Know Center Research

Publikationen

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.
Müllner Peter , Schmerda Stefan, Theiler Dieter, Lindstaedt Stefanie , Kowald Dominik
2022
Data and algorithm sharing is an imperative part of data- and AI-driven economies. The efficient sharing of data and algorithms relies on the active interplay between users, data providers, and algorithm providers. Although recommender systems are known to effectively interconnect users and items in e-commerce settings, there is a lack of research on the applicability of recommender systems for data and algorithm sharing. To fill this gap, we identify six recommendation scenarios for supporting data and algorithm sharing, where four of these scenarios substantially differ from the traditional recommendation scenarios in e-commerce applications. We evaluate these recommendation scenarios using a novel dataset based on interaction data of the OpenML data and algorithm sharing platform, which we also provide for the scientific community. Specifically, we investigate three types of recommendation approaches, namely popularity-, collaboration-, and content-based recommendations. We find that collaboration-based recommendations provide the most accurate recommendations in all scenarios. Plus, the recommendation accuracy strongly depends on the specific scenario, e.g., algorithm recommendations for users are a more difficult problem than algorithm recommendations for datasets. Finally, the content-based approach generates the least popularity-biased recommendations that cover the most datasets and algorithms.
Lacic Emanuel, Fadljevic Leon, Weissenböck Franz, Lindstaedt Stefanie , Kowald Dominik
2022
Personalized news recommender systems support readers in finding the right and relevant articles in online news platforms. In this paper, we discuss the introduction of personalized, content-based news recommendations on DiePresse, a popular Austrian online news platform, focusing on two specific aspects: (i) user interface type, and (ii) popularity bias mitigation. Therefore, we conducted a two-weeks online study that started in October 2020, in which we analyzed the impact of recommendations on two user groups, i.e., anonymous and subscribed users, and three user interface types, i.e., on a desktop, mobile and tablet device. With respect to user interface types, we find that the probability of a recommendation to be seen is the highest for desktop devices, while the probability of interacting with recommendations is the highest for mobile devices. With respect to popularity bias mitigation, we find that personalized, content-based news recommendations can lead to a more balanced distribution of news articles' readership popularity in the case of anonymous users. Apart from that, we find that significant events (e.g., the COVID-19 lockdown announcement in Austria and the Vienna terror attack) influence the general consumption behavior of popular articles for both, anonymous and subscribed users
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
Lindstaedt Stefanie , Geiger Bernhard, Pirker Gerhard
2019
Big Data and data-driven modeling are receiving more and more attention in various research disciplines, where they are often considered as universal remedies. Despite their remarkable records of success, in certain cases a purely data-driven approach has proven to be suboptimal or even insufficient.This extended abstract briefly defines the terms Big Data and data-driven modeling and characterizes scenarios in which a strong focus on data has proven to be promising. Furthermore, it explains what progress can be made by fusing concepts from data science and machine learning with current physics-based concepts to form hybrid models, and how these can be applied successfully in the field of engine pre-simulation and engine control.
Kowald Dominik, Traub Matthias, Theiler Dieter, Gursch Heimo, Lacic Emanuel, Lindstaedt Stefanie , Kern Roman, Lex Elisabeth
2019
Kowald Dominik, Lacic Emanuel, Theiler Dieter, Traub Matthias, Kuffer Lucky, Lindstaedt Stefanie , Lex Elisabeth
2019
Thalmann Stefan, Gursch Heimo, Suschnigg Josef, Gashi Milot, Ennsbrunner Helmut, Fuchs Anna Katharina, Schreck Tobias, Mutlu Belgin, Mangler Jürgen, Huemer Christian, Lindstaedt Stefanie
2019
Current trends in manufacturing lead to more intelligent products, produced in global supply chains in shorter cycles, taking more and complex requirements into account. To manage this increasing complexity, cognitive decision support systems, building on data analytic approaches and focusing on the product life cycle, stages seem a promising approach. With two high-tech companies (world market leader in their domains) from Austria, we are approaching this challenge and jointly develop cognitive decision support systems for three real world industrial use cases. Within this position paper, we introduce our understanding of cognitive decision support and we introduce three industrial use cases, focusing on the requirements for cognitive decision support. Finally, we describe our preliminary solution approach for each use case and our next steps.
