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Many prediction tasks can be done based on users’ trace data. In this paper, we explored convergent thinking as a personality-related attribute and its relation to features gathered in interactive and non-interactive tasks of an online course. This is an under-utilized attribute that could be used for adapting online courses according to the creativity level to enhance the motivation of learners. Therefore, we used the logfile data of a 60 minutes Moodle course with N=128 learners, combined with the Remote Associates Test (RAT). We explored the trace data and found a weak correlation between interactive tasks and the RAT score, which was the highest considering the overall dataset. We trained a Random Forest Regressor to predict convergent thinking based on the trace data and analyzed the feature importance. The result has shown that the interactive tasks have the highest importance in prediction, but the accuracy is very low. We discuss the potential for personalizing online courses and address further steps to improve the applicability.
Many prediction tasks can be done based on users’ trace data. This paper explores divergent and convergent thinking as person-related attributes and predicts them based on features gathered in an online course. We use the logfile data of a short Moodle course, combined with an image test (IMT), the Alternate Uses Task (AUT), the Remote Associates Test (RAT), and creative self-efficacy (CSE). Our results show that originality and elaboration metrics can be predicted with an accuracy of ~.7 in cross-validation, whereby predicting fluency and RAT scores perform worst. CSE items can be predicted with an accuracy of ~.45. The best performing model is a Random Forest Tree, where the features were reduced using a Linear Discriminant Analysis in advance. The promising results can help to adjust online courses to the learners’ needs based on their creative performances.
Digital Platforms (DPs) has established themself in recent years as a central concept of the Information Technology Science. Due to the great diversity of digital platform concepts, clear definitions are still required. Furthermore, DPs are subject to dynamic changes from internal and external factors, which pose challenges for digital platform operators, developers and customers. Which current digital platform research directions should be taken to address these challenges remains open so far. The following paper aims to contribute to this by outlining a systematic literature review (SLR) on digital platform concepts in the context of the Industrial Internet of Things (IIoT) for manufacturing companies and provides a basis for (1) a selection of definitions of current digital platform and ecosystem concepts and (2) a selection of current digital platform research directions. These directions are diverted into (a) occurrence of digital platforms, (b) emergence of digital platforms, (c) evaluation of digital platforms, (d) development of digital platforms, and (e) selection of digital platforms.
Openness indicators for the evaluation of digital platforms between the launch and maturity phase
(2024)
In recent years, the evaluation of digital platforms has become an important focus in the field of information systems science. The identification of influential indicators that drive changes in digital platforms, specifically those related to openness, is still an unresolved issue. This paper addresses the challenge of identifying measurable indicators and characterizing the transition from launch to maturity in digital platforms. It proposes a systematic analytical approach to identify relevant openness indicators for evaluation purposes. The main contributions of this study are the following (1) the development of a comprehensive procedure for analyzing indicators, (2) the categorization of indicators as evaluation metrics within a multidimensional grid-box model, (3) the selection and evaluation of relevant indicators, (4) the identification and assessment of digital platform architectures during the launch-to-maturity transition, and (5) the evaluation of the applicability of the conceptualization and design process for digital platform evaluation.
Developing a new paradigm
(2020)
Internet users commonly agree that it is important for them to protect their personal data. However, the same users readily disclose their data when requested by an online service. The dichotomy between privacy attitude and actual behaviour is commonly referred to as the “privacy paradox”. Over twenty years of research were not able to provide one comprehensive explanation for the paradox and seems even further from providing actual means to overcome the paradox. We argue that the privacy paradox is not just an instantiation of the attitude-behaviour gap. Instead, we introduce a new paradigm explaining the paradox as the result of attitude-intention and intentionbehaviour gaps. Historically, motivational goal-setting psychologists addressed the issue of intentionbehaviour gaps in terms of the Rubicon Model of Action Phases and argued that commitment and volitional strength are an essential mechanism that fuel intentions and translate them into action. Thus, in this study we address the privacy paradox from a motivational psychological perspective by developing two interventions on Facebook and assess whether the 287 participants of our online experiment actually change their privacy behaviour. The results demonstrate the presence of an intentionbehaviour gap and the efficacy of our interventions in reducing the privacy paradox.
Association between skeletal robustness and physical activity in schoolchildren - First results
(2011)
An increasing number of clinicians (i.e., nurses and physicians) suffer from mental health-related issues like depression and burnout. These, in turn, stress communication, collaboration, and decision- making—areas in which Conversational Agents (CAs) have shown to be useful. Thus, in this work, we followed a mixed-method approach and systematically analysed the literature on factors affecting the well-being of clinicians and CAs’ potential to improve said well-being by relieving support in communication, collaboration, and decision-making in hospitals. In this respect, we are guided by Brigham et al. (2018)’s model of factors influencing well-being. Based on an initial number of 840 articles, we further analysed 52 papers in more detail and identified the influences of CAs’ fields of application on external and individual factors affecting clinicians’ well-being. As our second method, we will conduct interviews with clinicians and experts on CAs to verify and extend these influencing factors.
