Article

A Context-Aware Interaction Model for the Analysis of Users’ QoE in Mobile Environments

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Abstract

This paper describes a novel approach to model the quality of experience (QoE) of users in mobile environments. The Context-Aware and Ratings Interaction Model (CARIM) addresses the open questions of how to quantify user experiences from the analysis of interaction in mobile scenarios, and how to compare different QoE records to each other. A set of parameters are used to dynamically describe the interaction between the user and the system, the context in which it is performed and the perceived quality of users. CARIM structures these parameters into a uniform representation, supporting the dynamic analysis of interaction to determine QoE of users and enabling the comparison between different interaction records. Its run-time nature allows applications to make context- and QoE-based decisions in real-time to adapt themselves, and thus provide a better experience to users. As a result, CARIM provides unified criteria for the inference and analysis of QoE in mobile scenarios. Its design and implementation can be integrated (and easily extended if needed) into many different development environments. An experiment with real users comparing two different interaction designs and validating user behavior hypotheses proved the effectiveness of applying CARIM for the assessment of QoE in mobile applications.

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... Snowballed source Year Jiang et al. [22] Yongfeng et al. [78] 2009 Lahami et al. [79] 2012 Merdes et al. [23] Lahami et al. [80] 2012 Ryan and Gonsalves [24] Navarro et al. [81] 2014 Hummel et al. [82] 2009 Satoh [25] Chan et al. [83] 2006 Navarro et al. [81] 2014 Püschel et al. [84] 2012 Wang et al. [28] Lian et al. [85] 2014 Yang et al. [29] 2014 Wang and Chan [26]. ...
... Snowballed source Year Jiang et al. [22] Yongfeng et al. [78] 2009 Lahami et al. [79] 2012 Merdes et al. [23] Lahami et al. [80] 2012 Ryan and Gonsalves [24] Navarro et al. [81] 2014 Hummel et al. [82] 2009 Satoh [25] Chan et al. [83] 2006 Navarro et al. [81] 2014 Püschel et al. [84] 2012 Wang et al. [28] Lian et al. [85] 2014 Yang et al. [29] 2014 Wang and Chan [26]. ...
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1 Introduction 1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.1.1 Human-Computer Interaction . . . . . . . . . . . . . . . . . . . . 2 1.1.2 Software Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.1.3 Data Verification . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.1.4 Software Usability . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 1.1.5 Quality of Experience . . . . . . . . . . . . . . . . . . . . . . . . . 10 Enhancing Software Quality . . . . . . . . . . . . . . . . . . . . . . . . . . 11 1.2.1 Block 1: Achieving Quality in Interaction Components Separately . 12 1.2.2 Block 2: Achieving Quality of User-System Interaction as a Whole . 14 1.3 Goals of this PhD Thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 1.4 Publications Related to this PhD Thesis . . . . . . . . . . . . . . . . . . . . 19 1.5 Software Contributions of this PhD Thesis . . . . . . . . . . . . . . . . . . 22 1.5.1 OHT: Open HMI Tester . . . . . . . . . . . . . . . . . . . . . . . . 23 1.5.2 S-DAVER: Script-based Data Verification . . . . . . . . . . . . . . 24 1.5.3 PALADIN: Practice-oriented Analysis and Description of Multi-modal Interaction . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 CARIM: Context-Aware and Ratings Interaction Metamodel . . . . 25 1.6 Summary of Research Goals, Publications, and Software Contributions . . 25 1.7 Context of this PhD Thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 1.8 Structure of this PhD Thesis . . . . . . . . . . . . . . . . . . . . . . . . . . 27 2 Related Work 2.1 Group 1: Approaches Assuring Quality of a Particular Interaction Component 30 2.2 Validation of Software Output . . . . . . . . . . . . . . . . . . . . 30 2.1.1.1 Methods Using a Complete Model of the GUI . . . . . . 31 2.1.1.2 Methods Using a Partial Model of the GUI . . . . . . . . 32 2.1.1.3 Methods Based on GUI Interaction . . . . . . . . . . . . 32 Validation of User Input . . . . . . . . . . . . . . . . . . . . . . . . 33 2.1.2.1 Data Verification Using Formal Logic . . . . . . . . . . . 34 2.1.2.2 Data Verification Using Formal Property Monitors . . . . 35 2.1.2.3 Data Verification in GUIs and in the Web . . . . . . . . . 36 Group 2: Approaches Describing and Analyzing User-System Interaction as a Whole . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 2.2.1 Analysis of User-System Interaction . . . . . . . . . . . . . . . . . 37 2.2.1.1 Analysis for the Development of Multimodal Systems . . 37 2.2.1.2 Evaluation of Multimodal Interaction . . . . . . . . . . . 41 2.2.1.3 Evaluation of User Experiences . . . . . . . . . . . . . . 44 Analysis of Subjective Data of Users . . . . . . . . . . . . . . . . . 