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.
Lindstaedt Stefanie , Ley Tobias, Klamma Ralf, Wild Fridolin
2016
Recognizing the need for addressing the rather fragmented character of research in this field, we have held a workshop on learning analytics for workplace and professional learning at the Learning Analytics and Knowledge (LAK) Conference. The workshop has taken a broad perspective, encompassing approaches from a number of previous traditions, such as adaptive learning, professional online communities, workplace learning and performance analytics. Being co-located with the LAK conference has provided an ideal venue for addressing common challenges and for benefiting from the strong research on learning analytics in other sectors that LAK has established. Learning Analytics for Workplace and Professional Learning is now on the research agenda of several ongoing EU projects, and therefore a number of follow-up activities are planned for strengthening integration in this emerging field.
Dennerlein Sebastian, Theiler Dieter, Marton Peter, Lindstaedt Stefanie , Lex Elisabeth, Santos Patricia, Cook John
2015
We present KnowBrain (KB), an open source Dropbox-like knowledge repository with social features for informal workplace learning. KB enables users (i) to share and collaboratively structure knowledge, (ii) to access knowledge via sophisticated content- and metadatabased search and recommendation, and (iii) to discuss artefacts by means of multimedia-enriched Q&A. As such, KB can support, integrate and foster various collaborative learning processes related to daily work-tasks.
Lindstaedt Stefanie , Reiter, T., Cik, M., Haberl, M., Breitwieser, C., Scherer, R., Kröll Mark, Horn Christopher, Müller-Putz, G., Fellendorf, M.
2013
Today, proper traffic incident management (IM) has to deal increasingly with problems such as traffic congestion and environmental sustainability. Therefore, IM intends to clear the road for traffic as quickly as possible after an incident has happened. Electronic data verifiably has great potential for supporting traffic incident management. As a consequence, this paper presents an innovative incident detection method using anonymized mobile communications data. The aim is to outline suitable methods for depicting the traffic situation of a designated test area. In order to be successful, the method needs to be able to calculate the traffic situation in-time and report anomalies back to the motorway operator. The resulting procedures are compared to data from real incidents and are thus validated. Special attention is turned to the question whether incidents can be detected quicker with the aid of mobile phone data than with conventional methods. Also, a focus is laid on the quicker deregistration of the incident, so that the traffic management can react superiorly.
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.
Höfler Patrick, Granitzer Michael, Sabol Vedran, Lindstaedt Stefanie
2013
Linked Data has become an essential part of the Semantic Web. A lot of Linked Data is already available in the Linked Open Data cloud, which keeps growing due to an influx of new data from research and open government activities. However, it is still quite difficult to access this wealth of semantically enriched data directly without having in-depth knowledge about SPARQL and related semantic technologies. In this paper, we present the Linked Data Query Wizard, a prototype that provides a Linked Data interface for non-expert users, focusing on keyword search as an entry point and a tabular interface providing simple functionality for filtering and exploration.
Kraker Peter, Trattner Christoph, Jack Kris, Lindstaedt Stefanie , Schlgl Christian
2013
At the beginning of a scientific study, it is usually quite hardto get an overview of a research field. We aim to addressthis problem of classic literature search using web data. Inthis extended abstract, we present work-in-progress on aninteractive visualization of research fields based on readershipstatistics from the social reference management systemMendeley. To that end, we use library co-occurrences as ameasure of subject similarity. In a first evaluation, we findthat the visualization covers current research areas withineducational technology but presents a view that is biasedby the characteristics of readers. With our presentation, wehope to elicit feedback from the Websci’13 audience on (1)the usefulness of the prototype, and (2) how to overcomethe aforementioned biases using collaborative constructiontechniques.
