Grade 9 | 2 |
| More ▼ | |
Audience
Location
| China | 3 |
| Brazil | 2 |
| Massachusetts | 2 |
| North Carolina | 2 |
| Afghanistan | 1 |
| Australia | 1 |
| Czech Republic | 1 |
| Illinois (Chicago) | 1 |
| Israel | 1 |
| Netherlands | 1 |
| Pennsylvania | 1 |
| More ▼ | |
Laws, Policies, & Programs
Assessments and Surveys
| Massachusetts Comprehensive… | 1 |
What Works Clearinghouse Rating
Peer reviewed
Direct linkAsselman, Amal; Khaldi, Mohamed; Aammou, Souhaib – Interactive Learning Environments, 2023
Performance Factors Analysis (PFA) is considered one of the most important Knowledge Tracing (KT) approaches used for constructing adaptive educational hypermedia systems. It has shown a high prediction accuracy against many other KT approaches. While, the desire to estimate more accurately the student level leads researchers to enhance PFA by…
Descriptors: Algorithms, Artificial Intelligence, Factor Analysis, Student Behavior
Jiawei Huang; Ding Zhou – Education and Information Technologies, 2024
Technological advancements have ushered in a new era of global educational development. Artificial Intelligence (AI) holds the potential to enhance teaching effectiveness and foster educational innovation. By utilizing student posture as a proxy, computer vision technology can accurately gauge levels of student engagement. While previous efforts…
Descriptors: Human Posture, Artificial Intelligence, Educational Technology, Learner Engagement
Ching-Huei Chen; Ching-Ling Chang – Education and Information Technologies, 2024
This study aimed to investigate the effectiveness of using AI-assisted game-based learning on science learning outcomes, intrinsic motivation, cognitive load, and learning behavior. A total of 202 seventh graders were recruited and randomly assigned to the following three groups: (1) Game only (N = 70), (2) GameGPT (N = 63), and (3)…
Descriptors: Artificial Intelligence, Game Based Learning, Technology Uses in Education, Science Instruction
Download full textHutt, Stephen; Ocumpaugh, Jaclyn; Ma, Juliana; Andres, Alexandra L.; Bosch, Nigel; Paquette, Luc; Biswas, Gautam; Baker, Ryan S. – International Educational Data Mining Society, 2021
Self-regulated learning (SRL) is a critical 21st -century skill. In this paper, we examine SRL through the lens of the searching, monitoring, assessing, rehearsing, and translating (SMART) schema for learning operations. We use microanalysis to measure SRL behaviors as students interact with a computer-based learning environment, Betty's Brain. We…
Descriptors: Models, Self Control, Learning Strategies, Student Behavior
Gong, Jie – Science Insights Education Frontiers, 2022
The Intelligent Research and Training Platform (IRTP) of the National Center for Educational Technology (NECT) is an application designed to integrate AI technology and teacher education in response to the "Artificial Intelligence + Teacher Education" strategy, in order to provide teacher professional development and power the…
Descriptors: Foreign Countries, Minority Group Students, Intelligent Tutoring Systems, Artificial Intelligence
Sao Pedro, Michael A.; Baker, Ryan S. J. d.; Gobert, Janice D.; Montalvo, Orlando; Nakama, Adam – Grantee Submission, 2013
We present work toward automatically assessing and estimating science inquiry skills as middle school students engage in inquiry within a physical science microworld. Towards accomplishing this goal, we generated machine-learned models that can detect when students test their articulated hypotheses, design controlled experiments, and engage in…
Descriptors: Artificial Intelligence, Inquiry, Middle School Students, Physical Sciences
A Contextualized, Differential Sequence Mining Method to Derive Students' Learning Behavior Patterns
Kinnebrew, John S.; Loretz, Kirk M.; Biswas, Gautam – Journal of Educational Data Mining, 2013
Computer-based learning environments can produce a wealth of data on student learning interactions. This paper presents an exploratory data mining methodology for assessing and comparing students' learning behaviors from these interaction traces. The core algorithm employs a novel combination of sequence mining techniques to identify deferentially…
Descriptors: Data Analysis, Middle School Students, Information Retrieval, Student Behavior
Sabourin, Jennifer L.; Rowe, Jonathan P.; Mott, Bradford W.; Lester, James C. – Journal of Educational Data Mining, 2013
Over the past decade, there has been growing interest in real-time assessment of student engagement and motivation during interactions with educational software. Detecting symptoms of disengagement, such as off-task behavior, has shown considerable promise for understanding students' motivational characteristics during learning. In this paper, we…
Descriptors: Student Behavior, Classification, Learner Engagement, Data Analysis
Rafferty, Anna N., Ed.; Whitehill, Jacob, Ed.; Romero, Cristobal, Ed.; Cavalli-Sforza, Violetta, Ed. – International Educational Data Mining Society, 2020
The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…
Descriptors: Educational Improvement, Teaching Methods, Information Retrieval, Data Processing
Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use
Barnes, Tiffany, Ed.; Chi, Min, Ed.; Feng, Mingyu, Ed. – International Educational Data Mining Society, 2016
The 9th International Conference on Educational Data Mining (EDM 2016) is held under the auspices of the International Educational Data Mining Society at the Sheraton Raleigh Hotel, in downtown Raleigh, North Carolina, in the USA. The conference, held June 29-July 2, 2016, follows the eight previous editions (Madrid 2015, London 2014, Memphis…
Descriptors: Data Analysis, Evidence Based Practice, Inquiry, Science Instruction
Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis
Barnes, Tiffany, Ed.; Desmarais, Michel, Ed.; Romero, Cristobal, Ed.; Ventura, Sebastian, Ed. – International Working Group on Educational Data Mining, 2009
The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…
Descriptors: Data Analysis, Educational Research, Conferences (Gatherings), Foreign Countries
