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Identifying the Content, Lesson Structure, and Data Use within Pre-Collegiate Data Science Curricula
Lee, Victor R.; Delaney, Victoria – Journal of Science Education and Technology, 2022
As data become more available and integrated into daily life, there has been growing interest in developing data science curricula for youth in conjunction with scientific practices and classroom technologies. However, the "what" and "how" of data science in pre-collegiate education have not yet reached consensus. This paper…
Descriptors: Data, Data Analysis, Curriculum Development, Educational Practices
Xhomara, Nazmi – International Journal of Learning and Change, 2022
The study aimed to investigate the impact of student-centred teaching approach, personalised learning, and previous education achievements on critical thinking skills. The quantitative correlational approach, the structured questionnaire, and the cluster random sample (N = 214) were selected to be used in the study. It is found that there is a…
Descriptors: Critical Thinking, Student Centered Learning, Individualized Instruction, Academic Achievement
Falk, Carl F.; Feuerstahler, Leah M. – Educational and Psychological Measurement, 2022
Large-scale assessments often use a computer adaptive test (CAT) for selection of items and for scoring respondents. Such tests often assume a parametric form for the relationship between item responses and the underlying construct. Although semi- and nonparametric response functions could be used, there is scant research on their performance in a…
Descriptors: Item Response Theory, Adaptive Testing, Computer Assisted Testing, Nonparametric Statistics
Joo, Seang-Hwane; Lee, Philseok – Journal of Educational Measurement, 2022
Abstract This study proposes a new Bayesian differential item functioning (DIF) detection method using posterior predictive model checking (PPMC). Item fit measures including infit, outfit, observed score distribution (OSD), and Q1 were considered as discrepancy statistics for the PPMC DIF methods. The performance of the PPMC DIF method was…
Descriptors: Test Items, Bayesian Statistics, Monte Carlo Methods, Prediction
Sourwine, Jasmine – Mathematics Teacher: Learning and Teaching PK-12, 2022
The reality is that textbooks and state standards have more content than can reasonably be covered for proficiency in most classrooms. In years past, this typically meant cutting the last unit or two or moving along regardless of who was keeping up, in many cases resulting in cutting statistics from the curriculum. This article provides five…
Descriptors: Statistics, Algebra, Social Justice, Secondary School Mathematics
Hedges, Sarai; Harkness, Shelly Sheats; Given, Kim – Middle Grades Research Journal, 2022
In this article we report on middle school students' understanding of concepts related to the second step of the statistical problem-solving process, study design: create a plan and collect data. Students participated in an open-ended statistics lesson involving nonexperimental study design. For this research we analyzed the students' discourse…
Descriptors: Middle School Students, Concept Formation, Research Design, Data Collection
Wang, Weimeng; Liu, Yang; Liu, Hongyun – Journal of Educational and Behavioral Statistics, 2022
Differential item functioning (DIF) occurs when the probability of endorsing an item differs across groups for individuals with the same latent trait level. The presence of DIF items may jeopardize the validity of an instrument; therefore, it is crucial to identify DIF items in routine operations of educational assessment. While DIF detection…
Descriptors: Test Bias, Test Items, Equated Scores, Regression (Statistics)
Schildroth, Samantha; Friedman, Alexa; Bauer, Julia Anglen; Claus Henn, Birgit – New Directions for Child and Adolescent Development, 2022
Iron is needed for normal development in adolescence. Exposure to individual environmental metals (e.g., lead) has been associated with altered iron status in adolescence, but little is known about the cumulative associations of multiple metals with Fe status. We used data from the 2017-2018 National Health and Nutrition Examination Survey…
Descriptors: Nutrition, National Surveys, Adolescent Development, Hazardous Materials
Myers, Nicholas D.; Lee, Seungmin; Chun, Haeyong; Silverman, Stephen – Measurement in Physical Education and Exercise Science, 2022
Purpose: The purpose of this manuscript is to provide a summary of Measurement in Physical Education and Exercise Science (MPEES)-related activities in 2021. Manuscripts submitted: In 2021 original submissions (i.e., not counting revised manuscripts) increased by [approximately]20% as compared to 2020. Fifty-eight countries were represented across…
Descriptors: Physical Education, Exercise, Measurement, Research
Trunkenwald, Jannick; Moungabio, Fernand Malonga; Laval, Dominique – Canadian Journal of Science, Mathematics and Technology Education, 2022
This article deals with an introduction of probability at school through sensory modalities. This approach is based on sampling fluctuation with empirical observations of frequencies. Initially, we analyze how students from high school work on such a task by using dice, pencil, and paper. We then identify the use of schemas and data visualization…
Descriptors: Probability, Mathematics Education, High School Students, Mathematics Activities
Luke W. Miratrix – Grantee Submission, 2022
We are sometimes forced to use the Interrupted Time Series (ITS) design as an identification strategy for potential policy change, such as when we only have a single treated unit and cannot obtain comparable controls. For example, with recent county- and state-wide criminal justice reform efforts, where judicial bodies have changed bail setting…
Descriptors: Causal Models, Case Studies, Quasiexperimental Design, Monte Carlo Methods
Adam J. Reeger – ProQuest LLC, 2022
Student growth percentiles (SGPs) have become a common means to measure and report on student academic growth for state education accountability, and some states have adopted SGP cutscores as a means of classifying student growth into categories like "high/medium/low" growth. It has therefore become important to understand properties of…
Descriptors: Academic Achievement, Achievement Gains, Accountability, Regression (Statistics)
Haiyan Liu; Wen Qu; Zhiyong Zhang; Hao Wu – Grantee Submission, 2022
Bayesian inference for structural equation models (SEMs) is increasingly popular in social and psychological sciences owing to its flexibility to adapt to more complex models and the ability to include prior information if available. However, there are two major hurdles in using the traditional Bayesian SEM in practice: (1) the information nested…
Descriptors: Bayesian Statistics, Structural Equation Models, Statistical Inference, Statistical Distributions
Ranger, Jochen; Kuhn, Jörg-Tobias – Journal of Educational and Behavioral Statistics, 2018
Diffusion-based item response theory models for responses and response times in tests have attracted increased attention recently in psychometrics. Analyzing response time data, however, is delicate as response times are often contaminated by unusual observations. This can have serious effects on the validity of statistical inference. In this…
Descriptors: Item Response Theory, Computation, Robustness (Statistics), Reaction Time
Silvia Heubach; Tuyetdong Phan-Yamada – Journal of Statistics and Data Science Education, 2025
We describe a hands-on project in which students collect data on the impact of distracted driving on driver reaction time. Initially they do this in class via a virtual driving applet, using themselves and fellow students as test subjects. Different applet versions simulate driving with and without distraction and measure the time it takes to…
Descriptors: Statistics, Relevance (Education), Student Projects, Experiential Learning

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