Hierarchical Processing in Seven-Month-Old Infants

Hierarchical structures are crucial to many aspects of cognitive processing and especially for language. However, there still is little experimental support for the ability of infants to learn such structures. Here, we show that, with structures simple enough to be processed by various animals, seven-month-old infants seem to learn hierarchical relations. Infants were presented with an artificial language composed of “sentences” made of three-syllable “words.” The syllables within words conformed to repetition patterns based on syllable tokens involving either adjacent repetitions (e.g., dubaba) or nonadjacent repetitions (e.g., dubadu). Importantly, the sequence of word structures in each sentence conformed to repetition patterns based on word types (e.g., aba-abb-abb). Infants learned this repetition pattern of repetition patterns and thus likely a hierarchical pattern based on repetitions, but only when the repeated word structure was based on adjacent repetitions. While our results leave open the question of which exact sentence-level pattern infants learned, they suggest that infants embedded the word-level patterns into a higher-level pattern and thus seemed to acquire a hierarchically embedded pattern

Syntax-induced pattern deafness

Perceptual systems often force systematically biased interpretations upon sensory input. These interpretations are obligatory, inaccessible to conscious control, and prevent observers from perceiving alternative percepts. Here we report a similarly impenetrable phenomenon in the domain of language, where the syntactic system prevents listeners from detecting a simple perceptual pattern. Healthy human adults listened to three-word sequences conforming to patterns readily learned even by honeybees, rats, and sleeping human neonates. Specifically, sequences either started or ended with two words from the same syntactic category (e.g., noun–noun–verb or verb–verb–noun). Although participants readily processed the categories and learned repetition patterns over nonsyntactic categories (e.g., animal–animal–clothes), they failed to learn the repetition pattern over syntactic categories, even when explicitly instructed to look for it. Further experiments revealed that participants successfully learned the repetition patterns only when they were consistent with syntactically possible structures, irrespective of whether these structures were attested in English or in other languages unknown to the participants. When the repetition patterns did not match such syntactically possible structures, participants failed to learn them. Our results suggest that when human adults hear a string of nouns and verbs, their syntactic system obligatorily attempts an interpretation (e.g., in terms of subjects, objects, and predicates). As a result, subjects fail to perceive the simpler pattern of repetitions—a form of syntax-induced pattern deafness that is reminiscent of how other perceptual systems force specific interpretations upon sensory input

Bayesian learning and the psychology of rule induction

In recent years, Bayesian learning models have been applied to an increasing variety of domains. While such models have been criticized on theoretical grounds, the underlying assumptions and predictions are rarely made concrete and tested experimentally. Here, I use Frank and Tenenbaum’s (2011) Bayesian model of rule-learning as a case study to spell out the underlying assumptions, and to confront them with the empirical results Frank and Tenenbaum (2011) propose to simulate, as well as with novel experiments. While rule-learning is arguably well suited to rational Bayesian approaches, I show that their models are neither psychologically plausible nor ideal observer models. Further, I show that their central assumption is unfounded: humans do not always preferentially learn more specific rules, but, at least in some situations, those rules that happen to be more salient. Even when granting the unsupported assumptions, I show that all of the experiments modeled by Frank and Tenenbaum (2011) either contradict their models, or have a large number of more plausible interpretations. I provide an alternative account of the experimental data based on simple psychological mechanisms, and show that this account both describes the data better, and is easier to falsify. I conclude that, despite the recent surge in Bayesian models of cognitive phenomena, psychological phenomena are best understood by developing and testing psychological theories rather than models that can be fit to virtually any data

Primitive computations in speech processing

Previous research suggests that artificial-language learners exposed to quasi-continuous speech can learn that the first and the last syllables of words have to belong to distinct classes (e.g., Endress & Bonatti, 2007; Peña, Bonatti, Nespor, & Mehler, 2002). The mechanisms of these generalizations, however, are debated. Here we show that participants learn such generalizations only when the crucial syllables are in edge positions (i.e., the first and the last), but not when they are in medial positions (i.e., the second and the fourth in pentasyllabic items). In contrast to the generalizations, participants readily perform statistical analyses also in word middles. In analogy to sequential memory, we suggest that participants extract the generalizations using a simple but specific mechanism that encodes the positions of syllables that occur in edges. Simultaneously, they use another mechanism to track the syllable distribution in the speech streams. In contrast to previous accounts, this model explains why the generalizations are faster than the statistical computations, require additional cues, and break down under different conditions, and why they can be performed at all. We also show that that similar edge-based mechanisms may explain many results in artificial-grammar learning and also various linguistic observations

