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Kim, Yunsung; Sreechan; Piech, Chris; Thille, Candace – International Educational Data Mining Society, 2023
Dynamic Item Response Models extend the standard Item Response Theory (IRT) to capture temporal dynamics in learner ability. While these models have the potential to allow instructional systems to actively monitor the evolution of learner proficiency in real time, existing dynamic item response models rely on expensive inference algorithms that…
Descriptors: Item Response Theory, Accuracy, Inferences, Algorithms
Shou, Tianze; Borchers, Conrad; Karumbaiah, Shamya; Aleven, Vincent – International Educational Data Mining Society, 2023
Spatial analytics receive increased attention in educational data mining. A critical issue in stop detection (i.e., the automatic extraction of timestamped and located stops in the movement of individuals) is a lack of validation of stop accuracy to represent phenomena of interest. Next to a radius that an actor does not exceed for a certain…
Descriptors: Classroom Design, Accuracy, Validity, Space Utilization
Weidlich, Joshua; Gaševic, Dragan; Drachsler, Hendrik – Journal of Learning Analytics, 2022
As a research field geared toward understanding and improving learning, Learning Analytics (LA) must be able to provide empirical support for causal claims. However, as a highly applied field, tightly controlled randomized experiments are not always feasible nor desirable. Instead, researchers often rely on observational data, based on which they…
Descriptors: Causal Models, Inferences, Learning Analytics, Comparative Analysis
Maddox, Bryan – OECD Publishing, 2023
The digital transition in educational testing has introduced many new opportunities for technology to enhance large-scale assessments. These include the potential to collect and use log data on test-taker response processes routinely, and on a large scale. Process data has long been recognised as a valuable source of validation evidence in…
Descriptors: Measurement, Inferences, Test Reliability, Computer Assisted Testing
PaaBen, Benjamin; Dywel, Malwina; Fleckenstein, Melanie; Pinkwart, Niels – International Educational Data Mining Society, 2022
Item response theory (IRT) is a popular method to infer student abilities and item difficulties from observed test responses. However, IRT struggles with two challenges: How to map items to skills if multiple skills are present? And how to infer the ability of new students that have not been part of the training data? Inspired by recent advances…
Descriptors: Item Response Theory, Test Items, Item Analysis, Inferences
Sibel Sögüt – GIST Education and Learning Research Journal, 2023
This study examines second language (L2) learners' perspectives regarding the affordances and challenges of using the Data-Driven Learning (DDL) to identify the properties of near-synonymous words. Employing a convergent mixed-method design, this study deciphers the perceptions of 40 undergraduate L2 learners majoring in English language teaching.…
Descriptors: Second Language Learning, Second Language Instruction, English (Second Language), Phrase Structure
Grimaldi, Phillip; Weatherholtz, Kodi; Hill, Kelli Millwood – International Educational Data Mining Society, 2022
As educational technology platforms become more and more commonplace in education, it is critical that these systems work well across a diverse range of student sub-groups. In this study, we estimated the effectiveness of MAP Accelerator; a large-scale, personalized, web-based, mathematics mastery learning platform. Our analysis placed a…
Descriptors: Educational Technology, Mastery Learning, Learning Management Systems, Middle School Students

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