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Robert Shand; Stephen M. Leach; Fiona M. Hollands; Florence Chang; Yilin Pan; Bo Yan; Dena Dossett; Samreen Nayyer-Qureshi; Yixin Wang; Laura Head – Grantee Submission, 2022
We assessed whether an adaptation of value-added analysis (VAA) can provide evidence on the relative effectiveness of interventions implemented in a large school district. We analyzed two datasets, one documenting interventions received by underperforming students, and one documenting interventions received by students in schools benefiting from…
Descriptors: Value Added Models, Data Analysis, Program Evaluation, Program Effectiveness
Olga Maria Belikov – ProQuest LLC, 2022
This article-format dissertation focuses on how scholars use social media to support their scholarship. The first article is a scoping literature review that outlines current research. While overviewing an emergent field of literature, the article highlights motivations for using social media use, discusses benefits and drawbacks of this use for…
Descriptors: Social Media, Technology Integration, Scholarship, Professional Identity
Robert Shand; Stephen M. Leach; Fiona M. Hollands; Florence Chang; Yilin Pan; Bo Yan; Dena Dossett; Samreen Nayyer-Qureshi; Yixin Wang; Laura Head – American Journal of Evaluation, 2022
We assessed whether an adaptation of value-added analysis (VAA) can provide evidence on the relative effectiveness of interventions implemented in a large school district. We analyzed two datasets, one documenting interventions received by underperforming students, and one documenting interventions received by students in schools benefiting from…
Descriptors: Value Added Models, Data Analysis, Program Evaluation, Program Effectiveness
Brendan Bartanen; Aliza N. Husain – Annenberg Institute for School Reform at Brown University, 2022
A growing literature uses value-added (VA) models to quantify principals' contributions to improving student outcomes. Principal VA is typically estimated using a connected networks model that includes both principal and school fixed effects (FE) to isolate principal effectiveness from fixed school factors that principals cannot control. While…
Descriptors: Principals, Administrator Role, Student Improvement, Outcomes of Education
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von Hippel, Paul T. – Sociological Methods & Research, 2020
When using multiple imputation, users often want to know how many imputations they need. An old answer is that 2-10 imputations usually suffice, but this recommendation only addresses the efficiency of point estimates. You may need more imputations if, in addition to efficient point estimates, you also want standard error (SE) estimates that would…
Descriptors: Computation, Error of Measurement, Data Analysis, Children
Sullivan, Amanda L.; Weeks, Mollie R.; Kulkarni, Tara; Nguyen, Thuy – Communique, 2020
Large-scale analyses are a powerful and increasingly common tool for investigating a range of public health and social concerns (Pienta, O'Rourke, & Franks, 2011). This series will provide a primer on large-scale secondary analysis in school psychology, with this article focusing on considerations for researchers interested in applying and…
Descriptors: Data Analysis, School Psychology, Research Problems, Research Utilization
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Yucesoy-Ozkan, Serife; Rakap, Salih; Gulboy, Emrah – British Journal of Special Education, 2020
The purpose of this study was to compare 12 commonly-used nonoverlap methods with each other and with the results of visual analysis. Data were obtained from 25 studies focused on embedded instruction and schema-based instruction and included a total of 101 graphs. Treatment effect estimates using 12 nonoverlap methods were calculated for each…
Descriptors: Effect Size, Graphs, Data Analysis, Computation
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Mavridis, Dimitris; White, Ian R. – Research Synthesis Methods, 2020
Missing data result in less precise and possibly biased effect estimates in single studies. Bias arising from studies with incomplete outcome data is naturally propagated in a meta-analysis. Conventional analysis using only individuals with available data is adequate when the meta-analyst can be confident that the data are missing at random (MAR)…
Descriptors: Meta Analysis, Data Analysis, Statistical Bias, Outcome Measures
Education Trust-West, 2023
As California invests in early learning and care, the state is also moving forward with a long-overdue plan to build a statewide longitudinal data system (SLDS) -- known as the Cradle-to-Career (C2C) Data System -- which will eventually connect data over time and across sectors like education, health, human services, and the workforce. This is a…
Descriptors: Early Childhood Education, Child Care, Young Children, Access to Education
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Langerbein, Janine; Massing, Till; Klenke, Jens; Striewe, Michael; Goedicke, Michael; Hanck, Christoph – International Educational Data Mining Society, 2023
Due to the precautionary measures during the COVID-19 pandemic many universities offered unproctored take-home exams. We propose methods to detect potential collusion between students and apply our approach on event log data from take-home exams during the pandemic. We find groups of students with suspiciously similar exams. In addition, we…
Descriptors: Information Retrieval, Pattern Recognition, Data Analysis, Information Technology
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Byram, Jessica N.; Lazarus, Michelle D.; Wilson, Adam B.; Brown, Kirsten M. – Anatomical Sciences Education, 2023
Altmetrics are non-traditional metrics that can capture downloads, social media shares, and other modern measures of research impact and reach. Despite most of the altmetrics literature focusing on evaluating the relationship between research outputs and academic impact/influence, the perceived and actual value of altmetrics among academicians…
Descriptors: Anatomy, Science Instruction, Medical Education, Content Analysis
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Gruss, Richard; Clemons, Josh – Journal of Computer Assisted Learning, 2023
Background: The sudden growth in online instruction due to COVID-19 restrictions has given renewed urgency to questions about remote learning that have remained unresolved. Web-based assessment software provides instructors an array of options for varying testing parameters, but the pedagogical impacts of some of these variations has yet to be…
Descriptors: Test Items, Test Format, Computer Assisted Testing, Mathematics Tests
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Phillips, Tanner M.; Saleh, Asmalina; Ozogul, Gamze – International Journal of Artificial Intelligence in Education, 2023
Encouraging teachers to reflect on their instructional practices and course design has been shown to be an effective means of improving instruction and student learning. However, the process of encouraging reflection is difficult; reflection requires quality data, thoughtful analysis, and contextualized interpretation. Because of this, research on…
Descriptors: Reflection, Artificial Intelligence, Natural Language Processing, Data Collection
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Kaplan, David; Chen, Jianshen; Lyu, Weicong; Yavuz, Sinan – Large-scale Assessments in Education, 2023
The purpose of this paper is to extend and evaluate methods of "Bayesian historical borrowing" applied to longitudinal data with a focus on parameter recovery and predictive performance. Bayesian historical borrowing allows researchers to utilize information from previous data sources and to adjust the extent of borrowing based on the…
Descriptors: Bayesian Statistics, Longitudinal Studies, Children, Surveys
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Caspari-Sadeghi, Sima – Journal of Educational Technology Systems, 2023
Intelligent assessment, the core of any AI-based educational technology, is defined as embedded, stealth and ubiquitous assessment which uses intelligent techniques to diagnose the current cognitive level, monitor dynamic progress, predict success and update students' profiling continuously. It also uses various technologies, such as learning…
Descriptors: Artificial Intelligence, Educational Technology, Computer Assisted Testing, Barriers
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