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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
Streeter, Matthew – International Educational Data Mining Society, 2015
We show that student learning can be accurately modeled using a mixture of learning curves, each of which specifies error probability as a function of time. This approach generalizes Knowledge Tracing [7], which can be viewed as a mixture model in which the learning curves are step functions. We show that this generality yields order-of-magnitude…
Descriptors: Probability, Error Patterns, Learning Processes, Models
Klingler, Severin; Käser, Tanja; Solenthaler, Barbara; Gross, Markus – International Educational Data Mining Society, 2015
Modeling student knowledge is a fundamental task of an intelligent tutoring system. A popular approach for modeling the acquisition of knowledge is Bayesian Knowledge Tracing (BKT). Various extensions to the original BKT model have been proposed, among them two novel models that unify BKT and Item Response Theory (IRT). Latent Factor Knowledge…
Descriptors: Intelligent Tutoring Systems, Knowledge Level, Item Response Theory, Prediction
Maher, Nicole; Muir, Tracey – Mathematics Education Research Group of Australasia, 2014
This paper reports on one aspect of a wider study that investigated a selection of final year pre-service primary teachers' responses to four probability tasks. The tasks focused on foundational ideas of probability including sample space, independence, variation and expectation. Responses suggested that strongly held intuitions appeared to…
Descriptors: Preservice Teachers, College Seniors, Probability, Mathematics Skills
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Chernoff, Egan J.; Russell, Gale L. – North American Chapter of the International Group for the Psychology of Mathematics Education, 2011
The main objective of this article is to contribute to the limited research on teachers' knowledge of probability. In order to meet this objective, we presented prospective mathematics teachers with a variation of a well known task and asked them to determine which of five possible coin flip sequences was least likely to occur. To analyze…
Descriptors: Probability, Knowledge Level, Knowledge Base for Teaching, Mathematics Teachers
Love, Gloria C. – 1988
The probability of experiment-wise error is explored. Overall, the experiment-wise error rate is directly related to the test-wise error rate--the alpha level set by researchers to curtail the existence of a Type I error. A Type I error occurs when a true null hypothesis is rejected in a given study or experiment. The experiment-wise error rate is…
Descriptors: Data Analysis, Error Patterns, Estimation (Mathematics), Experiments
Knoth, Russell L.; Benassi, Victor A. – 1987
The purpose of the study was to determine whether students had knowledge of the extension rule (the conjunction of two or more events cannot be greater than the probability of any one of those events) and understanding of conjunction by giving a test of multiplicative probabilities. Involved were 598 students enrolled in introductory psychology…
Descriptors: College Mathematics, Educational Research, Error Patterns, Higher Education
van der Linden, Wim J. – 1980
Latent class models for mastery testing differ from continuum models in that they do not postulate a latent mastery continuum but conceive mastery and non-mastery as two latent classes, each characterized by different probabilities of success. Several researchers use a simple latent class model that is basically a simultaneous application of the…
Descriptors: Cutting Scores, Error Patterns, Estimation (Mathematics), Foreign Countries
O'Connell, Ann Aileen; And Others – 1996
HyperProb is a Hypercard tutoring system designed to help students develop an effective step-by-step schema for solving probability problems. With this program, students are able to select areas they wish to study via hypermedia links and develop an understanding of terminology and procedures at their own pace with continued reinforcement. Nine…
Descriptors: Computer Assisted Instruction, Error Patterns, Formative Evaluation, Graduate Students
Tatsuoka, Kikumi K.; Tatsuoka, Maurice M. – 1986
The rule space model permits measurement of cognitive skill acquisition, diagnosis of cognitive errors, and detection of the strengths and weaknesses of knowledge possessed by individuals. Two ways to classify an individual into his or her most plausible latent state of knowledge include: (1) hypothesis testing--Bayes' decision rules for minimum…
Descriptors: Artificial Intelligence, Bayesian Statistics, Cognitive Development, Computer Assisted Testing