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Winne, Philip H. – International Journal of Artificial Intelligence in Education, 2021
Learner modeling systems so far formulated model learning in three main ways: a learner's "position" within a lattice of declarative and procedural knowledge about highly structured disciplines such as geometry or physics, a learner's path through curricular tasks compared to milestones, or profiles of a learner's achievements on a set…
Descriptors: Models, Student Characteristics, Access to Information, Learning Processes
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McEneaney, John; Morsink, Paul – Journal of Learning Analytics, 2022
Learning analytics (LA) provides tools to analyze historical data with the goal of better understanding how curricular structures and features have impacted student learning. Forward-looking curriculum design, however, frequently involves a degree of uncertainty. Historical data may be unavailable, a contemplated modification to curriculum may be…
Descriptors: Curriculum Design, Learning Analytics, Educational Change, Computer Software
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Bull, Susan – International Journal of Artificial Intelligence in Education, 2021
For the special issue of the International Journal of Artificial Intelligence in Education dedicated to the memory of Jim Greer, this paper highlights some of Jim's extensive and always-timely contributions to the field: from his early AI-focussed research on intelligent tutoring systems, through a variety of applications deployed to support…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Educational Research, College Students
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Hillman, Velislava – Learning, Media and Technology, 2023
The need for a comprehensive education data governance -- the regulation of who collects what data, how it is used and why -- continues to grow. Technologically, data can be collected by third parties, rendering schools unable to control their use. Legal frameworks partially achieve data governance as businesses continue to exploit existing…
Descriptors: Data Collection, Governance, Data Use, Laws
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Lajoie, Susanne P. – International Journal of Artificial Intelligence in Education, 2021
I first met Jim Greer at the NATO Advanced Study Institute on Syntheses of Instructional Sciences and Computing Science for Effective Instructional Computing Systems in 1990 in Calgary, Canada. It was during this meeting that I came to realize that Jim was one of those rare individuals that could help "translate" computer science…
Descriptors: Models, Student Characteristics, Artificial Intelligence, Computer Uses in Education
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Khosravi, Hassan; Shabaninejad, Shiva; Bakharia, Aneesha; Sadiq, Shazia; Indulska, Marta; Gasevic, Dragan – Journal of Learning Analytics, 2021
Learning analytics dashboards commonly visualize data about students with the aim of helping students and educators understand and make informed decisions about the learning process. To assist with making sense of complex and multidimensional data, many learning analytics systems and dashboards have relied strongly on AI algorithms based on…
Descriptors: Learning Analytics, Visual Aids, Artificial Intelligence, Information Retrieval
Gonzalez, Naihobe; Alberty, Elizabeth; Brockman, Stacey; Nguyen, Tutrang; Johnson, Matthew; Bond, Sheldon; O'Connell, Krista; Corriveau, Adrianna; Shoji, Megan; Streeter, Megan; Engle, Jennifer; Goodly, Chelsea; Neely, Adrian N.; White, Mary Aleta; Anderson, Mindelyn; Matthews, Channing; Mason, Leana; Means, Sheryl Felecia – Mathematica, 2022
The Education-to-Workforce Indicator Framework (E-W Framework), commissioned by the Bill & Melinda Gates Foundation and developed in partnership with leading experts representing more than 15 national and community organizations, is designed to encourage greater cross-sector collaboration and alignment across local, state, and national data…
Descriptors: Education Work Relationship, Evidence Based Practice, Student Characteristics, Partnerships in Education
Lafortune, Julien – Public Policy Institute of California, 2021
This document contains the technical appendices for the report "Targeted K-12 Funding and Student Outcomes: Evaluating the Local Control Funding Formula." Appendices include: (1) Data Sources and Sample Construction; (2) Estimating Effects on Student Outcomes; (3) Estimating Targeting Using School Site Spending Data; and (4) Supplemental…
Descriptors: Funding Formulas, Kindergarten, Elementary Secondary Education, Outcomes of Education