Hier finden Sie von Know-Center MitarbeiterInnen verfasste wissenschaftliche Publikationen


Kowald Dominik, Seitlinger Paul , Ley Tobias , Lex Elisabeth

The Impact of Semantic Context Cues on the User Acceptance of Tag Recommendations: An Online Study

Companion Proceedings of the 27th International World Wide Web Conference, ACM, Lyon, France, 2018

In this paper, we present the results of an online study with the aim to shed light on the impact that semantic context cues have on the user acceptance of tag recommendations. Therefore, we conducted a work-integrated social bookmarking scenario with 17 university employees in order to compare the user acceptance of a context-aware tag recommendation algorithm called 3Layers with the user acceptance of a simple popularity-based baseline. In this scenario, we validated and verified the hypothesis that semantic context cues have a higher impact on the user acceptance of tag recommendations in a collaborative tagging setting than in an individual tagging setting. With this paper, we contribute to the sparse line of research presenting online recommendation studies.

Seitlinger Paul, Ley Tobias, Kowald Dominik, Theiler Dieter, Hasani-Mavriqi Ilire, Dennerlein Sebastian, Lex Elisabeth, Albert Dietrich

Balancing the Fluency-Consistency Tradeoff in Collaborative Information Search Using a Recommender Approach

International Journal of Human-Computer Interaction, Constantine Stephanidis and Gavriel Salvendy , Taylor and Francis, 2017

Creative group work can be supported by collaborative search and annotation of Web resources. In this setting, it is important to help individuals both stay fluent in generating ideas of what to search next (i.e., maintain ideational fluency) and stay consistent in annotating resources (i.e., maintain organization). Based on a model of human memory, we hypothesize that sharing search results with other users, such as through bookmarks and social tags, prompts search processes in memory, which increase ideational fluency, but decrease the consistency of annotations, e.g., the reuse of tags for topically similar resources. To balance this tradeoff, we suggest the tag recommender SoMe, which is designed to simulate search of memory from user-specific tag-topic associations. An experimental field study (N = 18) in a workplace context finds evidence of the expected tradeoff and an advantage of SoMe over a conventional recommender in the collaborative setting. We conclude that sharing search results supports group creativity by increasing the ideational fluency, and that SoMe helps balancing the evidenced fluency-consistency tradeoff.

Ruiz Adolfo, Prieto Luis Pablo, Ley Tobias, Jesús Rodríguez Triana María , Dennerlein Sebastian

Learning Analytics for Professional and Workplace Learning: A Literature Review


Despite the ubiquity of learning in the everyday life of most workplaces, the learning analytics community only has paid attention to such settings very recently. One probable reason for this oversight is the fact that learning in the workplace is often informal, hard to grasp and not univocally defined. This paper summarizes the state of the art of Workplace Learning Analytics (WPLA), extracted from a systematic literature review of five academic databases as well as other known sources in the WPLA community. Our analysis of existing proposals discusses particularly on the role of different conceptions of learning and their influence on the LA proposals’ design and technology choices. We end the paper by discussing opportunities for future work in this emergent field.

Kopeinik Simone, Lex Elisabeth, Seitlinger Paul, Tschinkel, Ley Tobias

Supporting collaborative learning with tag recommendations: a real-world study in an inquiry-based classroom project

Proceedings of the 7th International Conference on Learning Analytics and Knowledge (LAK 2017), ACM, Vancouver, 2017

In online social learning environments, tagging has demonstratedits potential to facilitate search, to improve recommendationsand to foster reflection and learning.Studieshave shown that shared understanding needs to be establishedin the group as a prerequisite for learning. We hypothesisethat this can be fostered through tag recommendationstrategies that contribute to semantic stabilization.In this study, we investigate the application of two tag recommendersthat are inspired by models of human memory:(i) the base-level learning equation BLL and (ii) Minerva.BLL models the frequency and recency of tag use while Minervais based on frequency of tag use and semantic context.We test the impact of both tag recommenders on semanticstabilization in an online study with 56 students completinga group-based inquiry learning project in school. Wefind that displaying tags from other group members contributessignificantly to semantic stabilization in the group,as compared to a strategy where tags from the students’individual vocabularies are used. Testing for the accuracyof the different recommenders revealed that algorithms usingfrequency counts such as BLL performed better whenindividual tags were recommended. When group tags wererecommended, the Minerva algorithm performed better. Weconclude that tag recommenders, exposing learners to eachother’s tag choices by simulating search processes on learners’semantic memory structures, show potential to supportsemantic stabilization and thus, inquiry-based learning ingroups.