When forgetting fosters learning: A neural network model for Statistical Learning

Learning often requires splitting continuous signals into recurring units, such as the discrete words constituting fluent speech; these units then need to be encoded in memory. A prominent candidate mechanism involves statistical learning of co-occurrence statistics like transitional probabilities (TPs), reflecting the idea that items from the same unit (e.g., syllables within a word) predict each other better than items from different units. TP computations are surprisingly flexible and sophisticated. Humans are sensitive to forward and backward TPs, compute TPs between adjacent items and longer-distance items, and even recognize TPs in novel units. We explain these hallmarks of statistical learning with a simple model with tunable excitatory connections and inhibitory interactions controlling the overall activation. With weak forgetting, activations are long-lasting, yielding associations among all items; with strong forgetting, no associations ensue as activations do not outlast stimuli; with intermediate forgetting, the network reproduces the hallmarks above. Forgetting thus is a key determinant of these sophisticated learning abilities. Further, in line with earlier dissociations between statistical learning and memory encoding, our model reproduces the hallmarks of statistical learning in the absence of a memory store in which items could be placed

Statistical learning and memory

Learners often need to identify and remember recurring units in continuous sequences, but the underlying mechanisms are debated. A particularly prominent candidate mechanism relies on distributional statistics such as Transitional Probabilities (TPs). However, it is unclear what the outputs of statistical segmentation mechanisms are, and if learners store these outputs as discrete chunks in memory. We critically review the evidence for the possibility that statistically coherent items are stored in memory and outline difficulties in interpreting past research. We use Slone and Johnson's (2018) experiments as a case study to show that it is difficult to delineate the different mechanisms learners might use to solve a learning problem. Slone and Johnson (2018) reported that 8-month-old infants learned coherent chunks of shapes in visual sequences. Here, we describe an alternate interpretation of their findings based on a multiple-cue integration perspective. First, when multiple cues to statistical structure were available, infants' looking behavior seemed to track with the strength of the strongest one | backward TPs, suggesting that infants process multiple cues simultaneously and select the strongest one. Second, like adults, infants are exquisitely sensitive to chunks, but may require multiple cues to extract them. In Slone and Johnson's (2018) experiments, these cues were provided by immediate chunk repetitions during familiarization. Accordingly, infants showed strongest evidence of chunking following familiarization sequences in which immediate repetitions were more frequent. These interpretations provide a strong argument for infants' processing of multiple cues and the potential importance of multiple cues for chunk recognition in infancy

Learning multiple rules simultaneously: affixes are more salient than reduplications

Language learners encounter numerous opportunities to learn regularities, but need to decide which of these regularities to learn, because some are not productive in their native language. Here, we present an account of rule learning based on perceptual and memory primitives (Endress, Dehaene-Lambertz, & Mehler, 2007; Endress, Nespor, & Mehler, 2009), suggesting that learners preferentially learn regularities that are more salient to them, and that the pattern of salience reflects the frequency of language features across languages. We contrast this view with previous artificial grammar learning research, which suggests that infants “choose” the regularities they learn based on rational, Bayesian criteria (Frank & Tenenbaum, 2011; Gerken, 2006, 2010). In our experiments, adult participants listened to syllable strings starting with a syllable reduplication and always ending with the same “a!x” syllable, or to syllable strings starting with this “a!x” syllable and ending with the “reduplication.” Both a!xation and reduplication are frequently used for morphological marking across languages. We find three crucial results. First, participants learned both regularities simultaneously. Second, a!xation regularities seemed easier to learn than reduplication regularities. Third, regularities in sequence o↵sets were easier to learn than regularities at sequence onsets. We show that these results are inconsistent with previous Bayesian rule learning models, but mesh well with the perceptual or memory primitives view. Further, we show that the pattern of salience revealed in our experiments reflects the distribution of regularities across languages. Ease of acquisition might thus be one determinant of the frequency of regularities across languages

Precursors to Natural Grammar Learning: Preliminary Evidence from 4-Month-Old Infants

