Disch Leonie, Pammer-Schindler Viktoria
2023
Many knowledge-intensive tasks - where learning is required and expected - are now computer-supported. Subsequently, interaction design has the opportunity to support the learning that is necessary to complete a task. In our work, we specifically use knowledge construction theory to model learning. In this position paper, we elaborate on three overarching goals: I) identifying (computational) measurement methods that operationalize knowledge construction theory, II) using these measurement methods to evaluate and compare user interface design elements, and III) user interface adaptation using knowledge about which design elements support what step of knowledge construction - gained through II) together with user models. Our prior and ongoing work targets two areas, namely open science (knowledge construction is necessary to understand scientific texts) and data analytics (knowledge construction is necessary to develop insights based on data)
Wolfbauer Irmtraud, Bangerl Mia Magdalena, Maitz Katharina, Pammer-Schindler Viktoria
2023
In Rebo at Work, chatbot Rebo helps apprentices to reflect on a work experience and associate it with their training’s learning objectives. Rebo poses questions that motivate the apprentice to look at a work experience from different angles, pondering how it went, the problems they encountered, what they learned from it, and what they take away for the future. We present preliminary results of a 9-month field study (analysis of 90 interactions of the first 6 months) with 51 apprentices in the fields of metal technology, mechatronics, and electrical engineering. During reflection with Rebo at Work, 98% of apprentices were able to identify their work experience as a learning opportunity and reflect on that, and 83% successfully connected it with a learning objective. This shows that self-monitoring of learning objectives and reflection on work tasks can be guided by a conversational agent and motivates further research in this area.
Pammer-Schindler Viktoria, Lindstaedt Stefanie
2022
Digitale Kompetenzen sind im Bereich des strategischen Managements selbstverständlich, AI Literacy allerdings nicht. In diesem Artikel diskutieren wir, welches grundlegende Verständnis über künstliche Intelligenz (Artificial Intelligence – AI) für Entscheidungsträger:Innen im strategischen Management wichtig ist und welches darüber hinausgehende kontextspezifische und strategische Wissen.Digitale Kompetenzen für einen Großteil von beruflichen Tätigkeitsgruppen sind in aller Munde, zu Recht. Auf der Ebene von Entscheidungsträger:Innen im strategischen Management allerdings greifen diese zu kurz; sie sind größtenteils selbstverständlich im notwendigen Ausmaß: digitales Informationsmanagement, die Fähigkeit zur Kommunikation und Zusammenarbeit im Digitalen wie auch die Fähigkeiten, digitale Technologien zum Wissenserwerb und Lernen und zur Unterstützung bei kreativen Prozessen einzusetzen (Liste dieser typischen digitalen Kompetenzen aus [1]).Anders stellt sich die Sache dar, wenn es um spezialisiertes Wissen über moderne Computertechnologien geht, wie Methoden der automatischen Datenauswertung (Data Analytics) und der künstlichen Intelligenz, Internet of Things, Blockchainverfahren etc. (Auflistung in Anlehnung an Abb. 3 in [2]). Dieses Wissen wird in der Literatur durchaus als in Organisationen notwendiges Wissen behandelt [2]; allerdings üblicherweise mit dem Fokus darauf, dass dieses von Spezialist:Innen abgedeckt werden soll.Zusätzlich, und das ist die erste Hauptthese in diesem Kommentar, argumentieren wir, dass Entscheidungsträger:Innen im strategischen Management Grundlagenwissen in diesen technischen Bereichen brauchen, um in der Lage zu sein, diese Technologien in Bezug auf ihre Auswirkungen auf das eigene Unternehmen bzw. dessen Geschäftsumfeld einschätzen zu können. In diesem Artikel wird genauer das nötige Grundlagenwissen in Bezug auf künstliche Intelligenz (Artificial Intelligence – AI) betrachtet, das wir hier als „AI Literacy“ bezeichnen.
Maitz Katharina, Fessl Angela, Pammer-Schindler Viktoria, Kaiser Rene_DB, Lindstaedt Stefanie
2022
Artificial intelligence (AI) is by now used in many different work settings, including construction industry. As new technologies change business and work processes, one important aspect is to understand how potentially affected workers perceive and understand the existing and upcoming AI in their work environment. In this work, we present the results of an exploratory case study with 20 construction workers in a small Austrian company about their knowledge of and attitudes toward AI. Our results show that construction workers’ understanding of AI as a concept is rather superficial, diffuse, and vague, often linked to physical and tangible entities such as robots, and often based on inappropriate sources of information which can lead to misconceptions about AI and AI anxiety. Learning opportunities for promoting (future) construction workers’ AI literacy should be accessible and understandable for learners at various educational levels and encompass aspects such as i) conveying the basics of digitalization, automation, and AI to enable a clear distinction of these concepts, ii) building on the learners’ actual experience realm, i.e., taking into account their focus on physical, tangible, and visible entities, and iii) reducing AI anxiety by elaborating on the limits of AI.
Disch Leonie, Fessl Angela, Pammer-Schindler Viktoria
2022
The uptake of open science resources needs knowledge construction on the side of the readers/receivers of scientific content. The design of technologies surrounding open science resources can facilitate such knowledge construction, but this has not been investigated yet. To do so, we first conducted a scoping review of literature, from which we draw design heuristics for knowledge construction in digital environments. Subsequently, we grouped the underlying technological functionalities into three design categories: i) structuring and supporting collaboration, ii) supporting the learning process, and iii) structuring, visualising and navigating (learning) content. Finally, we mapped the design categories and associated design heuristics to core components of popular open science platforms. This mapping constitutes a design space (design implications), which informs researchers and designers in the HCI community about suitable functionalities for supporting knowledge construction in existing or new digital open science platforms.
Mirzababaei Behzad, Pammer-Schindler Viktoria
2022
Large-scale learning scenarios as well as the ongoing pandemic situation underline the importance of educational technology in order to support scalability and spatial as well as temporal flexibility in all kinds of learning and teaching settings. Educational conversational agents build on a long research tradition in intelligent tutoring systems and other adaptive learning technologies but build for interaction on the more recent interaction paradigm of conversational interaction. In this paper, we describe a tutorial conversational agent, called GDPRAgent, which teaches a lesson on the European General Data Protection Regulation (GDPR). This regulation governs how personal data must be treated in Europe. Instructionally, the agent’s dialogue structure follows a basic GDPR curriculum and uses Bloom’s revised taxonomy of learning objectives in order to teach GDPR topics. This overall design of the dialogue structure allows inserting more specific adaptive tutorial strategies. From a learner perspective, the learners experience a completely one-on-one tutorial session in which they receive relevant content (is “being taught”) as well as experiences active learning parts such as doing quizzes or summarising content. Our prototype, therefore, illustrates a move away from the dichotomy between content and the activity of teaching/learning in educational technology.
Mirzababaei Behzad, Pammer-Schindler Viktoria
2022
This paper reports a between-subjects experiment (treatment group N = 42, control group N = 53) evaluating the effect of a conversational agent that teaches users to give a complete argument. The agent analyses a given argument for whether it contains a claim, a warrant and evidence, which are understood to be essential elements in a good argument. The agent detects which of these elements is missing, and accordingly scaffolds the argument completion. The experiment includes a treatment task (Task 1) in which participants of the treatment group converse with the agent, and two assessment tasks (Tasks 2 and 3) in which both the treatment and the control group answer an argumentative question. We find that in Task 1, 36 out of 42 conversations with the agent are coherent. This indicates good interaction quality. We further find that in Tasks 2 and 3, the treatment group writes a significantly higher percentage of argumentative sentences (task 2: t(94) = 1.73, p = 0.042, task 3: t(94) = 1.7, p = 0.045). This shows that participants of the treatment group used the scaffold, taught by the agent in Task 1, outside the tutoring conversation (namely in the assessment Tasks 2 and 3) and across argumentation domains (Task 3 is in a different domain of argumentation than Tasks 1 and 2). The work complements existing research on adaptive and conversational support for teaching argumentation in essays.
Wolfbauer Irmtraud, Pammer-Schindler Viktoria, Maitz Katharina, Rosé Carolyn P.
