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Zhang, Mo; Guo, Hongwen; Liu, Xiang – International Educational Data Mining Society, 2021
We present an empirical study on the use of keystroke analytics to capture and understand how writers manage their time and make inferences on how they allocate their cognitive resources during essay writing. The results suggest three distinct longitudinal patterns of writing process that describe how writers approach an essay task in a writing…
Descriptors: Keyboarding (Data Entry), Learning Analytics, Data Collection, Cognitive Processes
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Sinharay, Sandip; Zhang, Mo; Deane, Paul – Applied Measurement in Education, 2019
Analysis of keystroke logging data is of increasing interest, as evident from a substantial amount of recent research on the topic. Some of the research on keystroke logging data has focused on the prediction of essay scores from keystroke logging features, but linear regression is the only prediction method that has been used in this research.…
Descriptors: Scores, Prediction, Writing Processes, Data Analysis
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Choi, Ikkyu; Hao, Jiangang; Deane, Paul; Zhang, Mo – ETS Research Report Series, 2021
"Biometrics" are physical or behavioral human characteristics that can be used to identify a person. It is widely known that keystroke or typing dynamics for short, fixed texts (e.g., passwords) could serve as a behavioral biometric. In this study, we investigate whether keystroke data from essay responses can lead to a reliable…
Descriptors: Accuracy, High Stakes Tests, Writing Tests, Benchmarking
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Zhang, Mo; Deane, Paul – ETS Research Report Series, 2015
In educational measurement contexts, essays have been evaluated and formative feedback has been given based on the end product. In this study, we used a large sample collected from middle school students in the United States to investigate the factor structure of the writing process features gathered from keystroke logs and the association of that…
Descriptors: Middle School Students, Student Writing Models, Writing Processes, Factor Structure