ArticleFrontiers in psychology2020
A Rasch Model and Rating System for Continuous Responses Collected in Large-Scale Learning Systems.
Article in Frontiers in psychology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Multidimensional item response theory models for testlet-based doubly bounded data.Behavior research methods · 2024Article
- The Dirichlet Dual Response Model: An Item Response Model for Continuous Bounded Interval Responses.Psychometrika · 2023Article
- Tracking a multitude of abilities as they develop.The British journal of mathematical and statistical psychology · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
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Abstract
An extension to a rating system for tracking the evolution of parameters over time using continuous variables is introduced. The proposed rating system assumes a distribution for the continuous responses, which is agnostic to the origin of the continuous scores and thus can be used for applications as varied as continuous scores obtained from language testing to scores derived from accuracy and response time from elementary arithmetic learning systems. Large-scale, high-stakes, online, anywhere anytime learning and testing inherently comes with a number of unique problems that require new psychometric solutions. These include (1) the cold start problem, (2) problem of change, and (3) the problem of personalization and adaptation. We outline how our proposed method addresses each of these problems. Three simulations are carried out to demonstrate the utility of the proposed rating system.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.