ProcData: An R Package for Process Data Analysis
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| Název: | ProcData: An R Package for Process Data Analysis |
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| Autoři: | Tang, Xueying, Zhang, Susu, Wang, Zhi, Liu, Jingchen, Ying, Zhiliang |
| Přispěvatelé: | University of Arizona |
| Zdroj: | Psychometrika |
| Informace o vydavateli: | Springer |
| Rok vydání: | 2021 |
| Sbírka: | The University of Arizona: UA Campus Repository |
| Témata: | autoencoder, multidimensional scaling, process data analysis, sequence model |
| Popis: | Process data refer to data recorded in log files of computer-based items. These data, represented as timestamped action sequences, keep track of respondents’ response problem-solving behaviors. Process data analysis aims at enhancing educational assessment accuracy and serving other assessment purposes by utilizing the rich information contained in response processes. The R package ProcData presented in this article is designed to provide tools for inspecting, processing, and analyzing process data. We define an S3 class ‘proc’ for organizing process data and extend generic methods summary and print for ‘proc’. Feature extraction methods for process data are implemented in the package for compressing information in the irregular response processes into regular numeric vectors. ProcData also provides functions for making predictions from neural-network-based sequence models. In addition, a real dataset of response processes from the climate control item in the 2012 Programme for International Student Assessment is included in the package. © 2021, The Psychometric Society. ; National Science Foundation ; 12 month embargo; published: 11 August 2021 ; This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu. |
| Druh dokumentu: | article in journal/newspaper |
| Jazyk: | English |
| Relation: | Tang, X., Zhang, S., Wang, Z., Liu, J., & Ying, Z. (2021). ProcData: An R Package for Process Data Analysis. Psychometrika.; http://hdl.handle.net/10150/661426; Psychometrika; 9798 |
| DOI: | 10.1007/s11336-021-09798-7 |
| Dostupnost: | http://hdl.handle.net/10150/661426 https://doi.org/10.1007/s11336-021-09798-7 |
| Rights: | © 2021 The Psychometric Society ; http://rightsstatements.org/vocab/InC/1.0/ |
| Přístupové číslo: | edsbas.D8BAFCB0 |
| Databáze: | BASE |
Nájsť tento článok vo Web of Science | Abstrakt: | Process data refer to data recorded in log files of computer-based items. These data, represented as timestamped action sequences, keep track of respondents’ response problem-solving behaviors. Process data analysis aims at enhancing educational assessment accuracy and serving other assessment purposes by utilizing the rich information contained in response processes. The R package ProcData presented in this article is designed to provide tools for inspecting, processing, and analyzing process data. We define an S3 class ‘proc’ for organizing process data and extend generic methods summary and print for ‘proc’. Feature extraction methods for process data are implemented in the package for compressing information in the irregular response processes into regular numeric vectors. ProcData also provides functions for making predictions from neural-network-based sequence models. In addition, a real dataset of response processes from the climate control item in the 2012 Programme for International Student Assessment is included in the package. © 2021, The Psychometric Society. ; National Science Foundation ; 12 month embargo; published: 11 August 2021 ; This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu. |
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| DOI: | 10.1007/s11336-021-09798-7 |