Hier finden Sie von Know-Center MitarbeiterInnen verfasste wissenschaftliche Publikationen


Barreiros Carla, Pammer-Schindler Viktoria, Veas Eduardo Enrique

Planting the Seed of Positive Human-IoT Interaction

International Journal of Human–Computer Interaction, Taylor and Francis, 2019

We present a visual interface for communicating the internal state of a coffee machine via a tree metaphor. Nature-inspired representations have a positive impact on human well-being. We also hypothesize that representing the coffee machine asa tree stimulates emotional connection to it, which leads to better maintenance performance.The first study assessed the understandability of the tree representation, comparing it with icon-based and chart-based representations. An online survey with 25 participants indicated no significant mean error difference between representations.A two-week field study assessed the maintenance performance of 12 participants, comparing the tree representation with the icon-based representation. Based on 240 interactions with the coffee machine, we concluded that participants understood themachine states significantly better in the tree representation. Their comments and behavior indicated that the tree representation encouraged an emotional engagement with the machine. Moreover, the participants performed significantly more optional maintenance tasks with the tree representation.

Renner Bettina, Wesiak Gudrun, Pammer-Schindler Viktoria, Prilla Michael, Müller Lars, Morosini Dalia, Mora Simone, Faltin Nils, Cress Ulrike

Computer-supported reflective learning: How apps can foster reflection at work.

Behaviour & Information Technology, Taylor & Francis, Taylor & Francis, 2019


Barreiros Carla, Veas Eduardo Enrique, Pammer-Schindler Viktoria

Can a green thumb make the difference? Using a Nature Metaphor to Communicate Sensor Information of a Coffee Machine

IEEE Consumers Electronics Magazine, 2018

This paper describes a novel visual metaphor to communicate sensor information of a connected device. The Internet of Things aims to extend every device with sensing and computing capabilities. A byproduct is that even domestic machines become increasingly complex, tedious to understand and maintain. This paper presents a prototype instrumenting a coffee machine with sensors. The machine streams the sensor data, which is picked up by an augmented reality application serving a nature metaphor. The nature metaphor, BioAR, represents the status derived from the coffee machine sensors in the features of a 3D virtual tree. The tree is meant to pass for a living proxy of the machine it represents. The metaphor, shown either with AR or a simple holographic display, reacts to the user manipulation of the machine and its workings. A first user study validates that the representation is correctly understood, and that it inspires affect for the machine. A second user study validates that the metaphor scales to a large number of machines.

Thalmann Stefan, Pammer-Schindler Viktoria

Die Rolle des Mitarbeiters in der Smart Factory

Wissensmanagement, 2017

Aktuelle Untersuchungen zeigen einerseits auf, dass der Mensch weiterhin eine zentrale Rolle in der Industrie spielt. Andererseits ist aber auch klar, dass die Zahl der direkt in der Produktion beschäftigten Mitarbeter sinken wird. Die Veränderung wird dahin gehen, dass der Mensch weniger gleichförmige Prozese bearbeitet, stattdessen aber in der Lage sein muss, sich schnell ändernden Arbeitstätigkeiten azupassen und individualisierte Fertigungsprozesse zu steuern. Die Reduktion der Mitarbeiter hat jedoch auch eine Reduktion von Redunanzen zur Folge. Dies führt dazu, dass dem Einzelnen mehr Verantwortung übertragen wird. Als Folge haben Fehlentscheidungen eine görßere Tragweite und bedeuten somit auch ein höheres Risikio. Der Erfolg einer Industrie 4.0 Kampagne wird daher im Wesentlichen von den Anpassungsfähigkeiten der Mitarbeiter abhängen.

Pammer-Schindler Viktoria, Fessl Angela, Weghofer Franz, Thalmann Stefan

Lernen 4.0 Herausforderungen für Menschen in der Industrie 4.0 erfolgreich meistern.

Productivity, 2017

Die Digitalisierung der Industrie wird aktuell sehr stark aus technoogischer Sicht betrachtet. Aber auch für den Menschen ergebn sich vielfältige Herausforderungen in dieser veränderten Arbeitsumgebung. Sie betreffen hautsächlich das Lernen von benötigtem Wissen.

