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Ken A. Fujimoto; Carl F. Falk – Educational and Psychological Measurement, 2024
Item response theory (IRT) models are often compared with respect to predictive performance to determine the dimensionality of rating scale data. However, such model comparisons could be biased toward nested-dimensionality IRT models (e.g., the bifactor model) when comparing those models with non-nested-dimensionality IRT models (e.g., a…
Descriptors: Item Response Theory, Rating Scales, Predictive Measurement, Bayesian Statistics
Anirudhan Badrinath; Zachary Pardos – Journal of Educational Data Mining, 2025
Bayesian Knowledge Tracing (BKT) is a well-established model for formative assessment, with optimization typically using expectation maximization, conjugate gradient descent, or brute force search. However, one of the flaws of existing optimization techniques for BKT models is convergence to undesirable local minima that negatively impact…
Descriptors: Bayesian Statistics, Intelligent Tutoring Systems, Problem Solving, Audience Response Systems
How, Meng-Leong; Hung, Wei Loong David – Education Sciences, 2019
Educational stakeholders would be better informed if they could use their students' formative assessments results and personal background attributes to predict the conditions for achieving favorable learning outcomes, and conversely, to gain awareness of the "at-risk" signals to prevent unfavorable or worst-case scenarios from happening.…
Descriptors: Artificial Intelligence, Bayesian Statistics, Models, Data Use
Slater, Stefan; Baker, Ryan – Distance Education, 2019
Considerable attention has been given to methods for knowledge estimation, a category of methods for automatic assessment of a student's degree of skill mastery or knowledge at a specific time. Knowledge estimation is frequently used to make decisions about when a student has reached mastery and is ready to advance to new material, but there has…
Descriptors: Prediction, Mastery Learning, Academic Achievement, Bayesian Statistics
Ames, Allison; Myers, Aaron – Educational Measurement: Issues and Practice, 2019
Drawing valid inferences from modern measurement models is contingent upon a good fit of the data to the model. Violations of model-data fit have numerous consequences, limiting the usefulness and applicability of the model. As Bayesian estimation is becoming more common, understanding the Bayesian approaches for evaluating model-data fit models…
Descriptors: Bayesian Statistics, Psychometrics, Models, Predictive Measurement
Larson, Jeffrey S.; Billeter, Darron M. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2017
Competition judges are often selected for their expertise, under the belief that a high level of performance expertise should enable accurate judgments of the competitors. Contrary to this assumption, we find evidence that expertise can reduce judgment accuracy. Adaptation level theory proposes that discriminatory capacity decreases with greater…
Descriptors: Expertise, Novices, Singing, Music
Blackwell, Matthew; Honaker, James; King, Gary – Sociological Methods & Research, 2017
We extend a unified and easy-to-use approach to measurement error and missing data. In our companion article, Blackwell, Honaker, and King give an intuitive overview of the new technique, along with practical suggestions and empirical applications. Here, we offer more precise technical details, more sophisticated measurement error model…
Descriptors: Error of Measurement, Correlation, Simulation, Bayesian Statistics
Martinkova, Patricia; Goldhaber, Dan – Center for Education Data & Research, 2015
Inter-rater reliability, commonly assessed by intra-class correlation coefficient ICC, is an important index for describing the extent to which there is consistency amongst two or more raters in assigned measures. In organizational research, the data structure is often hierarchical and designs deviate substantially from the ideal of a balanced…
Descriptors: Teacher Selection, Interrater Reliability, Public School Teachers, Hierarchical Linear Modeling
Koc, Levent – ProQuest LLC, 2013
With increasing Internet connectivity and traffic volume, recent intrusion incidents have reemphasized the importance of network intrusion detection systems for combating increasingly sophisticated network attacks. Techniques such as pattern recognition and the data mining of network events are often used by intrusion detection systems to classify…
Descriptors: Bayesian Statistics, Computer Security, Computer Networks, Data Collection
Austerweil, Joseph L.; Griffiths, Thomas L. – Cognitive Psychology, 2011
Most psychological theories treat the features of objects as being fixed and immediately available to observers. However, novel objects have an infinite array of properties that could potentially be encoded as features, raising the question of how people learn which features to use in representing those objects. We focus on the effects of…
Descriptors: Visual Stimuli, Novelty (Stimulus Dimension), Bayesian Statistics, Learning
Ting, Choo-Yee; Sam, Yok-Cheng; Wong, Chee-Onn – Computers & Education, 2013
Constructing a computational model of conceptual change for a computer-based scientific inquiry learning environment is difficult due to two challenges: (i) externalizing the variables of conceptual change and its related variables is difficult. In addition, defining the causal dependencies among the variables is also not trivial. Such difficulty…
Descriptors: Concept Formation, Bayesian Statistics, Inquiry, Science Instruction
Bekele, Rahel; McPherson, Maggie – British Journal of Educational Technology, 2011
This research work presents a Bayesian Performance Prediction Model that was created in order to determine the strength of personality traits in predicting the level of mathematics performance of high school students in Addis Ababa. It is an automated tool that can be used to collect information from students for the purpose of effective group…
Descriptors: Foreign Countries, Personality Traits, Mathematics Education, Prediction
Proctor, Thomas P.; Kim, YoungKoung Rachel – College Board, 2010
The purpose of this paper is to provide information about how students' scores change when they retake the PSAT/NMSQT as juniors or take the SAT in the spring after they take the PSAT/NMSQT as juniors. Two research questions guided this study and motivated the approach for analysis of the data: How do scores change for students who took the…
Descriptors: Scores, Achievement Gains, Bayesian Statistics, College Entrance Examinations
Killeen, Peter R. – Psychological Methods, 2010
Lecoutre, Lecoutre, and Poitevineau (2010) have provided sophisticated grounding for "p[subscript rep]." Computing it precisely appears, fortunately, no more difficult than doing so approximately. Their analysis will help move predictive inference into the mainstream. Iverson, Wagenmakers, and Lee (2010) have also validated…
Descriptors: Replication (Evaluation), Measurement Techniques, Research Design, Research Methodology
Laru, Jari; Naykki, Piia; Jarvela, Sanna – Internet and Higher Education, 2012
In this single-case study, small groups of learners were supported by use of multiple social software tools and face-to-face activities in the context of higher education. The aim of the study was to explore how designed learning activities contribute to students' learning outcomes by studying probabilistic dependencies between the variables.…
Descriptors: Web Sites, Electronic Publishing, Cooperative Learning, Group Activities
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