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Li, ZhaoBin; Yee, Luna; Sauerberg, Nathaniel; Sakson, Irene; Williams, Joseph Jay; Rafferty, Anna N. – International Educational Data Mining Society, 2020
Digital educational technologies offer the potential to customize students' experiences and learn what works for which students, enhancing the technology as more students interact with it. We consider whether and when attempting to discover how to personalize has a cost, such as if the adaptation to personal information can delay the adoption of…
Descriptors: Educational Technology, Technology Uses in Education, Student Needs, Student Characteristics
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Kwon, Yeil; Sahin, Nesrin – International Society for Technology, Education, and Science, 2021
Probability is generally considered one of the most challenging areas to teach in mathematics education due to its intricate nature. However, the simulation-based teaching method can increase students' accessibility significantly to the probability problems because it enables students to resolve the problems with minimal mathematical skills. By…
Descriptors: Probability, Mathematics Instruction, Difficulty Level, Teaching Methods
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Zhang, Qiao; Maclellan, Christopher J. – International Educational Data Mining Society, 2021
Knowledge tracing algorithms are embedded in Intelligent Tutoring Systems (ITS) to keep track of students' learning process. While knowledge tracing models have been extensively studied in offline settings, very little work has explored their use in online settings. This is primarily because conducting experiments to evaluate and select knowledge…
Descriptors: Electronic Learning, Mastery Learning, Computer Simulation, Intelligent Tutoring Systems
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Chen, Binglin; West, Matthew; Ziles, Craig – International Educational Data Mining Society, 2018
This paper attempts to quantify the accuracy limit of "nextitem-correct" prediction by using numerical optimization to estimate the student's probability of getting each question correct given a complete sequence of item responses. This optimization is performed without an explicit parameterized model of student behavior, but with the…
Descriptors: Accuracy, Probability, Student Behavior, Test Items
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Schnell, Susanne – North American Chapter of the International Group for the Psychology of Mathematics Education, 2014
This paper contributes to the discourse in stochastic education of how young students deal with learning settings that allow a data-based approach to probability. By using the micro-structure of arguments by Toulmin (1958), it explores which arguments students use and which role they play in the learning process. The data stems from design…
Descriptors: Probability, Persuasive Discourse, Experiments, Inferences
Prodromou, Theodosia – Mathematics Education Research Group of Australasia, 2012
This article seeks to address a pedagogical theory of introducing the classicist and the frequentist approach to probability, by investigating important elements in 9th grade students' learning process while working with a "TinkerPlots2" combinatorial problem. Results from this research study indicate that, after the students had seen…
Descriptors: Mathematics Instruction, Probability, Grade 9, Mathematics Skills
English, Lyn; Watson, Jane – Mathematics Education Research Group of Australasia, 2014
Students explored variation and expectation in a probability activity at the end of the first year of a 3-year longitudinal study across grades 4-6. The activity involved experiments in tossing coins both manually and with simulation using the graphing software, "TinkerPlots." Initial responses indicated that the students were aware of…
Descriptors: Foreign Countries, Elementary School Mathematics, Elementary School Students, Grade 4
Jarrell, Michele G. – 1991
A probability distribution was developed for the Andrews-Pregibon (AP) statistic. The statistic, developed by D. F. Andrews and D. Pregibon (1978), identifies multivariate outliers. It is a ratio of the determinant of the data matrix with an observation deleted to the determinant of the entire data matrix. Although the AP statistic has been used…
Descriptors: Computer Simulation, Error of Measurement, Matrices, Multivariate Analysis
Ware, William B.; Althouse, Linda Akel – 1999
This study was designed to derive the distribution of a test statistic based on normal probability plots. The first purpose was to provide an empirical derivation of the critical values for the Line Test (LT) with an extensive computer simulation. The goal was to develop a test that is sensitive to a wide range of alternative distributions,…
Descriptors: Computation, Computer Simulation, Monte Carlo Methods, Probability
Barnette, J. Jackson; McLean, James E. – 2000
The probabilities of attaining varying magnitudes of standardized effect sizes by chance and when protected by a 0.05 level statistical test were studied. Monte Carlo procedures were used to generate standardized effect sizes in a one-way analysis of variance situation with 2 through 5, 6, 8, and 10 groups with selected sample sizes from 5 to 500.…
Descriptors: Computer Simulation, Effect Size, Monte Carlo Methods, Probability
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Snijders, Tom A. B. – Psychometrika, 1991
A complete enumeration method and a Monte Carlo method are presented to calculate the probability distribution of arbitrary statistics of adjacency matrices when these matrices have the uniform distribution conditional on given row and column sums, and possibly on a given set of structural zeros. (SLD)
Descriptors: Computer Simulation, Equations (Mathematics), Mathematical Models, Matrices
Klockars, Alan J.; Hancock, Gregory R. – 1993
The challenge of multiple comparisons is to maximize the power for answering specific research questions, while still maintaining control over the rate of Type I error. Several multiple comparison procedures have been suggested to meet this challenge. The stagewise protected procedure (SPP) of A. J. Klockars and G. R. Hancock tests null hypotheses…
Descriptors: Comparative Analysis, Computer Simulation, Hypothesis Testing, Mathematical Models
Elliott, Ronald S.; Barcikowski, Robert S. – 1993
This Monte Carlo study examines whether, given various numbers of variables, treatments, and sample sizes, in a one-way multivariate analysis of variance, Type I error rates of the test approximations provided by the BMDP program, the Statistical Analysis System (SAS), and the Statistical Package for the Social Sciences (SPSS) for Roy's largest…
Descriptors: Analysis of Variance, Computer Simulation, Estimation (Mathematics), Monte Carlo Methods
De Ayala, R. J. – 1993
Previous work on the effects of dimensionality on parameter estimation was extended from dichotomous models to the polytomous graded response (GR) model. A multidimensional GR model was developed to generate data in one-, two-, and three-dimensions, with two- and three-dimensional conditions varying in their interdimensional associations. Test…
Descriptors: Computer Simulation, Correlation, Difficulty Level, Estimation (Mathematics)
Falkenhainer, Brian – 1987
This paper addresses the problem of probabilistic reasoning as it applies to Truth Maintenance Systems (TMS). A computer-based Belief Maintenance System (BMS) has been constructed which manages a current set of probabilistic beliefs in much the same way that a TMS manages a set of true/false beliefs. It may be thought of as a generalization of a…
Descriptors: Abstract Reasoning, Analogy, Artificial Intelligence, Beliefs