When learning a new language, grammar—although difficult—is very important, as grammatical rules determine the relations between the words in a sentence. There is evidence that very young infants can detect rules determining the relation between neighbouring syllables in short syllable sequences. A critical feature of all natural languages, however, is that many grammatical rules concern the dependency relation between non-neighbouring words or elements in a sentence i.e. between an auxiliary and verb inflection as in is singing. Thus, the issue of when and how children begin to recognize such non-adjacent dependencies is fundamental to our understanding of language acquisition. Here, we use brain potential measures to demonstrate that the ability to recognize dependencies between non-adjacent elements in a novel natural language is observable by the age of 4 months. Brain responses indicate that 4-month-old German infants discriminate between grammatical and ungrammatical dependencies in auditorily presented Italian sentences after only brief exposure to correct sentences of the same type. As the grammatical dependencies are realized by phonologically distinct syllables the present data most likely reflect phonologically based implicit learning mechanisms which can serve as a precursor to later grammar learning

Modeling human performance in statistical word segmentation

The ability to discover groupings in continuous stimuli on the basis of distributional information is present across species and across perceptual modalities. We investigate the nature of the computations underlying this ability using statistical word segmentation experiments in which we vary the length of sentences, the amount of exposure, and the number of words in the languages being learned. Although the results are intuitive from the perspective of a language learner (longer sentences, less training, and a larger language all make learning more difficult), standard computational proposals fail to capture several of these results. We describe how probabilistic models of segmentation can be modified to take into account some notion of memory or resource limitations in order to provide a closer match to human performance.National Science Foundation (U.S.) (Grant BCS-0631518

Human Practice. Digital Ecologies. Our Future. : 14. Internationale Tagung Wirtschaftsinformatik (WI 2019) : Tagungsband