45 2.2.2.1 User Ratings Collection . . . . . . . . . . . . . . . . . . 45 2.2.2.2 Users Mood and Attitude Measurement . . . . . . . . . . 47 Analysis of Interaction Context . . . . . . . . . . . . . . . . . . . . 49 2.2.3.1 Interaction Context Factors Analysis . . . . . . . . . . . 49 2.2.3.2 Interaction Context Modeling . . . . . . . . . . . . . . . 50 3 Evaluating Quality of System Output 3.1 Introduction and Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . 54 3.2 GUI Testing Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 3.3 Preliminary Considerations for the Design of a GUI Testing Architecture . 57 3.3.1 Architecture Actors . . . . . . . . . . . . . . . . . . . . . . . . . . 57 3.3.2 Organization of the Test Cases . . . . . . . . . . . . . . . . . . . . 57 3.3.3 Interaction and Control Events . . . . . . . . . . . . . . . . . . . . 58 The OHT Architecture Design . . . . . . . . . . . . . . . . . . . . . . . . . 58 3.4.1 The HMI Tester Module Architecture . . . . . . . . . . . . . . . . 60 3.4.2 The Preload Module Architecture . . . . . . . . . . . . . . . . . . . 61 3.4.3 The Event Capture Process . . . . . . . . . . . . . . . . . . . . . . 63 3.4.4 The Event Playback Process . . . . . . . . . . . . . . . . . . . . . . 64 The OHT Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 3.5.1 Implementation of Generic and Final Functionality . . . . . . . . . 66 3.5.1.1 Generic Data Model . . . . . . . . . . . . . . . . . . . . 66 3.5.1.2 Generic Recording and Playback Processes . . . . . . . . 66 Implementation of Specific and Adaptable Functionality . . . . . . 67 3.5.2.1 Using the DataModelAdapter . . . . . . . . . . . . . . . 68 3.5.2.2 The Preloading Process . . . . . . . . . . . . . . . . . . . 68 3.5.2.3 Adapting the GUI Event Recording and Playback Processes 69 3.7 Technical Details About the OHT Implementation . . . . . . . . . 70 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 3.6.1 Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 3.6.2 The Test Case Generation Process . . . . . . . . . . . . . . . . . . 73 3.6.3 Validation of Software Response . . . . . . . . . . . . . . . . . . . 74 3.6.4 Tolerance to Modifications, Robustness, and Scalability . . . . . . . 75 3.6.5 Performance Analysis . . . . . . . . . . . . . . . . . . . . . . . . . 76 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 4 Evaluating Quality of Users Input 4.1 Introduction and Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . 80 4.2 Practical Analysis of Common GUI Data Verification Approaches . . . . . 82 4.3 Monitoring GUI Data at Runtime . . . . . . . . . . . . . . . . . . . . . . . 83 4.4 Verification Rules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 4.4.1 Rule Definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 4.4.2 Using the Rules to Apply Correction . . . . . . . . . . . . . . . . . 87 4.4.3 Rule Arrangement . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 4.4.4 Rule Management . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 4.4.4.1 88 Loading the Rules . . . . . . . . . . . . . . . . . . . . . xviiContents 4.4.4.2 Evolution of the Rules and the GUI . . . . . . . . . . . . 89 Correctness and Consistency of the Rules . . . . . . . . . . . . . . 90 4.5 The Verification Feedback . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 4.6 S-DAVER Architecture Design . . . . . . . . . . . . . . . . . . . . . . . . . 92 4.6.1 Architecture Details . . . . . . . . . . . . . . . . . . . . . . . . . . 92 4.6.2 Architecture Adaptation . . . . . . . . . . . . . . . . . . . . . . . . 94 4.7 S-DAVER Implementation and Integration Considerations . . . . . . . . . 95 4.8 Practical Use Cases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 4.8.1 Integration, Configuration, and Deployment of S-DAVER . . . . . 99 4.8.2 Defining the Rules in Qt Bitcoin Trader . . . . . . . . . . . . . . . 100 4.8.3 Defining the Rules in Transmission . . . . . . . . . . . . . . . . . . 103 4.8.4 Development and Verification Experience with S-DAVER . . . . . 106 4.9 Performance Analysis of S-DAVER . . . . . . . . . . . . . . . . . . . . . . 106 4.10 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 4.10.1 A Lightweight Data Verification Approach . . . . . . . . . . . . . 108 4.10.2 The S-DAVER Open-Source Implementation . . . . . . . . . . . . . 110 4.10.3 S-DAVER Compared with Other Verification Approaches . . . . . . 111 4.11 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114 5 Modeling and Evaluating Quality of Multimodal User-System Interaction 115 5.1 Introduction and Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . 116 5.2 A Model-based Framework to Evaluate Multimodal Interaction . . . . . . . 118 5.2.1 Classification of Dialog Models by Level of Abstraction . . . . . . 119 5.2.2 The Dialog Structure . . . . . . . . . . . . . . . . . . . . . . . . . 120 5.2.3 Using Parameters to Describe Multimodal Interaction . . . . . . . 121 5.2.3.1 Adaptation of Base Parameters . . . . . . . . . . . . . . 