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Paul Tschisgale; Marcus Kubsch; Peter Wulff; Stefan Petersen; Knut Neumann – Physical Review Physics Education Research, 2025
Problem solving is considered an essential ability for becoming an expert in physics, and individualized feedback on the structure of problem-solving processes is a key component to support students in developing this ability. Problem-solving processes consist of multiple elements whose order forms the sequential structure of these processes.…
Descriptors: Problem Solving, Physics, Science Instruction, Teaching Methods
van Doorn, Johnny; Matzke, Dora; Wagenmakers, Eric-Jan – Psychology Learning and Teaching, 2020
Sir Ronald Fisher's venerable experiment "The Lady Tasting Tea" is revisited from a Bayesian perspective. We demonstrate how a similar tasting experiment, conducted in a classroom setting, can familiarize students with several key concepts of Bayesian inference, such as the prior distribution, the posterior distribution, the Bayes…
Descriptors: Bayesian Statistics, Statistical Inference, Statistical Distributions, Sequential Approach
Cook, Joshua; Lynch, Collin F.; Hicks, Andrew G.; Mostafavi, Behrooz – International Educational Data Mining Society, 2017
BKT and other classical student models are designed for binary environments where actions are either correct or incorrect. These models face limitations in open-ended and data-driven environments where actions may be correct but non-ideal or where there may even be degrees of error. In this paper we present BKT-SR and RKT-SR: extensions of the…
Descriptors: Models, Bayesian Statistics, Data Use, Intelligent Tutoring Systems
Xiong, Xiaolu; Zhao, Siyuan; Van Inwegen, Eric G.; Beck, Joseph E. – International Educational Data Mining Society, 2016
Over the last couple of decades, there have been a large variety of approaches towards modeling student knowledge within intelligent tutoring systems. With the booming development of deep learning and large-scale artificial neural networks, there have been empirical successes in a number of machine learning and data mining applications, including…
Descriptors: Intelligent Tutoring Systems, Computer Software, Bayesian Statistics, Knowledge Level
Muñoz, Karla; Noguez, Julieta; Neri, Luis; Mc Kevitt, Paul; Lunney, Tom – Educational Technology & Society, 2016
Game-based Learning (GBL) environments make instruction flexible and interactive. Positive experiences depend on personalization. Student modelling has focused on affect. Three methods are used: (1) recognizing the physiological effects of emotion, (2) reasoning about emotion from its origin and (3) an approach combining 1 and 2. These have proven…
Descriptors: Educational Games, Psychological Patterns, Models, Academic Achievement
Seong, Somi; Popper, Steven W.; Goldman, Charles A.; Evans, David K. – RAND Corporation, 2008
In the late 1990s, the Korea Ministry of Education and Human Resources, in response to concern over the relatively low standing of the nation's universities and researchers, launched the Brain Korea 21 program BK21). BK21 seeks to make Korean research universities globally competitive and to produce more high-quality researchers in Korea. It…
Descriptors: Higher Education, Database Design, Research Universities, Program Evaluation

White, Lee J.; And Others – 1975
The major advantage of sequential classification, a technique for automatically classifying documents into previously selected categories, is that the entire document need not be processed before it is classified. This method assumes the availability of a priori categories, a selection of keywords representative of these categories, and the a…
Descriptors: Algorithms, Automatic Indexing, Bayesian Statistics, Classification
McBride, James R.; Weiss, David J. – 1976
Four monte carlo simulation studies of Owen's Bayesian sequential procedure for adaptive mental testing were conducted. Whereas previous simulation studies of this procedure have concentrated on evaluating it in terms of the correlation of its test scores with simulated ability in a normal population, these four studies explored a number of…
Descriptors: Adaptive Testing, Bayesian Statistics, Branching, Computer Oriented Programs
Kar, B. Gautam; White, Lee J. – 1975
The feasibility of using a distance measure, called the Bayesian distance, for automatic sequential document classification was studied. Results indicate that, by observing the variation of this distance measure as keywords are extracted sequentially from a document, the occurrence of noisy keywords may be detected. This property of the distance…
Descriptors: Algorithms, Automatic Indexing, Bayesian Statistics, Classification

McBride, James R. – Applied Psychological Measurement, 1977
The results of a series of simulation studies designed to investigate the influence of guessing and item pool characteristics on the bias, accuracy, and information properties of the trait estimates derived from Owen's Bayesian sequential testing strategy are reported. (RC)
Descriptors: Ability, Adaptive Testing, Bayesian Statistics, Computer Oriented Programs
Clark, Cynthia L., Ed. – 1976
The principal objectives of this conference were to exchange information, discuss theoretical and empirical developments, and to coordinate research efforts. The papers and their authors are: "The Graded Response Model of Latent Trait Theory and Tailored Testing" by Fumiko Samejima; (Incomplete Orders and Computerized Testing" by…
Descriptors: Ability, Adaptive Testing, Bayesian Statistics, Branching
Weiss, David J. – 1976
Three and one-half years of research on computerized ability testing are summarized. The original objectives of the research were: (1) to develop and implement the stratified computer-based ability test; (2) to compare, on psychometric criteria, the various approaches to computer-based ability testing, including the stratified computerized test,…
Descriptors: Adaptive Testing, Bayesian Statistics, Branching, Comparative Analysis
Weiss, David J., Ed. – 1977
This symposium consists of five papers and presents some recent developments in adaptive testing which have applications to several military testing problems. The overview, by James R. McBride, defines adaptive testing and discusses some of its item selection and scoring strategies. Item response theory, or item characteristic curve theory, is…
Descriptors: Ability, Achievement Tests, Adaptive Testing, Bayesian Statistics