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Impact of Technological Support on the Workload of Software Prototyping

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Impact of Technological Support on the Workload of Software Prototyping Impact of Technological Support on the Workload of Software Prototyping Von der Fakultät für Mathematik, Informatik und Naturwissenschaften der RWTH Aachen University zur Erlangung des akademischen Grades einer Doktorin der Naturwissenschaften genehmigte Dissertation vorgelegt von Sarah Suleri, M.Sc. aus Toba Tek Singh, Pakistan Berichter: Prof. Dr. Matthias Jarke Prof. Dr. Wolfgang Prinz Prof. Dr. Ulrich J. Schröder Tag der mündlichen Prüfung: 18.02.2021 Diese Dissertation ist auf den Internetseiten der Universitätsbibliothek verfügbar. Sarah Suleri: Impact of Technological Support on the Workload of Software Prototyping, Doctoral Dissertation, © December 2020 Eidesstattliche Erklärung Declaration of Authorship I, Sarah Suleri declare that this thesis and the work presented in it are my own and has been generated by me as the result of my own original research. Hiermit erkläre ich an Eides statt / I do solemnely swear that: 1. This work was done wholly or mainly while in candidature for the doctoral degree at this faculty and university; 2. Where any part of this thesis has previously been submitted for a degree or any other qualification at this university or any other institution, this has been clearly stated; 3. Where I have consulted the published work of others or myself, this is always clearly attributed; 4. Where I have quoted from the work of others or myself, the source is always given. This thesis is entirely my own work, with the exception of such quotations; 5. I have acknowledged all major sources of assistance; 6. Where the thesis is based on work done by myself jointly with others, I have made clear exactly what was done by others and what I have contributed myself; 7. Parts of this work have been published before as: Suleri, S., Sermuga Pandian, V. P., Shishkovets, S., & Jarke, M. (2019, May). Eve: A sketch-based software prototyping workbench. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems. Suleri, S., Kipi, N., Tran, L. C., & Jarke, M. (2019, October). UI Design Pattern-driven Rapid Prototyping for Agile Development of Mobile Applications. In Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services. Suleri, S., Hajimiri, Y., & Jarke, M. (2020, October). Impact of using UI Design Patterns on the Workload of Rapid Prototyping of Smartphone Applications: An Experimental Study. In Proceedings of the 22nd International Conference on Human-Computer Interaction with Mobile Devices and Services. Sermuga Pandian, V. P., Suleri, S., & Jarke, M. (2020, May). Syn: Synthetic Dataset for Training UI Element Detector From Lo-Fi Sketches. In Proceedings of the 2020 IUI Conference on Intelligent User Interfaces. Sermuga Pandian, V. P., Suleri, S., Beecks C., & Jarke, M. (2020, Dec). MetaMorph: AI Assistance to Transform Lo-Fi Sketches to Higher Fidelities. In Proceedings of the 2020 OzCHI Australian Conference on Human Computer Interaction. Sermuga Pandian, V. P., Suleri, S., & Jarke, M. (2021, May). UISketch: A Large-Scale Dataset of UI Element Sketches. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. ____________________________ ____________________________ Sometimes it is the people no one can imagine anything of, who do the things no one can imagine. “ — Alan Turing ABSTRACT Prototyping is a broadly utilized iterative technique for brainstorming, communicating, and evaluating user interface (UI) designs. This research aims to analyze this process from three aspects: traditional UI prototyping, rapid prototyping, and prototyping for accessibility. We propose three novel approaches and realize them by introducing three artifacts: 1) Eve, a sketch-based prototyping workbench that supports automation of transforming low fidelity prototypes to higher fidelities, 2) Kiwi, a UI design pattern and guidelines library to support UI design pattern-driven prototyping, 3) Personify, a persona-based UI design guidelines library for accessible UI prototyping. We evaluate the usability of these artifacts, and the results indicate good usability and learnability. Furthermore, we use NASA-TLX to study the impact of using these three novel approaches on the subjective workload experienced by the designers during the soware prototyping process. Our workload analysis reveals that, unlike the traditional prototyping approach, Eve’s comprehensive support eliminates the need for switching between various prototyping tools while progressing through the low, medium, and high fidelity prototypes. Conse- quently, there is a significant decrease in subjective workload experienced by designers using the comprehensive approach offered by Eve. Also, there is a significant reduction