Erschienen bei: universi - Universitätsverlag Siegen. - ISBN: 978-3-96182-063-4Aus dem Inhalt: Track 1: Produktion & Cyber-Physische Systeme Requirements and a Meta Model for Exchanging Additive Manufacturing Capacities Service Systems, Smart Service Systems and Cyber- Physical Systems—What’s the difference? Towards a Unified Terminology Developing an Industrial IoT Platform – Trade-off between Horizontal and Vertical Approaches Machine Learning und Complex Event Processing: Effiziente Echtzeitauswertung am Beispiel Smart Factory Sensor retrofit for a coffee machine as condition monitoring and predictive maintenance use case Stakeholder-Analyse zum Einsatz IIoT-basierter Frischeinformationen in der Lebensmittelindustrie Towards a Framework for Predictive Maintenance Strategies in Mechanical Engineering - A Method-Oriented Literature Analysis Development of a matching platform for the requirement-oriented selection of cyber physical systems for SMEs Track 2: Logistic Analytics An Empirical Study of Customers’ Behavioral Intention to Use Ridepooling Services – An Extension of the Technology Acceptance Model Modeling Delay Propagation and Transmission in Railway Networks What is the impact of company specific adjustments on the acceptance and diffusion of logistic standards? Robust Route Planning in Intermodal Urban Traffic Track 3: Unternehmensmodellierung & Informationssystemgestaltung (Enterprise Modelling & Information Systems Design) Work System Modeling Method with Different Levels of Specificity and Rigor for Different Stakeholder Purposes Resolving Inconsistencies in Declarative Process Models based on Culpability Measurement Strategic Analysis in the Realm of Enterprise Modeling – On the Example of Blockchain-Based Initiatives for the Electricity Sector Zwischenbetriebliche Integration in der Möbelbranche: Konfigurationen und Einflussfaktoren Novices’ Quality Perceptions and the Acceptance of Process Modeling Grammars Entwicklung einer Definition für Social Business Objects (SBO) zur Modellierung von Unternehmensinformationen Designing a Reference Model for Digital Product Configurators Terminology for Evolving Design Artifacts Business Role-Object Specification: A Language for Behavior-aware Structural Modeling of Business Objects Generating Smart Glasses-based Information Systems with BPMN4SGA: A BPMN Extension for Smart Glasses Applications Using Blockchain in Peer-to-Peer Carsharing to Build Trust in the Sharing Economy Testing in Big Data: An Architecture Pattern for a Development Environment for Innovative, Integrated and Robust Applications Track 4: Lern- und Wissensmanagement (e-Learning and Knowledge Management) eGovernment Competences revisited – A Literature Review on necessary Competences in a Digitalized Public Sector Say Hello to Your New Automated Tutor – A Structured Literature Review on Pedagogical Conversational Agents Teaching the Digital Transformation of Business Processes: Design of a Simulation Game for Information Systems Education Conceptualizing Immersion for Individual Learning in Virtual Reality Designing a Flipped Classroom Course – a Process Model The Influence of Risk-Taking on Knowledge Exchange and Combination Gamified Feedback durch Avatare im Mobile Learning Alexa, Can You Help Me Solve That Problem? - Understanding the Value of Smart Personal Assistants as Tutors for Complex Problem Tasks Track 5: Data Science & Business Analytics Matching with Bundle Preferences: Tradeoff between Fairness and Truthfulness Applied image recognition: guidelines for using deep learning models in practice Yield Prognosis for the Agrarian Management of Vineyards using Deep Learning for Object Counting Reading Between the Lines of Qualitative Data – How to Detect Hidden Structure Based on Codes Online Auctions with Dual-Threshold Algorithms: An Experimental Study and Practical Evaluation Design Features of Non-Financial Reward Programs for Online Reviews: Evaluation based on Google Maps Data Topic Embeddings – A New Approach to Classify Very Short Documents Based on Predefined Topics Leveraging Unstructured Image Data for Product Quality Improvement Decision Support for Real Estate Investors: Improving Real Estate Valuation with 3D City Models and Points of Interest Knowledge Discovery from CVs: A Topic Modeling Procedure Online Product Descriptions – Boost for your Sales? Entscheidungsunterstützung durch historienbasierte Dienstreihenfolgeplanung mit Pattern A Semi-Automated Approach for Generating Online Review Templates Machine Learning goes Measure Management: Leveraging Anomaly Detection and Parts Search to Improve Product-Cost Optimization Bedeutung von Predictive Analytics für den theoretischen Erkenntnisgewinn in der IS-Forschung Track 6: Digitale Transformation und Dienstleistungen Heuristic Theorizing in Software Development: Deriving Design Principles for Smart Glasses-based Systems Mirroring E-service for Brick and Mortar Retail: An Assessment and Survey Taxonomy of Digital Platforms: A Platform Architecture Perspective Value of Star Players in the Digital Age Local Shopping Platforms – Harnessing Locational Advantages for the Digital Transformation of Local Retail Outlets: A Content Analysis A Socio-Technical Approach to Manage Analytics-as-a-Service – Results of an Action Design Research Project Characterizing Approaches to Digital Transformation: Development of a Taxonomy of Digital Units Expectations vs. Reality – Benefits of Smart Services in the Field of Tension between Industry and Science Innovation Networks and Digital Innovation: How Organizations Use Innovation Networks in a Digitized Environment Characterising