Parallel Hierarchies: Interactive Visualization of Multidimensional Hierarchical Aggregates

Exploring multi-dimensional hierarchical data is a long-standing problem present in a wide range of fields such as bioinformatics, software systems, social sciences and business intelligence. While each hierarchical dimension within these data structures can be explored in isolation, critical information lies in the relationships between dimensions. Existing approaches can either simultaneously visualize multiple non-hierarchical dimensions, or only one or two hierarchical dimensions. Yet, the challenge of visualizing multi-dimensional hierarchical data remains open. To address this problem, we developed a novel data visualization approach -- Parallel Hierarchies -- that we demonstrate on a real-life SAP SE product called SAP Product Lifecycle Costing. The starting point of the research is a thorough customer-driven requirement engineering phase including an iterative design process. To avoid restricting ourselves to a domain-specific solution, we abstract the data and tasks gathered from users, and demonstrate the approach generality by applying Parallel Hierarchies to datasets from bioinformatics and social sciences. Moreover, we report on a qualitative user study conducted in an industrial scenario with 15 experts from 9 different companies. As a result of this co-innovation experience, several SAP customers requested a product feature out of our solution. Moreover, Parallel Hierarchies integration as a standard diagram type into SAP Analytics Cloud platform is in progress. This thesis further introduces different uncertainty representation methods applicable to Parallel Hierarchies and in general to flow diagrams. We also present a visual comparison taxonomy for time-series of hierarchically structured data with one or multiple dimensions. Moreover, we propose several visual solutions for comparing hierarchies employing flow diagrams. Finally, after presenting two application examples of Parallel Hierarchies on industrial datasets, we detail two validation methods to examine the effectiveness of the visualization solution. Particularly, we introduce a novel design validation table to assess the perceptual aspects of eight different visualization solutions including Parallel Hierarchies.:1 Introduction 1.1 Motivation and Problem Statement 1.2 Research Goals 1.3 Outline and Contributions 2 Foundations of Visualization 2.1 Information Visualization 2.1.1 Terms and Definition 2.1.2 What: Data Structures 2.1.3 Why: Visualization Tasks 2.1.4 How: Visualization Techniques 2.1.5 How: Interaction Techniques 2.2 Visual Perception 2.2.1 Visual Variables 2.2.2 Attributes of Preattentive and Attentive Processing 2.2.3 Gestalt Principles 2.3 Flow Diagrams 2.3.1 Classifications of Flow Diagrams 2.3.2 Main Visual Features 2.4 Summary 3 Related Work 3.1 Cross-tabulating Hierarchical Categories 3.1.1 Visualizing Categorical Aggregates of Item Sets 3.1.2 Hierarchical Visualization of Categorical Aggregates 3.1.3 Visualizing Item Sets and Their Hierarchical Properties 3.1.4 Hierarchical Visualization of Categorical Set Aggregates 3.2 Uncertainty Visualization 3.2.1 Uncertainty Taxonomies 3.2.2 Uncertainty in Flow Diagrams 3.3 Time-Series Data Visualization 3.3.1 Time & Data 3.3.2 User Tasks 3.3.3 Visual Representation 3.4 Summary ii Contents 4 Requirement Engineering Phase 4.1 Introduction 4.2 Environment 4.2.1 The Product 4.2.2 The Customers and Development Methodology 4.2.3 Lessons Learned 4.3 Visualization Requirements for Product Costing 4.3.1 Current Visualization Practice 4.3.2 Visualization Tasks 4.3.3 Data Structure and Size 4.3.4 Early Visualization Prototypes 4.3.5 Challenges and Lessons Learned 4.4 Data and Task Abstraction 4.4.1 Data Abstraction 4.4.2 Task Abstraction 4.5 Summary and Outlook 5 Parallel Hierarchies 5.1 Introduction 5.2 The Parallel Hierarchies Technique 5.2.1 The Individual Axis: Showing Hierarchical Categories 5.2.2 Two Interlinked Axes: Showing Pairwise Frequencies 5.2.3 Multiple Linked Axes: Propagating Frequencies 5.2.4 Fine-tuning Parallel Hierarchies through Reordering 5.3 Design Choices 5.4 Applying Parallel Hierarchies 5.4.1 US Census Data 5.4.2 Yeast Gene Ontology Annotations 5.5 Evaluation 5.5.1 Setup of the Evaluation 5.5.2 Procedure of the Evaluation 5.5.3 Results from the Evaluation 5.5.4 Validity of the Evaluation 5.6 Summary and Outlook 6 Visualizing Uncertainty in Flow Diagrams 6.1 Introduction 6.2 Uncertainty in Product Costing 6.2.1 Background 6.2.2 Main Causes of Bad Quality in Costing Data 6.3 Visualization Concepts 6.4 Uncertainty Visualization using Ribbons 6.4.1 Selected Visualization Techniques 6.4.2 Study Design and Procedure 6.4.3 Results 6.4.4 Discussion 6.5 Revised Visualization Approach using Ribbons 6.5.1 Application to Sankey Diagram 6.5.2 Application to Parallel Sets 6.5.3 Application to Parallel Hierarchies 6.6 Uncertainty Visualization using Nodes 6.6.1 Visual Design of Nodes 6.6.2 Expert Evaluation 6.7 Summary and Outlook 7 Visual Comparison Task 7.1 Introduction 7.2 Comparing Two One-dimensional Time Steps 7.2.1 Problem Statement 7.2.2 Visualization Design 7.3 Comparing Two N-dimensional Time Steps 7.4 Comparing Several One-dimensional Time Steps 7.5 Summary and Outlook 8 Parallel Hierarchies in Practice 8.1 Application to Plausibility Check Task 8.1.1 Plausibility Check Process 8.1.2 Visual Exploration of Machine Learning Results 8.2 Integration into SAP Analytics Cloud 8.2.1 SAP Analytics Cloud 8.2.2 Ocean to Table Project 8.3 Summary and Outlook 9 Validation 9.1 Introduction 9.2 Nested Model Validation Approach 9.3 Perceptual Validation of Visualization Techniques 9.3.1 Design Validation Table 9.3.2 Discussion 9.4 Summary and Outlook 10 Conclusion and Outlook 10.1 Summary of Findings 10.2 Discussion 10.3 Outlook A Questionnaires of the Evaluation B Survey of the Quality of Product Costing Data C Questionnaire of Current Practice Bibliograph