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.
Moskaliuk, J., Rath, A.S., Devaurs, D., Weber, N., Lindstaedt Stefanie , Kimmerle, J., Cress, U.
2011
Jointly working on shared digital artifacts – such as wikis – is a well-tried method of developing knowledge collectively within a group or organization. Our assumption is that such knowledge maturing is an accommodation process that can be measured by taking the writing process itself into account. This paper describes the development of a tool that detects accommodation automatically with the help of machine learning algorithms. We applied a software framework for task detection to the automatic identification of accommodation processes within a wiki. To set up the learning algorithms and test its performance, we conducted an empirical study, in which participants had to contribute to a wiki and, at the same time, identify their own tasks. Two domain experts evaluated the participants’ micro-tasks with regard to accommodation. We then applied an ontology-based task detection approach that identified accommodation with a rate of 79.12%. The potential use of our tool for measuring knowledge maturing online is discussed.
Kraker Peter, Wagner Claudia, Jeanquartier Fleur, Lindstaedt Stefanie
2011
This paper presents an adaptable system for detecting trends based on the micro-blogging service Twitter, and sets out to explore to what extent such a tool can support researchers. Twitter has high uptake in the scientific community, but there is a need for a means of extracting the most important topics from a Twitter stream. There are too many tweets to read them all, and there is no organized way of keeping up with the backlog. Following the cues of visual analytics, we use visualizations to show both the temporal evolution of topics, and the relations between different topics. The Twitter Trend Detection was evaluated in the domain of Technology Enhanced Learning (TEL). The evaluation results indicate that our prototype supports trend detection but reveals the need for refined preprocessing, and further zooming and filtering facilities.
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.
Lindstaedt Stefanie , Beham Günter, Stern Hermann, Drachsler H., Bogers T., Vuorikari R., Verbert K., Duval E., Manouselis N., Friedrich M., Wolpers M.
2010
This paper raises the issue of missing data sets for recommender systems in Technology Enhanced Learning that can be used asbenchmarks to compare different recommendation approaches. It discusses how suitable data sets could be created according tosome initial suggestions, and investigates a number of steps that may be followed in order to develop reference data sets that willbe adopted and reused within a scientific community. In addition, policies are discussed that are needed to enhance sharing ofdata sets by taking into account legal protection rights. Finally, an initial elaboration of a representation and exchange format forsharable TEL data sets is carried out. The paper concludes with future research needs.
Beham Günter, Kump Barbara, Lindstaedt Stefanie , Ley Tobias
2010
According to studies into learning at work, interpersonal help seeking is the most important strategy of how people acquireknowledge at their workplaces. Finding knowledgeable persons, however, can often be difficult for several reasons. Expertfinding systems can support the process of identifying knowledgeable colleagues thus facilitating communication andcollaboration within an organization. In order to provide the expert finding functionality, an underlying user model is needed thatrepresents the characteristics of each individual user. In our article we discuss requirements for user models for the workintegratedlearning (WIL) situation. Then, we present the APOSDLE People Recommender Service which is based on anunderlying domain model, and on the APOSDLE User Model. We describe the APOSDLE People Recommender Service on thebasis of the Intuitive Domain Model of expert finding systems, and explain how this service can support interpersonal helpseeking at workplaces.
Lindstaedt Stefanie , Kraker Peter, Höfler Patrick, Fessl Angela
2010
In this paper we present an ecosystem for the lightweight exchangeof publication metadata based on the principles of Web 2.0. At the heart of thisecosystem, semantically enriched RSS feeds are used for dissemination. Thesefeeds are complemented by services for creation and aggregation, as well aswidgets for retrieval and visualization of publication metadata. In twoscenarios, we show how these publication feeds can benefit institutions,researchers, and the TEL community. We then present the formats, services,and widgets developed for the bootstrapping of the ecosystem. We concludewith an outline of the integration of publication feeds with the STELLARNetwork of Excellence1 and an outlook on future developments.