in mental demand, temporal demand, effort, and five times increase in the overall perceived performance using the comprehensive approach (Eve). Similarly, the subjective workload experienced by designers using the pattern-driven approach using Kiwi is significantly less than the workload experienced using the traditional approach of rapid prototyping. Specifically, there is a significant decrease in physical demand and effort of rapid prototyping while using the pattern-driven approach. Lastly, the subjective workload experienced by UI/UX designers using the persona-driven approach offered by Personify is significantly less than the workload experienced using the traditional approach of prototyping for accessibility. Specifically, there is a significant decrease in mental demand and effort of prototyping accessible UIs while using Personify. This work aims to extend prior work on UI prototyping and is broadly applicable to understand the impact of using deep learning, UI design patterns, and personas on the workload of UI prototyping. ix ÜBERBLICK Das Prototyping ist eine weit verbreitete iterative Technik für das Brainstorming, die Kommunika- tion und die Bewertung von UI-Designs. Diese Forschung zielt darauf ab, diesen Prozess unter drei Aspekten zu analysieren: traditionelles UI-Prototyping, Rapid Prototyping und Prototyping für Barrierefreiheit. Wir schlagen drei neuartige Ansätze vor und realisieren sie durch die Einführung von drei Artefakten: 1) Eve, eine skizzen-basierte Prototyping-Werkbank, die die Automatisierung der Umwandlung von Prototypen mit geringer Wiedergabetreue in höhere Wiedergabetreue un- terstützt, 2) Kiwi, eine Bibliothek mit UI-Design Patterns und Guidelines zur Unterstützung des Pattern-gesteuerten Prototypings von UI-Designs, 3) Personify, eine Persona-basierte Bibliothek mit UI-Design Guidelines für barrierefreies UI-Prototyping. Wir evaluieren die Nutzbarkeit dieser Arte- fakte, und die Ergebnisse weisen auf eine gute Nutzbarkeit und Lernfähigkeit hin. Darüber hinaus verwenden wir NASA-TLX, um die Auswirkungen der Verwendung dieser drei neuartigen Ansätze auf die subjektive Arbeitsbelastung der Designer während des Soware-Prototyping-Prozesses zu untersuchen. Unsere Analyse der Arbeitsbelastung zeigt, dass Eves umfassende Unterstützung im Gegensatz zum traditionellen Prototyping-Ansatz den Wechsel zwischen verschiedenen Prototyping-Tools über- flüssig macht, während die Prototypen mit niedriger, mittlerer und hoher Wiedergabetreue durch- laufen werden. Folglich ist die subjektive Arbeitsbelastung von Designern, die den von Eve ange- botenen umfassenden Ansatz nutzen, deutlich geringer. Auch die mentale Belastung, die zeitliche Belastung und der Arbeitsaufwand sind deutlich geringer, und die wahrgenommene Gesamtleistung steigt mit dem umfassenden Ansatz um das Fünffache (Eve). In ähnlicher Weise ist die subjektive Arbeitsbelastung von der Designer, die den Pattern-getriebenen Ansatz mit Kiwi verwenden, deutlich geringer als die Arbeitsbelastung, die mit dem traditionellen Ansatz des Rapid Prototyping verbunden ist. Insbesondere sind der physische Aufwand und die ph- ysische Beanspruchung beim Rapid Prototyping bei Verwendung des Pattern-getriebenen Ansatzes deutlich geringer als beim traditionellen Ansatz des Rapid Prototyping. Und schließlich ist die subjektive Arbeitsbelastung, die Designer mit dem Persona-getriebenen Ansatz von Personify erfahren, signifikant geringer als die Arbeitsbelastung, die mit dem tradi- tionellen Ansatz des Prototyping für die Zugänglichkeit erfahren wird. Genauer gesagt, es gibt einen signifikanten Rückgang der mentalen Anforderungen und des Aufwands für das Prototyping zugänglicher UI’s während der Verwendung von Personify. Diese Arbeit zielt darauf ab, frühere Arbeiten zum UI-Prototyping auszuweiten und ist allgemein anwendbar, um die Auswirkungen der Verwendung von tiefem Lernen, UI-Entwurfsmustern und Personas auf die Arbeitsbelastung beim UI-Prototyping zu verstehen. xi ACKNOWLEDGMENTS This has been a very long and difficult journey. One that makes or breaks you. Fortunately and unfortunately for me, it did a bit of both. While there have been a lot of people who have tried to make this journey harder, there has also been a lot of love and support from others. So instead of mentioning anyone despite whom I was able to reach wherever I am today, I would like to mention a few extremely special people who have been there for me through thick and thin. I would begin with my sister, Seemin Suleri. No one knows the hardships of this journey more than you. Thank you for making me believe that I can do anything in this world. Thank you for having my back, for being my guru, and most importantly, thank you for being there. This journey would have been a lot harder if it wasn’t for you. The voice of reason, Waleed
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