A graph theoretical perspective for the unsupervised clustering of free text corpora

This thesis introduces a robust end to end topic discovery framework that extracts a set of coherent topics stemming intrinsically from document similarities. Some topic clustering methods can support embedded vectors instead of traditional Bag-of-Words (BoW) representation. Some can be free from the number of topics hyperparameter and some others can extract a multi-scale relation between topics. However, no topic clustering method supports all these properties together. This thesis focuses on this gap in the literature by designing a framework that supports any type of document-level features especially the embedded vectors. This framework does not require any uninformed decision making about the underlying data such as the number of topics, instead, the framework extracts topics in multiple resolutions. To achieve this goal, we combine existing methods from natural language processing (NLP) for feature generation and graph theory, first for graph construction based on semantic document similarities, then for graph partitioning to extract corresponding topics in multiple resolutions. Finally, we use specific methods from statistical machine learning to obtain highly generalisable supervised models to deploy topic classifiers for the deployment of topic extraction in real-time. Our applications on both a noisy and specialised corpus of medical records (i.e., descriptions for patient incidents within the NHS) and public news articles in daily language show that our framework extracts coherent topics that have better quantitative benchmark scores than other methods in most cases. The resulting multi-scale topics in both applications enable us to capture specific details more easily and choose the relevant resolutions for the specific objective. This study contributes to topic clustering literature by introducing a novel graph theoretical perspective that provides a combination of new properties. These properties are multiple resolutions, independence from uninformed decisions about the corpus, and usage of recent NLP features, such as vector embeddings.Open Acces