Beham Günter, Jeanquartier Fleur, Lindstaedt Stefanie
2010
This paper introduces iAPOSDLE, a mobile application enabling the use of work-integrated learning services without being limited by location. iAPOSDLE makes use of the APOSDLE WIL system for self-directed work-integrated learning support, and extends its range of application to mobile learning. Core features of iAPOSDLE are described and possible extensions are discussed.
Schoefegger K., Weber Nicolas, Lindstaedt Stefanie , Ley Tobias
2009
The changes in the dynamics of the economy and thecorresponding mobility and fluctuations of knowledge workers within organizationsmake continuous social learning an essential factor for an organization.Within the underlying organizational processes, KnowledgeMaturing refers to the the corresponding evolutionary process in whichknowledge objects are transformed from informal and highly contextualizedartifacts into explicitly linked and formalized learning objects.In this work, we will introduce a definition of Knowledge (Maturing)Services and will present a collection of sample services that can be dividedinto service functionality classes supporting Knowledge Maturingin content networks. Furthermore, we developed an application of thesesample services, a demonstrator which supports quality assurance withina highly content based organisational context.
Beham Günter, Lindstaedt Stefanie , Kump Barbara, Resanovic D.
2009
Pammer-Schindler Viktoria, Serafini L., Lindstaedt Stefanie
2009
Lindstaedt Stefanie , Aehnelt M., de Hoog R.
2009
Lindstaedt Stefanie , de Hoog R., Aehnelt M.
2009
This contribution shortly introduces the collaborative APOSDLE environmentfor integrated knowledge work and learning. It proposes a video presentation and thepresentation of the third APOSDLE prototype.
Weber Nicolas, Ley Tobias, Lindstaedt Stefanie , Schoefegger K., Bimrose J., Brown A., Barnes S.
2009
Lindstaedt Stefanie , Beham Günter, Ley Tobias, Kump Barbara
2009
Work-integrated learning (WIL) poses unique challenges for usermodel design: on the one hand users’ knowledge levels need to be determinedbased on their work activities – testing is not a viable option; on the other handusers do interact with a multitude of different work applications – there is nocentral learning system. This contribution introduces a user model and correspondingservices (based on SOA) geared to enable unobtrusive adaptabilitywithin WIL environments. Our hybrid user model services interpret usage datain the context of enterprise models (semantic approaches) and utilize heuristics(scruffy approaches) in order to determine knowledge levels, identify subjectmatter experts, etc. We give an overview of different types of user model services(logging, production, inference, control), provide a reference implementationwithin the APOSDLE project, and discuss early evaluation results.
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 , Rath Andreas S., Devaurs Didier
2009
‘Understanding context is vital’ [1] and ‘context is key’ [2]signal the key interest in the context detection field. Oneimportant challenge in this area is automatically detectingthe user’s task because once it is known it is possible tosupport her better. In this paper we propose an ontologybaseduser interaction context model (UICO) that enhancesthe performance of task detection on the user’s computerdesktop. Starting from low-level contextual attention metadatacaptured from the user’s desktop, we utilize rule-based,information extraction and machine learning approaches toautomatically populate this user interaction context model.Furthermore we automatically derive relations between themodel’s entities and automatically detect the user’s task.We present evaluation results of a large-scale user study wecarried out in a knowledge-intensive business environment,which support our approach.
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 , 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.
