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Quantified Self Approaches for Reflective Learning in the Workplace Quantified Approaches Self for Reflective Learning in the Workplace V

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Quantified Self Approaches for Reflective Learning in the Workplace Quantified Approaches Self for Reflective Learning in the Workplace V Verónica Rivera Pelayo Design and Application of Quantified Self Approaches for Reflective Learning in the Workplace Quantified Approaches Self for Reflective Learning in the Workplace V. Rivera Pelayo Rivera V. Verónica Rivera Pelayo DESIGN AND AppLICATION OF QUANTIFIED SELF ApprOACHES FOR REFLECTIVE LEARNING IN THE WORKPLACE Design and Application of Quantified Self Approaches for Reflective Learning in the Workplace by Verónica Rivera Pelayo Dissertation, genehmigt von der Fakultät für Wirtschaftswissenschaften des Karlsruher Instituts für Technologie (KIT), 2015 Tag der mündlichen Prüfung: 2. Februar 2015 Referenten: Prof. Dr. Rudi Studer, Univ.-Prof. Dr. Stefanie Lindstaedt Impressum Karlsruher Institut für Technologie (KIT) KIT Scientific Publishing Straße am Forum 2 D-76131 Karlsruhe KIT Scientific Publishing is a registered trademark of Karlsruhe Institute of Technology. Reprint using the book cover is not allowed. www.ksp.kit.edu This document – excluding the cover – is licensed under the Creative Commons Attribution-Share Alike 3.0 DE License (CC BY-SA 3.0 DE): http://creativecommons.org/licenses/by-sa/3.0/de/ The cover page is licensed under the Creative Commons Attribution-No Derivatives 3.0 DE License (CC BY-ND 3.0 DE): http://creativecommons.org/licenses/by-nd/3.0/de/ Print on Demand 2015 ISBN 978-3-7315-0406-1 DOI 10.5445/KSP/1000047818 To my love Jan & my family — mam´a,pap´ay hermana Abstract Learning by reflection has been identified as one of the core processes for im- proving work performance. However, theories of reflective learning are of a cognitive or sociological nature and do not sufficiently consider the use of tech- nologies to enhance reflective learning processes. The aim of this thesis is to investigate if and how Quantified Self approaches can aid reflective learning at the workplace. Quantified Self (QS) is a collaboration of users and tool ma- kers who share an interest in self-knowledge through self-tracking, resulting in a variety of tools to collect personally relevant information. These are rather experimental approaches and currently there is no unifying framework that clusters and connects these many emergent tools with the goals and benefits of their use. From a theoretical perspective, this thesis contributes with an integrated model that provides a framework for technical support of reflective learning, derived from unifying reflective learning theory with a conceptual framework of Quan- tified Self tools. To instantiate our approach, mobile and web-based applications have been iteratively designed and developed following a design-based research methodology. Within the first use case of the empirical validation, we introduce and evaluate mood self-tracking in distinct work scenarios of the telecommunications and IT sector. The second use case explores the impact of reflection on trading behavior by integrating mood self-tracking in experimental asset markets. In the third use case, an application to track feedback from audiences enables reflective learning support for lecturers and public speakers. These applications have been evaluated in thirteen studies that demonstrate the support of reflective learning and measure the impact on work performance. The results of these user studies lead to the validation of the holistic approach through a body of empirical application-oriented insights. This thesis provides a novel approach for reflective learning support by transferring and adapting practices from the Quantified Self to workplace settings. i Acknowledgments I would like to express my profound gratitude to Prof. Dr. Rudi Studer for his constant support, unconditional supervision and useful feedback throughout this research work. For me it was an honor to have him as my Doktorvater and be part of his excellent team. I am deeply thankful to him for giving me the freedom to be creative in my research in an innovative field, yet being always present with his advice and mentorship. I am also proud of having Univ.