2022
We present a script for conversational reflection guidance embedded in reflective practice. Rebo Junior, a non-adaptive conversational agent, was evaluated in a 12-week field study with apprentices. We analysed apprentices’ interactions with Rebo Junior in terms of reflectivity, and measured the development of their reflection competence via reflective essays at three points in time during the field study. Reflection competence, a key competency for lifelong professional learning, becomes significantly higher by the third essay, after repeated interactions with Rebo Junior (paired-samples t-test t13=3.00, p=.010 from Essay 1 to Essay 3). However, we also observed a significant decrease in reflectivity in the Rebo Junior interactions over time (paired-samples t-test between the first and eighth interaction: t7=2.50, p=.041). We attribute this decline to i) the novelty of Rebo Junior wearing off (novelty effect) and ii) the apprentices learning the script and experiencing subsequent frustration due to the script not fading over time. Overall, this work i) informs future design through the observation of consistent decreases in engagement over 8 interactions with static scaffolding, and ii) contributes a reflection script applicable for reflection on tasks that resemble future expected work tasks, a typical setting in lifelong professional learning, and iii) indicates increased reflection competence after repeated reflection guided by a conversational agent.
Mirzababaei Behzad, Pammer-Schindler Viktoria
2021
This article discusses the usefulness of Toulmin’s model of arguments as structuring an assessment of different types of wrongness in an argument. We discuss the usability of the model within a conversational agent that aims to support users to develop a good argument. Within the article, we present a study and the development of classifiers that identify the existence of structural components in a good argument, namely a claim, a warrant (underlying understanding), and evidence. Based on a dataset (three sub-datasets with 100, 1,026, 211 responses in each) in which users argue about the intelligence or non-intelligence of entities, we have developed classifiers for these components: The existence and direction (positive/negative) of claims can be detected a weighted average F1 score over all classes (positive/negative/unknown) of 0.91. The existence of a warrant (with warrant/without warrant) can be detected with a weighted F1 score over all classes of 0.88. The existence of evidence (with evidence/without evidence) can be detected with a weighted average F1 score of 0.80. We argue that these scores are high enough to be of use within a conditional dialogue structure based on Bloom’s taxonomy of learning; and show by argument an example conditional dialogue structure that allows us to conduct coherent learning conversations. While in our described experiments, we show how Toulmin’s model of arguments can be used to identify structural problems with argumentation, we also discuss how Toulmin’s model of arguments could be used in conjunction with content-wise assessment of the correctness especially of the evidence component to identify more complex types of wrongness in arguments, where argument components are not well aligned. Owing to having progress in argument mining and conversational agents, the next challenges could be the developing agents that support learning argumentation. These agents could identify more complex type of wrongness in arguments that result from wrong connections between argumentation components.
Mirzababaei Behzad, Pammer-Schindler Viktoria
2021
This article discusses the usefulness of Toulmin’s model of arguments as structuring an assessment of different types of wrongness in an argument. We discuss the usability of the model within a conversational agent that aims to support users to develop a good argument. Within the article, we present a study and the development of classifiers that identify the existence of structural components in a good argument, namely a claim, a warrant (underlying understanding), and evidence. Based on a dataset (three sub-datasets with 100, 1,026, 211 responses in each) in which users argue about the intelligence or non-intelligence of entities, we have developed classifiers for these components: The existence and direction (positive/negative) of claims can be detected a weighted average F1 score over all classes (positive/negative/unknown) of 0.91. The existence of a warrant (with warrant/without warrant) can be detected with a weighted F1 score over all classes of 0.88. The existence of evidence (with evidence/without evidence) can be detected with a weighted average F1 score of 0.80. We argue that these scores are high enough to be of use within a conditional dialogue structure based on Bloom’s taxonomy of learning; and show by argument an example conditional dialogue structure that allows us to conduct coherent learning conversations. While in our described experiments, we show how Toulmin’s model of arguments can be used to identify structural problems with argumentation, we also discuss how Toulmin’s model of arguments could be used in conjunction with content-wise assessment of the correctness especially of the evidence component to identify more complex types of wrongness in arguments, where argument components are not well aligned. Owing to having progress in argument mining and conversational agents, the next challenges could be the developing agents that support learning argumentation. These agents could identify more complex type of wrongness in arguments that result from wrong connections between argumentation components.
Pammer-Schindler Viktoria, Prilla Michael
2021
A substantial body of human-computer interaction literature investigates tools that are intended to support reflection, e.g. under the header of quantified self or in computer-mediated learning. These works describe the issues that are reflected on by users in terms of examples, such as reflecting on financial expenditures, lifestyle, professional growth, etc. A coherent concept is missing. In this paper, the reflection object is developed based on activity theory, reflection theory and related design-oriented research. The reflection object is both what is reflected on and what is changed through reflection. It constitutes the link between reflection and other activities in which the reflecting person participates. By combining these two aspects—what is reflected on and what is changed—into a coherent conceptual unit, the concept of the reflection object provides a frame to focus on how to support learning, change and transformation, which is a major challenge when designing technologies for reflection.
Leski Florian, Fruhwirth Michael, Pammer-Schindler Viktoria
2021
The increasing volume of available data and the advances in analytics and artificial intelligence hold the potential for new business models also in offline-established organizations. To successfully implement a data-driven business model, it is crucial to understand the environment and the roles that need to be fulfilled by actors in the business model. This partner perspective is overlooked by current research on data-driven business models. In this paper, we present a structured literature review in which we identified 33 relevant publications. Based on this literature, we developed a framework consisting of eight roles and two attributes that can be assigned to actors as well as three classes of exchanged values between actors. Finally, we evaluated our framework through three cases from one automotive company collected via interviews in which we applied the framework to analyze data-driven business models for which our interviewees are responsible.
Pammer-Schindler Viktoria, Rosé Carolyn
2021
Professional and lifelong learning are a necessity for workers. This is true both for re-skilling from disappearing jobs, as well as for staying current within a professional domain. AI-enabled scaffolding and just-in-time and situated learning in the workplace offer a new frontier for future impact of AIED. The hallmark of this community’s work has been i) data-driven design of learning technology and ii) machine-learning enabled personalized interventions. In both cases, data are the foundation of AIED research and data-related ethics are thus central to AIED research. In this paper we formulate a vision how AIED research could address data-related ethics issues in informal and situated professional learning. The foundation of our vision is a secondary analysis of five research cases that offer insights related to data-driven adaptive technologies for informal professional learning. We describe the encountered data-related ethics issues. In our interpretation, we have developed three themes: Firstly, in informal and situated professional learning, relevant data about professional learning – to be used as a basis for learning analytics and reflection or as a basis for adaptive systems - is not only about learners. Instead, due to the situatedness of learning, relevant data is also about others (colleagues, customers, clients) and other objects from the learner’s context. Such data may be private, proprietary, or both. Secondly, manual tracking comes with high learner control over data. Thirdly, learning is not necessarily a shared goal in informal professional learning settings. From an ethics perspective, this is particularly problematic as much data that would be relevant for use within learning technologies hasn’t been collected for the purposes of learning. These three themes translate into challenges for AIED research that need to be addressed in order to successfully investigate and develop AIED technology for informal and situated professional learning. As an outlook of this paper, we connect these challenges to ongoing research directions within AIED – natural language processing, socio-technical design, and scenario-based data collection - that might be leveraged and aimed towards addressing data-related ethics challenges.
Fessl Angela, Maitz Katharina, Dennerlein Sebastian, Pammer-Schindler Viktoria
2021
Clear formulation and communication of learning goals is an acknowledged best practice in instruction at all levels. Typically, in curricula and course management systems, dedicated places for specifying learning goals at course-level exist. However, even in higher education, learning goals are typically formulated in a very heterogeneous manner. They are often not concrete enough to serve as guidance for students to master a lecture or to foster self-regulated learning. In this paper, we present a systematics for formulating learning goals for university courses, and a web-based widget that visualises these learning goals within a university's learning management system. The systematics is based on the revised version of Bloom's taxonomy of educational objectives by Anderson and Krathwohl. We evaluated both the learning goal systematics and the web-based widget in three lectures at our university.The participating lecturers perceived the systematics as easy-to-use and as helpful to structure their course and the learning content. Students' perceived benets lay in getting a quick overview of the lecture and its content as well as clear information regarding the requirements for passing the exam. By analysing the widget's activity log data, we could show that the widget helps students to track their learning progress and supports them in planning and conducting their learning in a self-regulated way. This work highlights how theory-based best practice in teaching can be transferred into a digital learning environment; at the same time it highlights that good non-technical systematics for formulating learning goals positively impacts on teaching and learning.