Jones S., Lynch P., Maiden N., Lindstaedt Stefanie
2008
In this paper, we describe a creativity workshop thatwas used in a large research project, called APOSDLE,to generate creative ideas and requirements for a workintegratedlearning system. We present an analysis ofempirical data collected during and after the workshop.On the basis of this analysis, we conclude that the workshopwas an efficient way of generating ideas for futuresystem development. These ideas, on average, were usedat least as much as requirements from other sources inwriting use cases, and 18 months after the workshop wereseen to have a similar degree of influence on the projectto other requirements. We make some observations aboutthe use of more and less creative ideas, and about thetechniques used to generate them. We end with suggestionsfor further work.
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.
Zinnen A., Hambach S., Faatz A., Lindstaedt Stefanie , Beham Günter, Godehardt E., Goertz M., Lokaiczyk R.
2008
Rath Andreas S., Weber Nicolas, Kröll Mark, Granitzer Michael, Dietzel O., Lindstaedt Stefanie
2008
Improving the productivity of knowledge workers is anopen research challenge. Our approach is based onproviding a large variety of knowledge services which takethe current work task and information need (work context)of the knowledge worker into account. In the following wepresent the DYONIPOS application which strives toautomatically identify a user’s work task and thencontextualizes different types of knowledge servicesaccordingly. These knowledge services then provideinformation (documents, people, locations) both from theuser’s personal as well as from the organizationalenvironment. The utility and functionality is illustratedalong a real world application scenario at the Ministry ofFinance in Austria.
Granitzer Michael, Kröll Mark, Seifer Christin, Rath Andreas S., Weber Nicolas, Dietzel O., Lindstaedt Stefanie
2008
’Context is key’ conveys the importance of capturing thedigital environment of a knowledge worker. Knowing theuser’s context offers various possibilities for support, likefor example enhancing information delivery or providingwork guidance. Hence, user interactions have to be aggregatedand mapped to predefined task categories. Withoutmachine learning tools, such an assignment has to be donemanually. The identification of suitable machine learningalgorithms is necessary in order to ensure accurate andtimely classification of the user’s context without inducingadditional workload.This paper provides a methodology for recording user interactionsand an analysis of supervised classification models,feature types and feature selection for automatically detectingthe current task and context of a user. Our analysisis based on a real world data set and shows the applicabilityof machine learning techniques.
Aehnelt M., Ebert M., Beham Günter, Lindstaedt Stefanie , Paschen A.
2008
Knowledge work in companies is increasingly carried out by teams of knowledge workers. They interact within and between teams with the common goal to acquire, apply, create and share knowledge. In this paper we propose a socio-technical model to support intra-organizational collaboration which specifically takes into account the social and collaborative nature of knowledge work. Our aim is to support in particular the efficiency of collaborative knowledge work processes through an automated recommendation of collaboration partners and collaboration media. We report on the theoretical as well as practical aspects of such a socio-technical model.
Ley Tobias, Kump Barbara, Ulbrich Armin, Scheir Peter, Lindstaedt Stefanie
2008
The paper suggests a way to support work-integrated learning for knowledge workwhich poses a great challenge for current research and practice. We first present a WorkplaceLearning Context Model which has been derived by analyzing knowledge work and the knowledgesources used by knowledge workers. The model specifies an integrative view on knowledgeworkers’ work environment by connecting learning, work and knowledge spaces. We then focuson the part of the context which specifies learning goals and their interrelations to task and domainmodels. Our purpose is to support learning needs analysis which is based on a comparison of tasksperformed in the past to those tasks to be tackled in the future. A first implementation in theAPOSDLE project is presented including the models generated for five real world applications andthe software prototype. We close with an outlook on future work.
Scheir Peter, Granitzer Michael, Lindstaedt Stefanie
2007
Evaluation of information retrieval systems is a critical aspect of information retrieval research. New retrieval paradigms, as retrieval in the Semantic Web, present an additional challenge for system evaluation as no off-the-shelf test corpora for evaluation exist. This paper describes the approach taken to evaluate an information retrieval system built for the Semantic Desktop and demonstrates how standard measures from information retrieval research are employed for evaluation.