Social Reading Platforms— A Taxonomy-Based Approach to Structure the Field Less Complex than Expected – What Really Drives IT Consulting Value Modularity Canvas – A Framework for Visualizing Potentials of Service Modularity Towards a Conceptualization of Capabilities for Innovating Business Models in the Industrial Internet of Things A Taxonomy of Barriers to Digital Transformation Ambidexterity in Service Innovation Research: A Systematic Literature Review Design and success factors of an online solution for cross-pillar pension information Track 7: IT-Management und -Strategie A Frugal Support Structure for New Software Implementations in SMEs How to Structure a Company-wide Adoption of Big Data Analytics The Changing Roles of Innovation Actors and Organizational Antecedents in the Digital Age Bewertung des Kundennutzens von Chatbots für den Einsatz im Servicedesk Understanding the Benefits of Agile Software Development in Regulated Environments Are Employees Following the Rules? On the Effectiveness of IT Consumerization Policies Agile and Attached: The Impact of Agile Practices on Agile Team Members’ Affective Organisational Commitment The Complexity Trap – Limits of IT Flexibility for Supporting Organizational Agility in Decentralized Organizations Platform Openness: A Systematic Literature Review and Avenues for Future Research Competence, Fashion and the Case of Blockchain The Digital Platform Otto.de: A Case Study of Growth, Complexity, and Generativity Track 8: eHealth & alternde Gesellschaft Security and Privacy of Personal Health Records in Cloud Computing Environments – An Experimental Exploration of the Impact of Storage Solutions and Data Breaches Patientenintegration durch Pfadsysteme Digitalisierung in der Stressprävention – eine qualitative Interviewstudie zu Nutzenpotenzialen User Dynamics in Mental Health Forums – A Sentiment Analysis Perspective Intent and the Use of Wearables in the Workplace – A Model Development Understanding Patient Pathways in the Context of Integrated Health Care Services - Implications from a Scoping Review Understanding the Habitual Use of Wearable Activity Trackers On the Fit in Fitness Apps: Studying the Interaction of Motivational Affordances and Users’ Goal Orientations in Affecting the Benefits Gained Gamification in Health Behavior Change Support Systems - A Synthesis of Unintended Side Effects Investigating the Influence of Information Incongruity on Trust-Relations within Trilateral Healthcare Settings Track 9: Krisen- und Kontinuitätsmanagement Potentiale von IKT beim Ausfall kritischer Infrastrukturen: Erwartungen, Informationsgewinnung und Mediennutzung der Zivilbevölkerung in Deutschland Fake News Perception in Germany: A Representative Study of People’s Attitudes and Approaches to Counteract Disinformation Analyzing the Potential of Graphical Building Information for Fire Emergency Responses: Findings from a Controlled Experiment Track 10: Human-Computer Interaction Towards a Taxonomy of Platforms for Conversational Agent Design Measuring Service Encounter Satisfaction with Customer Service Chatbots using Sentiment Analysis Self-Tracking and Gamification: Analyzing the Interplay of Motivations, Usage and Motivation Fulfillment Erfolgsfaktoren von Augmented-Reality-Applikationen: Analyse von Nutzerrezensionen mit dem Review-Mining-Verfahren Designing Dynamic Decision Support for Electronic Requirements Negotiations Who is Stressed by Using ICTs? A Qualitative Comparison Analysis with the Big Five Personality Traits to Understand Technostress Walking the Middle Path: How Medium Trade-Off Exposure Leads to Higher Consumer Satisfaction in Recommender Agents Theory-Based Affordances of Utilitarian, Hedonic and Dual-Purposed Technologies: A Literature Review Eliciting Customer Preferences for Shopping Companion Apps: A Service Quality Approach The Role of Early User Participation in Discovering Software – A Case Study from the Context of Smart Glasses The Fluidity of the Self-Concept as a Framework to Explain the Motivation to Play Video Games Heart over Heels? An Empirical Analysis of the Relationship between Emotions and Review Helpfulness for Experience and Credence Goods Track 11: Information Security and Information Privacy Unfolding Concerns about Augmented Reality Technologies: A Qualitative Analysis of User Perceptions To (Psychologically) Own Data is to Protect Data: How Psychological Ownership Determines Protective Behavior in a Work and Private Context Understanding Data Protection Regulations from a Data Management Perspective: A Capability-Based Approach to EU-GDPR On the Difficulties of Incentivizing Online Privacy through Transparency: A Qualitative Survey of the German Health Insurance Market What is Your Selfie Worth? A Field Study on Individuals’ Valuation of Personal Data Justification of Mass Surveillance: A Quantitative Study An Exploratory Study of Risk Perception for Data Disclosure to a Network of Firms Track 12: Umweltinformatik und nachhaltiges Wirtschaften Kommunikationsfäden im Nadelöhr – Fachliche Prozessmodellierung der Nachhaltigkeitskommunikation am Kapitalmarkt Potentiale und Herausforderungen der Materialflusskostenrechnung Computing Incentives for User-Based Relocation in Carsharing Sustainability’s Coming Home: Preliminary Design Principles for the Sustainable Smart District Substitution of hazardous chemical substances using Deep Learning and t-SNE A Hierarchy of DSMLs in Support of Product Life-Cycle Assessment A Survey of Smart Energy Services for Private Households Door-to-Door Mobility Integrators as Keystone Organizations of Smart Ecosystems: Resources and Value