Dennerlein Sebastian, Treasure-Jones Tamsin, Lex Elisabeth, Ley Tobias

The role of collaboration and shared understanding in interprofessional teamwork

AMEE - International Conference of Medical Education 2016, AMEE 2016, 2016

Background: Teamworking, within and acrosshealthcare organisations, is essential to deliverexcellent integrated care. Drawing upon an alternationof collaborative and cooperative phases, we exploredthis teamworking and respective technologicalsupport within UK Primary Care. Participants usedBits&Pieces (B&P), a sensemaking tool for tracedexperiences that allows sharing results and mutuallyelaborating them: i.e. cooperating and/orcollaborating.Summary of Work: We conducted a two month-longcase study involving six healthcare professionals. InB&P, they reviewed organizational processes, whichrequired the involvement of different professions ineither collaborative and/or cooperative manner. Weused system-usage data, interviews and qualitativeanalysis to understand the interplay of teamworkingpracticeand technology.Summary of Results: Within our analysis we mainlyidentified cooperation phases. In a f2f-meeting,professionals collaboratively identified subtasks andassigned individuals leading collaboration on them.However, these subtasks were undertaken asindividual sensemaking efforts and finally combined(i.e. cooperation). We found few examples ofreciprocal interpretation processes (i.e. collaboration):e.g. discussing problems during sensemaking ormonitoring other’s sensemaking-outcomes to makesuggestions.Discussion: These patterns suggest that collaborationin healthcare often helps to construct a minimalshared understanding (SU) of subtasks to engage incooperation, where individuals trust in other’scompetencies and autonomous completion. However,we also found that professionals with positivecollaboration history and deepened SU were willing toundertake subtasks collaboratively. It seems thatacquiring such deepened SU of concepts andmethods, leads to benefits that motivate professionalsto collaborate more.Conclusion: Healthcare is a challenging environmentrequiring interprofessional work across organisations.For effective teamwork, a deepened SU is crucial andboth cooperation and collaboration are required.However, we found a tendency of staff to rely mainlyon cooperation when working in teams and not fullyexplore benefits of collaboration.Take Home Messages: To maximise benefits ofinterprofessional working, tools for teamworkingshould support both cooperation and collaborationprocesses and scaffold the move between them

Trattner Christoph, Kowald Dominik, Ley Tobias, Seitlinger Paul

Modeling Activation Processes in Human Memory to Predict the Reuse of Tags

The Journal of Web Science, James Finlay, NOW publishing, 2016

Several successful tag recommendation mechanisms have been developed, including algorithms built upon Collaborative Filtering, Tensor Factorization, graph-based and simple "most popular tags" approaches. From an economic perspective, the latter approach has been convincing since calculating frequencies is computationally efficient and effective with respect to different recommender evaluation metrics. In this paper, we introduce a tag recommendation algorithm that mimics the way humans draw on items in their long-term memory in order to extend these conventional "most popular tags" approaches. Based on a theory of human memory, the approach estimates a tag's reuse probability as a function of usage frequency and recency in the user's past (base-level activation) as well as of the current semantic context (associative component).Using four real-world folksonomies gathered from bookmarks in BibSonomy, CiteULike, Delicious and Flickr, we show how refining frequency-based estimates by considering recency and semantic context outperforms conventional "most popular tags" approaches and another existing and very effective but less theory-driven, time-dependent recommendation mechanism. By combining our approach with a simple resource-specific frequency analysis, our algorithm outperforms other well-established algorithms, such as Collaborative Filtering, FolkRank and Pairwise Interaction Tensor Factorization with respect to recommender accuracy and runtime. We conclude that our approach provides an accurate and computationally efficient model of a user's temporal tagging behavior. Moreover, we demonstrate how effective principles of recommender systems can be designed and implemented if human memory processes are taken into account.

Dennerlein Sebastian, Ley Tobias, , Lex Elisabeth, Seitlinger Paul

Take up my Tags: Exploring Benefits of Collaborative Learning in a Social Tagging Field Study at the Workplace

European Conference on Technology Enhanced Learning (EC-TEL 2016), EC-TEL 2016, Springer-Verlag, Cham, 2016

In the digital realm, meaning making is reflected in the reciprocal manipulation of mediating artefacts. We understand uptake, i.e. interaction with and understanding of others’ artefact interpretations, as central mechanism and investigate its impact on individual and social learning at work. Results of our social tagging field study indicate that increased uptake of others’ tags is related to a higher shared understanding of collaborators as well as narrower and more elaborative exploration in individual information search. We attribute the social and individual impact to accommodative processes in the high uptake condition.