Kröll Mark, Rath Andreas S., Weber Nicolas, Lindstaedt Stefanie , Granitzer Michael
2007
Knowledge-intensive work plays an increasingly important role in organisations of all types. Knowledge workers contribute their effort to achieve a common purpose; they are part of (business) processes. Workflow Management Systems support them during their daily work, featuring guidance and providing intelligent resource delivery. However, the emergence of richly structured, heterogeneous datasets requires a reassessment of existing mining techniques which do not take possible relations between individual instances into account. Neglecting these relations might lead to inappropriate conclusions about the data. In order to uphold the support quality of knowledge workers, the application of mining methods, that consider structure information rather than content information, is necessary. In the scope of the research project DYONIPOS, user interaction patterns, e.g., relations between users, resources and tasks, are mapped in the form of graphs. We utilize graph kernels to exploit structural information and apply Support Vector Machines to classify task instances to task models
Rath Andreas S., Kröll Mark, Lindstaedt Stefanie , Granitzer Michael
2007
Knowledge intensive organizations demand a rethinking of business process awareness. Their employees are knowledge workers, who are performing their tasks in a weakly structured way. Stiff organizational processes have to be relaxed, adopted and flexibilized to be able to provide the essential freedom requested by knowledge workers. For effectively and efficiently supporting this type of creative worker the hidden patterns, i.e. how they reach their goals, have to be discovered. This paper focuses on perceiving the knowledge workers work habits in an automatic way for bringing their work patterns to the surface. Capturing low level operating system events, observing user interactions on a fine granular level and doing in deep application inspection, give the opportunity to interrelate the received data. In the scope of the research project DYONIPOS these interrelation abilities are utilized to semantically relate and enrich this captured data to picture the actual task of a knowledge worker. Once the goal of a knowledge worker is clear, intelligent information delivery can be applied
Scheir Peter, Granitzer Michael, Lindstaedt Stefanie , Hofmair P.
2006
In this contribution we present a tool for annotating documents, which are used for workintegratedlearning, with concepts from an ontology. To allow for annotating directly whilecreating or editing an ontology, the tool was realized as a plug-in for the ontology editor Protégé.Annotating documents with semantic metadata is a laborious task, most of the time knowledgerepresentations are created independently from the resources that should be annotated andadditionally in most work environments a high number of documents exist. To increase theefficiency of the person annotating, in our tool the process of assigning concepts to text-documentsis supported by automatic text-classification.
Rath Andreas S., Kröll Mark, Andrews K., Lindstaedt Stefanie , Granitzer Michael
2006
In a knowledge-intensive business environment, knowledgeworkers perform their tasks in highly creative ways. This essential freedomrequired by knowledge workers often conflicts with their organization’sneed for standardization, control, and transparency. Within thiscontext, the research project DYONIPOS aims to mitigate this contradictionby supporting the process engineer with insights into the processexecuter’s working behavior. These insights constitute the basis for balancedprocess modeling. DYONIPOS provides a process engineer supportenvironment with advanced process modeling services, such as processvisualization, standard process validation, and ad-hoc process analysisand optimization services.
Granitzer Michael, Lindstaedt Stefanie , Tochtermann K., Kröll Mark, Rath Andreas S.
2006
Knowledge-intensive work plays an increasinglyimportant role in organisations of all types. Thiswork is characterized by a defined input and adefined output but not the way how to transformthe input to an output. Within this context, theresearch project DYONIPOS aims at encouragingthe two crucial roles in a knowledge-intensiveorganization - the process executer and the processengineer. Ad-hoc support will be providedfor the knowledge worker by synergizing the developmentof context sensitive, intelligent, andagile semantic technologies with contextual retrieval.DYONIPOS provides process executerswith guidance through business processes andjust-in-time resource support based on the currentuser context, that are the focus of this paper.
Ley Tobias, Kump Barbara, Lindstaedt Stefanie , Albert D., Maiden N. A. M., Jones S.
