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Gustafson, S. C.; Costello, C. S.; Like, E. C.; Pierce, S. J.; Shenoy, K. N. – IEEE Transactions on Education, 2009
Bayesian estimation of a threshold time (hereafter simply threshold) for the receipt of impulse signals is accomplished given the following: 1) data, consisting of the number of impulses received in a time interval from zero to one and the time of the largest time impulse; 2) a model, consisting of a uniform probability density of impulse time…
Descriptors: Scientific Concepts, Computation, Probability, Bayesian Statistics
Gauch, Hugh G., Jr. – Science & Education, 2009
This article responds to the other 10 papers in this thematic issue on science and worldviews and it clarifies some of the points in my lead article. The Bayesian framework provides helpful structure for worldview inquiries by recognizing and integrating both public and personal evidence. Drawing upon the other 10 papers, six kinds of potential…
Descriptors: World Views, Natural Sciences, Philosophy, Humanities
Papay, John P.; Murnane, Richard J.; Willett, John B. – National Bureau of Economic Research, 2011
Students receive abundant information about their educational performance, but how this information affects future educational-investment decisions is not well understood. Increasingly common sources of information are state-mandated standardized tests. On these tests, students receive a score and a label that summarizes their performance. Using a…
Descriptors: Investment, Educational Objectives, Outcomes of Education, Standardized Tests
Zhao, Yuan – ProQuest LLC, 2010
Learning a phonetic category (or any linguistic category) requires integrating different sources of information. A crucial unsolved problem for phonetic learning is how this integration occurs: how can we update our previous knowledge about a phonetic category as we hear new exemplars of the category? One model of learning is Bayesian Inference,…
Descriptors: Evidence, Cues, Phonetics, Prior Learning
Tuttle, Christina Clark; Gleason, Philip; Knechtel, Virginia; Nichols-Barrer, Ira; Booker, Kevin; Chojnacki, Gregory; Coen, Thomas; Goble, Lisbeth – Mathematica Policy Research, Inc., 2015
KIPP (Knowledge is Power Program) is a national network of public charter schools whose stated mission is to help underserved students enroll in and graduate from college. Prior studies (see Tuttle et al. 2013) have consistently found that attending a KIPP middle school positively affects student achievement, but few have addressed longer-term…
Descriptors: Program Effectiveness, Program Evaluation, Academic Achievement, Charter Schools
Tuttle, Christina Clark; Gleason, Philip; Knechtel, Virginia; Nichols-Barrer, Ira; Booker, Kevin; Chojnacki, Gregory; Coen, Thomas; Goble, Lisbeth – Mathematica Policy Research, Inc., 2015
KIPP (Knowledge is Power Program) is a national network of public charter schools whose stated mission is to help underserved students enroll in and graduate from college. Prior studies (see Tuttle et al. 2013) have consistently found that attending a KIPP middle school positively affects student achievement, but few have addressed longer-term…
Descriptors: Program Effectiveness, Program Evaluation, Academic Achievement, Charter Schools
Tuttle, Christina Clark; Gleason, Philip; Knechtel, Virginia; Nichols-Barrer, Ira; Booker, Kevin; Chojnacki, Gregory; Coen, Thomas; Goble, Lisbeth – Mathematica Policy Research, Inc., 2015
KIPP (Knowledge is Power Program) is a national network of public charter schools whose stated mission is to help underserved students enroll in and graduate from college. Prior studies (see Tuttle et al. 2013) have consistently found that attending a KIPP middle school positively affects student achievement, but few have addressed longer-term…
Descriptors: Academic Achievement, Charter Schools, Educational Innovation, Institutional Characteristics
Frank, Michael C.; Slemmer, Jonathan A.; Marcus, Gary F.; Johnson, Scott P. – Developmental Science, 2009
By 7 months of age, infants are able to learn rules based on the abstract relationships between stimuli ( Marcus et al., 1999 ), but they are better able to do so when exposed to speech than to some other classes of stimuli. In the current experiments we ask whether multimodal stimulus information will aid younger infants in identifying abstract…
Descriptors: Cues, Infants, Experiments, Learning Modalities
Song, Xin-Yuan; Lee, Sik-Yum; Hser, Yih-Ing – Structural Equation Modeling: A Multidisciplinary Journal, 2009
In longitudinal studies, investigators often measure multiple variables at multiple time points and are interested in investigating individual differences in patterns of change on those variables. Furthermore, in behavioral, social, psychological, and medical research, investigators often deal with latent variables that cannot be observed directly…
Descriptors: Medical Research, Structural Equation Models, Longitudinal Studies, Multivariate Analysis
Gallistel, C. R. – Psychological Review, 2009
Null hypotheses are simple, precise, and theoretically important. Conventional statistical analysis cannot support them; Bayesian analysis can. The challenge in a Bayesian analysis is to formulate a suitably vague alternative, because the vaguer the alternative is (the more it spreads out the unit mass of prior probability), the more the null is…
Descriptors: Bayesian Statistics, Statistical Analysis, Probability, Hypothesis Testing
Enders, Craig K. – Guilford Press, 2010
Walking readers step by step through complex concepts, this book translates missing data techniques into something that applied researchers and graduate students can understand and utilize in their own research. Enders explains the rationale and procedural details for maximum likelihood estimation, Bayesian estimation, multiple imputation, and…
Descriptors: Data Analysis, Error of Measurement, Research Problems, Maximum Likelihood Statistics
Clark, Christina – National Literacy Trust, 2014
This report presents second year information about the degree to which children and young people in Middlesbrough enjoy reading and writing, how often then engage in reading and writing, what types of materials they read and write and how they feel about reading and writing. It also outlines information about their confidence in their own…
Descriptors: Foreign Countries, Literacy, Reading Attitudes, Reading Habits
Lu, Hongjing; Yuille, Alan L.; Liljeholm, Mimi; Cheng, Patricia W.; Holyoak, Keith J. – Psychological Review, 2008
The article presents a Bayesian model of causal learning that incorporates generic priors--systematic assumptions about abstract properties of a system of cause-effect relations. The proposed generic priors for causal learning favor sparse and strong (SS) causes--causes that are few in number and high in their individual powers to produce or…
Descriptors: Bayesian Statistics, Models, Learning Processes, Influences
Andrew, Megan; Hauser, Robert M. – Social Forces, 2011
Sociologists have long used educational expectations to understand the complex mental processes underlying individuals' educational decision making. Yet, little research evaluates how students actually formulate their educational expectations. Status attainment theory asserts that students adopt their educational expectations early based on family…
Descriptors: Learning Theories, Grade Point Average, Family Characteristics, Academic Achievement
Kieftenbeld, Vincent; Natesan, Prathiba; Eddy, Colleen – Journal of Psychoeducational Assessment, 2011
The mathematics teaching efficacy beliefs of preservice elementary teachers have been the subject of several studies. A widely used measure in these studies is the Mathematics Teaching Efficacy Beliefs Instrument (MTEBI). The present study provides a detailed analysis of the psychometric properties of the MTEBI using Bayesian item response theory.…
Descriptors: Item Response Theory, Bayesian Statistics, Mathematics Instruction, Preservice Teachers

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