Co-Creation – A Literature Review Ein Entscheidungsunterstützungssystem zur ökonomischen Bewertung von Mieterstrom auf Basis der Clusteranalyse Discovering Blockchain for Sustainable Product-Service Systems to enhance the Circular Economy Digitale Rückverfolgbarkeit von Lebensmitteln: Eine verbraucherinformatische Studie Umweltbewusstsein durch audiovisuelles Content Marketing? Eine experimentelle Untersuchung zur Konsumentenbewertung nachhaltiger Smartphones Towards Predictive Energy Management in Information Systems: A Research Proposal A Web Browser-Based Application for Processing and Analyzing Material Flow Models using the MFCA Methodology Track 13: Digital Work - Social, mobile, smart On Conversational Agents in Information Systems Research: Analyzing the Past to Guide Future Work The Potential of Augmented Reality for Improving Occupational First Aid Prevent a Vicious Circle! The Role of Organizational IT-Capability in Attracting IT-affine Applicants Good, Bad, or Both? Conceptualization and Measurement of Ambivalent User Attitudes Towards AI A Case Study on Cross-Hierarchical Communication in Digital Work Environments ‘Show Me Your People Skills’ - Employing CEO Branding for Corporate Reputation Management in Social Media A Multiorganisational Study of the Drivers and Barriers of Enterprise Collaboration Systems-Enabled Change The More the Merrier? The Effect of Size of Core Team Subgroups on Success of Open Source Projects The Impact of Anthropomorphic and Functional Chatbot Design Features in Enterprise Collaboration Systems on User Acceptance Digital Feedback for Digital Work? Affordances and Constraints of a Feedback App at InsurCorp The Effect of Marker-less Augmented Reality on Task and Learning Performance Antecedents for Cyberloafing – A Literature Review Internal Crowd Work as a Source of Empowerment - An Empirical Analysis of the Perception of Employees in a Crowdtesting Project Track 14: Geschäftsmodelle und digitales Unternehmertum Dividing the ICO Jungle: Extracting and Evaluating Design Archetypes Capturing Value from Data: Exploring Factors Influencing Revenue Model Design for Data-Driven Services Understanding the Role of Data for Innovating Business Models: A System Dynamics Perspective Business Model Innovation and Stakeholder: Exploring Mechanisms and Outcomes of Value Creation and Destruction Business Models for Internet of Things Platforms: Empirical Development of a Taxonomy and Archetypes Revitalizing established Industrial Companies: State of the Art and Success Principles of Digital Corporate Incubators When 1+1 is Greater than 2: Concurrence of Additional Digital and Established Business Models within Companies Special Track 1: Student Track Investigating Personalized Price Discrimination of Textile-, Electronics- and General Stores in German Online Retail From Facets to a Universal Definition – An Analysis of IoT Usage in Retail Is the Technostress Creators Inventory Still an Up-To-Date Measurement Instrument? Results of a Large-Scale Interview Study Application of Media Synchronicity Theory to Creative Tasks in Virtual Teams Using the Example of Design Thinking TrustyTweet: An Indicator-based Browser-Plugin to Assist Users in Dealing with Fake News on Twitter Application of Process Mining Techniques to Support Maintenance-Related Objectives How Voice Can Change Customer Satisfaction: A Comparative Analysis between E-Commerce and Voice Commerce Business Process Compliance and Blockchain: How Does the Ethereum Blockchain Address Challenges of Business Process Compliance? Improving Business Model Configuration through a Question-based Approach The Influence of Situational Factors and Gamification on Intrinsic Motivation and Learning Evaluation von ITSM-Tools für Integration und Management von Cloud-Diensten am Beispiel von ServiceNow How Software Promotes the Integration of Sustainability in Business Process Management Criteria Catalog for Industrial IoT Platforms from the Perspective of the Machine Tool Industry Special Track 3: Demos & Prototyping Privacy-friendly User Location Tracking with Smart Devices: The BeaT Prototype Application-oriented robotics in nursing homes Augmented Reality for Set-up Processe Mixed Reality for supporting Remote-Meetings Gamification zur Motivationssteigerung von Werkern bei der Betriebsdatenerfassung Automatically Extracting and Analyzing Customer Needs from Twitter: A “Needmining” Prototype GaNEsHA: Opportunities for Sustainable Transportation in Smart Cities TUCANA: A platform for using local processing power of edge devices for building data-driven services Demonstrator zur Beschreibung und Visualisierung einer kritischen Infrastruktur Entwicklung einer alltagsnahen persuasiven App zur Bewegungsmotivation für ältere Nutzerinnen und Nutzer A browser-based modeling tool for studying the learning of conceptual modeling based on a multi-modal data collection approach Exergames & Dementia: An interactive System for People with Dementia and their Care-Network Workshops Workshop Ethics and Morality in Business Informatics (Workshop Ethik und Moral in der Wirtschaftsinformatik – EMoWI’19) Model-Based Compliance in Information Systems - Foundations, Case Description and Data Set of the MobIS-Challenge for Students and Doctoral Candidates Report of the Workshop on Concepts and Methods of Identifying Digital Potentials in Information Management Control of Systemic Risks in Global Networks - A Grand Challenge to Information Systems Research Die Mitarbeiter von morgen - Kompetenzen künftiger Mitarbeiter im Bereich Business Analytics Digitaler Konsum: Herausforderungen und Chancen der Verbraucherinformati