The effects of temperament-based teaching strategies and gender on undergraduate music achievement in an introductory music course

The purpose of this study was to investigate effects of music instructional strategies, student temperaments, and gender on achievement in a college freshman music introduction course. Two sets of instructional strategies were implemented: Extravert-Sensing strategies (ES) and non- Extravert-Sensing (NES) strategies, as suggested by Lawrence (1986), Myers (1980), and Keirsey and Bates (1978). Two intact groups of undergraduate students at Piedmont Bible College in Winston-Salem, North Carolina, who were enrolled in a Music Introduction Course, served as subjects. One group (n = 26) received the ES instructional treatment. A second group (n=24) experienced the NES instructional treatment. Nineteen males and 7 females comprised the first group, and 12 males and 12 females comprised the second. Subjects received 50 minutes of music instruction three times weekly for 15 weeks, and were pretested and posttested using a Music Introduction Achievement Test (MIAT, Winner, 1989). The MIAT was used to measure subjects' music achievement relative to three areas of music instruction: music philosophy, music fundamentals, and song leading. Three subtests, one for each section of the course, were administered in each instructional group to determine the short-term effects of the independent variables. In addition, subjects were administered the Myers-Briggs Type Indicator (Briggs & Myers, 1976) to determine their temperament types

Biomass production, supply, uses and flows in the European Union: First results from an integrated assessment

The report delivers an assessment of EU biomass production, uses, flows and related environmental impacts for the sectors agriculture, forestry, fisheries and aquaculture, and algae. Quantitative estimates are derived from available data and current knowledge, yet highlighting the uncertainties and the remaining gaps. The work is framed within the JRC biomass study and is meant to support the EU bioeconomy and the related policies.JRC.D.1-Bio-econom

Vi(E)va LLM! A Conceptual Stack for Evaluating and Interpreting Generative AI-based Visualizations

The automatic generation of visualizations is an old task that, through the years, has shown more and more interest from the research and practitioner communities. Recently, large language models (LLM) have become an interesting option for supporting generative tasks related to visualization, demonstrating initial promising results. At the same time, several pitfalls, like the multiple ways of instructing an LLM to generate the desired result, the different perspectives leading the generation (code-based, image-based, grammar-based), and the presence of hallucinations even for the visualization generation task, make their usage less affordable than expected. Following similar initiatives for benchmarking LLMs, this paper copes with the problem of modeling the evaluation of a generated visualization through an LLM. We propose a theoretical evaluation stack, EvaLLM, that decomposes the evaluation effort in its atomic components, characterizes their nature, and provides an overview of how to implement and interpret them. We also designed and implemented an evaluation platform that provides a benchmarking resource for the visualization generation task. The platform supports automatic and manual scoring conducted by multiple assessors to support a fine-grained and semantic evaluation based on the EvaLLM stack. Two case studies on GPT3.5-turbo with Code Interpreter and Llama2-70-b models show the benefits of EvaLLM and illustrate interesting results on the current state-of-the-art LLM-generated visualizations

Analyzing colony dynamics and visualizing cell diversity in spatiotemporal experiments

