Prosepctive teachers‘ diagnostic judgements on students’ under- standing of conditional probabilities - Dröse, Jennifer; Griese, B.; Wessel, Lena (Twelfth Congress of the European Society for Research in Mathematics Education (CERME12))

Weiterentwicklung eines physikdidaktischen Tests zum Online-Assessment - Jordans, Melanie; Zeller, Jannis; Große-Heilmann, Rike Isabel; Riese, Josef (Unsicherheit als Element von naturwissenschaftsbezogenen Bildungsprozessen. Gesellschaft für Didaktik der Chemie und Physik. Jahrestagung virtuell 2021)

Ansätze zur Ermittlung von Kompetenzniveaus im Fachdidaktischen Wissen - Zeller, Jannis; Jordans, Melanie; Riese, Josef (Unsicherheit als Element von naturwissenschaftsbezogenen Bildungsprozessen. Gesellschaft für Didaktik der Chemie und Physik. Jahrestagung virtuell 2021)

Procrastination Among University Students: Differentiating Severe Cases in Need of Support From Less Severe Cases - Rozental, Alexander; Forsström, David; Hussoon, Ayah; Klingsieck, Katrin B. (Frontiers in Psychology)
Procrastination refers to voluntarily postponing an intended course of action despite expecting to be worse off for this delay, and students are considered to be especially negatively affected. According to estimates in the literature, at least half of the students believe procrastination impacts their academic achievements and well-being. As of yet, evidence-based ideas on how to differentiate severe from less severe cases of procrastination in this population do not exist, but are important in order to identify those students in need of support. The current study recruited participants from different universities in Sweden to participate in an anonymous online survey investigating self-rated levels of procrastination, impulsivity, perfectionism, anxiety, depression, stress, and quality of life. Furthermore, diagnostic criteria for pathological delay (PDC) as well as self-report items and open-ended questions were used to determine the severity of their procrastination and its associated physical and psychological issues. In total, 732 participants completed the survey. A median-split on the Pure Procrastination Scale (PPS) and the responses to the PDC were used to differentiate two groups; “less severe procrastination” (PPS ≤ 2.99; n = 344; 67.7% female; M age = 30.03; SD age = 9.35), and “severe procrastination” (PPS ≥ 3.00; n = 388; 66.2% female; M age = 27.76; SD age = 7.08). For participants in the severe group, 96–97% considered procrastination to a problem, compared to 42–48% in the less severe group. The two groups also differed with regard to considering seeking help for procrastination, 35–38% compared to 5–7%. Participants in the severe group also reported more problems of procrastination in different life domains, greater symptoms of psychological issues, and lower quality of life. A thematic analysis of the responses on what physical issues were related to procrastination revealed that these were characterized by stress and anxiety, e.g., tension, pain, and sleep and rest, while the psychological issues were related to stress and anxiety, but also depression, e.g., self-criticism, remorse, and self-esteem. The current study recommends the PPS to be used as an initial screening tool, while the PDC can more accurately determine the severity level of procrastination for a specific individual.
Keywords: General Psychology

Delaying Academic Tasks and Feeling Bad About It - Bobe, Julia; Schnettler, Theresa; Scheunemann, Anne; Fries, Stefan; Bäulke, Lisa; Thies, Daniel O.; Dresel, Markus; Leutner, Detlev; Wirth, Joachim; Klingsieck, Katrin B.; Grunschel, Carola (European Journal of Psychological Assessment)
Abstract. Procrastination is the irrational delay of an intended task and is common among students. A delay can only be defined as procrastination when it is voluntary, the action was intended but not implemented, and the delay is accompanied by subjective discomfort. Established scales of procrastination cover mainly behavioral aspects but have neglected the emotional aspect. This inaccuracy concerning the construct validity might entail misconceptions of procrastination. Accordingly, we developed and validated the Behavioral and Emotional Academic Procrastination Scale (BEPS), which covers all aspects of the definition of procrastination. The 6-item scale measuring self-reported academic procrastination was tested in three studies. Study 1 ( N = 239) evaluated the psychometric qualities of the BEPS, indicating good item characteristics and internal consistency. Study 2 ( N = 1,441) used confirmatory factor analysis and revealed two correlated factors: one covering the behavioral aspect and the other reflecting the emotional aspect. Measurement invariance was shown through longitudinal and multigroup confirmatory factor analyses. Study 3 ( N = 234) provided evidence for the scale’s convergent validity through correlations with established procrastination scales, self-efficacy, and neuroticism. The BEPS thus economically operationalizes all characteristics of academic procrastination and appears to be a reliable and valid self-report measure.
Keywords: Applied Psychology

Wie können unterschiedliche Aspekte diagnostischer Kompetenz gefördert werden? - Grotegut, Lea; Klingsieck, Katrin B. (Zeitschrift für Pädagogische Psychologie)
Zusammenfassung. Eine gut ausgebildete diagnostische Kompetenz von Lehrpersonen ist eine wesentliche Voraussetzung für gelingenden Unterricht und trägt maßgeblich zur akademischen und persönlichen Entwicklung von Schülern bei. Häufig sind Lehrpersonen jedoch nur bedingt dazu in der Lage, Schülermerkmale wie Leistung, Motivation oder Ängstlichkeit adäquat zu beurteilen. Eine Förderung der diagnostischen Kompetenz sollte bereits während des Studiums stattfinden, um Lehrpersonen früh auf diagnostische Situationen in der Schulpraxis vorzubereiten und negative Konsequenzen möglicher pädagogischer Fehlentscheidungen zu vermeiden. Dieser Beitrag vergleicht eine lehrendenzentrierte, eine problembasierte und eine digitale, simulationsbasierte Maßnahme zur Förderung unterschiedlicher Aspekte diagnostischer Kompetenz an einer Stichprobe von N = 166 Lehramtsstudierenden im Hinblick auf ihre Wirksamkeit. Es zeigen sich insbesondere Vorteile der simulationsbasierten Fördermaßnahme in den Bereichen intrinsische Motivation und Interesse sowie Nachteile der lehrendenzentrierten Maßnahme im Bereich des Wissens um das systematische Vorgehen im diagnostischen Prozess und der problembasierten Maßnahme im Bereich des Extraneous Cognitive Load. Die Ergebnisse werden insbesondere im Hinblick auf ihre praktischen Implikationen im Rahmen der Lehrerbildung und zunehmend digitalisierter Lehre diskutiert.
Keywords: Developmental and Educational Psychology