Rauter Romana, Lerch Anita, Lederer-Hutsteiner Thomas, Klinger Sabine, Mayr Andrea, Gutounig Robert, Pammer-Schindler Viktoria
2020
Barreiros Carla, Silva Nelson, Veas Eduardo Enrique, Pammer-Schindler Viktoria
2020
Dennerlein Sebastian, Wolf-Brenner Christof, Gutounig Robert, Schweiger Stefan, Pammer-Schindler Viktoria
2020
Künstliche Intelligenz (KI) ist zum Gegenstand gesellschaftlicher Debatten geworden. Die Beratung durch KI unterstützt uns in der Schule, im Alltag beim Einkauf, bei der Urlaubsplanung und beim Medienkonsum, manipuliert uns allerdings auch gezielt bei Entscheidungen oder führt durch Filter-Bubble-Phänomene zur Realitätsverzerrung.Eine der jüngsten Aufregungen hierzulande galt der Nutzung moderner Algorithmik durch das österreichische Arbeitsmarktservice AMS. Der sogenannte "AMS-Algorithmus" soll Beratende bei der Entscheidung über Fördermaßnahmen unterstützen.Wenn KI in einem so erheblichen Ausmaß in menschliches Handeln eingreift, bedarf sie im Hinblick auf ethische Prinzipien einer sorgfältigen Bewertung. Das ist notwendig, um unethische Folgen zu vermeiden. Üblicherweise wird gefordert, KI bzw. Algorithmen sollen fair sein, was bedeutet, sie sollen nicht diskriminieren und transparent sollen sie sein, also Einblick in ihre Funktionsweise ermöglichen
Dennerlein Sebastian, Wolf-Brenner Christof, Gutounig Robert, Schweiger Stefan, Pammer-Schindler Viktoria
2020
In society and politics, there is a rising interest in considering ethical principles in technological innovation, especially in the intersection of education and technology. We propose a first iteration of a theory-derived framework to analyze ethical issues in technology-enhanced learning (TEL) software development. The framework understands ethical issues as an expression of the overall socio-technical system that are rooted in the interactions of human actors with technology, so-called socio-technical interactions (STIs). For guiding ethical reflection, the framework helps to explicate this human involvement, and to elicit discussions of ethical principles on these STIs. Prompts in the form of reflection questions can be inferred to reflect on the technology functionality from relevant human perspectives, and in relation to a list of fundamental ethical principles. We illustrate the framework and discuss its implications for TEL
Gayane Sedrakya, Dennerlein Sebastian, Pammer-Schindler Viktoria, Lindstaedt Stefanie
2020
Our earlier research attempts to close the gap between learning behavior analytics based dashboard feedback and learning theories by grounding the idea of dashboard feedback onto learning science concepts such as feedback, learning goals, (socio-/meta-) cognitive mechanisms underlying learning processes. This work extends the earlier research by proposing mechanisms for making those concepts and relationships measurable. The outcome is a complementary framework that allows identifying feedback needs and timing for their provision in a generic context that can be applied to a certain subject in a given LMS. The research serves as general guidelines for educators in designing educational dashboards, as well as a starting research platform in the direction of systematically matching learning sciences concepts with data and analytics concepts
Fruhwirth Michael, Breitfuß Gert, Pammer-Schindler Viktoria
2020
The availability of data sources and advances in analytics and artificial intelligence offers the opportunity for organizationsto develop new data-driven products, services and business models. Though, this process is challenging for traditionalorganizations, as it requires knowledge and collaboration from several disciplines such as data science, domain experts, orbusiness perspective. Furthermore, it is challenging to craft a meaningful value proposition based on data; whereas existingresearch can provide little guidance. To overcome those challenges, we conducted a Design Science Research project toderive requirements from literature and a case study, develop a collaborative visual tool and evaluate it through severalworkshops with traditional organizations. This paper presents the Data Product Canvas, a tool connecting data sources withthe user challenges and wishes through several intermediate steps. Thus, this paper contributes to the scientific body ofknowledge on developing data-driven business models, products and services.
Fruhwirth Michael, Ropposch Christiana, Pammer-Schindler Viktoria
2020
Purpose: This paper synthesizes existing research on tools and methods that support data-driven business model innovation, and maps out relevant directions for future research.Design/methodology/approach: We have carried out a structured literature review and collected and analysed a respectable but not excessively large number of 33 publications, due to the comparatively emergent nature of the field.Findings: Current literature on supporting data-driven business model innovation differs in the types of contribution (taxonomies, patterns, visual tools, methods, IT tool and processes), the types of thinking supported (divergent and convergent) and the elements of the business models that are addressed by the research (value creation, value capturing and value proposition).Research implications: Our review highlights the following as relevant directions for future research. Firstly, most research focusses on supporting divergent thinking, i.e. ideation. However, convergent thinking, i.e. evaluating, prioritizing, and deciding, is also necessary. Secondly, the complete procedure of developing data-driven business models and also the development on chains of tools related to this have been under-investigated. Thirdly, scarcely any IT tools specifically support the development of data-driven business models. These avenues also highlight the necessity to integrate between research on specifics of data in business model innovation, on innovation management, information systems and business analytics.Originality/Value: This paper is the first to synthesize the literature on how to identify and develop data-driven
Dennerlein Sebastian, Pammer-Schindler Viktoria, Ebner Markus, Getzinger Günter, Ebner Martin
2020
Sustainably digitalizing higher education requires a human-centred approach. To address actual problems in teaching as well as learning and increase acceptance, the Technology Enhanced Learning (TEL) solution(s) must be co-designed with affected researchers, teachers, students and administrative staff. We present research-in-progress about a sandpit-informed innovation process with a f2f-marketplace of TEL research and problemmapping as well team formation alongside a competitive call phase, which is followed by a cooperative phase of funded interdisciplinary pilot teams codesigning and implementing TEL innovations. Pilot teams are supported by a University Innovation Canvas to document and reflect on their TEL innovation from multiple viewpoints.
Fadljevic Leon, Maitz Katharina, Kowald Dominik, Pammer-Schindler Viktoria, Gasteiger-Klicpera Barbara
2020
This paper describes the analysis of temporal behavior of 11--15 year old students in a heavily instructionally designed adaptive e-learning environment. The e-learning system is designed to support student's acquisition of health literacy. The system adapts text difficulty depending on students' reading competence, grouping students into four competence levels. Content for the four levels of reading competence was created by clinical psychologists, pedagogues and medicine students. The e-learning system consists of an initial reading competence assessment, texts about health issues, and learning tasks related to these texts. The research question we investigate in this work is whether temporal behavior is a differentiator between students despite the system's adaptation to students' reading competence, and despite students having comparatively little freedom of action within the system. Further, we also investigated the correlation of temporal behaviour with performance. Unsupervised clustering clearly separates students into slow and fast students with respect to the time they take to complete tasks. Furthermore, topic completion time is linearly correlated with performance in the tasks. This means that we interpret working slowly in this case as diligence, which leads to more correct answers, even though the level of text difficulty matches student's reading competence. This result also points to the design opportunity to integrate advice on overarching learning strategies, such as working diligently instead of rushing through, into the student's overall learning activity. This can be done either by teachers, or via additional adaptive learning guidance within the system.
