A Rasch Model and Rating System for Continuous Responses Collected in Large-Scale Learning Systems
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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2020-12-01
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| Series: | Frontiers in Psychology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyg.2020.500039/full |
| _version_ | 1818360420814028800 |
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| author | Benjamin Deonovic Maria Bolsinova Timo Bechger Gunter Maris Gunter Maris |
| author_facet | Benjamin Deonovic Maria Bolsinova Timo Bechger Gunter Maris Gunter Maris |
| author_sort | Benjamin Deonovic |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-13T21:00:31Z |
| format | Article |
| id | doaj.art-aa3a0f28587941359633c68280943aab |
| institution | Directory Open Access Journal |
| issn | 1664-1078 |
| language | English |
| last_indexed | 2024-12-13T21:00:31Z |
| publishDate | 2020-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychology |
| spelling | doaj.art-aa3a0f28587941359633c68280943aab2022-12-21T23:31:36ZengFrontiers Media S.A.Frontiers in Psychology1664-10782020-12-011110.3389/fpsyg.2020.500039500039A Rasch Model and Rating System for Continuous Responses Collected in Large-Scale Learning SystemsBenjamin Deonovic0Maria Bolsinova1Timo Bechger2Gunter Maris3Gunter Maris4ACT, Inc., Iowa City, IA, United StatesDepartment of Methodology and Statistics, Tilburg University, Tilburg, NetherlandsACT, Inc., Amsterdam, NetherlandsACT, Inc., Amsterdam, NetherlandsDepartment of Psychological Methods, University of Amsterdam, Amsterdam, NetherlandsAn 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.https://www.frontiersin.org/articles/10.3389/fpsyg.2020.500039/fullRasch modellongitudinal data analysisrating systemitem response theory (IRT)learning and assessment systemcontinuous response measurement |
| spellingShingle | Benjamin Deonovic Maria Bolsinova Timo Bechger Gunter Maris Gunter Maris A Rasch Model and Rating System for Continuous Responses Collected in Large-Scale Learning Systems Frontiers in Psychology Rasch model longitudinal data analysis rating system item response theory (IRT) learning and assessment system continuous response measurement |
| title | A Rasch Model and Rating System for Continuous Responses Collected in Large-Scale Learning Systems |
| title_full | A Rasch Model and Rating System for Continuous Responses Collected in Large-Scale Learning Systems |
| title_fullStr | A Rasch Model and Rating System for Continuous Responses Collected in Large-Scale Learning Systems |
| title_full_unstemmed | A Rasch Model and Rating System for Continuous Responses Collected in Large-Scale Learning Systems |
| title_short | A Rasch Model and Rating System for Continuous Responses Collected in Large-Scale Learning Systems |
| title_sort | rasch model and rating system for continuous responses collected in large scale learning systems |
| topic | Rasch model longitudinal data analysis rating system item response theory (IRT) learning and assessment system continuous response measurement |
| url | https://www.frontiersin.org/articles/10.3389/fpsyg.2020.500039/full |
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