Pammer-Schindler Viktoria, Fessl Angela, Wesiak Gudrun, Feyertag Sandra, Rivera-Pelayo Verónica

In-app Reflection Guidance: Lessons Learned across Four Field Trials at the Workplace

IEEE Transactions on Learning Technologies, IEEE, 2017

This paper presents a concept for in-app reflection guidance and its evaluation in four work-related field trials. By synthesizing across four field trials, we can show that computer-based reflection guidance can function in the workplace, in the sense of being accepted as technology, being perceived as useful and leading to reflective learning. This is encouraging for all endeavours aiming to transfer existing knowledge on reflection supportive technology from educational settings to the workplace. However,reflective learning in our studies was mostly visible to limited depth in textual entries made in the applications themselves; and proactive reflection guidance technology like prompts were often found to be disruptive. We offer these two issues as highly relevant questions for future research.

Pammer-Schindler Viktoria, Rivera-Pelayo Verónica, Fessl Angela, Müller Lars

Introducing Mood Self-Tracking at Work: Empirical Insights from Call Centers

ACM Transactions on Computer-Human Interaction (TOCHI), ACM New York, NY, USA , 2017

The benefits of self-tracking have been thoroughly investigated in private areas of life, like health or sustainable living, but less attention has been given to the impact and benefits of self-tracking in work-related settings. Through two field studies, we introduced and evaluated a mood self-tracking application in two call centers to investigate the role of mood self-tracking at work, as well as its impact on individuals and teams. Our studies indicate that mood self-tracking is accepted and can improve performance if the application is well integrated into the work processes and matches the management style. The results show that (i) capturing moods and explicitly relating them to work tasks facilitated reflection, (ii) mood self-tracking increased emotional awareness and this improved cohesion within teams, and (iii) proactive reactions by managers to trends and changes in team members’ mood were key for acceptance of reflection and correlated with measured improvements in work performance. These findings help to better understand the role and potential of self-tracking in work settings and further provide insights that guide future researchers and practitioners to design and introduce these tools in a workplace setting.

Fessl Angela, Pammer-Schindler Viktoria, Blunk Oliver, Prilla Michael

The known universe of reflection guidance: a literature review

International Journal of Technology Enhanced Learning, Inderscience Enterprises Ltd., 2016

Reflective learning has been established as a process that deepenslearning in both educational and work-related settings. We present a literaturereview on various approaches and tools (e.g., prompts, journals, visuals)providing guidance for facilitating reflective learning. Research consideredin this review coincides common understanding of reflective learning, hasapplied and evaluated a tool supporting reflection and presents correspondingresults. Literature was analysed with respect to timing of reflection, reflectionparticipants, type of reflection guidance, and results achieved regardingreflection. From this analysis, we were able to derive insights, guidelinesand recommendations for the design of reflection guidance functionality incomputing systems: (i) ensure that learners understand the purpose of reflectivelearning, (ii) combine reflective learning tools with reflective questions either inform of prompts or with peer-to-peer or group discussions, (iii) for work-relatedsettings consider the time with regard to when and how to motivate to reflect.

Simon Jörg Peter, Schmidt Peter, Pammer-Schindler Viktoria

Analysis of Differential Synchronisation's Energy Consumption on Mobile Devices

EAI Collaborative Computing, CoRR (2016), EAI, 2016

Synchronisation algorithms are central to collaborative editing software. As collaboration is increasingly mediated by mobile devices, the energy efficiency for such algorithms is interest to a wide community of application developers. In this paper we explore the differential synchronisation (diffsync) algorithm with respect to energy consumption on mobile devices. Discussions within this paper are based on real usage data of PDF annotations via the Mendeley iOS app, which requires realtime synchronisation. We identify three areas for optimising diffsync: a.) Empty cycles in which no changes need to be processed b.) tail energy by adapting cycle intervals and c.) computational complexity. Following these considerations, we propose a push-based diffsync strategy in which synchronisation cycles are triggered when a device connects to the network or when a device is notified of changes.

