KLM Form Analyzer: Automated Evaluation of Web Form Filling Tasks Using Human Performance Models

被引：0

作者：

Katsanos, Christos ^{[1
]}

Karousos, Nikos ^{[1
]}

Tselios, Nikolaos ^{[2
]}

Xenos, Michalis ^{[1
]}

Avouris, Nikolaos ^{[2
]}

机构：

[1] Hellenic Open Univ, Parodos Aristotelous 18, Patras 26335, Achaia, Greece

[2] Univ Patras, GR-26500 Patras, Greece

来源：

HUMAN-COMPUTER INTERACTION - INTERACT 2013, PT II | 2013年 / 8118卷

关键词：

Web form design; task efficiency; user performance time; automated tool; human performance models;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Filling forms is a common and frequent task in web interaction. Therefore, designing web forms that enhance users' efficiency is an important task. This paper presents a tool entitled KLM Form Analyzer ( KLM-FA) that enables effortless predictions of execution times of web form filling tasks. To this end, the tool employs established models of human performance, namely the Keystroke Level Model and optionally the Fitts' law. KLM-FA can support various evaluation scenarios, both in a formative and summative context, and according to different interaction strategies or modeled users' characteristics. A study investigated the accuracy of KLM-FA predictions by comparing them to participants' execution times for six form filling tasks in popular social networking websites. The tool produced highly accurate predictions (89.1% agreement with user data) in an efficient manner.

引用

页码：530 / 537

页数：8

共 36 条

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