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Geden, Michael; Emerson, Andrew; Carpenter, Dan; Rowe, Jonathan; Azevedo, Roger; Lester, James – International Journal of Artificial Intelligence in Education, 2021
Game-based learning environments are designed to provide effective and engaging learning experiences for students. Predictive student models use trace data extracted from students' in-game learning behaviors to unobtrusively generate early assessments of student knowledge and skills, equipping game-based learning environments with the capacity to…
Descriptors: Game Based Learning, Middle School Students, Microbiology, Secondary School Science
Allen, Laura K.; McNamara, Danielle S. – International Educational Data Mining Society, 2015
The current study investigates the degree to which the lexical properties of students' essays can inform stealth assessments of their vocabulary knowledge. In particular, we used indices calculated with the natural language processing tool, TAALES, to predict students' performance on a measure of vocabulary knowledge. To this end, two corpora were…
Descriptors: Vocabulary, Knowledge Level, Models, Natural Language Processing
Nguyen, Huy; Xiong, Wenting; Litman, Diane – International Journal of Artificial Intelligence in Education, 2017
A peer-review system that automatically evaluates and provides formative feedback on free-text feedback comments of students was iteratively designed and evaluated in college and high-school classrooms. Classroom assignments required students to write paper drafts and submit them to a peer-review system. When student peers later submitted feedback…
Descriptors: Computer Uses in Education, Computer Mediated Communication, Feedback (Response), Peer Evaluation
Mason, Lucia; Tornatora, Maria Caterina; Pluchino, Patrik – Reading and Writing: An Interdisciplinary Journal, 2015
Printed or digital textbooks contain texts accompanied by various kinds of visualisation. Successful comprehension of these materials requires integrating verbal and graphical information. This study investigates the time course of processing an illustrated text through eye-tracking methodology in the school context. The aims were to identify…
Descriptors: Illustrations, Language Processing, Reading, Eye Movements
Liu, Xiaochen; Marchis, Lavinia; DeBiase, Emily; Breaux, Kristina C.; Courville, Troy; Pan, Xingyu; Hatcher, Ryan C.; Koriakin, Taylor; Choi, Dowon; Kaufman, Alan S. – Journal of Psychoeducational Assessment, 2017
This study investigated the relationship between specific cognitive patterns of strengths and weaknesses (PSWs) and the errors children make in reading, writing, and spelling tests from the Kaufman Test of Educational Achievement-Third Edition (KTEA-3). Participants were selected from the KTEA-3 standardization sample based on five cognitive…
Descriptors: Achievement Tests, Cognitive Processes, Error Patterns, Reading
Berninger, Virginia; Abbott, Robert; Cook, Clayton R.; Nagy, William – Journal of Learning Disabilities, 2017
Relationships between attention/executive functions and language learning were investigated in students in Grades 4 to 9 (N = 88) with and without specific learning disabilities (SLDs) in multiword syntax in oral and written language (OWL LD), word reading and spelling (dyslexia), and subword letter writing (dysgraphia). Prior…
Descriptors: Correlation, Attention Control, Executive Function, Multiple Regression Analysis
Katz, Sandra; Albacete, Patricia L. – Journal of Educational Psychology, 2013
For some time, it has been clear that students who are tutored generally learn more than students who experience classroom instruction (e.g., Bloom, 1984). Much research has been devoted to identifying features of tutorial dialogue that can explain its effectiveness, so that these features can be simulated in natural-language tutoring systems. One…
Descriptors: Intelligent Tutoring Systems, Natural Language Processing, Interaction, Rhetorical Theory
Katz, Sandra; Albacete, Patricia L. – Grantee Submission, 2013
For some time, it has been clear that students who are tutored generally learn more than students who experience classroom instruction (e.g., Bloom, 1984). Much research has been devoted to identifying features of tutorial dialogue that can explain its effectiveness, so that these features can be simulated in natural-language tutoring systems. One…
Descriptors: Rhetorical Theory, Tutoring, Intelligent Tutoring Systems, Secondary School Science
Leong, Che Kan; Ho, Man Koon; Chang, Jianfang; Hau, Kit Tai – Language Testing, 2013
The present study examined pedagogic components of Chinese reading literacy in a representative sample of 1164 Grades 7, 9 and 11 Chinese students (mean age of 15 years) from 11 secondary schools in Hong Kong with each student tested for about 2.5 hours. Multiple group confirmatory factor analyses showed that across the three grade levels, the…
Descriptors: Foreign Countries, Secondary School Students, Grade 7, Grade 9
Bekebrede, Judith; van der Leij, Aryan; Share, David L. – Reading and Writing: An Interdisciplinary Journal, 2009
The phonological-core variable-orthographic differences (PCVOD) model [van der Leij, & Morfidi (2006). "Journal of Learning Disabilities," 39, 74-90] has been proposed as an explanation for the heterogeneity among dyslexic readers in their profiles of reading-related subskills. The predictions of this model were investigated in a…
Descriptors: Reading Difficulties, Spelling, Silent Reading, Reading Fluency
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
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
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