Pammer-Schindler Viktoria, Simon Nina, Lindstaedt Stefanie

Reflective Learning at Work

Advances in Technology Enhanced Learning, Fridolin Wild, Paul Lefrere, Peter Scott, 2013


Pammer-Schindler Viktoria, Kump Barbara, Lindstaedt Stefanie

Tag-based algorithms can predict human ratings of which objects a picture shows

Multimedia Tools and Applications, Springer US, 2012

Collaborative tagging platforms allow users to describe resources with freely chosen keywords, so called tags. The meaning of a tag as well as the precise relation between a tag and the tagged resource are left open for interpretation to the user. Although human users mostly have a fair chance at interpreting this relation, machines do not. In this paper we study the characteristics of the problem to identify descriptive tags, i.e. tags that relate to visible objects in a picture. We investigate the feasibility of using a tag-based algorithm, i.e. an algorithm that ignores actual picture content, to tackle the problem. Given the theoretical feasibility of a well-performing tag-based algorithm, which we show via an optimal algorithm, we describe the implementation and evaluation of a WordNet-based algorithm as proof-of-concept. These two investigations lead to the conclusion that even relatively simple and fast tag-based algorithms can yet predict human ratings of which objects a picture shows. Finally, we discuss the inherent difficulty both humans and machines have when deciding whether a tag is descriptive or not. Based on a qualitative analysis, we distinguish between definitional disagreement, difference in knowledge, disambiguation and difference in perception as reasons for disagreement between raters.

Stern Hermann, Pammer-Schindler Viktoria, Lindstaedt Stefanie

A Preliminary Study on Interruptibility Detection based on Location and Calendar Information

Third Workshop on Context-Systems Design, Evaluation and Optimisation (CoSDEO) 2011, December 6th - 8th, Copenhagen, Denmark, 2011., 2011

Modern communication technology-such as mobile phonesincreases our level of availability, but also raises the risk of being inappropriately interrupted. In this paper, we present our on-going research on automatically detecting a user’s interruptibility. This is the first step towards (i) contextualizing the modus of message notification, ie making the notification more or less attention-grabbing, and (ii) contextualizing message ranking, ie, prioritizing messages according to their relevance for the user’s current level of activity. We describe our approach of automatically detecting a user’s interruptibility based on location and calendar information. Both kinds of data are easily available in a mobile setting using smartphones. Second, we present a preliminary study that evaluates (i) whether GPS information is available sufficiently for our purpose in a real-world setting, and (ii) whether the computed interruptibility corresponds to a user’s own perception of interruptibility.

Erdmann Michael, Hansch Daniel, Pammer-Schindler Viktoria, Rospocher Marco, Ghidini Chiara, Lindstaedt Stefanie , Serafini Luciano

Applications of Semantic Wikis - Bringing Complementary Models and People Together: A Semantic Wiki for Enterprise Process and Application Modelling

Context and Semantics for Knowledge Management}, Warren, P., Davies, J., Simperl, E., Springer, 2011

This chapter describes some extensions to and applications of the Semantic MediaWiki. It complements the discussion of the SMW in Chap. 3. Semantic enterprise wikis combine the strengths of traditional content management systems, databases, semantic knowledge management systems and collaborative Web 2.0 platforms. Section 12.1 presents SMW+, a product for developing semantic enterprise applications. The section describes a number of real-world applications that are realized with SMW+. These include content management, project management and semantic data integration. Section 12.2 presents MoKi, a semantic wiki for modeling enterprise processes and application domains. Example applications of MoKi include modeling tasks and topics for work-integrated learning, collaboratively building an ontology and modeling clinical protocols. The chapter illustrates the wealth of activities which semantic wikis support.

Lindstaedt Stefanie , Moerzinger R., Sorschag R. , Pammer-Schindler Viktoria, Thallinger G.

Automatic Image Annotation using Visual Conent and Folksonomies

Multimedia Tools and Applications, Springer US, 2009

Automatic image annotation is an important and challenging task, andbecomes increasingly necessary when managing large image collections. This paperdescribes techniques for automatic image annotation that take advantage of collaborativelyannotated image databases, so called visual folksonomies. Our approachapplies two techniques based on image analysis: First, classification annotates imageswith a controlled vocabulary and second tag propagation along visually similar images.The latter propagates user generated, folksonomic annotations and is thereforecapable of dealing with an unlimited vocabulary. Experiments with a pool of Flickrimages demonstrate the high accuracy and efficiency of the proposed methods in thetask of automatic image annotation. Both techniques were applied in the prototypicaltag recommender “tagr”.
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