Hattab G. Analyzing colony dynamics and visualizing cell diversity in spatiotemporal experiments. Bielefeld: Universität Bielefeld; 2018.Bioimaging technologies enable the description of the life cycle of organisms at the microscopic scale, for example bacterial cells. In the particular case of time lapse imaging, the coupling of experimental setups and marker protocols results in the acquisition of biological changes in spatiotemporal experiments. Such experiments are devised to obtain a time-lapse image data, which I refer to as biomovies. Understanding how a cell behaves at every time point is crucial. In fact, this motivated all cell studies in the literature, which are single cell oriented. For the present biomovies, the task is to identify similarly fluorescing subpopulations across space and time. My interest lies in isogenic bacterial populations of *Sinorhizobium meliloti*. The biomovies’ particularity is a dynamic range of high values for a set of different properties (e.g. cell density, cell count, etc), herein, leading to a bottleneck. State of the art methods cannot address such a task, which is partly due to their inability to handle highly dense populations and their adaptability to different experimental setups. In particular, they fall short either at the segmentation step (to delineate individual cells and extract their abstraction, e.g. cell centroid) or at the tracking step (to follow identified cells in each frame). To gain insight into bacterial growth at the population level, I claim that one does not really need to know the fate of each single cell. In the context of this thesis, I present a series of pipelines and algorithms. First, preprocessing pipelines to reduce noise and enhance the object-to-background contrast. Second, an adaptive algorithm to correct spatial shift in the images (i.e. registration) and of each biomovie. Third and last, a modular algorithm that constructs coherent patch lineages by employing two adapted data abstractions, the particle and the patch, that are essential to solving the aforementioned bottleneck and are defined as follows: A particle is an intuitive geometric abstraction that results from considering whether the neighborhood around a pixel falls within a cell by checking for signal characteristics such as signal intensity, edge orientation, fluorescence signals, or texture. A patch is the aggregation of spatially contiguous particle trajectories that feature similar fluorescence patterns. The methodology that creates coherent patch lineages is automatic and modular. By integrating aspects of object recognition and spatiotemporal changes, it lays down the foundation for investigating colony growth. All of the aforementioned pipelines represent a new methodological contribution to the field of lineage analysis and colony growth. I evaluate the proposed pipelines and algorithms on simulated and biological data, respectively. In turn this enabled me to validate the algorithms, interpret changes in the colony growth and differences among conditions of an experiment. In particular, I found that in a same condition, two isogenic bacterial colonies grew differently when faced with the same stress. The methods pioneered herein provide a key step to investigating colony growth

Translation Alignment Applied to Historical Languages: methods, evaluation, applications, and visualization

Translation alignment is an essential task in Digital Humanities and Natural Language Processing, and it aims to link words/phrases in the source text with their translation equivalents in the translation. In addition to its importance in teaching and learning historical languages, translation alignment builds bridges between ancient and modern languages through which various linguistics annotations can be transferred. This thesis focuses on word-level translation alignment applied to historical languages in general and Ancient Greek and Latin in particular. As the title indicates, the thesis addresses four interdisciplinary aspects of translation alignment. The starting point was developing Ugarit, an interactive annotation tool to perform manual alignment aiming to gather training data to train an automatic alignment model. This effort resulted in more than 190k accurate translation pairs that I used for supervised training later. Ugarit has been used by many researchers and scholars also in the classroom at several institutions for teaching and learning ancient languages, which resulted in a large, diverse crowd-sourced aligned parallel corpus allowing us to conduct experiments and qualitative analysis to detect recurring patterns in annotators’ alignment practice and the generated translation pairs. Further, I employed the recent advances in NLP and language modeling to develop an automatic alignment model for historical low-resourced languages, experimenting with various training objectives and proposing a training strategy for historical languages that combines supervised and unsupervised training with mono- and multilingual texts. Then, I integrated this alignment model into other development workflows to project cross-lingual annotations and induce bilingual dictionaries from parallel corpora. Evaluation is essential to assess the quality of any model. To ensure employing the best practice, I reviewed the current evaluation procedure, defined its limitations, and proposed two new evaluation metrics. Moreover, I introduced a visual analytics framework to explore and inspect alignment gold standard datasets and support quantitative and qualitative evaluation of translation alignment models. Besides, I designed and implemented visual analytics tools and reading environments for parallel texts and proposed various visualization approaches to support different alignment-related tasks employing the latest advances in information visualization and best practice. Overall, this thesis presents a comprehensive study that includes manual and automatic alignment techniques, evaluation methods and visual analytics tools that aim to advance the field of translation alignment for historical languages

Gemeinschaften in neuen Medien. Forschung zu Wissensgemeinschaften in Wissenschaft, Wirtschaft, Bildung und öffentlicher Verwaltung: 21. Workshop GeNeMe‘18 Gemeinschaften in Neuen Medien

