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The “output-orientation” is omnipresent in teacher education. In order to evaluate teachers' and students' performances, a wide range of different quantitative questionnaires exist worldwide. One important goal of teaching evaluation is to increase the quality of teaching and learning. The author argues, that standard evaluations which are typically made at the end of the semester are problematic due to two reasons. The first one is that some of the questions are too general and don`t offer concrete ideas as to what kind of actions can be taken to make the courses better. The second problem is that the evaluation is mostly made when the course is already over. Because of this criticism, Apelojg invented the Felix-App which offers the possibility to give feedback in real-time by asking for the emotions and needs that occur during different learning situations. The idea is very simple: positive emotions and satisfied needs are helpful for the learning process. Negative emotions and unsatisfied needs have negative effects on the learning process. First descriptive results show, that “managing emotions” during classes can have positive effects on both motivation and emotions.
Web Tracking
(2018)
Web tracking seems to become ubiquitous in online business and leads to increased privacy concerns of users. This paper provides an overview over the current state of the art of web-tracking research, aiming to reveal the relevance and methodologies of this research area and creates a foundation for future work. In particular, this study addresses the following research questions: What methods are followed? What results have been achieved so far? What are potential future research areas? For these goals, a structured literature review based upon an established methodological framework is conducted. The identified articles are investigated with respect to the applied research methodologies and the aspects of web tracking they emphasize.
Visual Social Networking Sites (SNSs) enable users to present themselves favorably to gain likes and the attention of others. Especially, Instagram is known for its focus on beauty, fitness, fashion, and dietary topics. Although a large body of research reports negative weight-related outcomes of SNS usage (e.g., body dissatisfaction, body image concerns), studies examining how SNS usage relates to these outcomes are scarce. Based on the visual normalization theory, we argue that SNS content facilitates normalization of so-called thin- and fit-ideals, thereby leading to biased perceptions of the average body weight in society. Therefore, this study tests whether Instagram use is associated with perceiving that the average person weighs less. Responses of 181 survey participants confirm that Instagram use is negatively related to average weight perception of both women and men. These findings contribute to the growing body of research on how SNS use relates to negative weight-related outcomes.
The management of knowledge in organizations considers both established long-term
processes and cooperation in agile project teams. Since knowledge can be both tacit and explicit, its transfer from the individual to the organizational knowledge base poses a challenge in organizations. This challenge increases when the fluctuation of knowledge carriers is exceptionally high. Especially in large projects in which external consultants are involved, there is a risk that critical, company-relevant knowledge generated in the project will leave the company with the external knowledge carrier and thus be lost. In this paper, we show the advantages of an early warning system for knowledge management to avoid this loss. In particular, the potential of visual analytics in the context of knowledge management systems is presented and discussed. We present a project for the development of a business-critical software system and discuss the first implementations and results.
Despite the phenomenal growth of Big Data Analytics in the last few years, little research is done to explicate the relationship between Big Data Analytics Capability (BDAC) and indirect strategic value derived from such digital capabilities. We attempt to address this gap by proposing a conceptual model of the BDAC - Innovation relationship using dynamic capability theory. The work expands on BDAC business value research and extends the nominal research done on BDAC – innovation. We focus on BDAC's relationship with different innovation objects, namely product, business process, and business model innovation, impacting all value chain activities. The insights gained will stimulate academic and practitioner interest in explicating strategic value generated from BDAC and serve as a framework for future research on the subject
Ultrasound evaluation of the patellar tendon cross-sectional area and its relation to maximum force
(2012)
Turning shy on winter's day effects of season on personality and stress response in Microtus arvalis
(2013)
Track and Treat
(2018)
E-Mail tracking mechanisms gather information on individual recipients’ reading behavior. Previous studies show that e-mail newsletters commonly include tracking elements. However, prior work does not examine the degree to which e-mail senders actually employ gathered user information. The paper closes this research gap by means of an experimental study to clarify the use of tracking-based infor- mation. To that end, twelve mail accounts are created, each of which subscribes to a pre-defined set of newsletters from companies based in Germany, the UK, and the USA. Systematically varying e-mail reading patterns across accounts, each account simulates a different type of user with individual read- ing behavior. Assuming senders to track e-mail reading habits, we expect changes in mailer behavior. The analysis confirms the prominence of tracking in that over 92% of the newsletter e-mails contain tracking images. For 13 out of 44 senders an adjustment of communication policy in response to user reading behavior is observed. Observed effects include sending newsletters at different times, adapting advertised products to match the users’ IT environment, increased or decreased mailing frequency, and mobile-specific adjustments. Regarding legal issues, not all companies that adapt the mail-sending behavior state the usage of such mechanisms in their privacy policy.
Artificial intelligence (AI)-based technologies can increasingly perform knowledge work tasks, such as medical diagnosis. Thereby, it is expected that humans will not be replaced by AI but work closely with AI-based technology (“augmentation”). Augmentation has ethical implications for humans (e.g., impact on autonomy, opportunities to flourish through work), thus, developers and managers of AI-based technology have a responsibility to anticipate and mitigate risks to human workers. However, doing so can be difficult as AI encompasses a wide range of technologies, some of which enable fundamentally new forms of interaction. In this research-in-progress paper, we propose the development of a taxonomy to categorize unique characteristics of AI-based technology that influence the interaction and have ethical implications for human workers. The completed taxonomy will support researchers in forming cumulative knowledge on the ethical implications of augmentation and assist practitioners in the ethical design and management of AI-based technology in knowledge work.
