Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 3 |
| Since 2016 (last 10 years) | 10 |
| Since 2006 (last 20 years) | 14 |
Descriptor
Source
| International Educational… | 14 |
Author
Publication Type
| Speeches/Meeting Papers | 8 |
| Collected Works - Proceedings | 6 |
| Reports - Research | 6 |
| Reports - Descriptive | 1 |
| Reports - Evaluative | 1 |
Education Level
Audience
Location
| Afghanistan | 1 |
| Australia | 1 |
| Brazil | 1 |
| California | 1 |
| California (Stanford) | 1 |
| China | 1 |
| Finland | 1 |
| France | 1 |
| Germany | 1 |
| Illinois (Chicago) | 1 |
| North Carolina | 1 |
| More ▼ | |
Laws, Policies, & Programs
Assessments and Surveys
| Program for International… | 1 |
What Works Clearinghouse Rating
Peer reviewed
Download full textLoginova, Ekaterina; Benoit, Dries F. – International Educational Data Mining Society, 2021
Predicting academic performance using trace data from learning management systems is a primary research topic in educational data mining. An important application is the identification of students at risk of failing the course or dropping out. However, most approaches utilise past grades, which are not always available and capture little of the…
Descriptors: Navigation (Information Systems), Academic Achievement, Grade Prediction, Integrated Learning Systems
Fancsali, Stephen E.; Murphy, April; Ritter, Steve – International Educational Data Mining Society, 2022
Ten years after the announcement of the "rise of the super experiment" at Educational Data Mining 2012, challenges to implementing "internet scale" educational experiments often persist for educational technology providers, especially when they seek to test substantive instructional interventions. Studies that deploy and test…
Descriptors: Learning Analytics, Educational Technology, Barriers, Data Analysis
Jiang, Weijie; Pardos, Zachary A. – International Educational Data Mining Society, 2020
Data mining of course enrollment and course description records has soared as institutions of higher education begin tapping into the value of these data for academic and internal research purposes. This has led to a more than doubling of papers on course prediction tasks every year. The papers often center around a single prediction task and…
Descriptors: Course Descriptions, Models, Prediction, Course Selection (Students)
Sha, Lele; Rakovic, Mladen; Li, Yuheng; Whitelock-Wainwright, Alexander; Carroll, David; Gaševic, Dragan; Chen, Guanliang – International Educational Data Mining Society, 2021
Classifying educational forum posts is a longstanding task in the research of Learning Analytics and Educational Data Mining. Though this task has been tackled by applying both traditional Machine Learning (ML) approaches (e.g., Logistics Regression and Random Forest) and up-to-date Deep Learning (DL) approaches, there lacks a systematic…
Descriptors: Classification, Computer Mediated Communication, Learning Analytics, Data Analysis
Choi, Hongkyu; Lee, Ji Eun; Hong, Won-joon; Lee, Kyumin; Recker, Mimi; Walker, Andy – International Educational Data Mining Society, 2016
This research connects several data-driven educational data mining approaches to a framework for interaction developed in educational research. In particular, 10 million usage data points collected by a Learning Management System used by students and teachers in 450 online undergraduate courses were analyzed with this framework. A range of…
Descriptors: Integrated Learning Systems, Data Analysis, Multivariate Analysis, Multiple Regression Analysis
Gitinabard, Niki; Barnes, Tiffany; Heckman, Sarah; Lynch, Collin F. – International Educational Data Mining Society, 2019
Students' interactions with online tools can provide us with insights into their study and work habits. Prior research has shown that these habits, even as simple as the number of actions or the time spent on online platforms can distinguish between the higher performing students and low-performers. These habits are also often used to predict…
Descriptors: Blended Learning, Student Adjustment, Online Courses, Study Habits
Feild, Jacqueline – International Educational Data Mining Society, 2015
Providing students with continuous and personalized feedback on their performance is an important part of encouraging self regulated learning. As part of our higher education platform, we built a set of data visualizations to provide feedback to students on their assignment performance. These visualizations give students information about how they…
Descriptors: Student Improvement, Performance, Feedback (Response), Assignments
Santos, Olga Cristina, Ed.; Boticario, Jesus Gonzalez, Ed.; Romero, Cristobal, Ed.; Pechenizkiy, Mykola, Ed.; Merceron, Agathe, Ed.; Mitros, Piotr, Ed.; Luna, Jose Maria, Ed.; Mihaescu, Cristian, Ed.; Moreno, Pablo, Ed.; Hershkovitz, Arnon, Ed.; Ventura, Sebastian, Ed.; Desmarais, Michel, Ed. – International Educational Data Mining Society, 2015
The 8th International Conference on Educational Data Mining (EDM 2015) is held under auspices of the International Educational Data Mining Society at UNED, the National University for Distance Education in Spain. The conference held in Madrid, Spain, July 26-29, 2015, follows the seven previous editions (London 2014, Memphis 2013, Chania 2012,…
Descriptors: Data Analysis, Educational Research, Computer Uses in Education, Integrated Learning Systems
Kim, Jihie; Shaw, Erin; Xu, Hao; Adarsh, G. V. – International Educational Data Mining Society, 2012
In this paper we examine the collaborative performance of undergraduate engineering students who used shared project documents (Wikis, Google documents) and a software version control system (SVN) to support project collaboration. We present an initial implementation of TeamAnalytics, an instructional tool that facilitates the analyses of the…
Descriptors: Undergraduate Students, Engineering Education, Teamwork, Group Activities
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
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
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection
