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Tamara Broderick; Andrew Gelman; Rachael Meager; Anna L. Smith; Tian Zheng – Grantee Submission, 2022
Probabilistic machine learning increasingly informs critical decisions in medicine, economics, politics, and beyond. To aid the development of trust in these decisions, we develop a taxonomy delineating where trust in an analysis can break down: (1) in the translation of real-world goals to goals on a particular set of training data, (2) in the…
Descriptors: Taxonomy, Trust (Psychology), Algorithms, Probability
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
Cohen, Dale J.; Cromley, Amanda R.; Freda, Katelyn E.; White, Madeline – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2022
Here, we present a strong test of the hypothesis that sacrificial moral dilemmas are solved using the same value-based decision mechanism that operates on decisions concerning economic goods. To test this hypothesis, we developed Psychological Value Theory. Psychological Value Theory is an expansion and generalization of Cohen and Ahn's (2016)…
Descriptors: Hypothesis Testing, Decision Making, Moral Values, Problem Solving
How, Meng-Leong; Hung, Wei Loong David – Education Sciences, 2019
Artificial intelligence-enabled adaptive learning systems (AI-ALS) are increasingly being deployed in education to enhance the learning needs of students. However, educational stakeholders are required by policy-makers to conduct an independent evaluation of the AI-ALS using a small sample size in a pilot study, before that AI-ALS can be approved…
Descriptors: Stakeholders, Artificial Intelligence, Bayesian Statistics, Probability
Dentakos, Stella; Saoud, Wafa; Ackerman, Rakefet; Toplak, Maggie E. – Metacognition and Learning, 2019
Confidence and its accuracy have been most commonly examined in domains such as general knowledge and learning, with less study of other domains, such as applied knowledge and problem solving. Monitoring accuracy in real-world competencies may depend on characteristics of the domain. In this study, we examined whether monitoring accuracy, both…
Descriptors: Accuracy, Epistemology, Probability, Computation
Koparan, Timur – International Journal of Assessment Tools in Education, 2019
Technology and games are the areas where learners are most interested in today's world. If these two can be brought together within the framework of learning objectives, they can be an advantage for teachers and students. This study aims to investigate the learning environment supported by game and simulation. The games were used to evaluate the…
Descriptors: Computer Simulation, Game Based Learning, Educational Environment, Probability
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
Oh, Hanna; Beck, Jeffrey M.; Zhu, Pingping; Sommer, Marc A.; Ferrari, Silvia; Egner, Tobias – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2016
Much of our real-life decision making is bounded by uncertain information, limitations in cognitive resources, and a lack of time to allocate to the decision process. It is thought that humans overcome these limitations through "satisficing," fast but "good-enough" heuristic decision making that prioritizes some sources of…
Descriptors: Decision Making, Cues, Cognitive Processes, Time
Students' Informal Inference about the Binomial Distribution of "Bunny Hops": A Dialogic Perspective
Kazak, Sibel; Fujita, Taro; Wegerif, Rupert – Statistics Education Research Journal, 2016
The study explores the development of 11-year-old students' informal inference about random bunny hops through student talk and use of computer simulation tools. Our aim in this paper is to draw on dialogic theory to explain how students make shifts in perspective, from intuition-based reasoning to more powerful, formal ways of using probabilistic…
Descriptors: Inferences, Computer Simulation, Probability, Statistical Distributions
Murphy, Amanda; Terrizzi, Marissa; Cormas, Peter – Mathematics Teaching, 2012
"Probability is a difficult concept to teach, because children and adults find it counterintuitive." This is impetus to consider the detailed planning of a set of lessons with a "mixed", in many senses, group of fourth graders. Can the use of prior experience, and the knowledge associated with that experience, make probability a concept that is…
Descriptors: Probability, Grade 4, Mathematics Instruction, Prior Learning
Goldin, Ilya M.; Koedinger, Kenneth R.; Aleven, Vincent – International Educational Data Mining Society, 2012
Although ITSs are supposed to adapt to differences among learners, so far, little attention has been paid to how they might adapt to differences in how students learn from help. When students study with an Intelligent Tutoring System, they may receive multiple types of help, but may not comprehend and make use of this help in the same way. To…
Descriptors: Performance Factors, Intelligent Tutoring Systems, Individual Differences, Prediction
Boyce, Steven J.; Wilkins, Jesse L. M.; MacDonald, Beth Loveday – North American Chapter of the International Group for the Psychology of Mathematics Education, 2011
An interview with a sixth-grade student illustrates how her number sense and understanding of variability relate to her ability and proclivity to apply a frequentist (statistical) approach to probability tasks. A general suggestion for teaching about mathematics of uncertainty through the gradual strengthening of estimation, as per the historical…
Descriptors: Mathematics Instruction, Middle School Students, Grade 6, Probability
Holt, Melinda Miller; Scariano, Stephen M. – Journal of Statistics Education, 2009
The classroom activity described here allows mathematically mature students to explore the role of mean, median and mode in a decision-making environment. While students discover the importance of choosing a measure of central tendency, their understanding of probability distributions, maximization, and prediction is reinforced through active…
Descriptors: Active Learning, Probability, Statistics, Mathematics Instruction
Morrell, Christopher H.; Auer, Richard E. – Journal of Statistics Education, 2007
In the early 1990s, the National Science Foundation funded many research projects for improving statistical education. Many of these stressed the need for classroom activities that illustrate important issues of designing experiments, generating quality data, fitting models, and performing statistical tests. Our paper describes such an activity on…
Descriptors: Statistics, Learning Activities, Class Activities, Homework
Baker, Monica; Chick, Helen – Australian Primary Mathematics Classroom, 2007
Everyone knows that teachers do not have unlimited time, a log of experience, or a deep understanding of all the mathematics they teach. To solve this problem, teachers often use textbooks, and the accompanying teacher's resource books, as sources of activities and advice about how to help students learn mathematics. The activity that prompted…
Descriptors: Textbooks, Grade 5, Probability, Foreign Countries
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