Thalmann Stefan, Fessl Angela, Pammer-Schindler Viktoria
2020
Digitization is currently one of the major factors changing society and the business world. Most research focused on the technical issues of this change, but also employees and especially the way how they learn changes dramatically. In this paper, we are interested in exploring the perspectives of decision makers in huge manufacturing companies on current challenges in organizing learning and knowledge distribution in digitized manufacturing environments. Moreover, weinvestigated the change process and challenges of implementing new knowledge and learning processes.To this purpose, we have conducted 24 interviews with senior representatives of large manufacturing companies from Austria, Germany, Italy, Liechtenstein and Switzerland. Our exploratory study shows that decision makers perceive significant changes in work practice of manufacturing due to digitization and they currently plan changes in organizational training and knowledge distribution processes in response. Due to the lack of best practices, companies focus verymuch on technological advancements. The delivery of knowledge just-in-time directly into work practice is afavorite approach. Overall, digital learning services are growing and new requirements regarding compliance,quality management and organisational culture arise.
Kaiser Rene_DB, Thalmann Stefan, Pammer-Schindler Viktoria, Fessl Angela
2020
Organisations participate in collaborative projects that include competitors for a number of strategic reasons, even whilst knowing that this requires them to consider both knowledge sharing and knowledge protection throughout collaboration. In this paper, we investigated which knowledge protection practices representatives of organizations employ in a collaborative research and innovation project that can be characterized as a co-opetitive setting. We conducted a series of 30 interviews and report the following seven practices in structured form: restrictive partner selection in operative project tasks, communication through a gatekeeper, to limit access to a central platform, to hide details of machine data dumps, to have data not leave a factory for analysis, a generic model enabling to hide usage parameters, and to apply legal measures. When connecting each practice to a priori literature, we find three practices focussing on collaborative data analytics tasks had not yet been covered so far.
Fessl Angela, Apaolaza Aitor, Gledson Ann, Pammer-Schindler Viktoria, Vigo Markel
2019
Searching on the web is a key activity for working and learning purposes. In this work, we aimed to motivate users to reflect on their search behaviour, and to experiment with different search functionalities. We implemented a widget that logs user interactions within a search platform, mirrors back search behaviours to users, and prompts users to reflect about it. We carried out two studies to evaluate the impact of such widget on search behaviour: in Study 1 (N = 76), participants received screenshots of the widget including reflection prompts while in Study 2 (N = 15), a maximum of 10 search tasks were conducted by participants over a period of two weeks on a search platform that contained the widget. Study 1 shows that reflection prompts induce meaningful insights about search behaviour. Study 2 suggests that, when using a novel search platform for the first time, those participants who had the widget prioritised search behaviours over time. The incorporation of the widget into the search platform after users had become familiar with it, however, was not observed to impact search behaviour. While the potential to support un-learning of routines could not be shown, the two studies suggest the widget’s usability, perceived usefulness, potential to induce reflection and potential to impact search behaviour.
Fruhwirth Michael, Pammer-Schindler Viktoria, Thalmann Stefan
2019
Data plays a central role in many of today's business models. With the help of advanced analytics, knowledge about real-world phenomena can be discovered from data. This may lead to unintended knowledge spillover through a data-driven offering. To properly consider this risk in the design of data-driven business models, suitable decision support is needed. Prior research on approaches that support such decision-making is scarce. We frame designing business models as a set of decision problems with the lens of Behavioral Decision Theory and describe a Design Science Research project conducted in the context of an automotive company. We develop an artefact that supports identifying knowledge risks, concomitant with design decisions, during the design of data-driven business models and verify knowledge risks as a relevant problem. In further research, we explore the problem in-depth and further design and evaluate the artefact within the same company as well as in other companies.
Barreiros Carla, Pammer-Schindler Viktoria, Veas Eduardo Enrique
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.
Pammer-Schindler Viktoria
2019
This is a commentary of mine, created in the context of an open review process, selected for publication alongside the accepted original paper in a juried process, and published alongside the paper at the given DOI,
Xie Benjamin, Harpstead Erik, DiSalvo Betsy, Slovak Petr, Kharuffa Ahmed, Lee Michael J., Pammer-Schindler Viktoria, Ogan Amy, Williams Joseph Jay
2019
Renner Bettina, Wesiak Gudrun, Pammer-Schindler Viktoria, Prilla Michael, Müller Lars, Morosini Dalia, Mora Simone, Faltin Nils, Cress Ulrike
2019
Fessl Angela, Simic Ilija, Barthold Sabine, Pammer-Schindler Viktoria
2019
Information literacy, the access to knowledge and use of it are becoming a precondition for individuals to actively take part in social,economic, cultural and political life. Information literacy must be considered as a fundamental competency like the ability to read, write and calculate. Therefore, we are working on automatic learning guidance with respect to three modules of the information literacy curriculum developed by the EU (DigComp 2.1 Framework). In prior work, we havelaid out the essential research questions from a technical side. In this work, we follow-up by specifying the concept to micro learning, and micro learning content units. This means, that the overall intervention that we design is concretized to: The widget is initialized by assessing the learners competence with the help of a knowledge test. This is the basis for recommending suitable micro learning content, adapted to the identified competence level. After the learner has read/worked through the content, the widget asks a reflective question to the learner. The goal of the reflective question is to deepen the learning. In this paper we present the concept of the widget and its integration in a search platform.
Breitfuß Gert, Fruhwirth Michael, Pammer-Schindler Viktoria, Stern Hermann, Dennerlein Sebastian
2019
Increasing digitization is generating more and more data in all areas ofbusiness. Modern analytical methods open up these large amounts of data forbusiness value creation. Expected business value ranges from process optimizationsuch as reduction of maintenance work and strategic decision support to businessmodel innovation. In the development of a data-driven business model, it is usefulto conceptualise elements of data-driven business models in order to differentiateand compare between examples of a data-driven business model and to think ofopportunities for using data to innovate an existing or design a new businessmodel. The goal of this paper is to identify a conceptual tool that supports datadrivenbusiness model innovation in a similar manner: We applied three existingclassification schemes to differentiate between data-driven business models basedon 30 examples for data-driven business model innovations. Subsequently, wepresent the strength and weaknesses of every scheme to identify possible blindspots for gaining business value out of data-driven activities. Following thisdiscussion, we outline a new classification scheme. The newly developed schemecombines all positive aspects from the three analysed classification models andresolves the identified weaknesses.
Fessl Angela, Wesiak Gudrun, Pammer-Schindler Viktoria
2018
Managing knowledge in periods of digital change requires not only changes in learning processes but also in knowledge transfer. For this knowledge transfer, we see reflective learning as an important strategy to keep the vast body of theoretical knowledge fresh and up-to-date, and to transfer theoretical knowledge to practical experience. In this work, we present a study situated in a qualification program for stroke nurses in Germany. In the seven-week study, 21 stroke nurses used a quiz on medical knowledge as an additional learning instrument. The quiz contained typical quiz questions (“content questions”) as well as reflective questions that aimed at stimulating nurses to reflect on the practical relevance of the learned knowledge. We particularly looked at how reflective questions can support the transfer of theoretical knowledge into practice. The results show that by playful learning and presenting reflective questions at the right time, participants reflected and related theoretical knowledge to practical experience.
Pammer-Schindler Viktoria, Fessl Angela, Wertner Alfred
2018
Becoming a data-savvy professional requires skills and competencesin information literacy, communication and collaboration, and content creationin digital environments. In this paper, we present a concept for automatic learningguidance in relation to an information literacy curriculum. The learning guidanceconcept has three components: Firstly, an open learner model in terms of an informationliteracy curriculum is created. Based on the data collected in the learnermodel, learning analytics is used in combination with a corresponding visualizationto present the current learning status of the learner. Secondly, reflectionprompts in form of sentence starters or reflective questions adaptive to the learnermodel aim to guide learning. Thirdly, learning resources are suggested that arestructured along learning goals to motivate learners to progress. The main contributionof this paper is to discuss what we see as main research challenges withrespect to existing literature on open learner modeling, learning analytics, recommendersystems for learning, and learning guidance.