Social factors of procrastination: group work can reduce procrastination among students - Koppenborg, Markus; Klingsieck, Katrin B. (Social Psychology of Education)
Abstract Research on procrastination covers a variety of individual factors (e.g., conscientiousness) and this focus is reflected in interventions against procrastination. Less emphasis is put on situational and social factors that may help students reduce procrastination, such as social interdependence. Therefore, this study investigates the relationship between interdependence with academic procrastination and affective variables. Two vignette studies with student samples ( N 1 = 320, N 2 = 193) were conducted and data was analyzed with regression analyses and analyses of covariance. Results of both studies show lower state procrastination in group work with interdependence compared to individual work, especially in participants with high trait procrastination. This difference is more pronounced when interdependence is accompanied by an active commitment to finish the task on time. Further, interdependent group work is related to increased positive affect and decreased negative affect. The results demonstrate the relevance of situational and social factors for academic procrastination, and point toward new approaches for intervention.
Keywords: Sociology and Political Science; Developmental and Educational Psychology; Social Psychology

Group work and student procrastination - Koppenborg, Markus; Klingsieck, Katrin B. (Learning and Individual Differences)
Keywords: Developmental and Educational Psychology; Education; Social Psychology

Procrastination in the looking glass of self-awareness. Can gamified self-monitoring reduce academic procrastination? - Klingsieck, Katrin B.; John, Thomas; Kundisch, Dennis (die hochschullehre)

Flusseinsamkeiten: Hölderlins 'Ister' und 'Nekar' im Berlin der Gegenwart bei Tomer Dotan-Dreyfus - Spener, Anna Maria

Utterance-by-utterance overlap-aware neural diarization with Graph-PIT - Kinoshita, Keisuke; von Neumann, Thilo; Delcroix, Marc; Boeddeker, Christoph; Haeb-Umbach, Reinhold (Proc. Interspeech 2022)
Recent speaker diarization studies showed that integration of end-to-end neural diarization (EEND) and clustering-based diarization is a promising approach for achieving state-of-the-art performance on various tasks. Such an approach first divides an observed signal into fixed-length segments, then performs {\it segment-level} local diarization based on an EEND module, and merges the segment-level results via clustering to form a final global diarization result. The segmentation is done to limit the number of speakers in each segment since the current EEND cannot handle a large number of speakers. In this paper, we argue that such an approach involving the segmentation has several issues; for example, it inevitably faces a dilemma that larger segment sizes increase both the context available for enhancing the performance and the number of speakers for the local EEND module to handle. To resolve such a problem, this paper proposes a novel framework that performs diarization without segmentation. However, it can still handle challenging data containing many speakers and a significant amount of overlapping speech. The proposed method can take an entire meeting for inference and perform {\it utterance-by-utterance} diarization that clusters utterance activities in terms of speakers. To this end, we leverage a neural network training scheme called Graph-PIT proposed recently for neural source separation. Experiments with simulated active-meeting-like data and CALLHOME data show the superiority of the proposed approach over the conventional methods.

SA-SDR: A Novel Loss Function for Separation of Meeting Style Data - von Neumann, Thilo; Kinoshita, Keisuke; Boeddeker, Christoph; Delcroix, Marc; Haeb-Umbach, Reinhold (ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP))

MMS-MSG: A Multi-purpose Multi-Speaker Mixture Signal Generator - Cord-Landwehr, Tobias; von Neumann, Thilo; Boeddeker, Christoph; Haeb-Umbach, Reinhold (2022 International Workshop on Acoustic Signal Enhancement (IWAENC))
The scope of speech enhancement has changed from a monolithic view of single, independent tasks, to a joint processing of complex conversational speech recordings. Training and evaluation of these single tasks requires synthetic data with access to intermediate signals that is as close as possible to the evaluation scenario. As such data often is not available, many works instead use specialized databases for the training of each system component, e.g WSJ0-mix for source separation. We present a Multi-purpose Multi-Speaker Mixture Signal Generator (MMS-MSG) for generating a variety of speech mixture signals based on any speech corpus, ranging from classical anechoic mixtures (e.g., WSJ0-mix) over reverberant mixtures (e.g., SMS-WSJ) to meeting-style data. Its highly modular and flexible structure allows for the simulation of diverse environments and dynamic mixing, while simultaneously enabling an easy extension and modification to generate new scenarios and mixture types. These meetings can be used for prototyping, evaluation, or training purposes. We provide example evaluation data and baseline results for meetings based on the WSJ corpus. Further, we demonstrate the usefulness for realistic scenarios by using MMS-MSG to provide training data for the LibriCSS database.

Monaural source separation: From anechoic to reverberant environments - Cord-Landwehr, Tobias; Boeddeker, Christoph; von Neumann, Thilo; Zorila, Catalin; Doddipatla, Rama; Haeb-Umbach, Reinhold (2022 International Workshop on Acoustic Signal Enhancement (IWAENC))
Impressive progress in neural network-based single-channel speech source separation has been made in recent years. But those improvements have been mostly reported on anechoic data, a situation that is hardly met in practice. Taking the SepFormer as a starting point, which achieves state-of-the-art performance on anechoic mixtures, we gradually modify it to optimize its performance on reverberant mixtures. Although this leads to a word error rate improvement by 7 percentage points compared to the standard SepFormer implementation, the system ends up with only marginally better performance than a PIT-BLSTM separation system, that is optimized with rather straightforward means. This is surprising and at the same time sobering, challenging the practical usefulness of many improvements reported in recent years for monaural source separation on nonreverberant data.