-Prof. Dr. Stefanie Lindstaedt as my co-advisor. I would like to thank her for her generosity and hospitality, for sharing with me her extensive experience and knowledge, and for her valuable time and comments before, during and after my stay in Graz. It was a pleasure having the advice of these two great scientists and leaders. I would also like to thank Prof. Dr. Thomas Setzer and Prof. Dr. Oliver Stein for taking the time to review my thesis, giving their feedback from I would like to give my deepest gratitude and thanks to Valentin Zacharias, who supervised my work, guided me during the whole journey and offered me encouragement. Thanks for introducing me to the Quantified Self; it has not only contributed to my innovative research, but also changed my life. This thesis would not have been possible without him and his invaluable support. I am particularly grateful to Lars M ¨uller for being such a great fellow adventurer in MIRROR and for his valuable contribution to my research. Special thanks go to Simone Braun who was not only an unconditional colleague and friend but also a role model from whom I could learn so much. Had it not been for her, I would have not embarked on this exciting experiential academic journey I undertook. Thanks to Andreas Schmidt and Christine Kunzmann for their supporting advice and constant encouragement. I will never have enough words to thank all of them the inspiring discussions, valuable feedback as well as great help on my journey to accomplish this thesis and to become a good researcher. I thank all my colleagues and students at FZI Forschungszentrum Informatik and all the people I worked with in MIRROR for their feedback, help and col- laboration in the realization of this work. Special thanks to Philipp Astor and Achim Hendriks for their support and great joint work with the MoodMarket as well as to Angela Fessl for our joint work with the MoodMap App. I am partic- ularly grateful to Athanasios Mazarakis for so many constructive discussions, iii Acknowledgments his valuable advice and significant help. I also want to thank Heike D¨ohmer, Merc`eM ¨uller-Gorchs, Basil Ell, Julia Hoxha, Markus Ewald, and Christian Reichelt for their friendship and contribution to my daily work and life. I thank all the students that contributed to this research. I hope you have learned Inra K ¨uhn Johannes Munk, Emanuel Laci´c, Tomislav Duriˇci´c, and Leif Becker for their support and great joint work. I also thank Karlsruhe House of Young Scientists which financially supported my stay in Graz and the European Commission for funding the MIRROR Project. Thanks to all collaborating organizations (especially to my close collabo- rators Ellen Leenarts, Hans Dirkzwager, Andrew Patterson, Marco Parigi and Michele Biol`e) and anonymous participants in my studies. Thanks to all the people who have influenced my life and career. My immense thank to Jan Gutzeit for always believing in me and accompanying me in good and bad times. I am so lucky and grateful to have Jan in my life. I would like to express my deepest and most sincere appreciation to my parents Ma Carmen and Jos´eAntonio and sister Noem´ı: gracias mam´a,pap´ay hermana, por vuestro amor incondicional y por apoyarme en cada uno de mis d´ıas. Gracias por haberme transmitido todos esos valores que hacen de m´ıla persona que soy hoy y por ayudarme a llegar hasta aqu´ıy seguir adelante. Espero que est´eisorgullosos de m´ı. Thank you very much to my whole family and my friends, who have supported me from a distance and encouraged me to overcome every difficulty For those whom I may have left out, you may be the last but you are certainly not the least. I greatly appreciate all your invaluable contributions. This would not have been possible without you. Thank you! iv Contents List of Figures ................................. xiii List of Tables .................................. xvi 1 Introduction ................................. 1 1.1 Motivation and Problem Statement . 1 1.2 Research Questions . 3 1.3 Research Approach . 3 1.4 Contributions . 6 1.5 Thesis Structure . 7 1.6 Publications . 7 I Theoretical Model Overview ..................................... 13 2 Background ................................. 15 2.1 Reflective Learning at Work . 15 2.1.1 Reflective Learning by Boud et al. 16 2.2 Quantified Self . 18 2.2.1 The Quantified Self Community . 18 2.2.2 The Quantified Self Approaches . 20 3 Unification of Reflective Learning and the Quantified Self .... 25 3.1 Integrated Model of Reflective Learning and Quantified Self . 25 3.2 Tracking Cues . 26 3.2.1 Tracking Means . 27 3.2.2 Tracked Aspects . 28 3.2.3 Purposes . 29 3.3 Triggering . 29 3.3.1 Active Triggering . 29 3.3.2 Passive Triggering . 30 3.4 Recalling and Revisiting Experiences . 30 v Contents 3.4.1 Contextualizing . 30 3.4.2 Data Fusion: Objective, Self, Peer and Group Assessment . 32 3.4.3 Data Analysis: Aggregation, Averages, etc. 32 3.4.4 Visualization . 32 3.5 Exemplary Applications . 33 3.5.1 Philips DirectLife . 33 3.5.2 Moodscope . 34 3.6 Related Work . 35 3.6.1 The Quantified Self and Personal Informatics . 35 3.6.2 Computer-Supported Reflective Learning . 37 II Implementation and Empirical Validation Overview ..................................... 43 4 Use Case I: Emotions in the Telecommunications and IT Sector . 45 4.1 Work Context, Requirements and Challenges . 45 4.1.1 British Telecom – FWS Department . 46 4.1.2 British Telecom – Telecommunications Call Centers . 47 4.1.3 Regola – Software Solutions Department . 49 4.2 MoodMap App . 51 4.2.1 MoodMap App: IMRLQS Support Dimensions . 52 4.2.2 MoodMap App 1.0 . 55 4.2.3 MoodMap App 2.0 . 58 4.2.4 MoodMap App 3.0 . 67 4.2.5 Implementation .
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