Benchmark Keystroke Biometrics Accuracy from High-Stakes Writing Tasks. Research Report. ETS RR-21-15

Autor/inn/en	Choi, Ikkyu; Hao, Jiangang; Deane, Paul; Zhang, Mo
Titel	Benchmark Keystroke Biometrics Accuracy from High-Stakes Writing Tasks. Research Report. ETS RR-21-15
Quelle	In: ETS Research Report Series, (2021), (13 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2330-8516
Schlagwörter	Accuracy; High Stakes Tests; Writing Tests; Benchmarking; Writing Processes; Word Processing; Essay Tests; Computer Security; Reliability; Measurement Techniques; Error of Measurement; Intervals; Computer Assisted Testing; COVID-19; Pandemics; High School Equivalency Programs; Classification; Learning Analytics + Suchen Sie Ihr Suchwort? Writing test; Schreibtest; Textverarbeitung; Schriftlicher Sprachgebrauch; Computervirus; Computersicherheit; Reliabilität; Messtechnik; Messfehler; Classification system; Klassifikation; Klassifikationssystem
Abstract	"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 biometric measure, with implications for test security and the monitoring of writing fluency and style changes. Based on keystroke data collected from a high-stakes writing testing setting, we established a preliminary biometric benchmark for detecting test-taker identity by using features extracted from their writing process logs. We report a benchmark keystroke biometric accuracy of equal error rate of 4.7% for identifying same versus different individuals on an essay task. In particular, we show that the inclusion of writing process features (e.g., features designed to describe the writing process) in addition to the widely used typing-timing features (e.g., features based on the time intervals between two-letter key sequences) improves the accuracy of the keystroke biometrics. The proposed keystroke biometrics can have important implications for the writing assessments administered through the remotely proctored tests that have been widely adopted during the COVID pandemic. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01