Couleur Locale - Schulze, Max (Die Wirklichkeit ist sowieso da)

Single Club - Schulze, Max (Düsseldorf und Fotografie)

Rezension von: Viola Schrader: Historisches Denken und sprachliches Handeln. Eine qualitativ-empirische Untersuchung von Schülertexten. Münster et al.: LIT 2021 - Hartung, Olaf (sehepunkte)

‚Schreibsensibel‘ Geschichte unterrichten: Fachspezifische Textkompetenz als Gegenstand und Medium des historischen Lernens - Hartung, Olaf; Memminger, Josef (Schreiben fachübergreifend fördern. Grundlagen und Praxisanregungen für Schule, Unterricht und Lehrerinnen- und Lehrerbildung)

On Synchronization of Wireless Acoustic Sensor Networks in the Presence of Time-Varying Sampling Rate Offsets and Speaker Changes - Gburrek, Tobias; Schmalenstroeer, Joerg; Haeb-Umbach, Reinhold (ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP))

Semiparametric GARCH models with long memory applied to Value at Risk and Expected Shortfall - Letmathe, Sebastian; Feng, Yuanhua; Uhde, André (Journal of Risk)
In this paper new semiparametric generalized autoregressive conditional heteroscedasticity (GARCH) models with long memory are introduced. A multiplicative decomposition of the volatility into a conditional component and an unconditional component is assumed. The estimation of the latter is carried out by means of a data-driven local polynomial smoother. According to the revised recommendations by the Basel Committee on Banking Supervision to measure market risk in the banks’ trading books, these new semiparametric GARCH models are applied to obtain rolling one-step ahead forecasts for the value-at-risk and expected shortfall (ES) for market risk assets. Standard regulatory traffic-light tests and a newly introduced traffic-light test for the ES are carried out for all models. In addition, model performance is assessed via a recently introduced model selection criterion. The practical relevance of our proposal is demonstrated by a comparative study. Our results indicate that semiparametric long-memory GARCH models are a meaningful substitute for their conventional, parametric counterparts.
Keywords: long memory; generalized autoregressive conditional heteroscedasticity (GARCH) models; value-at-risk (VaR); expected shortfall (ES); traffic-light test; backtesting

Warping of Radar Data Into Camera Image for Cross-Modal Supervision in Automotive Applications - Grimm, Christopher; Fei, Tai; Warsitz, Ernst; Farhoud, Ridha; Breddermann, Tobias; Haeb-Umbach, Reinhold (IEEE Transactions on Vehicular Technology)
We present an approach to automatically generate semantic labels for real recordings of automotive range-Doppler (RD) radar spectra. Such labels are required when training a neural network for object recognition from radar data. The automatic labeling approach rests on the simultaneous recording of camera and lidar data in addition to the radar spectrum. By warping radar spectra into the camera image, state-of-the-art object recognition algorithms can be applied to label relevant objects, such as cars, in the camera image. The warping operation is designed to be fully differentiable, which allows backpropagating the gradient computed on the camera image through the warping operation to the neural network operating on the radar data. As the warping operation relies on accurate scene flow estimation, we further propose a novel scene flow estimation algorithm which exploits information from camera, lidar and radar sensors. The proposed scene flow estimation approach is compared against a state-of-the-art scene flow algorithm, and it outperforms it by approximately 30% w.r.t. mean average error. The feasibility of the overall framework for automatic label generation for RD spectra is verified by evaluating the performance of neural networks trained with the proposed framework for Direction-of-Arrival estimation.

Erfolgreiches People Management in KMU und Start-ups - Krebs, Benjamin; Kabst, Rüdiger (PERSONALquartely)

Methodenverliebt am Markt vorbei? - Rebert, Tobias; Tomin, Slawa; Wach, Bernhard; Kabst, Rüdiger (Intrapreneurship)

Pre-Training And Self-Training For Sound Event Detection In Domestic Environments - Ebbers, Janek; Haeb-Umbach, Reinhold
In this report we present our system for the Detection and Classification of Acoustic Scenes and Events (DCASE) 2022 Challenge Task 4: Sound Event Detection in Domestic Environments 1 . As in previous editions of the Challenge, we use forward-backward convolutional recurrent neural networks (FBCRNNs) [1, 2] for weakly labeled and semi-supervised sound event detection (SED) and eventually generate strong pseudo labels for weakly labeled and unlabeled data. Then, (tag-conditioned) bidirectional CRNNs (Bi-CRNNs) [1, 2] are trained in a strongly supervised manner as our final SED models. In each of the training stages we use multiple iterations of self-training. Compared to previous editions, we improved our system performance by 1) some tweaks regarding data augmentation, pseudo labeling and inference 2) using weakly labeled AudioSet data [3] for pretraining larger networks and 3) augmenting the DESED data [4] with strongly labeled AudioSet data [5] for finetuning of the networks. Source code is publicly available at https://github.com/fgnt/pb_sed.

If You Can’t Get Them to the Lab: Evaluating a Virtual Study Environment with Security Information Workers - Huaman, Nicolas; Krause, Alexander; Wermke, Dominik; Klemmer, Jan H.; Stransky, Christian; Acar, Yasemin; Fahl, Sascha (Eighteenth Symposium on Usable Privacy and Security, SOUPS 2022, Boston, MA, USA, August 7-9, 2022)

How Does Usable Security (Not) End Up in Software Products? Results From a Qualitative Interview Study - Gutfleisch, Marco; Klemmer, Jan H.; Busch, Niklas; Acar, Yasemin; Sasse, M. Angela; Fahl, Sascha (43rd IEEE Symposium on Security and Privacy, SP 2022, San Francisco, CA, USA, May 22-26, 2022)

27 Years and 81 Million Opportunities Later: Investigating the Use of Email Encryption for an Entire University - Stransky, Christian; Wiese, Oliver; Roth, Volker; Acar, Yasemin; Fahl, Sascha (43rd IEEE Symposium on Security and Privacy, SP 2022, San Francisco, CA, USA, May 22-26, 2022)

Where to Recruit for Security Development Studies: Comparing Six Software Developer Samples - Kaur, Harjot; Amft, Sabrina; Votipka, Daniel; Acar, Yasemin; Fahl, Sascha (31st USENIX Security Symposium, USENIX Security 2022, Boston, MA, USA, August 10-12, 2022)

They Would Do Better If They Worked Together: Interaction Problems Between Password Managers and the Web - Huaman, Nicolas; Amft, Sabrina; Oltrogge, Marten; Acar, Yasemin; Fahl, Sascha (IEEE Secur. Priv.)