2006
Challenges for learning in knowledge work are being discussed.These include the challenge to better support self-directed learning whileaddressing the organizational goals and constraints at the same time, andproviding guidance for learning. The use of competencies is introduced as away to deal with these challenges. Specifically, the competence performanceapproach offers ways to better leverage organizational context and to supportinformal learning interventions. A case study illustrates the application of thecompetence performance approach for the learning domain of requirementsengineering. We close with conclusions and an outlook on future work.
Lindstaedt Stefanie , Mayer H.
2006
The goal of the APOSDLE (Advanced Process-Oriented SelfDirectedLearning environment) project is to enhance knowledge worker productivityby supporting informal learning activities in the context of knowledgeworkers’ everyday work processes and within their work environments. Thiscontribution seeks to communicate the ideas behind this abstract vision to thereader by using a storyboard, scenarios and mock-ups. The project just startedin March 2006 and is funded within the European Commission’s 6th FrameworkProgram under the IST work program. APOSDLE is an Integrated Projectjointly coordinated by the Know-Center, Austria’s Competence Centre forKnowledge Management, and Joanneum Research. APOSDLE brings together12 partners from 7 European Countries.
Ulbrich Armin, Lindstaedt Stefanie , Scheir Peter, Goertz M.
2006
This contribution introduces the so-called Workplace Learning Contextas essential conceptualisation supporting self-directed learning experiencesdirectly at the workplace. The Workplace Learning Context is to be analysedand exploited for retrieving ‘learning’ material that best-possibly matches witha knowledge worker’s current learning needs. In doing so, several different‘flavours’ of work-integrated learning can be realised including task learning,competency-gap based support and domain-related support. The WorkplaceLearning Context Model, which is also outlined in this contribution, forms thetechnical representation of the Workplace Learning Context.
Ley Tobias, Lindstaedt Stefanie , Albert D.
2005
This paper seeks to suggest ways to support informal, self-directed, work-integrated learning within organizations. We focus on a special type of learning in organizations, namely on competency development, that is a purposeful development of employee capabilities to perform well in a large array of situations. As competency development is inherently a self-directed development activity, we seek to support these activities primarily in an informal learning context. AD-HOC environments which allow employees context specific access to documents in a knowledge repository have been suggested to support learning in the workplace. In this paper, we suggest to use the competence performance framework as a means to enhance the capabilities of AD HOC environments to support competency development. The framework formalizes the tasks employees are working in and the competencies needed to perform the tasks. Relating tasks and competencies results in a competence performance structure, which structures both tasks and competencies in terms of learning prerequisites. We conclude with two scenarios that make use of methods established in informal learning research. The scenarios show how competence performance structures enhance feedback mechanisms in a coaching process between supervisor and employee and provide assistance for self directed learning from a knowledge repository.
Lindstaedt Stefanie , Koller S., Krämer T.
2004
Farmer J., Lindstaedt Stefanie , Droschl G., Luttenberger P.
2004
Carrying out today’s knowledge work without information and communicationtechnology (ICT) is unimaginable. ICT makes it possible to process and exchangeinformation quickly and efficiently. However, accomplishing tasks with ICT isoften tedious: Colleagues have to be asked, how best to proceed. Necessaryresources have to be searched for in the intranet and internet. And one has toget familiar with applying the various systems and tools. This way, solving asimple task can become a time consuming process for inexperienced employeesand also for those who are asked for their expertise.Therefore, at the Know-Center Graz, Austria , the AD-HOC methodology hasbeen developed to support knowledge workers in task-oriented learning andteaching situations. This methodology is used to analyse the work processes, toidentify the needed resources, tools, and systems, and finally to design an ADHOCEnvironment. In this environment, systems and tools are arranged forspecific work processes. Users are then guided at their work tasks and areprovided with the necessary resources instantly.This article presents the AD-HOC methodology. It analyses the obstacles thathamper efficient knowledge work and how AD-HOC overcomes them. Finally, thesupport of users at their specific work tasks by deployed AD-HOC Environmentsis shown in two field studies.
