ACT-R Predictive Model of Korean Text Entry on Touchscreen

Abstract

Objective: The aim of this study is to predict Korean text entry on touchscreens using ACT-R cognitive architecture. Background: Touchscreen application in devices such as satellite navigation devices, PDAs, mobile phones, etc. has been increasing, and the market size is expanding. Accordingly, there is an increasing interest to develop and evaluate the interface to enhance the user experience and increase satisfaction in the touchscreen environment. Method: In this study, Korean text entry performance in the touchscreen environment was analyzed using ACT-R. The ACT-R model considering the characteristics of the Korean language which is composed of vowels and consonants was established. Further, this study analyzed if the prediction of Korean text entry is possible through the ACT-R cognitive model. Results: In the analysis results, no significant difference on performance time between model prediction and empirical data was found. Conclusion:The proposed model can predict the accurate physical movement time as well as cognitive processing time. Application: This study is useful in conducting model-based evaluation on the text entry interface of the touchscreen and enabled quantitative and effective evaluation on the diverse types of Korean text input interfaces through the cognitive models.

Prediction of Human Performance Time to Find Objects on Multi-display Monitors using ACT-R Cognitive Architecture

“…특히, ACT-R은 사람의 행동을 학습 (Anderson & Matessa, 1998), 운전 (Salvucci, 2006) 등과 같은 높은 수준의 인지 과정에서부터 메뉴 선 택 (Min et al, 2010;Lim et al, 2012;St. Amant et al, 2007) Goodale & Milner(1992) …”