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Tarasenko, Larissa V.; Ougolnitsky, Guennady A.; Usov, Anatoly B.; Vaskov, Maksim A.; Kirik, Vladimir A.; Astoyanz, Margarita S.; Angel, Olga Y. – International Journal of Environmental and Science Education, 2016
A dynamic game theoretic model of concordance of interests in the process of social partnership in the system of continuing professional education is proposed. Non-cooperative, cooperative, and hierarchical setups are examined. Analytical solution for a linear state version of the model is provided. Nash equilibrium algorithms (for non-cooperative…
Descriptors: Professional Continuing Education, Game Theory, Models, Partnerships in Education
Callies, Sophie; Gravel, Mathieu; Beaudry, Eric; Basque, Josianne – International Journal of Game-Based Learning, 2017
This paper presents an architecture designed for simulation serious games, which automatically generates game-based scenarios adapted to learner's learning progression. We present three central modules of the architecture: (1) the learner model, (2) the adaptation module and (3) the logs module. The learner model estimates the progression of the…
Descriptors: Simulation, Educational Games, Models, Computation
Yu, Chen; Smith, Linda B. – Psychological Review, 2012
Both adults and young children possess powerful statistical computation capabilities--they can infer the referent of a word from highly ambiguous contexts involving many words and many referents by aggregating cross-situational statistical information across contexts. This ability has been explained by models of hypothesis testing and by models of…
Descriptors: Testing, Associative Learning, Hypothesis Testing, Adults
Berry, Christopher J.; Shanks, David R.; Speekenbrink, Maarten; Henson, Richard N. A. – Psychological Review, 2012
We present a new modeling framework for recognition memory and repetition priming based on signal detection theory. We use this framework to specify and test the predictions of 4 models: (a) a single-system (SS) model, in which one continuous memory signal drives recognition and priming; (b) a multiple-systems-1 (MS1) model, in which completely…
Descriptors: Priming, Recognition (Psychology), Models, Prediction
Basarab, Dave – Performance Improvement, 2011
The Predictive Evaluation (PE) model is a training and evaluation approach with the element of prediction. PE allows trainers and business leaders to predict the results, value, intention, adoption, and impact of training, allowing them to make smarter, more strategic training and evaluation investments. PE is invaluable for companies that…
Descriptors: Staff Development, Training Objectives, Prediction, Models
Kreiner, Svend – Applied Psychological Measurement, 2011
To rule out the need for a two-parameter item response theory (IRT) model during item analysis by Rasch models, it is important to check the Rasch model's assumption that all items have the same item discrimination. Biserial and polyserial correlation coefficients measuring the association between items and restscores are often used in an informal…
Descriptors: Item Analysis, Correlation, Item Response Theory, Models
Kelley, Ken; Rausch, Joseph R. – Psychological Methods, 2011
Longitudinal studies are necessary to examine individual change over time, with group status often being an important variable in explaining some individual differences in change. Although sample size planning for longitudinal studies has focused on statistical power, recent calls for effect sizes and their corresponding confidence intervals…
Descriptors: Intervals, Sample Size, Effect Size, Longitudinal Studies
Rhemtulla, Mijke; Brosseau-Liard, Patricia E.; Savalei, Victoria – Psychological Methods, 2012
A simulation study compared the performance of robust normal theory maximum likelihood (ML) and robust categorical least squares (cat-LS) methodology for estimating confirmatory factor analysis models with ordinal variables. Data were generated from 2 models with 2-7 categories, 4 sample sizes, 2 latent distributions, and 5 patterns of category…
Descriptors: Factor Analysis, Computation, Simulation, Sample Size
Vallejo, G.; Fernandez, M. P.; Livacic-Rojas, P. E.; Tuero-Herrero, E. – Multivariate Behavioral Research, 2011
Missing data are a pervasive problem in many psychological applications in the real world. In this article we study the impact of dropout on the operational characteristics of several approaches that can be easily implemented with commercially available software. These approaches include the covariance pattern model based on an unstructured…
Descriptors: Personality Problems, Psychosis, Prevention, Patients
White, Sheida; Krenzke, Tom; Sherman, Dan – National Center for Education Statistics, 2010
In 2009, the National Center for Education Statistics (NCES) published a technical report titled "Indirect County and State Estimates of the Percentage of Adults at the Lowest Literacy Level for 1992 and 2003," (ED503830). NCES also published a corresponding online tool (http://nces.ed.gov/naal/estimates/index.aspx) that allows users to…
Descriptors: Adult Literacy, Incidence, Illiteracy, Statistical Analysis
Griffiths, Thomas L.; Tenenbaum, Joshua B. – Psychological Review, 2009
Inducing causal relationships from observations is a classic problem in scientific inference, statistics, and machine learning. It is also a central part of human learning, and a task that people perform remarkably well given its notorious difficulties. People can learn causal structure in various settings, from diverse forms of data: observations…
Descriptors: Causal Models, Prior Learning, Logical Thinking, Statistical Inference
Huff, Monica; Dotson, Edward G. – Performance Improvement, 2008
The purpose of the performance study was to review a proposed U.S. Navy Learning Center instructor computation (ICOMP) model for calculating the number of instructors required for teaching courses at Navy training sites. Based on recommendations from the initial analysis, a workweek breakdown was conducted for facilitated self-paced instructors.…
Descriptors: Working Hours, Computation, Armed Forces, Mathematical Models
Jian, Lian – ProQuest LLC, 2010
My dissertation contains three studies centering on the question: how to motivate people to share high quality information on online information aggregation systems, also known as social computing systems? I take a social scientific approach to "identify" the strategic behavior of individuals in information systems, and "analyze" how non-monetary…
Descriptors: Information Systems, Internet, Motivation Techniques, Incentives
Sampson, Demetrios G., Ed.; Ifenthaler, Dirk, Ed.; Isaías, Pedro, Ed. – International Association for Development of the Information Society, 2018
The aim of the 2018 International Association for Development of the Information Society (IADIS) Cognition and Exploratory Learning in the Digital Age (CELDA) conference was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There have been advances in both cognitive…
Descriptors: Learning Processes, Teaching Methods, Educational Technology, Technology Uses in Education
Barnes, Tiffany, Ed.; Desmarais, Michel, Ed.; Romero, Cristobal, Ed.; Ventura, Sebastian, Ed. – International Working Group on Educational Data Mining, 2009
The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…
Descriptors: Data Analysis, Educational Research, Conferences (Gatherings), Foreign Countries