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Köhler, Carmen; Pohl, Steffi; Carstensen, Claus H. – Educational and Psychological Measurement, 2015
When competence tests are administered, subjects frequently omit items. These missing responses pose a threat to correctly estimating the proficiency level. Newer model-based approaches aim to take nonignorable missing data processes into account by incorporating a latent missing propensity into the measurement model. Two assumptions are typically…
Descriptors: Competence, Tests, Evaluation Methods, Adults
Wetzel, Eunike; Xu, Xueli; von Davier, Matthias – Educational and Psychological Measurement, 2015
In large-scale educational surveys, a latent regression model is used to compensate for the shortage of cognitive information. Conventionally, the covariates in the latent regression model are principal components extracted from background data. This operational method has several important disadvantages, such as the handling of missing data and…
Descriptors: Surveys, Regression (Statistics), Models, Research Methodology
Parashar, Deepak – European Journal of Science and Mathematics Education, 2014
This study is motivated by the desire to address some of the enormous challenges faced by the students as well as the lecturer in fulfilling their respective expectations and duties demanded by the process of learning--teaching of mathematics and statistics within the framework of the constraining schedules laid down by the academic institutions…
Descriptors: Mathematics, Mathematics Instruction, Mathematics Education, Teacher Effectiveness
Herzog, Stefan M.; Hertwig, Ralph – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2014
Individuals can partly recreate the "wisdom of crowds" within their own minds by combining nonredundant estimates they themselves have generated. Herzog and Hertwig (2009) showed that this accuracy gain could be boosted by urging people to actively think differently when generating a 2nd estimate ("dialectical bootstrapping").…
Descriptors: Sampling, Statistical Inference, Experimental Psychology, Hypothesis Testing
Lu, Yun; Vasko, Francis J.; Drummond, Trevor J.; Vasko, Lisa E. – Mathematics Teacher, 2014
If the prospective students of probability lack a background in mathematical proofs, hands-on classroom activities may work well to help them to learn to analyze problems correctly. For example, students may physically roll a die twice to count and compare the frequency of the sequences. Tools such as graphing calculators or Microsoft Excel®…
Descriptors: Probability, Mathematical Logic, Validity, Heuristics
Rickles, Jordan H. – Society for Research on Educational Effectiveness, 2012
The study is designed to demonstrate and test the utility of the proposed two-stage matching method compared to other analytic methods traditionally employed for multisite observational studies. More specifically, the study addresses the following research questions: (1) How do different specifications of the matching method influence covariate…
Descriptors: Probability, Statistical Analysis, Computation, Observation
Petersen, Janne; Bandeen-Roche, Karen; Budtz-Jorgensen, Esben; Larsen, Klaus Groes – Psychometrika, 2012
Latent class regression models relate covariates and latent constructs such as psychiatric disorders. Though full maximum likelihood estimation is available, estimation is often in three steps: (i) a latent class model is fitted without covariates; (ii) latent class scores are predicted; and (iii) the scores are regressed on covariates. We propose…
Descriptors: Computation, Prediction, Regression (Statistics), Maximum Likelihood Statistics
McCaffrey, Daniel F.; Lockwood, J. R.; Setodji, Claude M. – Society for Research on Educational Effectiveness, 2011
Inverse probability weighting (IPW) estimates are widely used in applications where data are missing due to nonresponse or censoring or in observational studies of causal effects where the counterfactuals cannot be observed. This extensive literature has shown the estimators to be consistent and asymptotically normal under very general conditions,…
Descriptors: Computation, Probability, Weighted Scores, Error of Measurement
van de Sande, Brett – Journal of Educational Data Mining, 2013
Bayesian Knowledge Tracing is used very widely to model student learning. It comes in two different forms: The first form is the Bayesian Knowledge Tracing "hidden Markov model" which predicts the probability of correct application of a skill as a function of the number of previous opportunities to apply that skill and the model…
Descriptors: Bayesian Statistics, Markov Processes, Student Evaluation, Probability
Tipton, Elizabeth – Journal of Educational and Behavioral Statistics, 2013
As a result of the use of random assignment to treatment, randomized experiments typically have high internal validity. However, units are very rarely randomly selected from a well-defined population of interest into an experiment; this results in low external validity. Under nonrandom sampling, this means that the estimate of the sample average…
Descriptors: Generalization, Experiments, Classification, Computation
Shteingart, Hanan; Neiman, Tal; Loewenstein, Yonatan – Journal of Experimental Psychology: General, 2013
We quantified the effect of first experience on behavior in operant learning and studied its underlying computational principles. To that goal, we analyzed more than 200,000 choices in a repeated-choice experiment. We found that the outcome of the first experience has a substantial and lasting effect on participants' subsequent behavior, which we…
Descriptors: Operant Conditioning, Behavior, Models, Reinforcement
Dry, Matthew J.; Fontaine, Elizabeth L. – Journal of Problem Solving, 2014
The Traveling Salesperson Problem (TSP) is a computationally difficult combinatorial optimization problem. In spite of its relative difficulty, human solvers are able to generate close-to-optimal solutions in a close-to-linear time frame, and it has been suggested that this is due to the visual system's inherent sensitivity to certain geometric…
Descriptors: Problem Solving, Geographic Location, Computation, Visual Stimuli
Benakli, Nadia; Kostadinov, Boyan; Satyanarayana, Ashwin; Singh, Satyanand – International Journal of Mathematical Education in Science and Technology, 2017
The goal of this paper is to promote computational thinking among mathematics, engineering, science and technology students, through hands-on computer experiments. These activities have the potential to empower students to learn, create and invent with technology, and they engage computational thinking through simulations, visualizations and data…
Descriptors: Calculus, Probability, Data Analysis, Computation
Balasooriya, Uditha; Li, Jackie; Low, Chan Kee – Australian Senior Mathematics Journal, 2012
For any density function (or probability function), there always corresponds a "cumulative distribution function" (cdf). It is a well-known mathematical fact that the cdf is more general than the density function, in the sense that for a given distribution the former may exist without the existence of the latter. Nevertheless, while the…
Descriptors: Computation, Probability, Mathematics, Mathematics Curriculum
Deutsch, Jonah – ProQuest LLC, 2013
This dissertation is composed of three distinct chapters, each of which addresses issues of estimating treatment effects. The first chapter empirically tests the Value-Added (VA) model using school lotteries. The second chapter, co-authored with Michael Wood, considers properties of inverse probability weighting (IPW) in simple treatment effect…
Descriptors: Computation, Causal Models, Probability, Scores

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