Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 3 |
Since 2016 (last 10 years) | 13 |
Since 2006 (last 20 years) | 16 |
Descriptor
Data Collection | 16 |
Foreign Countries | 16 |
Data Analysis | 9 |
College Students | 8 |
Models | 8 |
Online Courses | 7 |
Prediction | 7 |
Student Behavior | 7 |
Academic Achievement | 6 |
Intelligent Tutoring Systems | 6 |
Large Group Instruction | 6 |
More ▼ |
Source
International Educational… | 16 |
Author
Publication Type
Speeches/Meeting Papers | 11 |
Reports - Research | 9 |
Collected Works - Proceedings | 5 |
Reports - Evaluative | 2 |
Education Level
Audience
Location
Brazil | 2 |
European Union | 2 |
Germany | 2 |
Netherlands | 2 |
Uruguay | 2 |
Australia | 1 |
China | 1 |
China (Shanghai) | 1 |
Czech Republic | 1 |
Denmark | 1 |
Finland | 1 |
More ▼ |
Laws, Policies, & Programs
Family Educational Rights and… | 1 |
Assessments and Surveys
Program for International… | 1 |
What Works Clearinghouse Rating
Hutt, Stephen; Das, Sanchari; Baker, Ryan S. – International Educational Data Mining Society, 2023
The General Data Protection Regulation (GDPR) in the European Union contains directions on how user data may be collected, stored, and when it must be deleted. As similar legislation is developed around the globe, there is the potential for repercussions across multiple fields of research, including educational data mining (EDM). Over the past two…
Descriptors: Data Analysis, Decision Making, Data Collection, Foreign Countries
Cechák, Jaroslav; Pelánek, Radek – International Educational Data Mining Society, 2021
Measuring similarity of educational items has several applications in the development of adaptive learning systems, and previous research has already proposed a wide range of similarity measures. In this work, we provide an experimental evaluation of selected similarity measures using a large dataset. The used items are alternate-choice questions…
Descriptors: Measurement, Proximity, Grammar, English (Second Language)
Sturludóttir, Erla Guðrún; Arnardóttir, Eydís; Hjálmtýsson, Gísli; Óskarsdóttir, María – International Educational Data Mining Society, 2021
Gaining insight into course choices holds significant value for universities, especially those who aim for flexibility in their programs and wish to adapt quickly to changing demands of the job market. However, little emphasis has been put on utilizing the large amount of educational data to understand these course choices. Here, we use network…
Descriptors: Course Selection (Students), Undergraduate Students, Engineering Education, Business Administration Education
Klose, Mark; Desai, Vasvi; Song, Yang; Gehringer, Edward – International Educational Data Mining Society, 2020
Imagine a student using an intelligent tutoring system. A researcher records the correctness and time of each of your attempts at solving a math problem, nothing more. With no names, no birth dates, no connections to the school, you would think it impossible to track the answers back to the class. Yet, class sections have been identified with no…
Descriptors: Privacy, Learning Analytics, Data Collection, Information Storage
Lorenzen, Stephan; Hjuler, Niklas; Alstrup, Stephen – International Educational Data Mining Society, 2018
Analysis of log data generated by online educational systems is an essential task to better the educational systems and increase our understanding of how students learn. In this study we investigate previously unseen data from Clio Online, the largest provider of digital learning content for primary schools in Denmark. We consider data for 14,810…
Descriptors: Data Collection, Student Behavior, Elementary School Students, Foreign Countries
Morsomme, Raphaël; Alferez, Sofia Vazquez – International Educational Data Mining Society, 2019
Liberal Arts programs are often characterized by their open curriculum. Yet, the abundance of courses available and the highly personalized curriculum are often overwhelming for students who must select courses relevant to their academic interests and suitable to their academic background. This paper presents the course recommender system that we…
Descriptors: Liberal Arts, Course Selection (Students), Courses, College Students
Development of a Trajectory Model for Visualizing Teacher ICT Usage Based on Event Segmentation Data
Zheng, Longwei; Shi, Rui; Wu, Bingcong; Gu, Xiaoqing; Feng, Yuanyuan – International Educational Data Mining Society, 2017
The adoption of educational technologies such as e-textbook has offered a new opportunity to gain insight into teachers' usage of ICT (Information and Communication Technologies). In the e-textbook platform, customized digital products and the learning activities organized in digital environment require teachers to make greater efforts in planning…
Descriptors: Educational Technology, Technology Uses in Education, Visualization, Data Collection
Bao, Yingying; Chen, Guanliang; Hauff, Claudia – International Educational Data Mining Society, 2017
Massive Open Online Courses (MOOCs) are a promising form of online education. However, the occurrence of academic dishonesty has been threatening MOOC certificates' effectiveness as a serious tool for recruiters and employers. Recently, a large-scale study on the log traces from more than one hundred MOOCs created by Harvard and MIT has identified…
Descriptors: Large Group Instruction, Online Courses, Cheating, Incidence
Voß, Lydia; Schatten, Carlotta; Mazziotti, Claudia; Schmidt-Thieme, Lars – International Educational Data Mining Society, 2015
Machine Learning methods for Performance Prediction in Intelligent Tutoring Systems (ITS) have proven their efficacy; specific methods, e.g. Matrix Factorization (MF), however suffer from the lack of available information about new tasks or new students. In this paper we show how this problem could be solved by applying Transfer Learning (TL),…
Descriptors: Transfer of Training, Intelligent Tutoring Systems, Statistics, Probability
McBroom, Jessica; Jeffries, Bryn; Koprinska, Irena; Yacef, Kalina – International Educational Data Mining Society, 2016
Effective mining of data from online submission systems offers the potential to improve educational outcomes by identifying student habits and behaviours and their relationship with levels of achievement. In particular, it may assist in identifying students at risk of performing poorly, allowing for early intervention. In this paper we investigate…
Descriptors: Data Collection, Student Behavior, Academic Achievement, Correlation
Strecht, Pedro; Cruz, Luís; Soares, Carlos; Mendes-Moreira, João; Abreu, Rui – International Educational Data Mining Society, 2015
Predicting the success or failure of a student in a course or program is a problem that has recently been addressed using data mining techniques. In this paper we evaluate some of the most popular classification and regression algorithms on this problem. We address two problems: prediction of approval/failure and prediction of grade. The former is…
Descriptors: Comparative Analysis, Classification, Regression (Statistics), Mathematics
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
Boyer, Kristy Elizabeth, Ed.; Yudelson, Michael, Ed. – International Educational Data Mining Society, 2018
The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…
Descriptors: Data Collection, Data Analysis, Computer Science Education, Program Proposals
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
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
Previous Page | Next Page »
Pages: 1 | 2