"Please help share!": Security and Privacy Advice on Twitter during the 2022 Russian Invasion of Ukraine - Schmüser, Juliane; Wöhler, Noah; Ramulu, Harshini Sri; Stransky, Christian; Wermke, Dominik; Fahl, Sascha; Acar, Yasemin (CoRR)

Technically enabled explaining of voice characteristics - Wiechmann, Jana; Glarner, Thomas; Rautenberg, Frederik; Wagner, Petra; Haeb-Umbach, Reinhold (18. Phonetik und Phonologie im deutschsprachigen Raum (P&P))

Erkenntnisse aus Arbeitgeberbewertungen – Potenzial von Atmosphäre und Arbeitsplätzen. - Radermacher, Katharina; Herdejürgen, Enja Marie (PERSONALquarterly)

Long‐term effects of institutional conditions on perceived corruption – A study on organizational imprinting in post‐communist countries - Auer, Thorsten Fabian; Knorr, Karin; Thommes, Kirsten (Business Ethics, the Environment & Responsibility)
In this paper, we apply imprinting theory to examine how institutional transformation substantially influences perceptions of corruption that we argue to be incorporated to a varying extent in organizations founded in that period. For this purpose, we compare the effect of a sudden shock (dissolution of the Soviet Union) on the managers' present perceptions to that of a steady transition (EU accession). We consult the 5th round of the Business Environment and Enterprise Performance Survey from 2012 to 2014 analyzing 4715 interviews with managers of organizations from twelve Central and Eastern European countries. Our results reveal striking differences in the present perception of corruption for organizations founded immediately before and immediately after these institutional transitions. The study's results contribute to the research on imprinting theory regarding the relationship between organizations and institutional conditions that constitutes a lasting effect on organizational structures. Thus, applying an institutional perspective that considers less stable periods for organizations yields a promising avenue in research on organizational behavior.
Keywords: Central and Eastern Europe; corruption; imprinting theory; institutional transformation; shock-imprinting

Die Wirksamkeit von Lernzielen für Studienleistungen – eine experimentelle Studie - Auer, Thorsten Fabian (die hochschullehre)
According to the German Rectors’ Conference (HRK), German higher education teaching fails to meet the demand to integrate competence-oriented learning objectives. Despite a wide-ranging debate on the use of learning objectives, empirical research on their effectiveness is scarce. The present study uses the features of digital teaching platforms to investigate the perception and effectiveness of learning objectives applying a randomised controlled experiment followed by a survey in a course for undergraduate economics students (N = 30). Controlling group preconditions and the treatment effect allows to draw conclusions about the different learning outcomes of the student groups. The specification of behaviour-oriented learning objectives in the online course system leads to significantly better performance in the treatment group. A stronger perception of the learning objectives in the treatment group supports this effect that remains significant in a regression analysis. Thus, the study provides an empirical justification to integrate learning objectives in university teaching.
Keywords: learning objectives; academic performance; perception; teaching methods; experiment

AI-Based Assistance System for Manufacturing - Deppe, Sahar; Brandt, Lukas; Brünninghaus, Marc; Papenkordt, Jörg; Heindorf, Stefan; Tschirner-Vinke, Gudrun
Manufacturing companies are challenged to make the increasingly complex work processes equally manageable for all employees to prevent an impending loss of competence. In this contribution, an intelligent assistance system is proposed enabling employees to help themselves in the workplace and provide them with competence-related support. This results in increasing the short- and long-term efficiency of problem solving in companies.
Keywords: Assistance system; Knowledge graph; Information retrieval; Neural networks; AR

AI-Based Assistance System for Manufacturing - Deppe, Sahar; Brandt, Lukas; Brunninghaus, Marc; Papenkordt, Jörg; Heindorf, Stefan; Tschirner-Vinke, Gudrun (2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA))

Determinants of Trust in Smart Technologies - Papenkordt, Jörg; Thommes, Kirsten (Human-Technology Interaction)

Warum werde ich nicht satt? Begehren und Begehrt-Werden bei den Ärzt*innen der Utopie. Grey’s Anatomy aus einer inklusiven religionspädagogischen Perspektive - Neumann, Anna (Lust und Abgrund. Theologische und kulturwissenschaftliche Zugänge zum Begehren)

Die Frage der Apostasie im Islam – Rationale Behandlung von Adlabī und El-ʿAwwā - Abdelrahem, Mohammed (Rationalität in der Islamischen Theologie Band II: Die Moderne)
Keywords: islamisches Recht. islamische Normenlehre; islamic law; Apostasie; Rationalität; Islam

Rationalität in der Islamischen Theologie II: Die Moderne

Ich habe nur die eine Hälfte genommen – Verstehensprozesse zur Achsensymmetrie - Wallner, Melina (Beiträge zum Mathematikunterricht 2022. 56. Jahrestagung der Gesellschaft für Didaktik der Mathematik)

Erkenntnisse aus Arbeitgeberbewertungen: Das Potential von Arbeitsatmosphäre und Arbeitsplatzgestaltung für die Weiterempfehlungsbereitschaft (Studie Industrieverband Büro und Arbeitswelt e. V. (IBA).)

Verification of safety critical control policies using kernel methods - Vertovec, Nikolaus; Ober-Blöbaum, Sina; Margellos, Kostas
Hamilton-Jacobi reachability methods for safety-critical control have been well studied, but the safety guarantees derived rely on the accuracy of the numerical computation. Thus, it is crucial to understand and account for any inaccuracies that occur due to uncertainty in the underlying dynamics and environment as well as the induced numerical errors. To this end, we propose a framework for modeling the error of the value function inherent in Hamilton-Jacobi reachability using a Gaussian process. The derived safety controller can be used in conjuncture with arbitrary controllers to provide a safe hybrid control law. The marginal likelihood of the Gaussian process then provides a confidence metric used to determine switches between a least restrictive controller and a safety controller. We test both the prediction as well as the correction capabilities of the presented method in a classical pursuit-evasion example.

