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Wilcox, Rand R.; Serang, Sarfaraz – Educational and Psychological Measurement, 2017
The article provides perspectives on p values, null hypothesis testing, and alternative techniques in light of modern robust statistical methods. Null hypothesis testing and "p" values can provide useful information provided they are interpreted in a sound manner, which includes taking into account insights and advances that have…
Descriptors: Hypothesis Testing, Bayesian Statistics, Computation, Effect Size
McNeish, Daniel – Educational and Psychological Measurement, 2017
In behavioral sciences broadly, estimating growth models with Bayesian methods is becoming increasingly common, especially to combat small samples common with longitudinal data. Although Mplus is becoming an increasingly common program for applied research employing Bayesian methods, the limited selection of prior distributions for the elements of…
Descriptors: Models, Bayesian Statistics, Statistical Analysis, Computer Software
Trafimow, David – Educational and Psychological Measurement, 2017
There has been much controversy over the null hypothesis significance testing procedure, with much of the criticism centered on the problem of inverse inference. Specifically, p gives the probability of the finding (or one more extreme) given the null hypothesis, whereas the null hypothesis significance testing procedure involves drawing a…
Descriptors: Statistical Inference, Hypothesis Testing, Probability, Intervals
Mahmud, Jumailiyah – Educational Research and Reviews, 2017
With the development in computing technology, item response theory (IRT) develops rapidly, and has become a user friendly application in psychometrics world. Limitation in classical theory is one aspect that encourages the use of IRT. In this study, the basic concept of IRT will be discussed. In addition, it will briefly review the ability…
Descriptors: Item Response Theory, Fundamental Concepts, Maximum Likelihood Statistics, Psychometrics
Chen, Yetian; González-Brenes, José P.; Tian, Jin – International Educational Data Mining Society, 2016
Skill prerequisite information is useful for tutoring systems that assess student knowledge or that provide remediation. These systems often encode prerequisites as graphs designed by subject matter experts in a costly and time-consuming process. In this paper, we introduce "Combined student Modeling and prerequisite Discovery"…
Descriptors: Bayesian Statistics, Prerequisites, Graphs, Intelligent Tutoring Systems
Karrie A. Shogren; Valerie L. Mazzotti; Tyler A. Hicks; Sheida K. Raley; Daria Gerasimova; Jesse R. Pace; Stephen M. Kwiatek; Darcy Fredrick; Jared H. Stewart-Ginsburg; Richard Chapman; Danielle C. Wysenski – Grantee Submission, 2022
Promoting self-determination is essential to effective transition services and supports. The Goal Setting Challenge App (GSC App) was developed to deliver self-determination instruction via technology, building on the evidence-based Self-Determined Learning Model of Instruction (SDLMI). This paper presents data on goal attainment outcomes for…
Descriptors: Goal Orientation, COVID-19, Pandemics, Computer Software
Tijms, Henk – Teaching Statistics: An International Journal for Teachers, 2015
This teaching note gives a real-life example of Bayesian thinking. It discusses how credible accusations are that the outcome of the draw for the quarter-finals in the 2013 European Champions League Football was manipulated.
Descriptors: Bayesian Statistics, Team Sports, Deception, Foreign Countries
Moreno-Estevaa, Enrique Garcia; White, Sonia L. J.; Wood, Joanne M.; Black, Alex A. – Frontline Learning Research, 2018
In this research, we aimed to investigate the visual-cognitive behaviours of a sample of 106 children in Year 3 (8.8 ± 0.3 years) while completing a mathematics bar-graph task. Eye movements were recorded while children completed the task and the patterns of eye movements were explored using machine learning approaches. Two different techniques of…
Descriptors: Artificial Intelligence, Man Machine Systems, Mathematics Education, Eye Movements
Založnik, Maja; Bonsall, Michael B.; Harper, Sarah – Sociological Methods & Research, 2021
An innovative mixed-methods approach to exploratory focus group design is presented using a case study conducted with smallholder rice farmers in Vietnam. Understanding human decision-making under the uncertainties of a complex and changing social and environmental context requires a flexible yet structured and theoretically grounded approach.…
Descriptors: Barriers, Second Languages, Agricultural Occupations, Decision Making
What Works Clearinghouse, 2023
The appendices accompany the full report "Using Bayesian Meta-Analysis to Explore the Components of Early Literacy Interventions. WWC 2023-008," (ED630495), which pilots a new taxonomy developed by early literacy experts and intervention developers as part of a larger effort to develop standard nomenclature for the components of literacy…
Descriptors: Bayesian Statistics, Meta Analysis, Early Intervention, Literacy
Jones, Samuel David; Brandt, Silke – Journal of Speech, Language, and Hearing Research, 2019
Purpose: This study reexamines the claim that difficulty forming memories of words comprising uncommon sound sequences (i.e., low phonological neighborhood density words) is a determinant of delayed expressive vocabulary development (e.g., Stokes, 2014). Method: We modeled communicative development inventory data from (N = 442) 18-month-old…
Descriptors: Delayed Speech, Expressive Language, Correlation, Vocabulary Development
Loftus, Mary; Madden, Michael G. – Teaching in Higher Education, 2020
How do we teach and learn with our students about data literacy, at the same time as Biesta (2015) calls for an emphasis on 'subjectification' i.e. 'the coming into presence of unique individual beings'? (Good Education in an Age of Measurement: Ethics, Politics, Democracy. Routledge) Our response to these challenges and the datafication of higher…
Descriptors: Teaching Methods, Data Analysis, Literacy, Learning Processes
Freeman, Suzanne C.; Carpenter, James R. – Research Synthesis Methods, 2017
Network meta-analysis (NMA) combines direct and indirect evidence from trials to calculate and rank treatment estimates. While modelling approaches for continuous and binary outcomes are relatively well developed, less work has been done with time-to-event outcomes. Such outcomes are usually analysed using Cox proportional hazard (PH) models.…
Descriptors: Bayesian Statistics, Network Analysis, Meta Analysis, Data
Zhao, Mintao; Bülthoff, Isabelle – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2017
Humans' face ability develops and matures with extensive experience in perceiving, recognizing, and interacting with faces that move most of the time. However, how facial movements affect 1 core aspect of face ability--holistic face processing--remains unclear. Here we investigated the influence of rigid facial motion on holistic and part-based…
Descriptors: Human Body, Visual Perception, Motion, Holistic Approach
Doroudi, Shayan; Brunskill, Emma – Grantee Submission, 2017
In this paper, we investigate two purported problems with Bayesian Knowledge Tracing (BKT), a popular statistical model of student learning: "identifiability" and "semantic model degeneracy." In 2007, Beck and Chang stated that BKT is susceptible to an "identifiability problem"--various models with different…
Descriptors: Bayesian Statistics, Research Problems, Statistical Analysis, Models

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