The rise of open source models for software and hardware development has catalyzed the debate regarding sustainable business models. Open Source Software has already become a dominant part in the software industry, whereas Open Source Hardware is still a little-researched phenomenon but has the potential to do the same to manufacturing in a wide range of products. This article addresses this potential by introducing a research design to analyze the prototyping phase of six different Open Source Hardware projects tackling ecological, social, and economical challenges. Using a design science research methodology, a process model is developed to concretise the prototype development steps. The prototype phase is important because it is where fundamental decisions are made that affect the openness of the final product. This paper aims to advance the discourse on open production as a concept that enables companies to apply the aspect of openness towards collaboration-oriented and sustainable business models.
The variability of bone strength and skeletal robustness of young men - how it can be influenced
(2011)
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.
The interplay of autonomy goals and spousal support a prospective study with couples facing cancer
(2012)
The game itself?
(2020)
In this paper, we reassess the notion and current state of ludohermeneutics in game studies, and propose a more solid foundation for how to conduct hermeneutic game analysis. We argue that there can be no ludo-hermeneutics as such, and that every game interpretation rests in a particular game ontology, whether implicit or explicit. The quality of this ontology, then, determines a vital aspect of the quality of the analysis.
The game itself?
(2020)
In this paper, we reassess the notion and current state of ludohermeneutics in game studies, and propose a more solid foundation for how to conduct hermeneutic game analysis. We argue that there can be no ludo-hermeneutics as such, and that every game interpretation rests in a particular game ontology, whether implicit or explicit. The quality of this ontology, then, determines a vital aspect of the quality of the analysis.
The envy spiral
(2020)
On Social Networking Sites (SNS) users disclose mostly positive and often self-enhancing information. Scholars refer to this phenomenon as the positivity bias in SNS communication (PBSC). However, while theoretical explanations for this phenomenon have been proposed, an empirical proof of these theorized mechanisms is still missing. The project presented in this Research-in-Progress paper aims at explaining the PBSC with the mechanism specified in the self-enhancement envy spiral. Specifically, we hypothesize that feelings of envy drive people to post positive and self-enhancing content on SNS. To test this hypothesis, we developed an experimental design allowing to examine the causal effect of envy on the positivity of users’ subsequently posted content. In a preliminary study, we tested our manipulation of envy and could show its effectiveness in inducing different levels of envy between our groups. Our project will help to broaden the understanding of the complex dynamics of SNS and the potentially adverse driving forces underlying them.
e-ASTROGAM is a concept for a breakthrough observatory space mission carrying a gamma-ray telescope dedicated to the study of the non-thermal Universe in the photon energy range from 0.15 MeV to 3 GeV. The lower energy limit can be pushed down to energies as low as 30 keV for gamma-ray burst detection with the calorimeter. The mission is based on an advanced space-proven detector technology, with unprecedented sensitivity, angular and energy resolution, combined with remarkable polarimetric capability. Thanks to its performance in the MeV-GeV domain, substantially improving its predecessors, e-ASTROGAM will open a new window on the non-thermal Universe, making pioneering observations of the most powerful Galactic and extragalactic sources, elucidating the nature of their relativistic outflows and their effects on the surroundings. With a line sensitivity in the MeV energy range one to two orders of magnitude better than previous and current generation instruments, e-ASTROGAM will determine the origin of key isotopes fundamental for the understanding of supernova explosion and the chemical evolution of our Galaxy. The mission will be a major player of the multiwavelength, multimessenger time-domain astronomy of the 2030s, and provide unique data of significant interest to a broad astronomical community, complementary to powerful observatories such as LISA, LIGO, Virgo, KAGRA, the Einstein Telescope and the Cosmic Explorer, IceCube-Gen2 and KM3NeT, SKA, ALMA, JWST, E-ELT, LSST, Athena, and the Cherenkov Telescope Array.
The devil in disguise
(2021)
Envy constitutes a serious issue on Social Networking Sites (SNSs), as this painful emotion can severely diminish individuals' well-being. With prior research mainly focusing on the affective consequences of envy in the SNS context, its behavioral consequences remain puzzling. While negative interactions among SNS users are an alarming issue, it remains unclear to which extent the harmful emotion of malicious envy contributes to these toxic dynamics. This study constitutes a first step in understanding malicious envy’s causal impact on negative interactions within the SNS sphere. Within an online experiment, we experimentally induce malicious envy and measure its immediate impact on users’ negative behavior towards other users. Our findings show that malicious envy seems to be an essential factor fueling negativity among SNS users and further illustrate that this effect is especially pronounced when users are provided an objective factor to mask their envy and justify their norm-violating negative behavior.
The paper deals with the increasing growth of embedded systems and their role within structures similar to the Internet (Internet of Things) as those that provide calculating power and are more or less appropriate for analytical tasks. Faced with the example of a cyber-physical manufacturing system, a common objective function is developed with the intention to measure efficient task processing within analytical infrastructures. A first validation is realized on base of an expert panel.
Test-retest-reliability of metabolic and cardiovascular load during isokinetic strength testing
(2012)
The term Personal Learning Environment (PLE) is associated with the desire to put the learner in control of his own learning process, so that he is able to set and accomplish the desired learning goals at the right time with the learning environment chosen by him. Gradually, such a learning environment includes several digital content, services and tools. It is thus summarized as the Virtual Learning Environment (VLE). Even though the construction of an individual PLE is a complex task, several approaches to support this process already exist. They mostly occur under the umbrella term PLE or with little accentuations like iPLE, which especially live within the context of institutions. This paper sums up the variety of attempts and technical approaches to establish a PLE and suggests a categorization for them.