Gottesbilder in den Deuteropaulinen. Metaphernrezeption im Kontext von Bildfeldtraditionen - Taschl-Erber, Andrea (Gottes-Bilder. Zur Metaphorik biblischer Gottesrede (Beiträge zur Wissenschaft vom Alten und Neuen Testament 232))

"Von dem, der getragen wurde durch die Vier und Rettung erfuhr. Ein etwas anderer Blick in die Erzählung von der Heilung des Gelähmten in Mk 2,1-12" - Breuer, Saskia Rebecca (Der Dom. Katholisches Magazin im Erzbistum Paderborn)

Cho, Bernardo K., "Royal Messianism and the Jerusalem Priesthood in the Gospel of Mark" - Breuer, Saskia Rebecca (Theologische Revue)

* - Scharlau, Ingrid; Jenert, Tobias (Doing Research: Wissenschaftspraktiken zwischen Positionierung und Suchanfrage)

Teilen und die mediale Logik des Dabei-seins - Bartz, Christina (Following. Ein Kompendium zu Medien der Gefolgschaft und Prozesse des Folgens)

“They’re not that hard to mitigate”: What Cryptographic Library Developers Think About Timing Attacks - Jancar, Jan; Fourné, Marcel; Braga, Daniel De Almeida; Sabt, Mohamed; Schwabe, Peter; Barthe, Gilles; Fouque, Pierre-Alain; Acar, Yasemin (2022 IEEE Symposium on Security and Privacy (SP))

Committed to Trust: A Qualitative Study on Security & Trust in Open Source Software Projects - Wermke, Dominik; Wohler, Noah; Klemmer, Jan H.; Fourné, Marcel; Acar, Yasemin; Fahl, Sascha (2022 IEEE Symposium on Security and Privacy (SP))

Mensch, Natur, Technik. Miteinander leben, Umwelt und Technik. Zyklus 2. - Tenberge, Claudia; von Braunmühl, Susanne

Große Fragen. Vergänglichkeit, Werte, Existenz und Welt. Zyklus 2. - Tenberge, Claudia; von Braunmühl, Susanne

Kultur und Kommunikation. Verständigung und Fantasie. Zyklus 2. - Tenberge, Claudia; von Braunmühl, s

Ich und die anderen. Persönliche Beziehungen. Zyklus 3. - Tenberge, Claudia; von Braunmühl, Susanne

Ich. Orientierung und Entwicklung. Zyklus 3. - Tenberge, Claudia; von Braunmühl, Susanne

Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping - Philipo, Godiana Hagile; Kakande, Josephine Nakato; Krauter, Stefan (Energies)
Due to failures or even the absence of an electricity grid, microgrid systems are becoming popular solutions for electrifying African rural communities. However, they are heavily stressed and complex to control due to their intermittency and demand growth. Demand side management (DSM) serves as an option to increase the level of flexibility on the demand side by scheduling users’ consumption patterns profiles in response to supply. This paper proposes a demand-side management strategy based on load shifting and peak clipping. The proposed approach was modelled in a MATLAB/Simulink R2021a environment and was optimized using the artificial neural network (ANN) algorithm. Simulations were carried out to test the model’s efficacy in a stand-alone PV-battery microgrid in East Africa. The proposed algorithm reduces the peak demand, smoothing the load profile to the desired level, and improves the system’s peak to average ratio (PAR). The presence of deferrable loads has been considered to bring more flexible demand-side management. Results promise decreases in peak demand and peak to average ratio of about 31.2% and 7.5% through peak clipping. In addition, load shifting promises more flexibility to customers.
Keywords: Energy (miscellaneous); Energy Engineering and Power Technology; Renewable Energy; Sustainability and the Environment; Electrical and Electronic Engineering; Control and Optimization; Engineering (miscellaneous); Building and Construction

Brillouin and Raman imaging of domain walls in periodically-poled 5%-MgO:LiNbO3 - Rix, Jan; Rüsing, Michael; Galli, Roberta; Golde, Jonas; Reitzig, Sven; Eng, Lukas M.; Koch, Edmund (Optics Express)
Recently, ferroelectric domain walls (DWs) have attracted considerable attention due to their intrinsic topological effects and their huge potential for optoelectronic applications. In contrast, many of the underlying physical properties and phenomena are not well characterized. In this regard, analyzing the vibrational properties, e.g. by Raman spectroscopy, provides direct access to the various local material properties, such as strains, defects or electric fields. While the optical phonon spectra of DWs have been widely investigated in the past, no reports on the acoustic phonon properties of DWs exist. In this work, we present a joint Raman and Brillouin visualization of ferroelectric DWs in the model ferroelectric lithium niobate. This is possible by using a combined Raman and virtually imaged phased array Brillouin setup. Here, we show that DWs can be visualized via frequency shifts observed in the acoustic phonons, as well. The observed contrast then is qualitatively explained by models adapted from Raman spectroscopy. This work, hence, provides a novel route to study ferroelectric DWs and their intrinsic mechanical properties.
Keywords: Atomic and Molecular Physics; and Optics

Denkschrift - Markewitz, Friedrich; Schuster, Britt-Marie (Im Nationalsozialismus)
Keywords: Kommunikationsgeschichte

Blut - Schuster, Britt-Marie; Wilk, Nicole M. (Im Nationalsozialismus)
Keywords: Kommunikationsgeschichte

CARS Domain-Wall Analysis in single-crystalline Lithium Niobate - Reitzig, Sven; Hempel, Franz; Rüsing, Michael; Eng, Lukas M. (OSA Nonlinear Optics 2021)
We apply coherent anti-Stokes Raman scattering (CARS) for high-speed imaging of domain walls in lithium niobate. The domain wall signature provides similar spectral features as in spontaneous Raman spectroscopy, however at drastically increased scan speeds.

Second-harmonic microscopy in optically confining nanostructures - Amber, Zeeshan H.; Kirbus, Benjamin; Rüsing, Michael; Eng, Lukas M. (OSA Nonlinear Optics 2021)
The influence of geometrical confinement in back-reflection Second-Harmonic microscopy is experimentally and theoretically investigated in the wedge-shaped model system lithium niobate. The co-propagating signal is found to be the dominating contribution.

Broadband Coherent Anti-Stokes Raman Scattering on Solid State Systems - Hempel, Franz; Reitzig, Sven; Rüsing, Michael; Eng, Lukas M. (OSA Nonlinear Optics 2021)
We apply broadband coherent anti-Stokes Raman scattering, an imaging tech- nique mostly applied in biology, to the solid state system lithium niobate, where we show an enhanced full spectrum and a working signal transformation.