121 5.2.3.2 Defining new Modality and Meta-communication Param- eters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122 5.2.3.3 Defining new Parameters for GUI and Gesture Interaction 123 5.2.3.4 Classification of the Multimodal Interaction Parameters . 124 5.3 Design of PALADIN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 5.4 Implementation, Integration, and Usage of PALADIN . . . . . . . . . . . . 129 5.5 Application Use Cases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 5.6 Assessment of PALADIN as an Evaluation Tool . . . . . . . . . . . 132 5.5.1.1 Participants and Material . . . . . . . . . . . . . . . . . 134 5.5.1.2 Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . 136 5.5.1.3 Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . 137 Usage of PALADIN in a User Study . . . . . . . . . . . . . . . . . 140 5.5.2.1 Participants and Material . . . . . . . . . . . . . . . . . 140 5.5.2.2 Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . 144 5.5.2.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 5.6.1 Research Questions . . . . . . . . . . . . . . . . . . . . . . . . . . 146 5.6.2 Practical Application of PALADIN . . . . . . . . . . . . . . . . . . 147 5.6.3 Completeness of PALADIN According to Evaluation Guidelines . . 148 5.6.4 Limitations in Automatic Logging of Interactions Parameters . . . 151 5.7 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 5.8 Parameters Used in PALADIN . . . . . . . . . . . . . . . . . . . . . . . . . 152 6 Modeling and Evaluating Mobile Quality of Experience 163 6.1 Introduction and Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . 164 6.2 Context- and QoE-aware Interaction Analysis . . . . . . . . . . . . . . . . 166 6.2.1 Incorporating Context Information and User Ratings into Interaction Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166 6.2.2 Arranging the Parameters for the Analysis of Mobile Experiences . 168 6.2.3 Using CARIM for QoE Assessment . . . . . . . . . . . . . . . . . . 169 Context Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 6.3.1 Quantifying the Surrounding Context . . . . . . . . . . . . . . . . 170 6.3.2 Arranging Context Parameters into CARIM . . . . . . . . . . . . . 173 User Perceived Quality Parameters . . . . . . . . . . . . . . . . . . . . . . 173 6.4.1 Measuring the Attractiveness of Interaction . . . . . . . . . . . . . 173 6.4.2 Measuring Users Emotional State and Attitude toward Technology Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 6.5 Arranging User Parameters into CARIM . . . . . . . . . . . . . . . 177 CARIM Model Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177 6.5.1 The Base Design: PALADIN . . . . . . . . . . . . . . . . . . . . . 177 6.5.2 The New Proposed Design: CARIM . . . . . . . . . . . . . . . . . 178 6.6 CARIM Model Implementation . . . . . . . . . . . . . . . . . . . . . . . . 181 6.7 Experiment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 6.7.1 Participants and Material . . . . . . . . . . . . . . . . . . . . . . . 183 6.7.2 Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184 6.7.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 6.9 Comparing the Two Interaction Designs for UMU Lander 185 Validating the User Behavior Hypotheses . . . . . . . . . 186 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187 6.8.1 Modeling Mobile Interaction and QoE . . . . . . . . . . . . . . . . 188 6.8.3 CARIM Implementation and Experimental Validation . . . . . . . 190 CARIM Compared with Other Representative Approaches . . . . . 191 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192 7 Conclusions and Further Work 7.2 Conclusions of this PhD Thesis . . . . . . . . . . . . . . . . . . . . . . . . 196 7.1.2 Driving Forces of this PhD Thesis . . . . . . . . . . . . . . . . . . 196 Work and Research in User-System Interaction Assessment . . . . 197 7.1.3 Goals Achieved in this PhD Thesis . . . . . . . . . . . . . . . . . . 200 Future Lines of Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202 Bibliography 205 A List of Acronyms 231
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[presents] an exploration of response organization in fear and anxiety / includes a discussion of how information about physiological mobilization and action are represented in memory, their relationship to semantic knowledge, and a speculation as to their significance in the cognitive processing of emotion / it is argued that psychophysiological responses are integral to the expression of clinical anxiety and that their activation plays a significant role in mediating other syndromal behaviors (PsycINFO Database Record (c) 2012 APA, all rights reserved)
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This study investigated if cognitive skills, mood, attitudes and personality traits influence quality perceptions, modality choice (speech vs. touch), and performance. It was shown that attitudes and mood are related to quality perceptions while performance is linked to personality traits. Modality choice is influenced by attitudes and personality. Cognitive abilities had no effect.
