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Owolabi Paul Adelana; Musa Adekunle Ayanwale; Ismaila Temitayo Sanusi – Cogent Education, 2024
This study addresses the challenge of teaching genetics effectively to high school students, a topic known to be particularly challenging. Leveraging the growing importance of artificial intelligence (AI) in education, the research explores the perspectives, attitudes, and behavioral intentions of pre-service teachers regarding the integration of…
Descriptors: Preservice Teachers, Biology, Science Teachers, Intention
Jaylin Lowe; Charlotte Z. Mann; Jiaying Wang; Adam Sales; Johann A. Gagnon-Bartsch – Grantee Submission, 2024
Recent methods have sought to improve precision in randomized controlled trials (RCTs) by utilizing data from large observational datasets for covariate adjustment. For example, consider an RCT aimed at evaluating a new algebra curriculum, in which a few dozen schools are randomly assigned to treatment (new curriculum) or control (standard…
Descriptors: Randomized Controlled Trials, Middle School Mathematics, Middle School Students, Middle Schools
Katz, Sandra; Albacete, Patricia; Jordan, Pamela – Grantee Submission, 2016
This poster reports on a study that compared three types of summaries at the end of natural-language tutorial dialogues and a no-dialogue control, to determine which type of summary, if any, best predicted learning gains. Although we found no significant differences between conditions, analyses of gender differences indicate that female students…
Descriptors: Natural Language Processing, Intelligent Tutoring Systems, Reflection, Dialogs (Language)
Likens, Aaron D.; McCarthy, Kathryn S.; Allen, Laura K.; McNamara, Danielle D. – Grantee Submission, 2018
Self-explanations are commonly used to assess on-line reading comprehension processes. However, traditional methods of analysis ignore important temporal variations in these explanations. This study investigated how dynamical systems theory could be used to reveal linguistic patterns that are predictive of self-explanation quality. High school…
Descriptors: Reading Comprehension, High School Students, Content Area Reading, Sciences
Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Grantee Submission, 2015
This study builds upon previous work aimed at developing a student model of reading comprehension ability within the intelligent tutoring system, iSTART. Currently, the system evaluates students' self-explanation performance using a local, sentence-level algorithm and does not adapt content based on reading ability. The current study leverages…
Descriptors: Reading Comprehension, Reading Skills, Natural Language Processing, Intelligent Tutoring Systems
Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Grantee Submission, 2014
In the current study, we utilize natural language processing techniques to examine relations between the linguistic properties of students' self-explanations and their reading comprehension skills. Linguistic features of students' aggregated self-explanations were analyzed using the Linguistic Inquiry and Word Count (LIWC) software. Results…
Descriptors: Natural Language Processing, Reading Comprehension, Linguistics, Predictor Variables
Roscoe, Rod D.; Snow, Erica L.; Brandon, Russell D.; McNamara, Danielle S. – Grantee Submission, 2013
The ability of educational games to promote students' engagement in learning and practice depends on perceived enjoyment of those games. This study investigated high school students' perceptions and enjoyment of games within the Writing Pal intelligent tutoring system. In accord with research on motivation, results showed that perceived…
Descriptors: Educational Games, Educational Technology, Technology Uses in Education, Intelligent Tutoring Systems
Barrus, Angela – ProQuest LLC, 2013
This study empirically evaluated the effectiveness of the instructional design, learning tools, and role of the teacher in three versions of a semester-long, high-school remedial Algebra I course to determine what impact self-regulated learning skills and learning pattern training have on students' self-regulation, math achievement, and…
Descriptors: Learning Strategies, Independent Study, High School Students, Instructional Design
Baker, Ryan S. J. D.; Goldstein, Adam B.; Heffernan, Neil T. – International Journal of Artificial Intelligence in Education, 2011
Intelligent tutors have become increasingly accurate at detecting whether a student knows a skill, or knowledge component (KC), at a given time. However, current student models do not tell us exactly at which point a KC is learned. In this paper, we present a machine-learned model that assesses the probability that a student learned a KC at a…
Descriptors: Intelligent Tutoring Systems, Mastery Learning, Probability, Knowledge Level
Petersen, Kenneth A. – ProQuest LLC, 2010
Interaction research on recasts has been largely confined to examining the effects of recasts delivered in an oral, face-to-face modality. The challenge of creating task conditions in a written interactive mode, in which the dynamism and immediacy of recasts can be brought to bear on L2 development, has been a formidable obstacle to advancing the…
Descriptors: Feedback (Response), Interaction, Second Language Learning, Oral Language
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

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