HPO x ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis - Schneider, Lennart; Schäpermeier, Lennart; Prager, Raphael Patrick; Bischl, Bernd; Trautmann, Heike; Kerschke, Pascal (Parallel Problem Solving from Nature — PPSN XVII)
Hyperparameter optimization (HPO) is a key component of machine learning models for achieving peak predictive performance. While numerous methods and algorithms for HPO have been proposed over the last years, little progress has been made in illuminating and examining the actual structure of these black-box optimization problems. Exploratory landscape analysis (ELA) subsumes a set of techniques that can be used to gain knowledge about properties of unknown optimization problems. In this paper, we evaluate the performance of five different black-box optimizers on 30 HPO problems, which consist of two-, three- and five-dimensional continuous search spaces of the XGBoost learner trained on 10 different data sets. This is contrasted with the performance of the same optimizers evaluated on 360 problem instances from the black-box optimization benchmark (BBOB). We then compute ELA features on the HPO and BBOB problems and examine similarities and differences. A cluster analysis of the HPO and BBOB problems in ELA feature space allows us to identify how the HPO problems compare to the BBOB problems on a structural meta-level. We identify a subset of BBOB problems that are close to the HPO problems in ELA feature space and show that optimizer performance is comparably similar on these two sets of benchmark problems. We highlight open challenges of ELA for HPO and discuss potential directions of future research and applications.

A Collection of Deep Learning-based Feature-Free Approaches for Characterizing Single-Objective Continuous Fitness Landscapes - Seiler, Moritz Vinzent; Prager, Raphael Patrick; Kerschke, Pascal; Trautmann, Heike (Proceedings of the Genetic and Evolutionary Computation Conference)
Exploratory Landscape Analysis is a powerful technique for numerically characterizing landscapes of single-objective continuous optimization problems. Landscape insights are crucial both for problem understanding as well as for assessing benchmark set diversity and composition. Despite the irrefutable usefulness of these features, they suffer from their own ailments and downsides. Hence, in this work we provide a collection of different approaches to characterize optimization landscapes. Similar to conventional landscape features, we require a small initial sample. However, instead of computing features based on that sample, we develop alternative representations of the original sample. These range from point clouds to 2D images and, therefore, are entirely feature-free. We demonstrate and validate our devised methods on the BBOB testbed and predict, with the help of Deep Learning, the high-level, expert-based landscape properties such as the degree of multimodality and the existence of funnel structures. The quality of our approaches is on par with methods relying on the traditional landscape features. Thereby, we provide an exciting new perspective on every research area which utilizes problem information such as problem understanding and algorithm design as well as automated algorithm configuration and selection.

Automated Algorithm Selection in Single-Objective Continuous Optimization: A Comparative Study of Deep Learning and Landscape Analysis Methods - Prager, Raphael Patrick; Seiler, Moritz Vinzent; Trautmann, Heike; Kerschke, Pascal (Parallel Problem Solving from Nature — PPSN XVII)
In recent years, feature-based automated algorithm selection using exploratory landscape analysis has demonstrated its great potential in single-objective continuous black-box optimization. However, feature computation is problem-specific and can be costly in terms of computational resources. This paper investigates feature-free approaches that rely on state-of-the-art deep learning techniques operating on either images or point clouds. We show that point-cloud-based strategies, in particular, are highly competitive and also substantially reduce the size of the required solver portfolio. Moreover, we highlight the effect and importance of cost-sensitive learning in automated algorithm selection models.

Artificial Social Media Campaign Creation for Benchmarking and Challenging Detection Approaches - Pohl, Janina Susanne; Assenmacher, Dennis; Seiler, Moritz Vincent; Trautmann, Heike; Grimme, Christian (Workshop Proceedings of the 16$^th$ International Conference on Web and Social Media (ICWSM))
Social media platforms are essential for information sharing and, thus, prone to coordinated dis- and misinformation campaigns. Nevertheless, research in this area is hampered by strict data sharing regulations imposed by the platforms, resulting in a lack of benchmark data. Previous work focused on circumventing these rules by either pseudonymizing the data or sharing fragments. In this work, we will address the benchmarking crisis by presenting a methodology that can be used to create artificial campaigns out of original campaign building blocks. We conduct a proof-of-concept study using the freely available generative language model GPT-Neo in this context and demonstrate that the campaign patterns can flexibly be adapted to an underlying social media stream and evade state-of-the-art campaign detection approaches based on stream clustering. Thus, we not only provide a framework for artificial benchmark generation but also demonstrate the possible adversarial nature of such benchmarks for challenging and advancing current campaign detection methods.

On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems - Rook, J; Trautmann, Heike; Bossek, J; Grimme, C (Proceedings of the Genetic and Evolutionary Computation Conference Companion)
Hardness of Multi-Objective (MO) continuous optimization problems results from an interplay of various problem characteristics, e. g. the degree of multi-modality. We present a benchmark study of classical and diversity focused optimizers on multi-modal MO problems based on automated algorithm configuration. We show the large effect of the latter and investigate the trade-off between convergence in objective space and diversity in decision space.

Process-Oriented Stream Classification Pipeline: A Literature Review - Clever, Lena; Pohl, Janina Susanne; Bossek, Jakob; Kerschke, Pascal; Trautmann, Heike (Applied Sciences)
Due to the rise of continuous data-generating applications, analyzing data streams has gained increasing attention over the past decades. A core research area in stream data is stream classification, which categorizes or detects data points within an evolving stream of observations. Areas of stream classification are diverse—ranging, e.g., from monitoring sensor data to analyzing a wide range of (social) media applications. Research in stream classification is related to developing methods that adapt to the changing and potentially volatile data stream. It focuses on individual aspects of the stream classification pipeline, e.g., designing suitable algorithm architectures, an efficient train and test procedure, or detecting so-called concept drifts. As a result of the many different research questions and strands, the field is challenging to grasp, especially for beginners. This survey explores, summarizes, and categorizes work within the domain of stream classification and identifies core research threads over the past few years. It is structured based on the stream classification process to facilitate coordination within this complex topic, including common application scenarios and benchmarking data sets. Thus, both newcomers to the field and experts who want to widen their scope can gain (additional) insight into this research area and find starting points and pointers to more in-depth literature on specific issues and research directions in the field.