Ruiz-Calleja Adolfo, Dennerlein Sebastian, Tomberg Vladimir , Ley Tobias , Theiler Dieter, Lex Elisabeth

Integrating data across workplace learning applications with a social semantic infrastructure

Proceedings of the International Conference on Web-based Learning, Springer International Publishing, Hong Kong, China, 2015

This paper presents our experiences using a social semantic infrastructure that implements a semantically-enriched Actor Artifact Network (AAN) to support informal learning at the workplace. Our previous research led us to define the Model of Scaling Informal Learning, to identify several common practices when learning happens at the workplace, and to propose a social semantic infrastructure able to support them. This paper shows this support by means of two illustrative examples where practitioners employed several applications integrated into the infrastructure. Thus, this paper clarifies how workplace learning processes can be supported with such infrastructure according to the aforementioned model. The initial analysis of these experiences gives promising results since it shows how the infrastructure mediates in the sharing of contextualized learning artifacts and how it builds up an AAN that makes explicit the relationships between actors and artifacts when learning at the workplace.

Cook John, Ley Tobias, Maier Ronald, Mor Yishay, Santos Patricia, Lex Elisabeth, Dennerlein Sebastian, Trattner Christoph, Holley Debbie

Using the Hybrid Social Learning Network to Explore Concepts, Practices, Designs and Smart Services for Networked Professional Learning

In Proceedings of the International Conference on Smart Learning Environments 2015 (ICSLE 2015), Springer, Sinaia, Romania, 2015

In this paper we define the notion of the Hybrid Social Learning Network. We propose mechanisms for interlinking and enhancing both the practice of professional learning and theories on informal learning. Our approach shows how we employ empirical and design work and a participatory pattern workshop to move from (kernel) theories via Design Principles and prototypes to social machines articulating the notion of a HSLN. We illustrate this approach with the example of Help Seeking for healthcare professionals.

Dennerlein Sebastian, Kowald Dominik, Lex Elisabeth, Lacic Emanuel, Theiler Dieter, Ley Tobias

The Social Semantic Server: A Flexible Framework to Support Informal Learning at the Workplace

In Proceedings of the 15th International Conference on Knowledge Technologies and Data-Driven Business, i-know 2015, ACM, Graz, Austria, 2015

Informal learning at the workplace includes a multitude of processes. Respective activities can be categorized into multiple perspectives on informal learning, such as reflection, sensemaking, help seeking and maturing of collective knowledge. Each perspective raises requirements with respect to the technical support, this is why an integrated solution relying on social, adaptive and semantic technologies is needed. In this paper, we present the Social Semantic Server, an extensible, open-source application server that equips clientside tools with services to support and scale informal learning at the workplace. More specifically, the Social Semantic Server semantically enriches social data that is created at the workplace in the context of user-to-user or user-artifact interactions. This enriched data can then in turn be exploited in informal learning scenarios to, e.g., foster help seeking by recommending collaborators, resources, or experts. Following the design-based research paradigm, the Social Semantic Server has been implemented based on design principles, which were derived from theories such as Distributed Cognition and Meaning Making. We illustrate the applicability and efficacy of the Social Semantic Server in the light of three real-world applications that have been developed using its social semantic services. Furthermore, we report preliminary results of two user studies that have been carried out recently.

Dennerlein Sebastian, Treasure Jones T, Tomberg V, Theiler Dieter, Lex Elisabeth, Ley Tobias

Making Sense of Informal Learning at the Workplace

AMEE - Conference (The Association for Medical Education in Europe), Glasgow, UK, 2015

Sensemaking at the workplace and in educational contexts has been extensively studied for decades. Interestingly, making sense out of the own wealth of learning experiences at the workplace has been widely ignored. To tackle this issue, we have implemented a novel sensemaking interface for healthcare professionals to support learning at the workplace. The proposed prototype supports remembering of informal experiences from episodic memory followed by sensemaking in semantic memory. Results from an initial study conducted as part of an iterative co-design process reveal the prototype is being perceived as useful and supportive for informal sensemaking by study participants from the healthcare domain. Furthermore, we find first evidence that re-evaluation of collected information is a potentially necessary process that needs further exploration to fully understand and support sensemaking of informal learning experiences.

