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Analysis of Process Data of PISA 2012 Computer-Based Problem Solving: Application of the Modified Multilevel Mixture IRT Model
Computer-based assessments provide new insights into cognitive processes related to task completion that cannot be easily observed using paper-based instruments. In particular, such new insights may be revealed by time-tamped actions, which are recorded as computer log-files in the assessments. Thes...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6085588/ https://www.ncbi.nlm.nih.gov/pubmed/30123171 http://dx.doi.org/10.3389/fpsyg.2018.01372 |
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author | Liu, Hongyun Liu, Yue Li, Meijuan |
author_facet | Liu, Hongyun Liu, Yue Li, Meijuan |
author_sort | Liu, Hongyun |
collection | PubMed |
description | Computer-based assessments provide new insights into cognitive processes related to task completion that cannot be easily observed using paper-based instruments. In particular, such new insights may be revealed by time-tamped actions, which are recorded as computer log-files in the assessments. These actions, nested in individual level, are logically interconnected. This interdependency can be modeled straightforwardly in a multi-level framework. This study draws on process data recorded in one of complex problem-solving tasks (Traffic CP007Q02) in Program for International Student Assessment (PISA) 2012 and proposes a modified Multilevel Mixture IRT model (MMixIRT) to explore the problem-solving strategies. It was found that the model can not only explore whether the latent classes differ in their response strategies at the process level, but provide ability estimates at both the process level and the student level. The two level abilities are different across latent classes, and they are related to operational variables such as the number of resets or clicks. The proposed method may allow for better exploration of students' specific strategies for solving a problem, and the strengths and weaknesses of the strategies. Such findings may be further used to design targeted instructional interventions. |
format | Online Article Text |
id | pubmed-6085588 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-60855882018-08-17 Analysis of Process Data of PISA 2012 Computer-Based Problem Solving: Application of the Modified Multilevel Mixture IRT Model Liu, Hongyun Liu, Yue Li, Meijuan Front Psychol Psychology Computer-based assessments provide new insights into cognitive processes related to task completion that cannot be easily observed using paper-based instruments. In particular, such new insights may be revealed by time-tamped actions, which are recorded as computer log-files in the assessments. These actions, nested in individual level, are logically interconnected. This interdependency can be modeled straightforwardly in a multi-level framework. This study draws on process data recorded in one of complex problem-solving tasks (Traffic CP007Q02) in Program for International Student Assessment (PISA) 2012 and proposes a modified Multilevel Mixture IRT model (MMixIRT) to explore the problem-solving strategies. It was found that the model can not only explore whether the latent classes differ in their response strategies at the process level, but provide ability estimates at both the process level and the student level. The two level abilities are different across latent classes, and they are related to operational variables such as the number of resets or clicks. The proposed method may allow for better exploration of students' specific strategies for solving a problem, and the strengths and weaknesses of the strategies. Such findings may be further used to design targeted instructional interventions. Frontiers Media S.A. 2018-08-03 /pmc/articles/PMC6085588/ /pubmed/30123171 http://dx.doi.org/10.3389/fpsyg.2018.01372 Text en Copyright © 2018 Liu, Liu and Li. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychology Liu, Hongyun Liu, Yue Li, Meijuan Analysis of Process Data of PISA 2012 Computer-Based Problem Solving: Application of the Modified Multilevel Mixture IRT Model |
title | Analysis of Process Data of PISA 2012 Computer-Based Problem Solving: Application of the Modified Multilevel Mixture IRT Model |
title_full | Analysis of Process Data of PISA 2012 Computer-Based Problem Solving: Application of the Modified Multilevel Mixture IRT Model |
title_fullStr | Analysis of Process Data of PISA 2012 Computer-Based Problem Solving: Application of the Modified Multilevel Mixture IRT Model |
title_full_unstemmed | Analysis of Process Data of PISA 2012 Computer-Based Problem Solving: Application of the Modified Multilevel Mixture IRT Model |
title_short | Analysis of Process Data of PISA 2012 Computer-Based Problem Solving: Application of the Modified Multilevel Mixture IRT Model |
title_sort | analysis of process data of pisa 2012 computer-based problem solving: application of the modified multilevel mixture irt model |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6085588/ https://www.ncbi.nlm.nih.gov/pubmed/30123171 http://dx.doi.org/10.3389/fpsyg.2018.01372 |
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