Barreiros Carla, Veas Eduardo Enrique, Pammer-Schindler Viktoria
2018
In the context of the Internet of Things (IoT), every device have sensing and computing capabilities to enhance many aspects of human life. There are more and more IoT devices in our homes and at our workplaces, and they still depend on human expertise and intervention for tasks as maintenance and (re)configuration. Using biophilic design and calm computing principles, we developed a nature-inspired representation, BioIoT, to communicate sensor information. This visual language contributes to the users’ well-being and performance while being as easy to understand as traditional data representations. Our work is based on the assumption that if machines are perceived to be more like living beings, users will take better care of them, which ideally would translate into a better device maintenance. In addition, the users’ overall well-being can be improved by bringing nature to their lives. In this work, we present two use case scenarios under which the BioIoT concept can be applied and demonstrate its potential benefits in households and at workplaces.
Dennerlein Sebastian, Kowald Dominik, Lex Elisabeth, Ley Tobias, Pammer-Schindler Viktoria
2018
Co-Creation methods for interactive computer systems design are by now widely accepted as part of the methodological repertoire in any software development process. As the communityis becoming more and more aware of the factthat software is driven by complex, artificially intelligent algorithms, the question arises what “co-creation of algorithms” in the sense of users ex-plicitly shaping the parameters of algorithms during co-creation, could mean, and how it would work. They are not tangible like featuresin a tool and desired effects are harder to be explained or understood. Therefore, we propose an it-erative simulation-based Co-Design approach that allows to Co-Create Algo-rithms together with the domain professionals by making their assumptions and effects observable. The proposal is a methodological idea for discussion within the EC-TEL community, yet to be applied in a research practice
Cicchinelli Analia, Veas Eduardo Enrique, Pardo Abelardo, Pammer-Schindler Viktoria, Fessl Angela, Barreiros Carla, Lindstaedt Stefanie
2018
This paper aims to identify self-regulation strategies from students' interactions with the learning management system (LMS). We used learning analytics techniques to identify metacognitive and cognitive strategies in the data. We define three research questions that guide our studies analyzing i) self-assessments of motivation and self regulation strategies using standard methods to draw a baseline, ii) interactions with the LMS to find traces of self regulation in observable indicators, and iii) self regulation behaviours over the course duration. The results show that the observable indicators can better explain self-regulatory behaviour and its influence in performance than preliminary subjective assessments.
Fessl Angela, Wertner Alfred, Pammer-Schindler Viktoria
2018
In this demonstration paper, we describe a prototype that visualizes usage of different search interfaces on a single search platform with the goal to motivate users to explore alternative search interfaces. The underlying rationale is, that by now the one-line-input to search engines is so standard, that we can assume users’ search behavior to be operationalized. This means, that users may be reluctant to explore alternatives even though these may be suited better to their context of use / search task.
Pammer-Schindler Viktoria, Thalmann Stefan, Fessl Angela, Füssel Julia
2018
Traditionally, professional learning for senior professionalsis organized around face-2-face trainings. Virtual trainingsseem to offer an opportunity to reduce costs related to traveland travel time. In this paper we present a comparative casestudy that investigates the differences between traditionalface-2-face trainings in physical reality, and virtualtrainings via WebEx. Our goal is to identify how the way ofcommunication impacts interaction between trainees,between trainees and trainers, and how it impactsinterruptions. We present qualitative results fromobservations and interviews of three cases in differentsetups (traditional classroom, web-based with allparticipants co-located, web-based with all participants atdifferent locations) and with overall 25 training participantsand three trainers. The study is set within one of the BigFour global auditing companies, with advanced seniorauditors as learning cohort
Fruhwirth Michael, Breitfuß Gert, Pammer-Schindler Viktoria
2018
The increasing amount of generated data and advances in technology and data analytics and are enablers and drivers for new business models with data as a key resource. Currently established organisations struggle with identifying the value and benefits of data and have a lack of know-how, how to develop new products and services based on data. There is very little research that is narrowly focused on data-driven business model innovation in established organisations. The aim of this research is to investigate existing activities within Austrians enterprises with regard to exploring data-driven business models and challenges encountered in this endeavour. The outcome of the research in progress paper are categories of challenges related to organisation, business and technology, established organisations in Austria face during data-driven business model innovation
Wertner Alfred, Stern Hermann, Pammer-Schindler Viktoria, Weghofer Franz
2018
Sprachsteuerung stellt ein potentiell sehr mächtiges Werkzeug dar und sollte rein von der Theorie (grundlegende Spracheingabe) her schon seit 20 Jahren einsetzbar sein. Sie ist in der Vergangenheit im industriellen Umfeld jedoch primär an nicht ausgereifter Hardware oder gar der Notwendigkeit einer firmenexternen aktiven Datenverbindung gescheitert. Bei Magna Steyr am Standort Graz wird die Kommissionierung bisher mit Hilfe von Scan-nern erledigt. Dieser Prozess ließe sich sehr effektiv durch eine durchgängige Sprachsteue-rung unterstützen, wenn diese einfach, zuverlässig sowie Compliance-konform umsetzbar wäre und weiterhin den Menschen als zentralen Mittelpunkt und Akteur (Stichwort Hu-man in the Loop) verstehen würde. Daher wurden bestehende Spracherkennungssysteme für mobile Plattformen sowie passende „off the shelf“ Hardware (Smartphones und Headsets) ausgewählt und prototypisch als Android Applikation („Talk2Me“) umgesetzt. Ziel war es, eine Aussage über die Einsetzbarkeit von sprachgesteuerten mobilen Anwen-dungen im industriellen Umfeld liefern zu können.Mit dem Open Source Speech Recognition Kit CMU Sphinx in Kombination mit speziell auf das Vokabular der abgebildeten Prozesse angepassten Wörterbüchern konnten wir eine sehr gute Erkennungsrate erreichen ohne das Sprachmodell individuell auf einzelne Mitar-beiterInnen trainieren zu müssen. Talk2Me zeigt innovativ, wie erprobte, kostengünstige und verfügbare Technologie (Smartphones und Spracherkennung als Eingabe sowie Sprachsynthese als Ausgabe) Ein-zug in unseren Arbeitsalltag haben kann.
Barreiros Carla, Veas Eduardo Enrique, Pammer-Schindler Viktoria
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.
Lukas Sabine, Pammer-Schindler Viktoria, Almer Alexander, Schnabel Thomas
2017
Köfler Armin, Pammer-Schindler Viktoria, Almer Alexander, Schnabel Thomas
2017
Breitfuß Gert, Kaiser Rene_DB, Kern Roman, Kowald Dominik, Lex Elisabeth, Pammer-Schindler Viktoria, Veas Eduardo Enrique
2017
Proceedings of the Workshop Papers of i-Know 2017, co-located with International Conference on Knowledge Technologies and Data-Driven Business 2017 (i-Know 2017), Graz, Austria, October 11-12, 2017.
Luzhnica Granit, Veas Eduardo Enrique, Stein Sebastian, Pammer-Schindler Viktoria, Williamson John, Murray-Smith Roderick
2017
Haptic displays are commonly limited to transmitting a dis- crete set of tactile motives. In this paper, we explore the transmission of real-valued information through vibrotactile displays. We simulate spatial continuity with three perceptual models commonly used to create phantom sensations: the lin- ear, logarithmic and power model. We show that these generic models lead to limited decoding precision, and propose a method for model personalization adjusting to idiosyncratic and spatial variations in perceptual sensitivity. We evaluate this approach using two haptic display layouts: circular, worn around the wrist and the upper arm, and straight, worn along the forearm. Results of a user study measuring continuous value decoding precision show that users were able to decode continuous values with relatively high accuracy (4.4% mean error), circular layouts performed particularly well, and per- sonalisation through sensitivity adjustment increased decoding precision.
Barreiros Carla, Veas Eduardo Enrique, Pammer-Schindler Viktoria
2017
In our research we explore representing the state of production machines using a new nature metaphor, called BioIoT. The underlying rationale is to represent relevant information in an agreeable manner and to increase machines’ appeal to operators. In this paper we describe a study with twelve participants in which sensory information of a coffee machine is encoded in a virtual tree. All participants considered the interaction with the BioIoT pleasant; and most reported to feel more inclined to perform machine maintenance, take “care” for the machine, than given classic state representation. The study highlights as directions for follow-up research personalization, intelligibility vs representational power, limits of the metaphor, and immersive visualization.