Dennerlein Sebastian, Rella Matthias, Tomberg Vladimir, Theiler Dieter, Treasure-Jones Tamsin, Kerr Micky, Ley Tobias, Al-Smadi Mohammad, Trattner Christoph

Making Sense of Bits and Pieces: A Sensemaking Tool for Informal Workplace Learning

European Conference on Technology Enhanced Learning, Springer International Publishing, 2015

Sensemaking at the workplace and in educational contexts has beenextensively studied for decades. Interestingly, making sense out of the own wealthof learning experiences at the workplace has been widely ignored. To tackle thisissue, we have implemented a novel sensemaking interface for healthcare professionalsto support learning at the workplace. The proposed prototype supportsremembering of informal experiences from episodic memory followed by sensemakingin semantic memory. Results from an initial study conducted as part ofan iterative co-design process reveal the prototype is being perceived as usefuland supportive for informal sensemaking by study participants from the healthcaredomain. Furthermore, we find first evidence that re-evaluation of collectedinformation is a potentially necessary process that needs further exploration tofully understand and support sensemaking of informal learning experiences.

Lindstaedt Stefanie , Ley Tobias, Sack Harald

Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business

i-KNOW '15 15th International Conference on Knowledge Technologies and Data-Driven Business, 2015


Seitlinger Paul, Kowald Dominik, Kopeinik Simone, Hasani-Mavriqi Ilire, Ley Tobias, Lex Elisabeth

Attention Please! A Hybrid Resource Recommender Mimicking Attention-Interpretation Dynamics

In 24rd International World Wide Web Conference, Web-Science Track, Aldo Gangemi, Stefano Leonardi and Alessandro Panconesi, ACM, Florence, 2015

Classic resource recommenders like Collaborative Filtering(CF) treat users as being just another entity, neglecting non-linear user-resource dynamics shaping attention and inter-pretation. In this paper, we propose a novel hybrid rec-ommendation strategy that re nes CF by capturing thesedynamics. The evaluation results reveal that our approachsubstantially improves CF and, depending on the dataset,successfully competes with a computationally much moreexpensive Matrix Factorization variant.

Kowald Dominik, Seitlinger Paul, Kopeinik Simone, Ley Tobias, Trattner Christoph

Forgetting the Words but Remembering the Meaning: Modeling Forgetting in a Verbal and Semantic Tag Recommender

Mining, Modeling, and Recommending'Things' in Social Media, MSM'2015, Springer, 2015

We assume that recommender systems are more successful,when they are based on a thorough understanding of how people processinformation. In the current paper we test this assumption in the contextof social tagging systems. Cognitive research on how people assign tagshas shown that they draw on two interconnected levels of knowledge intheir memory: on a conceptual level of semantic fields or LDA topics,and on a lexical level that turns patterns on the semantic level intowords. Another strand of tagging research reveals a strong impact oftime-dependent forgetting on users' tag choices, such that recently usedtags have a higher probability being reused than "older" tags. In thispaper, we align both strands by implementing a computational theory ofhuman memory that integrates the two-level conception and the processof forgetting in form of a tag recommender. Furthermore, we test theapproach in three large-scale social tagging datasets that are drawn fromBibSonomy, CiteULike and Flickr.As expected, our results reveal a selective effect of time: forgetting ismuch more pronounced on the lexical level of tags. Second, an extensiveevaluation based on this observation shows that a tag recommender interconnectingthe semantic and lexical level based on a theory of humancategorization and integrating time-dependent forgetting on the lexicallevel results in high accuracy predictions and outperforms other wellestablishedalgorithms, such as Collaborative Filtering, Pairwise InteractionTensor Factorization, FolkRank and two alternative time-dependentapproaches. We conclude that tag recommenders will benefit from goingbeyond the manifest level of word co-occurrences, and from includingforgetting processes on the lexical level.

Ruiz-Calleja Adolfo, Dennerlein Sebastian, Tomberg Vladimir , Pata Kai, Ley Tobias, Theiler Dieter, Lex Elisabeth

Supporting learning analytics for informal workplace learning with a social semantic infrastructure

In Proceedings of the European Conference on Technology Enhanced Learning, Springer International Publishing (in press)., Springer, Toledo, Spain, 2015

This paper presents the potential of a social semantic infrastructure that implements an Actor Artifact Network (AAN) with the final goal of supporting learning analytics at the workplace. Two applications were built on top of such infrastructure and make use of the emerging relations of such a AAN. A preliminary evaluation shows that an AAN can be created out of the usage of both applications, thus opening the possibility to implement learning analytics at the workplace.