Timbrell G., Koller S., Lindstaedt Stefanie
2004
Lindstaedt Stefanie , Farmer J., Hrastnik J., Rollett H., Strohmaier M.
2003
Personalisierbare Portale als Fenster zu Unternehmensgedachtnissen finden ¨in der Praxis immer haufiger Anwendung. Bei dem Design dieser Portale stellt sich die ¨Frage nach der Strukturierung der Informationen: auf der einen Seite soll der tagliche ¨Arbeitsprozess unterstutzt werden, auf der anderen Seite sollen aber auch Informa- ¨tionen zuganglich gemacht werden, die den Prozess in einen gr ¨ oßeren Kontext set- ¨zen. Unsere Erfahrungen bei der Portalentwicklungen haben gezeigt, dass zwei unterschiedlicheStrategien Anwendung finden: Prozessfokus und Wissensfokus. Die Wahlder individuellen Strategie hangt einerseits von den Zielen ab, die das Portal erf ¨ ullen ¨soll. Andererseits hangen sie aber auch von der Ausgangssituation im anwendenden ¨Unternehmen ab. Dieser Beitrag stellt die beiden Designstrategien vor und identifiziertRahmenbedingungen, die bei der Wahl der Stategie helfen konnen.
Tochtermann K., Zirm K., Lindstaedt Stefanie
2003
Lindstaedt Stefanie
2002
Lindstaedt Stefanie , Fischer M.
2002
Westbomke J., Kussmaul A., Raiber A., Haase M., Hicks D., Lindstaedt Stefanie
2002
This paper presents research results obtained from the project Personal AdaptableDigital Library Environment (PADDLE). The main focus of the DFG funded research projectis to apply concepts of knowledge management to digital libraries by introducingpersonalization techniques. The idea is to enable the specific needs, experiences, skills andtasks of a knowledge worker using a digital library could be taken into account. Metadata is thekey issue for doing this. Therefore the PADDLE system architecture describes a metadatamanager, which allows the association of metadata with the knowledge objects stored indistributed information resources. Based on this architecture several personalization conceptslike workspaces and profiles are introduced. Finally, a geographic information portal isdescribed that realizes a new way of seeking and accessing geodata related knowledge objectswithin a digital library.
Lindstaedt Stefanie , Strohmaier M., Rollett Herwig, Hrastnik Janez, Bruhnsen Karin, Droschl Georg, Gerold Markus
2002
One of the first question each knowledge management project facesis: Which concrete activities are referred to under the name of knowledgemanagement and how do they relate to each other? To help answer this questionand to provide guidance when introducing knowledge management we havedeveloped KMap. KMap is an environment which supports a practitioner in theinteractive exploration of a map of knowledge management activities. Theinteraction helps trigger interesting questions crucial to the exploration of thesolution space and makes hidden argumentation lines visible. KMap is not anew theory of knowledge management but a pragmatic “object to think with”and is currently in use in two case studies.
Lindstaedt Stefanie , Strohmaier M.
2002
Lindstaedt Stefanie
2002
Wir betrachten kooperative Lern- und Lehrsituationen im Kontext dertäglichen Arbeitsprozesse aus der Perspektive des Wissensmanagements. In einerCase Study bei DaimlerChrysler wurden Szenarien entwickelt, in denen Wissen inGruppen erarbeitet und weitergegeben wird, um konkrete Arbeitsaufgaben unterZeitdruck erfüllen zu können. Zur Zeit entwickeln wir im Kontext eines WissensmanagementsystemsMethoden und technische Hilfsmittel zur Unterstützung dieseraufgaben-orientierten kooperativen Lern- und Lehrprozesse.
Lindstaedt Stefanie
2000