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San Pedro, Maria Ofelia Z.; Snow, Erica L.; Baker, Ryan S.; McNamara, Danielle S.; Heffernan, Neil T. – International Educational Data Mining Society, 2015
There is increasing evidence that fine-grained aspects of student performance and interaction within educational software are predictive of long-term learning. Machine learning models have been used to provide assessments of affect, behavior, and cognition based on analyses of system log data, estimating the probability of a student's particular…
Descriptors: Mathematics Tests, Achievement Tests, Middle School Students, Intelligent Tutoring Systems
Heffernan, Neil T.; Heffernan, Cristina Lindquist – International Journal of Artificial Intelligence in Education, 2014
The ASSISTments project is an ecosystem of a few hundred teachers, a platform, and researchers working together. Development professionals help train teachers and get teachers to participate in studies. The platform and these teachers help researchers (sometimes explicitly and sometimes implicitly) simply by using content the teacher selects. The…
Descriptors: Intelligent Tutoring Systems, Educational Research, Formative Evaluation, Artificial Intelligence
Arroyo, Ivon; Woolf, Beverly Park; Burelson, Winslow; Muldner, Kasia; Rai, Dovan; Tai, Minghui – International Journal of Artificial Intelligence in Education, 2014
This article describes research results based on multiple years of experimentation and real-world experience with an adaptive tutoring system named Wayang Outpost. The system represents a novel adaptive learning technology that has shown successful outcomes with thousands of students, and provided teachers with valuable information about students'…
Descriptors: Intelligent Tutoring Systems, Multimedia Instruction, Mathematics Instruction, Learner Engagement
Feng, Mingyu; Beck, Joseph – International Working Group on Educational Data Mining, 2009
Representing domain knowledge is important for constructing educational software, and automated approaches have been proposed to construct and refine such models. In this paper, instead of applying automated and computationally intensive approaches, we simply start with existing hand-constructed transfer models at various levels of granularity and…
Descriptors: Data Analysis, Models, Transfer of Training, Intelligent Tutoring Systems
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