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研究生: 樂代義
Yogi Tri Prasetyo
論文名稱: 單向Fitts’ Law任務於滑鼠操作之使用性測量發展
Development of Usability Measures for Computer Mice using One-Directional Fitts’ Law Task
指導教授: 林久翔
Chiu-Hsiang Lin
江行全
Bernard C. Jiang
口試委員: 林希偉
Shi-Woei Lin
石裕川
Yuh-Chuan Shih
孫天龍
Tien-Lung Sun
學位類別: 博士
Doctor
系所名稱: 管理學院 - 工業管理系
Department of Industrial Management
論文出版年: 2019
畢業學年度: 107
語文別: 英文
論文頁數: 89
中文關鍵詞: 費茲法則使用性指向裝置結構方程式模型
外文關鍵詞: Fitts’ Law, usability, pointing device, structural equation modeling
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  • 使用性在使用者經驗中是一個很重要的範疇,因此本研究的目的為以電腦滑鼠為基礎,利用單向式費茨法則作業(Fitts’Law task),進而發展一使用性量測之方法。本研究招募12位受試者,使用5種滑鼠與3種速度於分離式單向性點擊作業,採用為組內設計,移動時間和位置座標資料被用於計算五種人類表現的指標:(1) 平均完成時間(2) 決定係數(3)準確度(4)Cp(5)總體績效指標(throughput)。主觀偏好基於ISO 9241-9的語意差別量表來建構,並通過成對比較分析用戶偏好以評估使用性。使用性單因子相依變異數分析結果顯示滑鼠的類型和速度對於平均完成時間、決定係數有顯著的效果,此外,速度被發現對於Cp有邊緣性顯著,當滑鼠的種類對總體績效指標(throughput)達顯著時。逐步多元回歸分析顯示平均完成時間和Cp是預測使用性的兩個重要的人類績效指標。最後,結構方程式模型基於ISO 9241-11的使用性維度來建構,並應用結構方程模型得出使用性與主觀偏好之間的因果關係。這些結果有助於辨認出影響主觀滿意度的重要人類績效指標。最後,綜合本研究及其他相關研究的發現,提出一個針對指向裝置的使用性量測之準則。

    產業關聯:這個研究利用單一指向點擊作業和主觀偏好並藉由成對比較和語意差異尺度,發展一電腦滑鼠之使用性量測方法。以ISO 9241-9為基礎,選用的人類績效指標和主觀偏好導出的因果關係將有助於輸入裝置的評估和設計。


    Usability is one of the important dimensions of user experience (UX). The purpose of this study was to develop usability measures based on computer mice by utilizing one-directional Fitts’ Law task. Twelve participants were recruited to perform discrete one-directional tapping task using within-subject design with five different mice and three different speeds. Movement time and coordinate position data were used to compute five human performance measures: 1) average completion time 2) coefficient of determination (R2) 3) accuracy 4) Cp 5) throughput. Subjective assessment was evaluated by utilizing semantic differential scale based on ISO 9241-9. Usability was evaluated by applying pairwise comparison to analyze the user preference. Repeated measures analysis of variance (RM-ANOVA) results revealed that the type of mouse and speed had significant effects on average completion time and coefficient of determination (R2). In addition, speed was found had a borderline statistically significant effect on Cp while type of mouse was found had a significant effect on throughput. Stepwise multiple regression showed that average completion time and Cp were two significant human performance measures for predicting usability. Finally, structural equation modeling (SEM) was applied to derive the causal relationship between usability and subjective assessment. The SEM was build based on the proposed usability dimensions supported by ISO 9241-11. These results can help to identify the significant human performance measures and subjective assessment affecting usability. In the end, some recommendations are proposed for developing usability measures that adopt the current study’s research findings.

    Relevance to industry: This study illustrates the comprehensive usability analysis of computer mice by utilizing a one-directional tapping task. The causal relationship between selected human performance measures and subjective assessment based on ISO 9241-9 should benefit input devices assessment and design.  

    Table of Contents Cover Page i 摘要 vi Abstract vii Acknowledgements viiiii Table of Contents x List of Tables xii List of Figures xiv List of Equations xvi CHAPTER 1 INTRODUCTION 1 1.1 Background 1 1.2 Study Objectives 3 1.3 Study Framework – Usability Dimension 4 CHAPTER 2 LITERATURE REVIEW 8 2.1 Fitts’ Law and its Variations 8 2.2 Performance Measures based on Fitts’ Law 10 2.3 Potential Movement Variance Measures 12 2.4 Structural Equation Modeling (SEM) 12 CHAPTER 3 METHODOLOGY 15 3.1 Participants 15 3.2 Apparatus and Stimuli 15 3.3 Independent Variables 16 3.4 Dependent Variabels 19 3.5 Index of Difficulty 19 3.6 Procedures 20 3.7 Human Performance Measures 24 3.8 Semantic Differential Scale 26 3.9 Pairwise Comparison 28 3.10 Data Processing of Human Performance Measures 29 3.11 Stepwise Muliple Regression 29 3.12 Structural Equation Modeling 29 3.13 Circular Error 31 CHAPTER 4 RESULTS 33 4.1 Average Completion Time 33 4.2 Coefficient of Determination (R2) 36 4.3 Accuracy 39 4.4 Cp 40 4.5 Throughput 42 4.6 Pairwise Comparison 45 4.7 Stepwise Multiple Regression 46 4.8 Structural Equation Modeling 49 CHAPTER 5 DISCUSSION 53 5.1 Human Performance Measures 53 5.2 Subjective Measures 55 CHAPTER 6 CONCLUSION AND FUTURE RESEARCH 58 REFERENCES 60 APPENDIX A – Personal Information of Participants 66 Appendix B – Task Questionnaire 67 Curriculum Vitae 70

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