Thalmann Stefan, Larrazábal Jorge, Pammer-Schindler Viktoria, Kreuzthaler Armin, Fessl Angela
2017
n times of globalization, also workforce needs to be able to go global. This holds true especially for technical experts holding an exclusive expertise. Together with a global manufacturing company, we addressed the challenge of being able to send staff into foreign countries for managing technical projects in the foreign language. We developed a language learning concept that combines a language learning platform with conventional individual but virtually conducted coaching sessions. In our use case, we developed this ...
Thalmann Stefan, Pammer-Schindler Viktoria
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
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, Wiese Michael, Thalmann Stefan
2017
Financial auditors routinely search internal as well as public knowledge bases as part of the auditing process. Efficient search strategies are crucial for knowledge workers in general and for auditors in particular. Modern search technology quickly evolves; and features beyond keyword search like fac-etted search or visual overview of knowledge bases like graph visualisations emerge. It is therefore desirable for auditors to learn about new innovations and to explore and experiment with such technologies. In this paper, we present a reflection intervention concept that intends to nudge auditors to reflect on their search behaviour and to trigger informal learning in terms of by trying out new or less frequently used search features. The reflection intervention concept has been tested in a focus group with six auditors using a mockup. Foremost, the discussion centred on the timing of reflection interventions and how to raise mo-tivation to achieve a change in search behaviour.
Pammer-Schindler Viktoria, Fessl Angela, Wesiak Gudrun, Feyertag Sandra, Rivera-Pelayo Verónica
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
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.
Stern Hermann, Dennerlein Sebastian, Pammer-Schindler Viktoria, Ginthör Robert, Breitfuß Gert
2017
To specify the current understanding of business models in the realm of Big Data, we used a qualitative approach analysing 25 Big Data projects spread over the domains of Retail, Energy, Production, and Life Sciences, and various company types (SME, group, start-up, etc.). All projects have been conducted in the last two years at Austria’s competence center for Data-driven Business and Big Data Analytics, the Know-Center.
Luzhnica Granit, Öjeling Christoffer, Veas Eduardo Enrique, Pammer-Schindler Viktoria
2016
This paper presents and discusses the technical concept of a virtualreality version of the Sokoban game with a tangible interface. Theunderlying rationale is to provide spinal-cord injury patients whoare learning to use a neuroprosthesis to restore their capability ofgrasping with a game environment for training. We describe as rel-evant elements to be considered in such a gaming concept: input,output, virtual objects, physical objects, activity tracking and per-sonalised level recommender. Finally, we also describe our experi-ences with instantiating the overall concept with hand-held mobilephones, smart glasses and a head mounted cardboard setup
Fessl Angela, Pammer-Schindler Viktoria, Blunk Oliver, Prilla Michael
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.
Luzhnica Granit, Veas Eduardo Enrique, Pammer-Schindler Viktoria
2016
This paper presents and discusses the technical concept of a virtualreality version of the Sokoban game with a tangible interface. Theunderlying rationale is to provide spinal-cord injury patients whoare learning to use a neuroprosthesis to restore their capability ofgrasping with a game environment for training. We describe as rel-evant elements to be considered in such a gaming concept: input,output, virtual objects, physical objects, activity tracking and per-sonalised level recommender. Finally, we also describe our experi-ences with instantiating the overall concept with hand-held mobilephones, smart glasses and a head mounted cardboard setup.Index Terms: H.5.2 [HCI]: User Interfaces—Input devicesand strategies; H.5.1 [HCI]: Multimedia Information Systems—Artificial, augmented, and virtual realities
Barreiros Carla, Veas Eduardo Enrique, Pammer-Schindler Viktoria
2016
The movement towards cyberphysical systems and Industry 4.0promises to imbue each and every stage of production with a myr-iad of sensors. The open question is how people are to comprehendand interact with data originating from industrial machinery. Wepropose a metaphor that compares machines with natural beingsthat appeal to people by representing machine states with patternsoccurring in nature. Our approach uses augmented reality (AR)to represent machine states as trees of different shapes and col-ors (BioAR). We performed a study on pre-attentive processing ofvisual features in AR to determine if our BioAR metaphor con-veys fast changes unambiguously and accurately. Our results indi-cate that the visual features in our BioAR metaphor are processedpre-attentively. In contrast to previous research, for the BioARmetaphor, variations in form induced less errors than variations inhue in the target detection task.
Luzhnica Granit, Veas Eduardo Enrique, Pammer-Schindler Viktoria
2016
This paper investigates the communication of natural lan-guage messages using a wearable haptic display. Our re-search spans both the design of the haptic display, as wellas the methods for communication that use it. First, threewearable configurations are proposed basing on haptic per-ception fundamentals. To encode symbols, we devise an over-lapping spatiotemporal stimulation (OST) method, that dis-tributes stimuli spatially and temporally with a minima gap.An empirical study shows that, compared with spatial stimu-lation, OST is preferred in terms of recall. Second, we pro-pose an encoding for the entire English alphabet and a train-ing method for letters, words and phrases. A second study in-vestigates communication accuracy. It puts four participantsthrough five sessions, for an overall training time of approx-imately 5 hours per participant. Results reveal that after onehour of training, participants were able to discern 16 letters,and identify two- and three-letter words. They could discernthe full English alphabet (26letters,92%accuracy) after ap-proximately three hours of training, and after five hours par-ticipants were able to interpret words transmitted at an aver-age duration of0.6s per word
Luzhnica Granit, Pammer-Schindler Viktoria, Fessl Angela, Mutlu Belgin, Veas Eduardo Enrique
2016
Especially in lifelong or professional learning, the picture of a continuous learning analytics process emerges. In this proces s, het- erogeneous and changing data source applications provide data relevant to learning, at the same time as questions of learners to data cha nge. This reality challenges designers of analytics tools, as it req uires ana- lytics tools to deal with data and analytics tasks that are unk nown at application design time. In this paper, we describe a generic vi sualiza- tion tool that addresses these challenges by enabling the vis ualization of any activity log data. Furthermore, we evaluate how well parti cipants can answer questions about underlying data given such generic versus custom visualizations. Study participants performed better in 5 out of 10 tasks with the generic visualization tool, worse in 1 out of 1 0 tasks, and without significant difference when compared to the visuali zations within the data-source applications in the remaining 4 of 10 ta sks. The experiment clearly showcases that overall, generic, standalon e visualiza- tion tools have the potential to support analytical tasks suffi ciently well
Fessl Angela, Wesiak Gudrun, Pammer-Schindler Viktoria
2016
Reflective learning is an important strategy to keep the vast body of theoretical knowledge fresh, stay up-to-date with new knowledge, and to relate theoretical knowledge to practical experience. In this work, we present a study situated in a qualification program for stroke nurses in Germany. In the seven-week study, $21$ stroke nurses used a quiz on medical knowledge as additional learning instrument. The quiz contained typical quiz questions (``content questions'') as well as reflective questions that aimed at stimulating nurses to reflect on the practical relevance of the learned knowledge.We particularly looked at how reflective questions can support the transfer of theoretical knowledge to practice.The results show that by playful learning and presenting reflective questions at the right time, participants were motivated to reflect, deepened their knowledge and related theoretical knowledge to practical experience. Subsequently, they were able to better understand patient treatments and increased their self-confidence.
Simon Jörg Peter, Schmidt Peter, Pammer-Schindler Viktoria
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.
Luzhnica Granit, Simon Jörg Peter, Lex Elisabeth, Pammer-Schindler Viktoria
2016
This paper explores the recognition of hand gestures based on a dataglove equipped with motion, bending and pressure sensors. We se-lected 31 natural and interaction-oriented hand gestures that canbe adopted for general-purpose control of and communication withcomputing systems. The data glove is custom-built, and contains13 bend sensors, 7 motion sensors, 5 pressure sensors and a magne-tometer. We present the data collection experiment, as well as thedesign, selection and evaluation of a classification algorithm. As weuse a sliding window approach to data processing, our algorithm issuitable for stream data processing. Algorithm selection and featureengineering resulted in a combination of linear discriminant anal-ysis and logistic regression with which we achieve an accuracy ofover 98. 5% on a continuous data stream scenario. When removingthe computationally expensive FFT-based features, we still achievean accuracy of 98. 2%.
