Conference Paper

Model-based Measurement of Human-Computer Interaction in Mobile Multimodal Environments

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Abstract

The complexity in developing and evaluating user interfaces has been extremely increased in the last few years, because more and more devices offer capabilities for multimodal interaction. This applies in particular to mobile devices like smartphones and tablet computers. An existing parameter set, aimed at describing aspects of various modalities, was extended and modified to obtain a formal, seamless and generic model of multimodal interaction. This new model is used for run-time and offline analysis of multimodal human-computer interaction. As proof of concept we also developed the Android HCI Extractor. This tool is used to quantify multimodal interaction within Android devices, and to create instances of the proposed model for further analysis and live decision. An example of this tool running on a real application is also described.

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... The proposed design is based on PALADIN [137,139], a model resulted from a joint eort between the Cátedra SAES [39] and the Telekom Innovation Laboratories [206]. This model was described in detail in Chapter 5. ...
... As said above, this work is based on PALADIN [137]. This multimodal interaction model was previously described in Chapter 5, and briey summarized in this subsection. ...
... The following three approaches were selected for the comparison for the reasons described next. PALADIN [137], because it proposes an interaction representation model, and because it is the model in which CARIM is based on. CUE-model [127], because it proposes a model of user experience concerning the relation between interaction characteristics, emotional reactions and the perceived usability and system aesthetics quality. ...
Thesis
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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
... To collect interaction and context parameters and use them to fill the model instances we propose using the AHE11. This open-source tool was developed for this work based on the Android HCI Extractor (Mateo Navarro, 2011) and can can be downloaded from Mateo Navarro (2013). It is aimed at collecting different interaction and context data automatically by using built-in device capabilities. ...
... To implement questionnaires we also developed the Generic Quest Library (GQL8) for Android, that is available also at Mateo Navarro (2013). This open-source tool automatically generates and displays questionnaires from a very simple JSON (Crockford, 2006) specification. ...
... The IF provides access to such instance during interaction for run-time analysis, or once the interaction is finished for off-line analysis. The open-source implementation of this framework is also available at Mateo Navarro (2013). Figure 4 depicts a typical instantiation scenario for CARIM, similar to the described later in the Experiment section. ...
Article
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.
... El diseño que proponemos en este trabajo está basado en PALADIN [16,17,18], un modelo destinado a cuantificar y describir de forma dinámica (i.e., paso a paso) el proceso de interacción en entornos multimodales. ...
Article
Full-text available
Este artículo describe un nuevo enfoque para modelar la calidad de la experiencia de los usuarios (QoE) en entornos móviles. El modelo presentado tiene el nombre de CARIM, e intenta dar respuesta a las siguientes preguntas: ¿cómo se puede medir la QoE en entornos móviles a partir del análisis de la interacción usuario-sistema? ¿cómo se pueden comparar y contrastar diferentes medidas de QoE? Para ello, CARIM utiliza un conjunto de parámetros con los que describe, paso a paso, la interacción entre el usuario y el sistema, el contexto en el cual se produce esta interacción, y el nivel de calidad percibido por los usuarios. Estos parámetros se estructuran dentro de un modelo, lo que proporciona (1) una representación común de cómo transcurre el proceso de interacción en diferentes entornos móviles y (2) una base para calcular la QoE automáticamente así como para comprar diferentes registros de interacción. CARIM es un modelo en tiempo real que permite el análisis dinámico de la interacción, así como la toma de decisiones basadas en un cierto nivel de QoE en tiempo de ejecución. Esto es utilizado por ciertas aplicaciones durante la ejecución para adaptarse y así proporcionar una mejor experiencia a los usuarios. A modo de conclusión, CARIM proporciona un criterio unificado con el cual calcular, analizar y comparar la QoE en sistemas móviles de distinta naturaleza.
... inference processes. The proposed design is based on PAL-ADIN[16,17,18], a model aimed at quantifying interaction at run-time in multimodal contexts. This work was a result of a joint effort between the Cátedra SAES[4] and the Telekom Innovation Laboratories[22]. ...
Conference Paper
Full-text available
This paper describes a novel approach to model users quality of experience (QoE) in mobile environments. A new model is presented to address the open questions of how to extract QoE from users interaction in mobile scenarios, and how to compare different QoE records to each other. This model establishes a set of parameters to dynamically describe the interaction between users and the system, the context in which it is performed and the quality perceived by the user. It provides a uniform representation of the interaction in mobile contexts, helping user-analysis applications to deter- mine QoE and allowing the comparison between different QoE records. Its run-time nature also allows to make QoE- based decisions in real-time, enabling applications to adapt themselves and provide a better experience to users. result, the proposed model provides unified criteria for the inference and analysis of QoE in mobile scenarios.
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