Die 21. Tagung der Gemeinschaften in Neuen Medien (GeNeMe) stellt innovative Technologien und Prozesse zur Organisation, Kooperation und Kommunikation in virtuellen Gemeinschaften vor und bildet ein Forum zum fachlichen Austausch insbesondere in den Themenfeldern Wissensmanagement und E-Learning. Die diesjährige Konferenz Gemeinschaften in Neuen Medien – GeNeMe 2018 findet in den neuen Räumlichkeiten der Fachhochschule Dresden (FHD) statt, gelegen am Straßburger Platz. Am HighTech-Industrie- und Forschungsstandort Dresden bietet die zentrale Lage des Tagungsortes den idealen Ausgangspunkt, um die kulturell vielschichtige Stadt Dresden kennenzulernen. Auf der GeNeMe 2018 werden Sie Teil einer bewusst interaktiven Tagung, bei der Sie nicht nur Wissen aufnehmen, sondern insbesondere gemeinsam mit Akteuren aus Wirtschaft, Wissenschaft und Verwaltung austauschen und weiter entwickeln! Die Leitung der Konferenz obliegt einer Gruppe von Wissenschaftlern aus den Fakultäten Erziehungs- und Wirtschaftswissenschaften sowie dem Medienzentrum der Technischen Universität Dresden, mit freundlicher Unterstützung des Silicon Saxony e.V. Als Partnerhochschulen beteiligen sich die Hochschule der DGUV (HGU), die HTW Dresden und die FH Dresden als Co-Ausrichter an der inhaltlichen und organisatorischen Gestaltung der 21. GeNeMe 2018. Ein internationales Steering Committee hat vorangehend die Begutachtung der deutsch- und englischsprachigen Einreichungen übernommen, in deren Ergebnis der vorliegende Tagungsband zusammengestellt werden konnte. [... aus der Einleitung]:Wissensgemeinschaften in Wirtschaft, Wissenschaft und öffentlicher Verwaltung XXI Wissensgemeinschaften in Wirtschaft, Wissenschaft und öffentlicher Verwaltung XXI Eingeladene Vorträge 1 The “Communities in New Media” Conference Series. Over 20 years of Research about Knowledge Communities in Science, Business, Education, Public Administration and beyond 1 Community Management in 2018: Bedeutung, Trends und Praktiken 10 Digitalisierung – Das Ende der Unternehmens-IT? 12 Game Thinking: Spielen und Lernen 15 Motivationsdesign im Lernmanagementsystem. Das gamifizierte Studienassistenzsystem gOPAL 15 Einfluss der Qualität eines Serious Games zum Lernen auf den Wissensgewinn 25 Gamification einer B2B-Community – Handlungsempfehlungen für den Einsatz im Personalmanagement zur Beteiligungsförderung 35 Funnyfication: Nutzung von Memes zur Motivationsförderung 44 Kapitel 53 Zur Leistungsfähigkeit von Blended Learning im Zeitalter der Digitalisierung ... 53 Lernplattformen oder Content-Halden? Learning-Management-Systeme in der Schulpraxis ...62 Befragungsdesign: „Digitale Qualifizierungs-angebote in der betrieblichen Weiterbildung“ ... 72 Wissenschaft 2.0 und offene Forschungsmethoden vermitteln: Der MOOC „Science 2.0 and open research methods“ ... 82 Organisationsentwicklung und Planung 91 Möglichkeiten digital gestützter, hochschulübergreifender Kooperation in der Lehre. Fallbeispiele aus der sächsischen Hochschulbildung 91 Digitalisierung in Einrichtungen der beruflichen Aus- und Weiterbildung – empirische Ergebnisse zum aktuellen Stand 105 Professionalisierungstendenzen in der Sozialen Arbeit im Kontext von Medienbildung und Medienpädagogik 114 Transformation im stationären Einzelhandel: Emotionen und digitale Kundenbeziehungen 122 Innovation im Mittelstand – Start-Ups als Vermittler alternativer Methoden 134 Kollaboration und Partizipation 139 Bleiben Belohnung und Anerkennung in virtuellen standort- verteilten Teams auf der Strecke? – Reward and Recognition Systeme als Lösungsansatz 139 Partizipativ planen für die berufliche Bildung – Hybride Lernräume gemeinsam gestalten 150 Wann ist Lernen mit digitalen Medien (wirklich) selbstgesteuert? Ansätze zur Ermöglichung und Förderung von Selbststeuerung in technologieunterstützten Lernprozessen 155 Arbeiten und Lernen 167 „Ich führe – also bin ich?