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Jessica Herring Watson; Ayanna Perkins; Amanda J. Rockinson-Szapkiw – TechTrends: Linking Research and Practice to Improve Learning, 2024
This predictive correlational study investigated to what extent, if at all, the constructs of the Unified Theory of Acceptance and Use of Technology (UTAUT) predicted special educators' use of assistive technology (AT) in virtual and hybrid settings during the COVID-19 pandemic. A survey was distributed to educators (n = 104) across the United…
Descriptors: Special Education Teachers, Technology Uses in Education, Electronic Learning, Blended Learning
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Riofrio-Luzcando, Diego; Ramirez, Jaime; Berrocal-Lobo, Marta – IEEE Transactions on Learning Technologies, 2017
Data mining is known to have a potential for predicting user performance. However, there are few studies that explore its potential for predicting student behavior in a procedural training environment. This paper presents a collective student model, which is built from past student logs. These logs are first grouped into clusters. Then, an…
Descriptors: Student Behavior, Predictive Validity, Predictor Variables, Predictive Measurement
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Northrop, Laura; Kelly, Sean – Urban Education, 2018
This study investigates whether adequate yearly progress (AYP) status, locale, and sector--common variables used to judge the quality of schools--accurately signal true differences in instructional practices in high school mathematics and science. Using data from the High School Longitudinal Study (HSLS), we find the school-to-school variation in…
Descriptors: Instructional Effectiveness, Intermode Differences, Federal Programs, Educational Indicators