The objective that freed me: a multi-objective local search approach for continuous single-objective optimization - Aspar, Pelin; Steinhoff, Vera; Schäpermeier, Lennart; Kerschke, Pascal; Trautmann, Heike; Grimme, Christian (Natural Computing)
Single-objective continuous optimization can be challenging, especially when dealing with multimodal problems. This work sheds light on the effects that multi-objective optimization may have in the single-objective space. For this purpose, we examine the inner mechanisms of the recently developed sophisticated local search procedure SOMOGSA. This method solves multimodal single-objective continuous optimization problems based on first expanding the problem with an additional objective (e.g., a sphere function) to the bi-objective domain and subsequently exploiting local structures of the resulting landscapes. Our study particularly focuses on the sensitivity of this multiobjectivization approach w.r.t. (1) the parametrization of the artificial second objective, as well as (2) the position of the initial starting points in the search space. As SOMOGSA is a modular framework for encapsulating local search, we integrate Nelder–Mead local search as optimizer in the respective module and compare the performance of the resulting hybrid local search to its original single-objective counterpart. We show that the SOMOGSA framework can significantly boost local search by multiobjectivization. Hence, combined with more sophisticated local search and metaheuristics, this may help solve highly multimodal optimization problems in the future.

BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems - Heins, J; Rook, J; Schäpermeier, L; Kerschke, P; Bossek, J; Trautmann, Heike (Parallel Problem Solving from Nature — PPSN XVII)

Das Stützpunktsystem im paralympischen Leistungssport. Eine empirische Studie unter Berücksichtigung der Perspektive von Para-Athletinnen und -Athleten sowie des Stützpunktpersonals. - Radtke, Sabine; Freier, M. Pia
Keywords: Para Sport

Das Stützpunktsystem im paralympischen Leistungssport. Eine empirische Studie unter Berücksichtigung der Perspektive von Para-Athletinnen und -Athleten sowie des Stützpunktpersonals. - Radtke, Sabine; Freier, M. Pia

An approach to teaching data science in middle school - Podworny, Susanne; Fleischer, Yannik (Proceedings of the 15th international conference on technology in mathematics teaching (ICTMT 15))

Teaching machine learning with decision trees in middle school using CODAP - Fleischer, Yannik; Podworny, Susanne (Proceedings of the 15th international conference on technology in mathematics teaching (ICTMT 15))

A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING - PODWORNY, SUSANNE; HÜSING, SVEN; SCHULTE, CARSTEN (STATISTICS EDUCATION RESEARCH JOURNAL)
Aspects of data science surround us in many contexts, for example regarding climate change, air pollution, and other environmental issues. To open the “data-science-black-box” for lower secondary school students we developed a data science project focussing on the analysis of self-collected environmental data. We embed this project in computer science education, which enables us to use a new knowledge-based programming approach for the data analysis within Jupyter Notebooks and the programming language Python. In this paper, we evaluate the second cycle of this project which took place in a ninth-grade computer science class. In particular, we present how the students coped with the professional tool of Jupyter Notebooks for doing statistical investigations and which insights they gained.
Keywords: Education; Statistics and Probability

Grade 6 Students’ Perception and Use of Data-Based Decision Trees - Podworny, Susanne; Fleischer, Yannik; Hüsing, Sven (Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics)
Decision-making processes are often based on data and data-driven machine learning methods in different areas such as recommender systems, medicine, criminalistics, etc. Well-informed citizens need at least a minimal understanding and critical reflection of corresponding data-driven machine learning methods. Decision trees are a method that can foster a preformal understanding of machine learning. We developed an exploratory teaching unit introducing decision trees in grade 6 along the question “How can Artificial Intelligence help us decide whether food is rather recommendable or not?” Students’ performances in an assessment task and self-assessment show that young learners can use a decision tree to classify new items and that they found the corresponding teaching unit informative.

Jupyter Notebooks for Teaching, Learning, and Doing Data Science - Fleischer, Yannik; Hüsing, Sven; Biehler, Rolf; Podworny, Susanne; Schulte, Carsten (Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics)
We report on our work with students in our data science courses, focusing on the analysis of students’ results. This study represents an in-depth analysis of students’ creation and documentation of machine learning models. The students were supported by educationally designed Jupyter Notebooks, which are used as worked examples. Using the worked example, students document their results in a so-called computational essay. We examine which aspects of creating computational essays are difficult for students to find out how worked examples should be designed to support students without being too prescriptive. We analyze the computational essays produced by students and draw consequences for redesigning our worked example.

An example of rich, real and multivariate survey data for use in school - Podworny, Susanne; Fleischer, Yannik; Stroop, Dietlinde; Biehler, Rolf

Vokabeln lernen im Schlaf? Statistische Testprozeduren verstehen - Podworny, Susanne (mathematik lehren)

Privacy-Preserving Graph Convolutional Networks for Text Classification - Igamberdiev, Timour; Habernal, Ivan (Proceedings of the Thirteenth Language Resources and Evaluation Conference)
Graph convolutional networks (GCNs) are a powerful architecture for representation learning on documents that naturally occur as graphs, e.g., citation or social networks. However, sensitive personal information, such as documents with people{’}s profiles or relationships as edges, are prone to privacy leaks, as the trained model might reveal the original input. Although differential privacy (DP) offers a well-founded privacy-preserving framework, GCNs pose theoretical and practical challenges due to their training specifics. We address these challenges by adapting differentially-private gradient-based training to GCNs and conduct experiments using two optimizers on five NLP datasets in two languages. We propose a simple yet efficient method based on random graph splits that not only improves the baseline privacy bounds by a factor of 2.7 while retaining competitive F1 scores, but also provides strong privacy guarantees of epsilon = 1.0. We show that, under certain modeling choices, privacy-preserving GCNs perform up to 90{%} of their non-private variants, while formally guaranteeing strong privacy measures.

DP-Rewrite: Towards Reproducibility and Transparency in Differentially Private Text Rewriting - Igamberdiev, Timour; Arnold, Thomas; Habernal, Ivan (Proceedings of the 29th International Conference on Computational Linguistics)
Text rewriting with differential privacy (DP) provides concrete theoretical guarantees for protecting the privacy of individuals in textual documents. In practice, existing systems may lack the means to validate their privacy-preserving claims, leading to problems of transparency and reproducibility. We introduce DP-Rewrite, an open-source framework for differentially private text rewriting which aims to solve these problems by being modular, extensible, and highly customizable. Our system incorporates a variety of downstream datasets, models, pre-training procedures, and evaluation metrics to provide a flexible way to lead and validate private text rewriting research. To demonstrate our software in practice, we provide a set of experiments as a case study on the ADePT DP text rewriting system, detecting a privacy leak in its pre-training approach. Our system is publicly available, and we hope that it will help the community to make DP text rewriting research more accessible and transparent.

