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Jinnie Shin; Bowen Wang; Wallace N. Pinto Junior; Mark J. Gierl – Large-scale Assessments in Education, 2024
The benefits of incorporating process information in a large-scale assessment with the complex micro-level evidence from the examinees (i.e., process log data) are well documented in the research across large-scale assessments and learning analytics. This study introduces a deep-learning-based approach to predictive modeling of the examinee's…
Descriptors: Prediction, Models, Problem Solving, Performance
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Eva de Schipper; Remco Feskens; Franck Salles; Saskia Keskpaik; Reinaldo dos Santos; Bernard Veldkamp; Paul Drijvers – Large-scale Assessments in Education, 2025
Background: Students take many tests and exams during their school career, but they usually receive feedback about their test performance based only on an analysis of the item responses. With the increase in digital assessment, other data have become available for analysis as well, such as log data of student actions in online assessment…
Descriptors: Problem Solving, Mathematics Instruction, Learning Analytics, Identification
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Salles, Franck; Dos Santos, Reinaldo; Keskpaik, Saskia – Large-scale Assessments in Education, 2020
During this digital era, France, like many other countries, is undergoing a transition from paper-based assessments to digital assessments in education. There is a rising interest in technology-enhanced items which offer innovative ways to assess traditional competencies, as well as addressing problem solving skills, specifically in mathematics.…
Descriptors: Foreign Countries, Didacticism, Mathematics Tests, Learning Analytics
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Murchan, Damian; Siddiq, Fazilat – Large-scale Assessments in Education, 2021
Analysis of user-generated data (for example process data from logfiles, learning analytics, and data mining) in computer-based environments has gained much attention in the last decade and is considered a promising evolving field in learning sciences. In the area of educational assessment, the benefits of such data and how to exploit them are…
Descriptors: Ethics, Federal Regulation, Learning Analytics, Data Use
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Jiang, Yang; Gong, Tao; Saldivia, Luis E.; Cayton-Hodges, Gabrielle; Agard, Christopher – Large-scale Assessments in Education, 2021
In 2017, the mathematics assessments that are part of the National Assessment of Educational Progress (NAEP) program underwent a transformation shifting the administration from paper-and-pencil formats to digitally-based assessments (DBA). This shift introduced new interactive item types that bring rich process data and tremendous opportunities to…
Descriptors: Data Use, Learning Analytics, Test Items, Measurement