Wertner Alfred, Pammer-Schindler Viktoria, Czech Paul
2015
Fall detection is a classical use case for mobile phone sensing.Nonetheless, no open dataset exists that could be used totrain, test and compare fall detection algorithms.We present a dataset for mobile phone sensing-based fall detection.The dataset contains both accelerometer and gyroscopedata. Data were labelled with four types of falls(e.g., “stumbling”) and ten types of non-fall activities (e.g.,“sit down”). The dataset was collected with martial artistswho simulated falls. We used five different state-of-the-artAndroid smartphone models worn on the hip in a small bag.Due to the datasets properties of using multiple devices andbeing labelled with multiple fall- and non-fall categories, weargue that it is suitable to serve as benchmark dataset.
Simon Jörg Peter, Schmidt Peter, Pammer-Schindler Viktoria
2015
Synchronisation algorithms are central components of collab- orative editing software. The energy efficiency for such algo- rithms becomes of interest to a wide community of mobile application developers. In this paper we explore the differen- tial synchronisation (diffsync) algorithm with respect to en- ergy consumption on mobile devices. We identify three areas for optimisation: a.) Empty cycles where diffsync is executed although no changes need to be processed b.) tail energy by adapting cycle intervals and c.) computational complexity. 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. Discussions within this paper are based on real usage data of PDF annotations via the Mendeley iOS app.
Kravcik Milos, Mikroyannidis Alexander, Pammer-Schindler Viktoria, Prilla Michael , Ullmann T.D.
2015
Pammer-Schindler Viktoria, Bratic Marina, Feyertag Sandra, Faltin Nils
2015
We report two 6-week studies, each with 10 participants, on improving time management. In each study a different interventions was administered, in parallel to otherwise regular work: In the self-tracking setting, participants used only an activity logging tool to track their time use and a reflective practice, namely daily review of time use, to improve time management. In the coaching setting, participants did the same, but additionally received weekly bilateral coaching. In both settings, participants reported learning about time management. This is encouraging, as such self-directed learning is clearly cheaper than coaching. Only participants in the coaching setting however improved their self-assessment with respect to predefined time management best practices. The Value of Self-tracking and the Added Value of Coaching in the Case of Improving Time Management. Available from: https://www.researchgate.net/publication/300259607_The_Value_of_Self-tracking_and_the_Added_Value_of_Coaching_in_the_Case_of_Improving_Time_Management [accessed Oct 24 2017].
Scherer Reinhold, Schwarz Andreas , Müller-Putz G. R. , Pammer-Schindler Viktoria, Lloria Garcia Mariano
2015
Mutual brain-machine co-adaptation is the mostcommon approach used to gain control over spontaneouselectroencephalogram (EEG) based brain-computer interfaces(BCIs). Co-adaptation means the concurrent or alternating useof machine learning and the brain’s reinforcement learningmechanisms. Results from the literature, however, suggest thatcurrent implementations of this approach does not lead todesired results (“BCI inefficiency”). In this paper, we proposean alternative strategy that implements some recommendationsfrom educational psychology and instructional design. We presenta jigsaw puzzle game for Android devices developed to train theBCI skill in individuals with cerebral palsy (CP). Preliminaryresults of a supporting study in four CP users suggest high useracceptance. Three out of the four users achieved better thanchance accuracy in arranging pieces to form the puzzle.Index Terms—Brain-Computer Interface, Electroencephalo-gram, Human-Computer Interaction, Game-based learning,Cerebral palsy.
Fessl Angela, Feyertag Sandra, Pammer-Schindler Viktoria
2015
This paper presents a case study on co-designing digitaltechnologies for knowledge management and data-driven businessfor an SME. The goal of the case study was to analysethe status quo of technology usage and to develop designsuggestions in form of mock-ups tailored to the company’sneeds. We used both requirements engineering and interactivesystem design methods such as interviews, workshops,and mock-ups for work analysis and system design. The casestudy illustrates step-by-step the processes of knowledge extractionand combination (analysis) and innovation creation(design). These processes resulted in non-functional mockups,which are planned to be implemented within the SME.
Wertner Alfred, Czech Paul, Pammer-Schindler Viktoria
2015
Fall detection is a classical use case for mobile phone sensing.Nonetheless, no open dataset exists that could be used totrain, test and compare fall detection algorithms.We present a dataset for mobile phone sensing-based fall detection.The dataset contains both accelerometer and gyroscopedata. Data were labelled with four types of falls(e.g., “stumbling”) and ten types of non-fall activities (e.g.,“sit down”). The dataset was collected with martial artistswho simulated falls. We used five different state-of-the-artAndroid smartphone models worn on the hip in a small bag.Due to the datasets properties of using multiple devices andbeing labelled with multiple fall- and non-fall categories, weargue that it is suitable to serve as benchmark dataset.
Simon Jörg Peter, Pammer-Schindler Viktoria, Schmidt Peter
2015
Synchronisation algorithms are central components of collab- orative editing software. The energy efficiency for such algo- rithms becomes of interest to a wide community of mobile application developers. In this paper we explore the differen- tial synchronisation (diffsync) algorithm with respect to en- ergy consumption on mobile devices.We identify three areas for optimisation: a.) Empty cycles where diffsync is executed although no changes need to be processed b.) tail energy by adapting cycle intervals and c.) computational complexity. 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. Discussions within this paper are based on real usage data of PDF annotations via the Mendeley iOS app.
Fessl Angela, Bratic Marina, Pammer-Schindler Viktoria
2014
A continuous learning solution was sought which allows strokenurses to keep the vast body of theoretical knowledge fresh, stay up-to-datewith new knowledge, and relate theoretical knowledge to practical experience.Based on the theoretical background of learning in the medical domain,reflective and game-based learning, we carried out a user-oriented designprocess that involved a focus group and a design workshop. In this process, aquiz that includes both content-based and reflection questions was identified asa viable means of transportation for theoretical knowledge. In this paper wepresent the result of trialling a quiz with both content-based and metacognitive(reflective) questions in two settings: In one trial the quiz was used by nursesas part of a qualification programme for stroke nurses, in the second trial bynurses outside such a formal continuous learning setting. Both trials weresuccessful in terms of user acceptance, user satisfaction and learning. Beyondthis success report, we discuss barriers to integrating a quiz into work processeswithin an emergency ward such as a stroke unit.
Pammer-Schindler Viktoria, Simon Jörg Peter, Wilding Karin, Keller Stephan, Scherer Reinhold
2014
Brain-computer interface (BCI) technology translatesbrain activity to machine-intelligible patterns, thusserving as input “device” to computers. BCI traininggames make the process of acquiring training data forthe machine learning more engaging for the users. Inthis work, we discuss the design space for BCI traininggames based on existing literature, and a traininggame in form of a Jigsaw Puzzle. The game wastrialled with four cerebral palsy patients. All patientswere very acceptant of the involved technology, which,we argue, relates back to the concept of BCI traininggames plus the adaptations we made. On the otherhand, the data quality was unsatisfactory. Hence, infuture work both concept and implementation need tobe finetuned to achieve a balance between useracceptance and data quality.
Divitini Monica, Lindstaedt Stefanie , Pammer-Schindler Viktoria, Ley Tobias
2013
With this workshop, we intend to bring together the European communities of technology-enhanced learning, which typically meets at the ECTEL, and of computersupported cooperative work, which typically meets at the ECSCW. While the ECTEL community has traditionally focused on technology support for learning, be it in formal learning environments like schools, universities, etc. or in informal learning environments like workplaces, the ECSCW community has traditionally investigated how computers can and do mediate and influence collaborative work, in settings as diverse as the typical “gainful employment” situations, project work within university courses, volunteer settings in NGOs etc. Despite overlapping areas of concerns, the two communities are also exploiting different theories and methodological approaches. Within this workshop, we discuss issues that are relevant for both communities, and have the potential to contribute to a more lively communication between both communities.