“ – Wahrnehmung und Beurteilung der Legitimität von Führungspositionen in virtuellen Kooperationen 167 Das integrierte Lernszenario für proaktive Produktsicherheit im Maschinenbau – ein innovatives und nachhaltiges Lehrkonzept für die universitäre Ausbildung? 185 Technical working skills of vocational high school students at the interface between digital workplaces and school. An empirical study about construction engineering drawings in Indonesia 191 Design Thinking für Industrienahe Dienstleister: Herausforderungen und Möglichkeiten ... 201 Erlebnis und Wissensgewinn 207 The Effect of Reflective Audiotaped Journals on Complexity, Accuracy, and Fluency of L2 Oral Performance 207 Novel Approaches to research and discover Urban History 224 Catch them all again! – Eine Pokémon Go Vergleichsstudie 233 Data4City – A Hyperlocal Citizen App 243 Mediengestaltung: Form und Design 249 Attraktivität von Visualisierungsformen in Online-Lernumgebungen 249 Designempfehlungen für Fragebogen auf mobilen Endgeräten 261 Virtuelles Training von Gefahrensituationen – am Beispiel der Entwicklung und Evaluation einer virtuellen Pannensimulation 271 Mediennutzung: Analysen und Methoden 281 Erfolgsgeschichte GeNeMe? – Eine bibliometrische Untersuchung der Autorenschaft über zwei Jahrzehnte 281 „Das perfekte Opfer“ – eine Analyse sicherheitsbezogener Einstellungen und Verhaltensweisen im Internet in Abhängigkeit der Nutzerpersönlichkeit 291 A Hurricane Lamp in a Dark Night: Exploring Smartphone Use for Acculturation by Refugees 308 Komitee- und Autorenverzeichnis 320The 21.st Conference on Communities in New Media (GeNeMe) presents innovative technologies and processes for the organization, cooperation and communication in virtual communities and is a forum for professional exchange especially in the fields of knowledge management and online learning. This years’ conference takes place in the new premises of the Dresden University of Applied Sciences (FHD). At the high-tech industrial and research spot Dresden, the central location of the conference venue provides the ideal starting point for getting to know the culturally diverse city of Dresden. At GeNeMe 2018, you will be part of an interactive conference in which you not only exchange knowledge but, in particular, further develop it together with stakeholders from business, science and administration! The conference is managed by a group of scientists from the Faculties of Education and Business Management & Economics as well as the Media Center of the Technische Universität Dresden, with the kind support of Silicon Saxony e.V. The partner universities are the Hochschule der DGUV (HGU), the HTW Dresden and the FH Dresden as co-organizers on the content and organization of the 21st GeNeMe 2018. An international steering Committee took over the review of German and English language submissions. [... from the introduction]:Wissensgemeinschaften in Wirtschaft, Wissenschaft und öffentlicher Verwaltung XXI Wissensgemeinschaften in Wirtschaft, Wissenschaft und öffentlicher Verwaltung XXI Eingeladene Vorträge 1 The “Communities in New Media” Conference Series. Over 20 years of Research about Knowledge Communities in Science, Business, Education, Public