Ley Tobias, Dennerlein Sebastian, Cook John, Kravcik Milos, Kunzmann Christine, Pata Kai, Purma Jukka, Sanders John, Santos Patricia , Schmidt Andreas, Al-Smadi Mohammad, Trattner Christoph

Scaling informal learning at the workplace: A model and four designs from a large‐scale design‐based research effort

British Journal of Educational Technology, 2014

Workplace learning happens in the process and context of work, is multi-episodic, often informal, problem based and takes place on a just-in-time basis. While this is a very effective means of delivery, it also does not scale very well beyond the immediate context. We review three types of technologies that have been suggested to scale learning and three connected theoretical discourses around learning and its support. Based on these three strands and an in-depth contextual inquiry into two workplace learning domains, health care and building and construction, four design-based research projects were conducted that have given rise to designs for scaling informal learning with technology. The insights gained from the design and contextual inquiry contributed to a model that provides an integrative view on three informal learning processes at work and how they can be supported with technology: (1) task performance, reflection and sensemaking; (2) help seeking, guidance and support; and (3) emergence and maturing of collective knowledge. The model fosters our understanding of how informal learning can be scaled and how an orchestrated set of technologies can support this process.

Dennerlein Sebastian, Ley Tobias, Kump Barbara, Moskaliuk Johannes

Tracing knowledge co-evolution in a realistic course setting: A wiki-based field experiment

Computers & Education, Pergamon, 2013

The co-evolution model of collaborative knowledge building by Cress & Kimmerle (2008) assumes that cognitive and social processes interact when users build knowledge with shared digital artifacts. While these assumptions have been tested in various lab experiments, a test under natural field conditions in educational settings has not been conducted. Here, we present a field experiment where we triggered knowledge co-evolution in an accommodation and an assimilation condition, and measured effects on student knowledge building outside the laboratory in the context of two university courses. Therefore, 48 students received different kinds of prompts that triggered external accommodation and assimilation while writing a wiki text. Knowledge building was measured with a content analysis of the students‟ texts and comments (externalization), and with concept maps and association tests (internalization). The findings reveal that (a) different modes of externalization (accommodation and assimilation) could be triggered with prompts, (b) across both conditions, this externalization co-occurred with internalization (student learning), and (c) there is some evidence that external assimilation and accommodation had differential effects on internal assimilation and accommodation. Thus, the field experiment supports the assumptions of the co-evolution model in a realistic course setting. On a more general note, the study provides an example of how wikis can be used successfully for collaborative knowledge building within educational contexts.

Cook John, Santos Patricia, Ley Tobias, Dennerlein Sebastian, Pata Kai, Colley Joanna, Sandars John, Treasure-Jones Tasmin

D2. 1 Concept & Prototype Networked Scaffolding Layer

, 2013


Ley Tobias, Cook John, Dennerlein Sebastian, Kravcik Milos, Kunzmann Christine, Laanpere Mart, Pata Kai, Purma Jukka, Sandars John, Santos Patricia, Schmidt Andreas

Scaling Informal Learning: An Integrative Systems View on Scaffolding at the Workplace

European Conference on Technology Enhanced Learning, Springer Berlin Heidelberg, 2013

While several technological advances have been suggested to scale learning at the workplace, none has been successful to scale informal learning. We review three theoretical discourses and suggest an integrated systems model of scaffolding informal workplace learning that has been created to tackle this challenge. We derive research questions that emerge from this model and illustrate these with an in-depth analysis of two workplace learning domains.

Lindstaedt Stefanie , Farmer J., Ley Tobias

Betriebliche Weiterbildung

CSCL-Kompendium - Lehr- und Handbuch für das computerunterstützte kooperative Lernen, Haake, J., Schwabe, G., Wessner, M., Oldenbourg Wissenschaftsverlag, München,Germany, 2004

Kontakt Karriere

Hiermit erkläre ich ausdrücklich meine Einwilligung zum Einsatz und zur Speicherung von Cookies. Weiter Informationen finden sich unter Datenschutzerklärung

The cookie settings on this website are set to "allow cookies" to give you the best browsing experience possible. If you continue to use this website without changing your cookie settings or you click "Accept" below then you are consenting to this.