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While multimodal systems are an active research field, there is no agreed-upon set of multimodal interaction parameters, which would allow to quantify the performance of such systems and their underlying modules, and would there for be necessary for a systematic evaluation. In this paper we propose an extension to established parameters describing the interaction with spoken dialog systems [1] in order to be used for multimodal systems. Focussing on the evaluation of a multimodal system, three usage scenarios for these parameters are given.
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Different questionnaires assessing the usability of two multimodal systems and one unimodal system were compared. Each participant (N=21) performed several tasks with each device and was afterwards asked to rate the system by filling out different questionnaires. The results show that standardized questionnaires are applicable only to a limited extent. Despite some concordance, the results differ considerably and thus indicate the need for the development of a valid and reliable questionnaire covering the usability and quality of multimodal systems.
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Quality of Telephone-Based Spoken Dialogue Systems is a systematic overview of assessment, evaluation, and prediction methods for the quality of services such as travel and touristic information, phone-directory and messaging, or telephone-banking services. A new taxonomy of quality-of-service is presented which serves as a tool for classifying assessment and evaluation methods, for planning and interpreting evaluation experiments, and for estimating quality. A broad overview of parameters and evaluation methods is given, both on a system-component level and for a fully integrated system. Three experimental investigations illustrate the relationships between system characteristics and perceived quality. The resulting information is needed in all phases of system specification, design, implementation, and operation. Although Quality of Telephone-Based Spoken Dialogue Systems is written from the perspective of an engineer in telecommunications, it is an invaluable source of information for professionals in signal processing, communication acoustics, computational linguistics, speech and language sciences, human factor design and ergonomics. © 2005 Springer Science + Business Media, Inc. All rights reserved.
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This article presents an approach to Web Engineering which aims to account for context-awareness in a comprehensive and integrated fashion, thus enabling an enhanced adaptation of the application to the end-user. A conceptual model, permitting the combination of a domain ontology with context-relevant parameters and a degree of relevance, is presented. Subsequently, the use of such a model in a Web Engineering process is discussed, including appropriate modeling software, and requirements for a runtime system.
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In order to provide “intimate” and “dynamic” adaptations under Weiser's vision for ubiquitous computing environments, we propose the utilization of context history together with user modeling and machine learning techniques. Our approach supports proactive adaptations by inducing patterns of user behavior. In addition, we support the requirement for enabling the user to receive an explicit and understandable explanation when a proactive adaptation occurs in order to encourage a trust relationship between the user and the context-aware system. In this article, we describe an experiment to examine the feasibility of our approach for supporting proactive adaptations in the domain of an intelligent office environment. The initial results of our experiment are promising and demonstrate how our system could gradually learn the user's preferences for controling his office environment by making inductions from the context history. Based on these initial findings, we believe that context history has a concrete role to play in supporting proactive adaptation in a ubiquitous computing environment.
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Usability testing of software applications developed for mobile devices is an emerging research area that faces a variety of challenges due to unique features of mobile devices, limited bandwidth, unreliability of wireless networks, as well as the changing context (environmental factors). Traditional guidelines and methods used in usability testing of desktop applications may not be directly applicable to a mobile environment. Therefore, it is essential to develop and adopt appropriate research methodologies that can evaluate the usability of mobile applications. The aim of this paper is to analyze and highlight research questions, methodologies, and usability attributes while conducting a usability test for mobile applications. First, the paper provides an overview of existing usability studies and discusses major research questions that have been investigated. Then, it proposes a generic framework for usability testing of mobile applications and provides some suggestions on how to conduct such usability studies.