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Dragos-Georgian Corlatescu; Micah Watanabe; Stefan Ruseti; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
Modeling reading comprehension processes is a critical task for Learning Analytics, as accurate models of the reading process can be used to match students to texts, identify appropriate interventions, and predict learning outcomes. This paper introduces an improved version of the Automated Model of Comprehension, namely version 4.0. AMoC has its…
Descriptors: Computer Software, Artificial Intelligence, Learning Analytics, Natural Language Processing
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Devika Venugopalan; Ziwen Yan; Conrad Borchers; Jionghao Lin; Vincent Aleven – Grantee Submission, 2025
Caregivers (i.e., parents and members of a child's caring community) are underappreciated stakeholders in learning analytics. Although caregiver involvement can enhance student academic outcomes, many obstacles hinder involvement, most notably knowledge gaps with respect to modern school curricula. An emerging topic of interest in learning…
Descriptors: Homework, Computational Linguistics, Teaching Methods, Learning Analytics
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Perrotta, Carlo – Research in Education, 2021
This article offers a case study of how platforms and predictive infrastructures are emerging in higher education. It examines a Learning Analytics Application Programming Interface (API) from a popular Learning Management System. The API is treated firstly as an artefact based on the computational abstraction of educational principles, and…
Descriptors: Learning Analytics, Programming, Programming Languages, Computer Interfaces
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Fancsali, Stephen E.; Murphy, April; Ritter, Steve – International Educational Data Mining Society, 2022
Ten years after the announcement of the "rise of the super experiment" at Educational Data Mining 2012, challenges to implementing "internet scale" educational experiments often persist for educational technology providers, especially when they seek to test substantive instructional interventions. Studies that deploy and test…
Descriptors: Learning Analytics, Educational Technology, Barriers, Data Analysis
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Winne, Philip H.; Teng, Kenny; Chang, Daniel; Lin, Michael Pin-Chuan; Marzouk, Zahia; Nesbit, John C.; Patzak, Alexandra; Rakovic, Mladen; Samadi, Donya; Vytasek, Jovita – Journal of Learning Analytics, 2019
Data used in learning analytics rarely provide strong and clear signals about how learners process content. As a result, learning as a process is not clearly described for learners or for learning scientists. GaĊĦevic, Dawson, and Siemens (2015) urged data be sought that more straightforwardly describe processes in terms of events within learning…
Descriptors: Learning Analytics, Learning Processes, Independent Study, Computer Software
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Zhongzhou Chen; Tom Zhang; Michelle Taub – Journal of Learning Analytics, 2024
The current study measures the extent to which students' self-regulated learning tactics and learning outcomes change as the result of a deliberate, data-driven improvement in the learning design of mastery-based online learning modules. In the original design, students were required to attempt the assessment once before being allowed to access…
Descriptors: Learning Analytics, Algorithms, Instructional Materials, Course Content