Volume 8 Number 11 (Nov. 2013)
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JSW 2013 Vol.8(11): 2890-2898 ISSN: 1796-217X
doi: 10.4304/jsw.8.11.2890-2898

An Experimental Method Study of User Error Classification in Human-computer Interface

Xiaoli Wu1, 2, Xin Huang1, Ruicong Xu1, Qingwei Yang1
1College of Mechanical and Electrical Engineering, Hohai University, Changzhou 213022, China
2Changzhou Key Laboratory of Digital Manufacturing Technology, Hohai University, Changhzou, China


Abstract—In the paper, we proposed an experimental analysis model of user error and established the error-cognition corresponding relationship according to the error collection-classification method. Through the design of error experiment, various errors in operation interface as well as reasonable and sufficient data were obtained. Based on the repeated experiments and user interviews, we classified errors to extract typical errors according corresponding frequency. According to the cognitive processing, five error types were identified. In the later secondary experiment, we verified the rationality of the error types. The obtained experimental results validated the three basic assumptions proposed before the experiment. Each error can be classified as the identified corresponding error type. In the statistics data, perception confusion is the dominant error type, indicating that operation interface contains understanding deviation. With time limit, error rate was significantly increased. We identified error types in operation interface according to the user error classification experiment method.

Index Terms—User interfaces; User error; Cognition; error classification; Experiment analysis model.

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Cite: Xiaoli Wu, Xin Huang, Ruicong Xu, and Qingwei Yang, "An Experimental Method Study of User Error Classification in Human-computer Interface," Journal of Software vol. 8, no. 11, pp. 2890-2898, 2013.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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