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Showing 1 to 15 of 51 results Save | Export
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Rashelle J. Musci; Joseph Kush; Elise T. Pas; Catherine P. Bradshaw – Grantee Submission, 2024
Given the increased focus of educational research on what works for whom and under what circumstances over the last decade, educational researchers are increasingly turning toward mixture models to identify heterogeneous subgroups among students. Such data are inherently nested, as students are nested within classrooms and schools. Yet there has…
Descriptors: Hierarchical Linear Modeling, Data Analysis, Nonparametric Statistics, Educational Research
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Junming Guo; Chuanbin Liu; Han Zhang; Dan Wang; Jintao Lu – Evaluation Review, 2025
Performance management in university-based scientific research institutions is essential for driving reform, advancing education quality, and fostering innovation. However, current performance evaluation models often focus solely on research indicators, neglecting the critical interdependence between the education and research systems. This…
Descriptors: Performance Based Assessment, Institutional Evaluation, Research Universities, Scientific Research
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Parian Haghighat; Denisa Gandara; Lulu Kang; Hadis Anahideh – Grantee Submission, 2024
Predictive analytics is widely used in various domains, including education, to inform decision-making and improve outcomes. However, many predictive models are proprietary and inaccessible for evaluation or modification by researchers and practitioners, limiting their accountability and ethical design. Moreover, predictive models are often opaque…
Descriptors: Prediction, Learning Analytics, Multivariate Analysis, Regression (Statistics)
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Olsson, Ulf – Practical Assessment, Research & Evaluation, 2022
We discuss analysis of 5-grade Likert type data in the two-sample case. Analysis using two-sample "t" tests, nonparametric Wilcoxon tests, and ordinal regression methods, are compared using simulated data based on an ordinal regression paradigm. One thousand pairs of samples of size "n"=10 and "n"=30 were generated,…
Descriptors: Regression (Statistics), Likert Scales, Sampling, Nonparametric Statistics
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Ting Ye; Ted Westling; Lindsay Page; Luke Keele – Grantee Submission, 2024
The clustered observational study (COS) design is the observational study counterpart to the clustered randomized trial. In a COS, a treatment is assigned to intact groups, and all units within the group are exposed to the treatment. However, the treatment is non-randomly assigned. COSs are common in both education and health services research. In…
Descriptors: Nonparametric Statistics, Identification, Causal Models, Multivariate Analysis
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Reimers, Jennifer; Turner, Ronna C.; Tendeiro, Jorge N.; Lo, Wen-Juo; Keiffer, Elizabeth – Measurement: Interdisciplinary Research and Perspectives, 2023
Person-fit analyses are commonly used to detect aberrant responding in self-report data. Nonparametric person fit statistics do not require fitting a parametric test theory model and have performed well compared to other person-fit statistics. However, detection of aberrant responding has primarily focused on dominance response data, thus the…
Descriptors: Goodness of Fit, Nonparametric Statistics, Error of Measurement, Comparative Analysis
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Silva-Lugo, Jose L.; Warner, Laura A.; Galindo, Sebastian – Journal of Agricultural Education and Extension, 2022
Purpose: A literature research conducted in education and agricultural education journals published during a period of 10 years revealed that 98% of the studies used parametric analyses. In general, model assumptions were not tested, and statistical criteria were not followed to apply the parametric approach. The objective of this paper is to…
Descriptors: Agricultural Education, Nonparametric Statistics, Educational Research, Models
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Shero, Jeffrey A.; Al Otaiba, Stephanie; Schatschneider, Chris; Hart, Sara A. – Journal of Experimental Education, 2022
Many of the analytical models commonly used in educational research often aim to maximize explained variance and identify variable importance within models. These models are useful for understanding general ideas and trends, but give limited insight into the individuals within said models. Data envelopment analysis (DEA), is a method rooted in…
Descriptors: Data Analysis, Educational Research, Nonparametric Statistics, Efficiency
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Qian, Minghui; Hu, Ridong; Chen, Jianwei – EURASIA Journal of Mathematics, Science & Technology Education, 2016
Spatial panel data models have been widely studied and applied in both scientific and social science disciplines, especially in the analysis of spatial influence. In this paper, we consider the spatial dynamic nonparametric Durbin model (SDNDM) with fixed effects, which takes the nonlinear factors into account base on the spatial dynamic panel…
Descriptors: Nonparametric Statistics, Models, Hypothesis Testing, Statistical Analysis
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Wind, Stefanie A. – Educational and Psychological Measurement, 2017
Molenaar extended Mokken's original probabilistic-nonparametric scaling models for use with polytomous data. These polytomous extensions of Mokken's original scaling procedure have facilitated the use of Mokken scale analysis as an approach to exploring fundamental measurement properties across a variety of domains in which polytomous ratings are…
Descriptors: Nonparametric Statistics, Scaling, Models, Item Response Theory
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Pearl, Judea – Sociological Methods & Research, 2017
We address the task of determining, from statistical averages alone, whether a population under study consists of several subpopulations, unknown to the investigator, each responding to a given treatment markedly differently. We show that such determination is feasible in three cases: (1) randomized trials with binary treatments, (2) models where…
Descriptors: Statistical Analysis, Models, Social Science Research, Randomized Controlled Trials
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Cheng, Xue Jun; McCarthy, Callum J.; Wang, Tony S. L.; Palmeri, Thomas J.; Little, Daniel R. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2018
Upright faces are thought to be processed more holistically than inverted faces. In the widely used composite face paradigm, holistic processing is inferred from interference in recognition performance from a to-be-ignored face half for upright and aligned faces compared with inverted or misaligned faces. We sought to characterize the nature of…
Descriptors: Holistic Approach, Models, Comparative Analysis, Correlation
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Costa, Carolina; Alvelos, Helena; Teixeira, Leonor – International Journal of Information and Communication Technology Education, 2018
The Educast is an educational videos' platform that captures simultaneously video and digital support materials. This paper presents a study on the acceptance of Educast, by students, using the Technology Acceptance Model--TAM. The data was collected through a questionnaire applied to 54 students which results were analyzed using descriptive…
Descriptors: Video Technology, Positive Attitudes, Student Attitudes, Foreign Countries
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Anders, Jake – Oxford Review of Education, 2017
A much larger proportion of English 14-year-olds expect to apply to university than ultimately make an application by age 21, but the proportion expecting to apply falls from age 14 onwards. In order to assess the role of socioeconomic status in explaining changes in expectations, this paper applies duration modelling techniques to the…
Descriptors: Socioeconomic Status, Expectation, Academic Aspiration, College Applicants
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Mao, Ye; Lin, Chen; Chi, Min – Journal of Educational Data Mining, 2018
Bayesian Knowledge Tracing (BKT) is a commonly used approach for student modeling, and Long Short Term Memory (LSTM) is a versatile model that can be applied to a wide range of tasks, such as language translation. In this work, we directly compared three models: BKT, its variant Intervention-BKT (IBKT), and LSTM, on two types of student modeling…
Descriptors: Prediction, Pretests Posttests, Bayesian Statistics, Short Term Memory
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