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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
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
Crupi, Vincenzo; Nelson, Jonathan D.; Meder, Björn; Cevolani, Gustavo; Tentori, Katya – Cognitive Science, 2018
Searching for information is critical in many situations. In medicine, for instance, careful choice of a diagnostic test can help narrow down the range of plausible diseases that the patient might have. In a probabilistic framework, test selection is often modeled by assuming that people's goal is to reduce uncertainty about possible states of the…
Descriptors: Information Theory, Cognitive Processes, Information Seeking, 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
Wulff, Dirk U.; Pachur, Thorsten – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2016
What are the cognitive mechanisms underlying subjective valuations formed on the basis of sequential experiences of an option's possible outcomes? Ashby and Rakow (2014) have proposed a sliding window model (SWIM), according to which people's valuations represent the average of a limited sample of recent experiences (the size of which is estimated…
Descriptors: Experimental Psychology, Cognitive Psychology, Modeling (Psychology), Models
Matsumoto, Paul S.; Cao, Jiankang – Journal of Chemical Education, 2017
Computational thinking is a component of the Science and Engineering Practices in the Next Generation Science Standards, which were adopted by some states. We describe the activities in a high school chemistry course that may develop students' computational thinking skills by primarily using Excel, a widely available spreadsheet software. These…
Descriptors: Secondary School Science, High School Students, Computation, Thinking Skills
Andrade, Alejandro; Danish, Joshua A.; Maltese, Adam V. – Journal of Learning Analytics, 2017
Interactive learning environments with body-centric technologies lie at the intersection of the design of embodied learning activities and multimodal learning analytics. Sensing technologies can generate large amounts of fine-grained data automatically captured from student movements. Researchers can use these fine-grained data to create a…
Descriptors: Measurement, Interaction, Models, Educational Environment
MacCoun, Robert J. – Psychological Review, 2012
[Correction Notice: An erratum for this article was reported in Vol 119(2) of Psychological Review (see record 2012-06153-001). In the article, incorrect versions of figures 3 and 6 were included. Also, Table 8 should have included the following information in the table footnote "P(A V) = probability of acquittal given unanimous verdict." All…
Descriptors: Social Influences, Probability, Item Response Theory, Psychological Studies
Koenig, Alan D.; Lee, John J.; Iseli, Markus; Wainess, Richard – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2010
The military's need for high-fidelity games and simulations is substantial, as these environments can be valuable for demonstration of essential knowledge, skills, and abilities required in complex tasks. However assessing performance in these settings can be difficult--particularly in non-linear simulations where more than one pathway to success…
Descriptors: Military Training, Fire Protection, Computers, Games
Fong, Soon Fook; Por, Fei Ping; Tang, Ai Ling – Turkish Online Journal of Educational Technology - TOJET, 2012
The purpose of this study was to investigate the effects of multiple simulation presentation in interactive multimedia are on the achievement of students with different levels of anxiety in the learning of Probability. The interactive multimedia courseware was developed in two different modes, which were Multiple Simulation Presentation (MSP) and…
Descriptors: Anxiety, Courseware, Probability, Computer Simulation
McMaster, Kirby; Sambasivam, Samuel E.; Anderson, Nicole – Information Systems Education Journal, 2010
In demand paging virtual memory systems, the page fault rate of a process varies with the number of memory frames allocated to the process. When an increase in the number of allocated frames leads to an increase in the number of page faults, Belady's anomaly is said to occur. In this paper, we present a probability model for Belady's anomaly. We…
Descriptors: Probability, Models, Computer Science Education, Information Systems
Iseli, Markus R.; Koenig, Alan D.; Lee, John J.; Wainess, Richard – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2010
Assessment of complex task performance is crucial to evaluating personnel in critical job functions such as Navy damage control operations aboard ships. Games and simulations can be instrumental in this process, as they can present a broad range of complex scenarios without involving harm to people or property. However, "automatic"…
Descriptors: Performance Tests, Performance Based Assessment, Decision Making Skills, Military Training
Lehrer, Richard; Kim, Min-joung; Schauble, Leona – International Journal of Computers for Mathematical Learning, 2007
New capabilities in "TinkerPlots 2.0" supported the conceptual development of fifth- and sixth-grade students as they pursued several weeks of instruction that emphasized data modeling. The instruction highlighted links between data analysis, chance, and modeling in the context of describing and explaining the distributions of measures that result…
Descriptors: Computer Assisted Instruction, Concept Formation, Statistical Analysis, Statistics
Schmitt, J. Eric; Mehta, Paras D.; Aggen, Steven H.; Kubarych, Thomas S.; Neale, Michael C. – Multivariate Behavioral Research, 2006
Ordered latent class analysis (OLCA) can be used to approximate unidimensional latent distributions. The main objective of this study is to evaluate the method of OLCA in detecting non-normality of an unobserved continuous variable (i.e., a common factor) used to explain the covariation between dichotomous item-level responses. Using simulation,…
Descriptors: Probability, Sample Size, Effect Size, Depression (Psychology)
Levy, Roy; Mislevy, Robert J. – US Department of Education, 2004
The challenges of modeling students' performance in simulation-based assessments include accounting for multiple aspects of knowledge and skill that arise in different situations and the conditional dependencies among multiple aspects of performance in a complex assessment. This paper describes a Bayesian approach to modeling and estimating…
Descriptors: Probability, Markov Processes, Monte Carlo Methods, Bayesian Statistics
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