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Takashi Kawakami; Akihiko Saeki – Mathematics Education Research Group of Australasia, 2024
This study elaborates on the pivotal roles of mathematical and statistical models in data-driven predictions in an integrated STEM context using the case of Year 4 students: (?) "a descriptive means" to describe the features of trends and variability of data and (?) "an explanatory means" to explain causal relationships behind…
Descriptors: Mathematical Models, Statistical Analysis, Data Use, Prediction
Yu-Jie Wang; Chang-Lei Gao; Xin-Dong Ye – Education and Information Technologies, 2024
The continuous development of Educational Data Mining (EDM) and Learning Analytics (LA) technologies has provided more effective technical support for accurate early warning and interventions for student academic performance. However, the existing body of research on EDM and LA needs more empirical studies that provide feedback interventions, and…
Descriptors: Precision Teaching, Data Use, Intervention, Educational Improvement
Emma Shanahan; Kristen L. McMaster; Britta Cook Bresina; Nicole M. McKevett; Seohyeon Choi; Erica S. Lembke – Journal of Learning Disabilities, 2023
Teacher-level factors are theoretically linked to student outcomes in data-based instruction (DBI; Lembke et al., 2018). Professional development and ongoing support can increase teachers' knowledge, skills, and beliefs related to DBI, as well as their instructional fidelity (McMaster et al., 2020). However, less is known about how each of these…
Descriptors: Prediction, Student Evaluation, Data Use, Writing Instruction
Oslington, Gabrielle Ruth; Mulligan, Joanne; Van Bergen, Penny – Mathematics Education Research Group of Australasia, 2021
This longitudinal study aimed to determine changes in students' predictive reasoning across one year. Forty-four Australian students predicted future temperatures from a table of maximum monthly temperatures, explained their predictive strategies, and represented the data at two time points: Grade 3 and 4. Responses were analysed using a…
Descriptors: Foreign Countries, Thinking Skills, Prediction, Grade 3
van Dijk, Wilhelmina; Pico, Danielle L.; Kaplan, Rachel; Contesse, Valentina; Lane, Holly B. – Computers in the Schools, 2022
The use of online literacy applications is proliferating in elementary classrooms. Using data generated by these applications is assumed to be helpful for teachers to identify struggling readers. Unfortunately, many teachers are unsure how to use and interpret the plethora of data from these apps. In this longitudinal study, we followed a cohort…
Descriptors: Kindergarten, Grade 1, Reading Difficulties, Data Use
Fancsali, Stephen E.; Li, Hao; Sandbothe, Michael; Ritter, Steven – International Educational Data Mining Society, 2021
Recent work describes methods for systematic, data-driven improvement to instructional content and calls for diverse teams of learning engineers to implement and evaluate such improvements. Focusing on an approach called "design-loop adaptivity," we consider the problem of how developers might use data to target or prioritize particular…
Descriptors: Instructional Development, Instructional Improvement, Data Use, Educational Technology
Filderman, Marissa J.; Toste, Jessica R.; Cooc, North – Assessment for Effective Intervention, 2021
Although national legislation and policy call for the use of student assessment data to support instruction, evidence suggests that teachers lack the knowledge and skills required to effectively use data. Previous studies have demonstrated the potential of training for increasing immediate teacher outcomes (i.e., knowledge, skills, and beliefs),…
Descriptors: Grade 2, Elementary School Teachers, Mathematics Instruction, Learning Analytics
Jeffrey Steven Chenier – ProQuest LLC, 2012
Federal and state initiatives (No Child Left Behind, 2001) require schools and districts to set high standards for student growth and achievement. Currently, student growth and progress are measured in Louisiana via statewide achievement tests. In 4th and 8th grades these assessments are considered to be 'high-stakes', as promotion and retention…
Descriptors: Educational Legislation, Federal Legislation, Data Use, Academic Achievement

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