How reparametrization trick broke differentially-private text representation learning - Habernal, Ivan (Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers))

Qualification of Different Carbon Fiber Reinforced Polyether Ether Ketone Materials for the FFF Process - Moritzer, Elmar; Wächter, Julian

Bewertung von IR-Schweißverbindungen an kurzfaserverstärkten Thermoplasten mittels digitaler Bildkorrelation - Gevers, Karina; Schraa, L; Uhlig, K; Töws, P; Stommel, M

Schweißnahtkennwerte für die lebensdaueroptimierte Bauteilauslegung von hochtemperaturbeständigen Thermoplasten - Schöppner, Volker; Vogtschmidt, Sascha

On the Wave to Successful Mixing - Schöppner, Volker; Dörner, M.; Frank, Maximilian; Schall, Christoph

An Open-Source FEM Magnetic Toolbox for Calculating Electric and Thermal Behavior of Power Electronic Magnetic Components - Förster, Nikolas; Hölscher, Jonas; Piepenbrock, Till; Rehlaender, Philipp; Wallscheid, Oliver; Schafmeister, Frank; Böcker, Joachim (2022 24th European Conference on Power Electronics and Applications (EPE’22 ECCE Europe))

Lamb wave based approach to the determination of acoustic material parameters - Johannesmann, Sarah; Claes, Leander; Feldmann, Nadine; Zeipert, Henning; Henning, Bernd (tm - Technisches Messen)
Abstract In this paper a measurement procedure to identify viscoelastic material parameters of plate-like samples using broadband ultrasonic waves is presented. Ultrasonic Lamb waves are excited via the thermoelastic effect using laser radiation and detected by a piezoelectric transducer. The resulting measurement data is transformed to yield information about multiple propagating Lamb waves as well as their attenuation. These results are compared to simulation results in an inverse procedure to identify the parameters of an elastic and a viscoelastic material model.
Keywords: Electrical and Electronic Engineering; Instrumentation

Estimation of viscoelastic material parameters of polymers using Lamb waves - Johannesmann, Sarah; Claes, Leander; Henning, Bernd (Fortschritte der Akustik - DAGA 2022)

Inverses Verfahren zur Bestimmung viskoelastischer Materialparameter - Johannesmann, Sarah

Towards an Edwardian Renaissance? The Super-Rich and the Shifting Social Geography of the British Countryside Today - Behler, Felix (Journal for the Study of British Cultures (JSBC))

Lydia Böttger (Universität Paderborn) rezensiert: Michalak, Magdalena; Döll, Marion (Hrsg.) (2021): Lehrwerke und Lehrmaterialien im Kontext des Deutschen als Zweitsprache und der sprachlichen Bildung. [Deutsch als Zweitsprache Positionen, Perspektiven, Potenziale, Bd. 2]. Münster, New York: Waxmann, 164 Seiten. ISBN 978-3-8309-4105-7. - Böttger, Lydia (www.daz-portal.de)

Performing Utopia? The Contestation of Dystopian Space in Cecelia Ahern's Flawed-Series - Schneider, Julia Christina (Twenty-First Century Anxieties: Dys/Utopian Spaces and Contexts in Contemporary British Theatre)

Investigation into Target Speaking Rate Adaptation for Voice Conversion - Kuhlmann, Michael; Seebauer, Fritz; Ebbers, Janek; Wagner, Petra; Haeb-Umbach, Reinhold (Interspeech 2022)

Schorsch Kamerun: „Extra Vages machen wir aus tiefer Überzeugung“. - Jacke, Christoph (Kaput. Magazin für Insolvenz & Pop.)

Forward & Rewind: Retromania in Music Documentary. - Jacke, Christoph; Reynolds, Simon (Jugend, Musik und Film.)

Ein kommentierter Tagungsbericht zur 4. Werkstatt Unterrichtsfach Pädagogik Ostwestfalen-Lippe (WUPO) - Engemann, Mario (Zeitschrift PädagogikUNTERRICHT)

The Greatest Advantage of Polytheism: Monotheism and Normalization through Truth - Corall, Niklas (Nietzsche's Gods)

What kind of leader am I? An exploration of professionals' leader identity construal - Rehbock, Stephanie K.; Hubner-Benz, Sylvia; Knipfer, Kristin; Peus, Claudia V. (Applied Psychology)
Although the leadership literature has emphasized the importance of leader identity for leader behaviors and leader effectiveness, little is known about whether and how professionals, who are experts in their field and hold a formal leader role, construe a leader identity. To expand our understanding of leader identity construal, we explored how professors in German research universities interpreted their formal leader role and whether and how they saw themselves as leaders. Based on findings from an inductive interview study, we contribute to the literature in three ways: First, our findings imply that patterns of professional identity and leader identity dimensions likely predict when a leader role is rejected , accommodated , incorporated , or emphasized . Second, we explain why professionals with a formal leader role see themselves primarily as specialists , mentors , managers , or shapers . Third, we extend previous notions of the leader identity concept by elaborating on its dimensions. Our findings have practical implications on an individual and organizational level, and may help design more effective leadership development programs.
Keywords: Applied Psychology; Arts and Humanities (miscellaneous); Developmental and Educational Psychology

Wait-and-see-ism as partial adoption of management practices: The rise and stall of integrated reporting - Endenich, Christoph; Hahn, Rüdiger; Reimsbach, Daniel; Wickert, Christopher (Strategic Organization)
Integrated reporting has widely been promoted as the next evolutionary step in corporate disclosure, which would soon replace traditional reporting practices. Embedded in a zeitgeist that favors sustainability, this outlook would suggest high integrated reporting adoption rates among reporting organizations. Our analysis of integrated reporting in Germany from 2008 to 2019 shows, however, that organizations approached integrated reporting with a wait-and-see mentality. This approach cannot be described adequately by the existing conceptualizations of (partial) practice adoption. We therefore develop the notion of wait-and-see-ism, defined as the deliberate and potentially long-lasting postponement of a decision to adopt a practice while its further development is monitored silently. We see limited, though continuous, efforts to prepare for the prospect of adopting the practice of integrated reporting quickly at a later stage. Wait-and-see-ism expands on prior work on partial adoption by emphasizing its temporal dimension. This adds an important yet undertheorized option that organizations can employ to respond to ambiguous institutional demands, thus explaining the stalling of promising management practices.
Keywords: Strategy and Management; Industrial relations; Education; Business and International Management