Fluvial systems are one of the major features shaping a landscape. They adjust to the prevailing tectonic and climatic setting and therefore are very sensitive markers of changes in these systems. If their response to tectonic and climatic forcing is quantified and if the climatic signal is excluded, it is possible to derive a local deformation history. Here, we investigate fluvial terraces and erosional surfaces in the southern Chilean forearc to assess a long-term geomorphic and hence tectonic evolution. Remote sensing and field studies of the Nahuelbuta Range show that the long-term deformation of the Chilean forearc is manifested by breaks in topography, sequences of differentially uplifted marine, alluvial and strath terraces as well as tectonically modified river courses and drainage basins. We used SRTM-90-data as basic elevation information for extracting and delineating drainage networks. We calculated hypsometric curves as an indicator for basin uplift, stream-length gradient indices to identify stream segments with anomalous slopes, and longitudinal river profiles as well as DS-plots to identify knickpoints and other anomalies. In addition, we investigated topography with elevation-slope graphs, profiles, and DEMs to reveal erosional surfaces. During the first field trip we already measured palaeoflow directions, performed pebble counting and sampled the fluvial terraces in order to apply cosmogenic nuclide dating (<sup>10Be, <sup>26Al) as well as provenance analyses. Our preliminary analysis of the Coastal Cordillera indicates a clear segmentation between the northern and southern parts of the Nahuelbuta Range. The Lanalhue Fault, a NW-SE striking fault zone oblique to the plate boundary, defines the segment boundary. Furthermore, we find a complex drainage re-organisation including a drainage reversal and wind gap on the divide between the Tirúa and Pellahuén basins east of the town Tirúa. The coastal basins lost most of their Andean sediment supply areas that existed in Tertiary and in part during early Pleistocene time. Between the Bío-Bío and Imperial rivers no Andean river is recently capable to traverse the Coastal Cordillera, suggesting ongoing Quaternary uplift of the entire range. From the spatial distribution of geomorphic surfaces in this region two uplift signals may be derived: (1) a long-term differential uplift process, active since the Miocene and possibly caused by underplating of subducted trench sediments, (2) a younger, local uplift affecting only the northern part of the Nahuelbuta Range that may be caused by the interaction of the forearc with the subduction of the Mocha Fracture Zone at the latitude of the Arauco peninsula. Our approach thus provides results in our attempt to decipher the characteristics of forearc development of active convergent margins using long-term geomorphic indicators. Furthermore, it is expected that our ongoing assessment will constrain repeatedly active zones of deformation. <hr> Interdisziplinäres Zentrum für Musterdynamik und Angewandte Fernerkundung Workshop vom 9. - 10. Februar 2006
In honour of Seymour Papert
(2018)
Forth is nice and flexible but to a philosopher and teacher educator Logo is the more impressing language. Both are relatives of Lisp, but Forth has a reverse Polish notation where as Logo has an infix notation. Logo allows top down programming, Forth only bottom up. Logo enables recursive programming, Forth does not. Logo includes turtle graphics, Forth has nothing comparable. So what to do if you can't get Logo and have no information about its inner architecture? This should be a case of "empirical modelling": How can you model observable results of the behaviour of Logo in terms of Forth? The main steps to solve this problem are shown in the first part of the paper.
The second part of the paper discusses the problem of modelling and shows that the modelling of making and the modelling of recognition have the same mathematical structure. So "empirical modelling" can also serve for modelling desired behaviour of technical systems.
The last part of the paper will show that the heuristic potential of a problem which should be modeled is more important than the programming language. The Picasso construal shows, in a very simple way, how children of different ages can model emotional relations in human behaviour with a simple Logo system.
Increasingly fast development cycles and individualized products pose major challenges for today's smart production systems in times of industry 4.0. The systems must be flexible and continuously adapt to changing conditions while still guaranteeing high throughputs and robustness against external disruptions. Deep rein- forcement learning (RL) algorithms, which already reached impressive success with Google DeepMind's AlphaGo, are increasingly transferred to production systems to meet related requirements. Unlike supervised and unsupervised machine learning techniques, deep RL algorithms learn based on recently collected sensor- and process-data in direct interaction with the environment and are able to perform decisions in real-time. As such, deep RL algorithms seem promising given their potential to provide decision support in complex environments, as production systems, and simultaneously adapt to changing circumstances. While different use-cases for deep RL emerged, a structured overview and integration of findings on their application are missing. To address this gap, this contribution provides a systematic literature review of existing deep RL applications in the field of production planning and control as well as production logistics. From a performance perspective, it became evident that deep RL can beat heuristics significantly in their overall performance and provides superior solutions to various industrial use-cases. Nevertheless, safety and reliability concerns must be overcome before the widespread use of deep RL is possible which presumes more intensive testing of deep RL in real world applications besides the already ongoing intensive simulations.
CpG-oligonucleotides modulate sphingosine-1-phosphate metabolism in normal human keratinocytes
(2012)
This first volume of the DIGAREC Series holds the proceedings of the conference “The Philosophy of Computer Games”, held at the University of Potsdam from May 8-10, 2008. The contributions of the conference address three fields of computer game research that are philosophically relevant and, likewise, to which philosophical reflection is crucial. These are: ethics and politics, the action-space of games, and the magic circle. All three topics are interlinked and constitute the paradigmatic object of computer games: Whereas the first describes computer games on the outside, looking at the cultural effects of games as well as on moral practices acted out with them, the second describes computer games on the inside, i.e. how they are constituted as a medium. The latter finally discusses the way in which a border between these two realms, games and non-games, persists or is already transgressed in respect to a general performativity.