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Direct linkVinay Kumar Yadav; Shakti Prasad – Measurement: Interdisciplinary Research and Perspectives, 2024
In sample survey analysis, accurate population mean estimation is an important task, but traditional approaches frequently ignore the intricacies of real-world data, leading to biassed results. In order to handle uncertainties, indeterminacies, and ambiguity, this work presents an innovative approach based on neutrosophic statistics. We proposed…
Descriptors: Sampling, Statistical Bias, Predictor Variables, Predictive Measurement
Omar Abu-Ghalyoun; Adnan Al-Abed – Teaching Statistics: An International Journal for Teachers, 2024
This study investigates a range of non-normative ideas that pre-service teachers (PSTs) employ in reasoning about sampling variability. This issue was studied in the context of a content course on statistics and probability for pre-service middle grade teachers at a Midwestern American university. Analysis of seven PSTs' video and screen records…
Descriptors: Preservice Teachers, Middle School Teachers, Teacher Characteristics, Knowledge Level
Ting Zhang; Paul Bailey; Yuqi Liao; Emmanuel Sikali – Large-scale Assessments in Education, 2024
The EdSurvey package helps users download, explore variables in, extract data from, and run analyses on large-scale assessment data. The analysis functions in EdSurvey account for the use of plausible values for test scores, survey sampling weights, and their associated variance estimator. We describe the capabilities of the package in the context…
Descriptors: National Competency Tests, Information Retrieval, Data Collection, Test Validity
Download full textAssielou, Kouamé Abel; Haba, Cissé Théodore; Kadjo, Tanon Lambert; Goore, Bi Tra; Yao, Kouakou Daniel – Journal of Education and e-Learning Research, 2021
Intelligent Tutoring Systems (ITS) are computer-based learning environments that aim to imitate to the greatest possible extent the behavior of a human tutor in their capacity as a pedagogical and subject expert. One of the major challenges of these systems is to know how to adapt the training both to changing requirements of all kinds and to…
Descriptors: Psychological Patterns, Predictor Variables, Intelligent Tutoring Systems, Secondary School Students
Kelli A. Bird; Benjamin L. Castleman; Zachary Mabel; Yifeng Song – AERA Open, 2021
Colleges have increasingly turned to predictive analytics to target at-risk students for additional support. Most of the predictive analytic applications in higher education are proprietary, with private companies offering little transparency about their underlying models. We address this lack of transparency by systematically comparing two…
Descriptors: At Risk Students, Identification, Two Year College Students, Community Colleges
Kelli A. Bird; Benjamin L. Castleman; Zachary Mabel; Yifeng Song – Annenberg Institute for School Reform at Brown University, 2021
Colleges have increasingly turned to predictive analytics to target at-risk students for additional support. Most of the predictive analytic applications in higher education are proprietary, with private companies offering little transparency about their underlying models. We address this lack of transparency by systematically comparing two…
Descriptors: At Risk Students, Higher Education, Predictive Measurement, Models