Administration and beyond 1 Community Management in 2018: Bedeutung, Trends und Praktiken 10 Digitalisierung – Das Ende der Unternehmens-IT? 12 Game Thinking: Spielen und Lernen 15 Motivationsdesign im Lernmanagementsystem. Das gamifizierte Studienassistenzsystem gOPAL 15 Einfluss der Qualität eines Serious Games zum Lernen auf den Wissensgewinn 25 Gamification einer B2B-Community – Handlungsempfehlungen für den Einsatz im Personalmanagement zur Beteiligungsförderung 35 Funnyfication: Nutzung von Memes zur Motivationsförderung 44 Kapitel 53 Zur Leistungsfähigkeit von Blended Learning im Zeitalter der Digitalisierung ... 53 Lernplattformen oder Content-Halden? Learning-Management-Systeme in der Schulpraxis ...62 Befragungsdesign: „Digitale Qualifizierungs-angebote in der betrieblichen Weiterbildung“ ... 72 Wissenschaft 2.0 und offene Forschungsmethoden vermitteln: Der MOOC „Science 2.0 and open research methods“ ... 82 Organisationsentwicklung und Planung 91 Möglichkeiten digital gestützter, hochschulübergreifender Kooperation in der Lehre. Fallbeispiele aus der sächsischen Hochschulbildung 91 Digitalisierung in Einrichtungen der beruflichen Aus- und Weiterbildung – empirische Ergebnisse zum aktuellen Stand 105 Professionalisierungstendenzen in der Sozialen Arbeit im Kontext von Medienbildung und Medienpädagogik 114 Transformation im stationären Einzelhandel: Emotionen und digitale Kundenbeziehungen 122 Innovation im Mittelstand – Start-Ups als Vermittler alternativer Methoden 134 Kollaboration und Partizipation 139 Bleiben Belohnung und Anerkennung in virtuellen standort- verteilten Teams auf der Strecke? – Reward and Recognition Systeme als Lösungsansatz 139 Partizipativ planen für die berufliche Bildung – Hybride Lernräume gemeinsam gestalten 150 Wann ist Lernen mit digitalen Medien (wirklich) selbstgesteuert? Ansätze zur Ermöglichung und Förderung von Selbststeuerung in technologieunterstützten Lernprozessen 155 Arbeiten und Lernen 167 „Ich führe – also bin ich?“ – Wahrnehmung und Beurteilung der Legitimität von Führungspositionen in virtuellen Kooperationen 167 Das integrierte Lernszenario für proaktive Produktsicherheit im Maschinenbau – ein innovatives und nachhaltiges Lehrkonzept für die universitäre Ausbildung? 185 Technical working skills of vocational high school students at the interface between digital workplaces and school. An empirical study about construction engineering drawings in Indonesia 191 Design Thinking für Industrienahe Dienstleister: Herausforderungen und Möglichkeiten ... 201 Erlebnis und Wissensgewinn 207 The Effect of Reflective Audiotaped Journals on Complexity, Accuracy, and Fluency of L2 Oral Performance 207 Novel Approaches to research and discover Urban History 224 Catch them all again! – Eine Pokémon Go Vergleichsstudie 233 Data4City – A Hyperlocal Citizen App 243 Mediengestaltung: Form und Design 249 Attraktivität von Visualisierungsformen in Online-Lernumgebungen 249 Designempfehlungen für Fragebogen auf mobilen Endgeräten 261 Virtuelles Training von Gefahrensituationen – am Beispiel der Entwicklung und Evaluation einer virtuellen Pannensimulation 271 Mediennutzung: Analysen und Methoden 281 Erfolgsgeschichte GeNeMe? – Eine bibliometrische Untersuchung der Autorenschaft über zwei Jahrzehnte 281 „Das perfekte Opfer“ – eine Analyse sicherheitsbezogener Einstellungen und Verhaltensweisen im Internet in Abhängigkeit der Nutzerpersönlichkeit 291 A Hurricane Lamp in a Dark Night: Exploring Smartphone Use for Acculturation by Refugees 308 Komitee- und Autorenverzeichnis 32