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Shimmei, Machi; Matsuda, Noboru – International Educational Data Mining Society, 2023
We propose an innovative, effective, and data-agnostic method to train a deep-neural network model with an extremely small training dataset, called VELR (Voting-based Ensemble Learning with Rejection). In educational research and practice, providing valid labels for a sufficient amount of data to be used for supervised learning can be very costly…
Descriptors: Artificial Intelligence, Training, Natural Language Processing, Educational Research
Hao Zhou; Wenge Rong; Jianfei Zhang; Qing Sun; Yuanxin Ouyang; Zhang Xiong – IEEE Transactions on Learning Technologies, 2025
Knowledge tracing (KT) aims to predict students' future performances based on their former exercises and additional information in educational settings. KT has received significant attention since it facilitates personalized experiences in educational situations. Simultaneously, the autoregressive (AR) modeling on the sequence of former exercises…
Descriptors: Learning Experience, Academic Achievement, Data, Artificial Intelligence
Razvan Paroiu; Stefan Ruseti; Mihai Dascalu; Stefan Trausan-Matu; Danielle S. McNamara – Grantee Submission, 2023
The exponential growth of scientific publications increases the effort required to identify relevant articles. Moreover, the scale of studies is a frequent barrier to research as the majority of studies are low or medium-scaled and do not generalize well while lacking statistical power. As such, we introduce an automated method that supports the…
Descriptors: Science Education, Educational Research, Scientific and Technical Information, Journal Articles
Nicula, Bogdan; Perret, Cecile A.; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2020
Open-ended comprehension questions are a common type of assessment used to evaluate how well students understand one of multiple documents. Our aim is to use natural language processing (NLP) to infer the level and type of inferencing within readers' answers to comprehension questions using linguistic and semantic features within their responses.…
Descriptors: Natural Language Processing, Taxonomy, Responses, Semantics
Sharp, Rebecca Reynolds – ProQuest LLC, 2017
We address the challenging task of "computational natural language inference," by which we mean bridging two or more natural language texts while also providing an explanation of how they are connected. In the context of question answering (i.e., finding short answers to natural language questions), this inference connects the question…
Descriptors: Computation, Natural Language Processing, Inferences, Questioning Techniques
Liu, Ming; Calvo, Rafael A.; Rus, Vasile – Educational Technology & Society, 2014
Critical review skill is one important aspect of academic writing. Generic trigger questions have been widely used to support this activity. When students have a concrete topic in mind, trigger questions are less effective if they are too general. This article presents a learning-to-rank based system which automatically generates specific trigger…
Descriptors: Electronic Learning, Natural Language Processing, Questioning Techniques, Classification
Becker, Lee – ProQuest LLC, 2012
While many studies have demonstrated that conversational tutoring systems have a positive effect on learning, the amount of manual effort required to author, design, and tune dialogue behaviors remains a major barrier to widespread deployment and adoption of these systems. Such dialogue systems must not only understand student speech, but must…
Descriptors: Intelligent Tutoring Systems, Speech, Computer Mediated Communication, Natural Language Processing
Moffitt, Kevin Christopher – ProQuest LLC, 2011
The three objectives of this dissertation were to develop a question type model for predicting linguistic features of responses to interview questions, create a tool for linguistic analysis of documents, and use lexical bundle analysis to identify linguistic differences between fraudulent and non-fraudulent financial reports. First, The Moffitt…
Descriptors: Cues, Verbs, Natural Language Processing, Discriminant Analysis
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.; 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
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
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers