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Peter Arcidiacono; Karthik Muralidharan; John D. Singleton – National Bureau of Economic Research, 2024
We leverage a unique two-stage experiment that randomized access to private school vouchers across markets as well as students to estimate the revealed preference value of school choice. To do this, we estimate several choice models on data only from control markets before turning to the treatment data for model validation. This exercise reveals…
Descriptors: Private Schools, Educational Vouchers, School Choice, Preferences
Hyemin Yoon; HyunJin Kim; Sangjin Kim – Measurement: Interdisciplinary Research and Perspectives, 2024
We have maintained the customer grade system that is being implemented to customers with excellent performance through customer segmentation for years. Currently, financial institutions that operate the customer grade system provide similar services based on the score calculation criteria, but the score calculation criteria vary from the financial…
Descriptors: Classification, Artificial Intelligence, Prediction, Decision Making
Finch, Holmes – Applied Measurement in Education, 2022
Much research has been devoted to identification of differential item functioning (DIF), which occurs when the item responses for individuals from two groups differ after they are conditioned on the latent trait being measured by the scale. There has been less work examining differential step functioning (DSF), which is present for polytomous…
Descriptors: Comparative Analysis, Item Response Theory, Item Analysis, Simulation
Zhang, Yanhui – Advances in Language and Literary Studies, 2020
This paper takes a system dynamic approach to study homogeneous texts where the dynamics of the lexical richness of such texts over time are of the focal concern. It is hypothesized that the progress of the lexical complexity is driven by how far away this process is from the maximum level of complexity, while is subject to the fluctuations due to…
Descriptors: Difficulty Level, Models, Validity, Language Research
Candace Walkington; Mitchell J. Nathan; Min Wang; Kelsey Schenck – Grantee Submission, 2022
Theories of grounded and embodied cognition offer a range of accounts of how reasoning and body-based processes are related to each other. To advance theories of grounded and embodied cognition, we explore the "cognitive relevance" of particular body states to associated math concepts. We test competing models of action-cognition…
Descriptors: Thinking Skills, Mathematics Skills, Cognitive Processes, Models
Candace Walkington; Mitchell J. Nathan; Min Wang; Kelsey Schenck – Cognitive Science, 2022
Theories of grounded and embodied cognition offer a range of accounts of how reasoning and body-based processes are related to each other. To advance theories of grounded and embodied cognition, we explore the "cognitive relevance" of particular body states to associated math concepts. We test competing models of action-cognition…
Descriptors: Thinking Skills, Mathematics Skills, Cognitive Processes, Models
Merkle, E. C.; Furr, D.; Rabe-Hesketh, S. – Grantee Submission, 2019
Typical Bayesian methods for models with latent variables (or random effects) involve directly sampling the latent variables along with the model parameters. In high-level software code for model definitions (using, e.g., BUGS, JAGS, Stan), the likelihood is therefore specified as conditional on the latent variables. This can lead researchers to…
Descriptors: Bayesian Statistics, Comparative Analysis, Computer Software, Models
Monica Yin-Chen Li – ProQuest LLC, 2021
There is a general consensus in theories of human speech recognition that humans engage in predictive processing during online speech processing. There are also claims that predictive processing indicates the operation of a predictive coding (PC) mechanism (Rao & Ballard, 1999). Formally, PC is a generative model where top-down signals consist…
Descriptors: Audio Equipment, Speech Communication, Error Patterns, Artificial Intelligence
Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Interactive Learning Environments, 2024
This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined 1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction and 2)…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
Sonia, Allison N.; O'Brien, Edward J. – Discourse Processes: A Multidisciplinary Journal, 2021
The coherence threshold marks the point at which a reader has gained a sufficient comprehension level to move on in a text. Previous research has demonstrated that the readers' coherence threshold can be manipulated by increasing or decreasing task demands. The present experiments examined a manipulation of the coherence threshold within the text…
Descriptors: Reading Comprehension, Difficulty Level, Comparative Analysis, Reading Rate
Lúcio, Patrícia Silva; Vandekerckhove, Joachim; Polanczyk, Guilherme V.; Cogo-Moreira, Hugo – Journal of Psychoeducational Assessment, 2021
The present study compares the fit of two- and three-parameter logistic (2PL and 3PL) models of item response theory in the performance of preschool children on the Raven's Colored Progressive Matrices. The test of Raven is widely used for evaluating nonverbal intelligence of factor g. Studies comparing models with real data are scarce on the…
Descriptors: Guessing (Tests), Item Response Theory, Test Validity, Preschool Children
Jönsson, Anders; Balan, Andreia – Practical Assessment, Research & Evaluation, 2018
Research on teachers' grading has shown that there is great variability among teachers regarding both the process and product of grading, resulting in low comparability and issues of inequality when using grades for selection purposes. Despite this situation, not much is known about the merits or disadvantages of different models for grading. In…
Descriptors: Grading, Models, Reliability, Validity
Xu, Tianxi; Qian, Xueqin; Rifenbark, Graham G.; Shogren, Karrie A.; Hagiwara, Mayumi – Intellectual and Developmental Disabilities, 2022
This study explores the psychometric properties of "Self-Determination Inventory: Student Report" (SDI:SR) in students with intellectual and developmental disabilities (IDD) and without disabilities in China. The paper-and-pencil version of SDI:SR Chinese Translation (SDI:SR Chinese) was used to explore self-determination across students…
Descriptors: Foreign Countries, Psychometrics, Self Determination, Intellectual Disability
Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Grantee Submission, 2023
This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction; and…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
von Davier, Matthias; Khorramdel, Lale; He, Qiwei; Shin, Hyo Jeong; Chen, Haiwen – Journal of Educational and Behavioral Statistics, 2019
International large-scale assessments (ILSAs) transitioned from paper-based assessments to computer-based assessments (CBAs) facilitating the use of new item types and more effective data collection tools. This allows implementation of more complex test designs and to collect process and response time (RT) data. These new data types can be used to…
Descriptors: International Assessment, Computer Assisted Testing, Psychometrics, Item Response Theory