Pammer-Schindler Viktoria, Kump Barbara, Lindstaedt Stefanie
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.
Erdmann Michael, Hansch Daniel, Pammer-Schindler Viktoria, Rospocher Marco, Ghidini Chiara, Lindstaedt Stefanie , Serafini Luciano
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.
Kump Barbara, Knipfer Kristin, Pammer-Schindler Viktoria, Schmidt Andreas, Maier Ronald, Kunzmann Christine, Cress Ulrike, Lindstaedt Stefanie
2011
The Knowledge Maturing Phase Model has been presented as a model aligning knowledge management and organizational learning. The core argument underlying the present paper is that maturing organizational knowhow requires individual and collaborative reflection at work. We present an explorative interview study that analyzes reflection at the workplace in four organizations in different European countries. Our qualitative findings suggest that reflection is not equally self-evident in different settings. A deeper analysis of the findings leads to the hypothesis that different levels of maturity of processes come along with different expectations towards the workers with regard to compliance and flexibility, and to different ways of how learning at work takes place. Furthermore, reflection in situations where the processes are in early maturing phases seems to lead to consolidation of best practice, while reflection in situations where processes are highly standardized may lead to a modification of these standard processes. Therefore, in order to support the maturing of organizational know-how by providing reflection support, one should take into account the degree of standardisation of the processes in the target group.
Lindstaedt Stefanie , Kump Barbara, Beham Günter, Pammer-Schindler Viktoria, Ley Tobias, de Hoog R., Dotan A.
2010
We present a work-integrated learning (WIL) concept which aims atempowering employees to learn while performing their work tasks. Withinthree usage scenarios we introduce the APOSDLE environment whichembodies the WIL concept and helps knowledge workers move fluidly alongthe whole spectrum of WIL activities. By doing so, they are experiencingvarying degrees of learning guidance: from building awareness, over exposingknowledge structures and contextualizing cooperation, to triggering reflectionand systematic competence development. Four key APOSDLE components areresponsible for providing this variety of learning guidance. The challenge intheir design lies in offering learning guidance without being domain-specificand without relying on manually created learning content. Our three monthsummative workplace evaluation within three application organizationssuggests that learners prefer awarenss building functionalities and descriptivelearning guidance and reveals that they benefited from it.
Pammer-Schindler Viktoria, Serafini L., Lindstaedt Stefanie
2009
Lindstaedt Stefanie , Rospocher M., Ghidini C., Pammer-Schindler Viktoria, Serafini L.
2009
Enterprise modelling focuses on the construction of a structureddescription of relevant aspects of an enterprise, the so-called enterprisemodel. Within this contribution we describe a wiki-based tool forenterprise modelling, called MoKi (Modelling wiKi). It specifically facilitatescollaboration between actors with different expertise to develop anenterprise model by using structural (formal) descriptions as well as moreinformal and semi-formal descriptions of knowledge. It also supports theintegrated development of interrelated models covering different aspectsof an enterprise.
Lindstaedt Stefanie , Ghidini C., Kump Barbara, Mahbub N., Pammer-Schindler Viktoria, Rospocher M., Serafini L.
2009
Enterprise modelling focuses on the construction of a structureddescription, the so-called enterprise model, which represents aspectsrelevant to the activity of an enterprise. Although it has becomeclearer recently that enterprise modelling is a collaborative activity, involvinga large number of people, most of the enterprise modelling toolsstill only support very limited degrees of collaboration. Within thiscontribution we describe a tool for enterprise modelling, called MoKi(MOdelling wiKI), which supports agile collaboration between all differentactors involved in the enterprise modelling activities. MoKi is basedon a Semantic Wiki and enables actors with different expertise to developan enterprise model not only using structural (formal) descriptions butalso adopting more informal and semi-formal descriptions of knowledge.
Lindstaedt Stefanie , Moerzinger R., Sorschag R. , Pammer-Schindler Viktoria, Thallinger G.
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”.
Lindstaedt Stefanie , Pammer-Schindler Viktoria, Mörzinger Roland, Kern Roman, Mülner Helmut, Wagner Claudia
2008
Imagine you are member of an online social systemand want to upload a picture into the community pool. In currentsocial software systems, you can probably tag your photo, shareit or send it to a photo printing service and multiple other stuff.The system creates around you a space full of pictures, otherinteresting content (descriptions, comments) and full of users aswell. The one thing current systems do not do, is understandwhat your pictures are about.We present here a collection of functionalities that make a stepin that direction when put together to be consumed by a tagrecommendation system for pictures. We use the data richnessinherent in social online environments for recommending tags byanalysing different aspects of the same data (text, visual contentand user context). We also give an assessment of the quality ofthus recommended tags.
Stocker A., Höfler Patrick, Granitzer Gisela, Willfort R., Anna Maria Köck, Pammer-Schindler Viktoria
2008
Social web platforms have become very popular in the so-called Web 2.0, and there is no end in sight. However, very few systematic models for the constitution of such sociotechnical infrastructures exist in the scientific literature. We therefore present a generic framework for building social web platforms based on the creation of value for individuals, communities and social networks. We applied this framework in the Neurovation project, aiming to establish a platform for creative knowledge workers. This paper describes work in progress and the lessons we have learned so far.
Lindstaedt Stefanie , , , Lokaiczyk R., Kump Barbara, Beham Günter, Pammer-Schindler Viktoria
2008
In order to support work-integrated learning scenarios task- andcompetency-aware knowledge services are needed. In this paper we introducethree key knowledge services of the APOSDLE system and illustrate how theyinteract. The context determination daemon observes user interactions andinfers the current work task of the user. The user profile service uses theidentified work tasks to determine the competences of the user. And finally, theassociative retrieval service utilizes both the current work task and the inferredcompetences to identify relevant (learning) content. All of these knowledgeservices improve through user feedback.
Christl C., Ghidini C. , Guss J., Lindstaedt Stefanie , Pammer-Schindler Viktoria, Scheir Peter, Serafini L.
2008
Modern businesses operate in a rapidly changing environment.Continuous learning is an essential ingredient in order to stay competitivein such environments. The APOSDLE system utilizes semanticweb technologies to create a generic system for supporting knowledgeworkers in different domains to learnwork. Since APOSDLE relies onthree interconnected semantic models to achieve this goal, the questionon how to efficiently create high-quality semantic models has become oneof the major research challenges. On the basis of two concrete examplesnamelydeployment of such a learning system at EADS, a large corporation,and deployment at ISN, a network of SMEs-we report in detail theissues a company has to face, when it wants to deploy a modern learningenvironment relying on semantic web technology.
Pammer-Schindler Viktoria, Lindstaedt Stefanie
Cicchinelli Analia, Pammer-Schindler Viktoria
Purpose – The goal of this study is to understand what drives people (i.e., their motivations, autonomous learning attitudes and learning interests) to volunteer as mentors for a program that helps families to ideate technological solutions to community problems.Design/methodology/approach – A three-phase method was used to i) create volunteer mentor profiles; ii) elicit topics of interest; and iii) establish relationships between those. The mentor profiles were based on self-assessments of motivation, attitudes towards lifelong learning and self-regulated learning strategies. The topics of interests were defined by analyzing answers to reflection questions. Statistical methods were applied to analyze the relationships between the interests and the mentor profiles.Findings –Three mentor groups (G1 “low,” G2 “high” and G3 “medium”) were identified based on pre-survey data via bottom-up clustering. Content analysis was used to define the topics of interest: communication skills; learning AI; mentoring; prototype development; problem solving skills; and working with families. Examining relationships between the mentor profile and the topics of interest showed that group G3 “medium” with strong intrinsic motivation had significantly more interest in working with families. The group with overall highest scores (G2 “high”) expressed substantial interest in learning about AI. However, there was a high variability between members of this group. Originality/value –The study established different types of learning interests of volunteer mentors and related them to the mentor profiles based on motivation, self-regulated learning strategies and attitudes towards lifelong learning. Such knowledge can help organizations shape volunteering experience, offering more value to volunteers. Furthermore, the reflection questions can be used by: i) volunteers as an instrument of reflection; and ii) organizations for eliciting learning interests of volunteers.