ProcData: An R Package for Process Data Analysis

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 purpo...

Full description

Saved in:
Bibliographic Details
Published in:Psychometrika Vol. 86; no. 4; pp. 1058 - 1083
Main Authors: Tang, Xueying, Zhang, Susu, Wang, Zhi, Liu, Jingchen, Ying, Zhiliang
Format: Journal Article
Language:English
Published: New York Springer US 01.12.2021
Springer Nature B.V
Subjects:
Application Reviews and Case Studies
Application Reviews and Case Studies (ARCS)
Assessment
Behavioral Science and Psychology
Case Studies
Climate Control
Computers
Data Analysis
Data processing
Discovery Processes
Educational Assessment
Educational Measurement
Educational Technology
Feedback (Response)
Humanities
Humans
Information processing
International Assessment
Item Response Theory
Law
Multidimensional scaling
Networks
Neural networks
Problem Solving
Psychological Patterns
Psychology
Psychometrics
Simulated Environment
Software
Statistical Data
Statistical Theory and Methods
Statistics for Social Sciences
Student Evaluation
Testing and Evaluation
autoencoder
multidimensional scaling
sequence model
process data analysis
ISSN:0033-3123, 1860-0980, 1860-0980
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:0033-3123
1860-0980
1860-0980
DOI:10.1007/s11336-021-09798-7