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Wu, Tong; Kim, Stella Y.; Westine, Carl – Educational and Psychological Measurement, 2023
For large-scale assessments, data are often collected with missing responses. Despite the wide use of item response theory (IRT) in many testing programs, however, the existing literature offers little insight into the effectiveness of various approaches to handling missing responses in the context of scale linking. Scale linking is commonly used…
Descriptors: Data Analysis, Responses, Statistical Analysis, Measurement
Tanner, Sean; Terrell, Jenna; Vislosky, Emily; Gellar, Jonathan; Gill, Brian – Regional Educational Laboratory Mid-Atlantic, 2021
Predicting incoming enrollment is an ongoing concern for the School District of Philadelphia (SDP) and similar districts with school choice systems, substantial student mobility, or both. Inaccurate predictions can disrupt learning as districts adjust to enrollment fluctuations by reshuffling teachers and students well into the fall semester. This…
Descriptors: Enrollment, Enrollment Projections, School Districts, Statistical Analysis
Regional Educational Laboratory Mid-Atlantic, 2021
Predicting incoming enrollment is an ongoing concern for the School District of Philadelphia (SDP) and similar districts with school choice systems, substantial student mobility, or both. Inaccurate predictions can disrupt learning as districts adjust to enrollment fluctuations by reshuffling teachers and students well into the fall semester. This…
Descriptors: Enrollment, Enrollment Projections, School Districts, Statistical Analysis
Regional Educational Laboratory Mid-Atlantic, 2021
Predicting incoming enrollment is an ongoing concern for the School District of Philadelphia (SDP) and similar districts with school choice systems, substantial student mobility, or both. Inaccurate predictions can disrupt learning as districts adjust to enrollment fluctuations by reshuffling teachers and students well into the fall semester. The…
Descriptors: Enrollment, Enrollment Projections, School Districts, Statistical Analysis
Chaney, Bradford – American Journal of Evaluation, 2016
The primary technique that many researchers use to analyze data from randomized control trials (RCTs)--detecting the average treatment effect (ATE)--imposes assumptions upon the data that often are not correct. Both theory and past research suggest that treatments may have significant impacts on subgroups even when showing no overall effect.…
Descriptors: Randomized Controlled Trials, Data Analysis, Outcomes of Treatment, Simulation
Lei, Pui-Wa; Li, Hongli – Applied Psychological Measurement, 2013
Minimum sample sizes of about 200 to 250 per group are often recommended for differential item functioning (DIF) analyses. However, there are times when sample sizes for one or both groups of interest are smaller than 200 due to practical constraints. This study attempts to examine the performance of Simultaneous Item Bias Test (SIBTEST),…
Descriptors: Sample Size, Test Bias, Computation, Accuracy
Sweeney, Mack; Rangwala, Huzefa; Lester, Jaime; Johri, Aditya – Journal of Educational Data Mining, 2016
An enduring issue in higher education is student retention to successful graduation. National statistics indicate that most higher education institutions have four-year degree completion rates around 50%, or just half of their student populations. While there are prediction models which illuminate what factors assist with college student success,…
Descriptors: Systems Approach, Data Analysis, Prediction, Academic Achievement
Rankin, Jenny Grant – Online Submission, 2014
The benefits of making data-informed decisions to improve learning rely on educators correctly interpreting given data. Many educators routinely misinterpret data, even at districts with proactive support for data use. The tool most educators use for data analyses, which is an information technology data system or its reports, typically reports…
Descriptors: Data Analysis, Information Systems, Information Utilization, Guides
Géryk, Jan – International Educational Data Mining Society, 2015
The efficacy of animated data visualizations in comparison with static data visualizations is still inconclusive. Some researches resulted that the failure to find out the benefits of animations may relate to the way how they are constructed and perceived. In this paper, we present visual analytics (VA) tool which makes use of enhanced animated…
Descriptors: Animation, Visualization, Visual Stimuli, Program Effectiveness
Nye, Benjamin D.; Morrison, Donald M.; Samei, Borhan – International Educational Data Mining Society, 2015
Archived transcripts from tens of millions of online human tutoring sessions potentially contain important knowledge about how online tutors help, or fail to help, students learn. However, without ways of automatically analyzing these large corpora, any knowledge in this data will remain buried. One way to approach this issue is to train an…
Descriptors: Tutoring, Instructional Effectiveness, Tutors, Models
Svetina, Dubravka – Educational and Psychological Measurement, 2013
The purpose of this study was to investigate the effect of complex structure on dimensionality assessment in noncompensatory multidimensional item response models using dimensionality assessment procedures based on DETECT (dimensionality evaluation to enumerate contributing traits) and NOHARM (normal ogive harmonic analysis robust method). Five…
Descriptors: Item Response Theory, Statistical Analysis, Computation, Test Length
Casey, Stephanie A. – Journal of Statistics Education, 2015
The purpose of this research study was to learn about students' conceptions concerning the line of best fit just prior to their introduction to the topic. Task-based interviews were conducted with thirty-three students, focused on five tasks that asked them to place the line of best fit on a scatterplot and explain their reasoning throughout the…
Descriptors: Goodness of Fit, Statistical Analysis, Student Attitudes, Task Analysis
Rankin, Jenny Grant – ProQuest LLC, 2013
There is extensive research on the benefits of making data-informed decisions, but research also contains evidence many educators incorrectly interpret student data. Meanwhile, the types of detailed labeling on over-the-counter medication have been shown to improve use of "non"-medication products, as well. However, data systems most…
Descriptors: Data, Data Analysis, Accuracy, Decision Making
Crossley, Scott; McNamara, Danielle S.; Baker, Ryan; Wang, Yuan; Paquette, Luc; Barnes, Tiffany; Bergner, Yoav – International Educational Data Mining Society, 2015
Completion rates for massive open online classes (MOOCs) are notoriously low, but learner intent is an important factor. By studying students who drop out despite their intent to complete the MOOC, it may be possible to develop interventions to improve retention and learning outcomes. Previous research into predicting MOOC completion has focused…
Descriptors: Online Courses, Large Group Instruction, Information Retrieval, Data Analysis
Crossley, Scott A.; Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Journal of Educational Data Mining, 2016
This study investigates a novel approach to automatically assessing essay quality that combines natural language processing approaches that assess text features with approaches that assess individual differences in writers such as demographic information, standardized test scores, and survey results. The results demonstrate that combining text…
Descriptors: Essays, Scoring, Writing Evaluation, Natural Language Processing
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