TY - JOUR
AB - ZusammenfassungIn diesem Beitrag der Zeitschrift Gruppe. Interaktion. Organisation. (GIO) wird das Instrument zur Diagnose pädagogischer Kompetenzen von Pflegelehrpersonen (PädKomPflege) vorgestellt.Die Berufsbildung in der Pflege ist durch sich verändernde inhaltliche und gesetzliche Anforderungen geprägt. Verschiedene landesspezifische rechtliche Vorgaben führen zu einem sehr heterogenen Bild von Qualifikationen und Kompetenzen der Pflegelehrpersonen. Die Anrechnung bereits erworbener Kompetenzen auf pflegepädagogische Studiengänge sowie die Kompetenzerfassung und -bilanzierung in Berufsbildungseinrichtungen spielt daher eine wichtige Rolle. Vor diesem Hintergrund wurde das Instrument PädKomPflege entwickelt und erprobt. Grundlage des Kompetenzmodells sind die Empfehlungen der Kultusministerkonferenz (2004) zu den Standards für die (allgemeine) Lehrerbildung sowie Expertenworkshops und -interviews mit PflegedidaktikerInnen. Die empirische Erprobung erfolgte an einer Stichprobe von 1096 Pflegelehrpersonen. Psychometrische Analysen auf Grundlage der klassischen Testtheorie sowie IRT-basierte Analysen führten zu einer Überarbeitung des Instruments, welches nun als zweisprachiges Online-Self-Assessmenttool (eng./deut.) vorliegt. Die Validierung der deutschsprachigen Version fand anhand von 545 TeilnehmerInnen im Jahr 2016 statt, sodass ein geprüftes Instrument mit 54 Items in den fünf Hauptskalen (Unterricht, Beurteilung, Beratung, Lernortkooperation sowie Organisations- und Schulentwicklung) und 18 Subskalen zur Verfügung steht.Sowohl klassische als auch probabilistische Testgütekriterien werden erfüllt. Die Skalen weisen hohe interne Konsistenzen auf (α > 0,80) und sind überwiegend konstruktvalide. So lassen sich für 17 der 18 Subskalen ordinale Raschmodelle anpassen. Auf der Ebene der Hauptskalen können Partial Credit Modelle für alle Items von modellkonformen Subskalen einer Hauptskala angepasst werden. Das Instrument kann zur individuellen Kompetenzdiagnostik, zur Identifikation von Bildungsbedarfen in Schulen des Gesundheitswesens und im Kontext beruflicher Bildungsprozesse genutzt werden. In der Onlineversion erhalten Teilnehmende abschließend ein individuelles Kompetenzprofil mit möglichen Vergleichswerten. Das Tool kann begleitend zu Qualifizierungsprozessen als Monitoring-Instrument oder zur individuellen Kompetenzbilanzierung eingesetzt werden.
AU - Schürmann, Mirko
AU - Bender, Elena
AU - Grebe, Christian
ID - 37231
JF - Gruppe. Interaktion. Organisation. Zeitschrift für Angewandte Organisationspsychologie (GIO)
KW - Organizational Behavior and Human Resource Management
KW - Applied Psychology
KW - Developmental and Educational Psychology
KW - Education
KW - Social Psychology
SN - 2366-6145
TI - Kompetenzdiagnose in der Berufsbildung von Pflegelehrpersonen
ER -
TY - JOUR
AB - AbstractOrganizations increasingly introduce collaborative technologies in form of virtual assistants (VAs) to save valuable resources, especially when employees are assisted with work-related tasks. However, the effect of VAs on virtual teams and collaboration remains uncertain, particularly whether employees show social loafing (SL) tendencies, i.e., applying less effort for collective tasks compared to working alone. While extant research indicates that VAs collaboratively working in teams exert greater results, less is known about SL in virtual collaboration and how responsibility attribution alters. An online experiment with N = 102 was conducted in which participants were assisted by a VA in solving a task. The results indicate SL tendencies in virtual collaboration with VAs and that participants tend to cede responsibility to the VA. This study makes a first foray and extends the information systems (IS) literature by analyzing SL and responsibility attribution thus updates our knowledge on virtual collaboration with VAs.
AU - Stieglitz, Stefan
AU - Mirbabaie, Milad
AU - Möllmann, Nicholas R. J.
AU - Rzyski, Jannik
ID - 37146
IS - 3
JF - Information Systems Frontiers
KW - Computer Networks and Communications
KW - Information Systems
KW - Theoretical Computer Science
KW - Software
SN - 1387-3326
TI - Collaborating with Virtual Assistants in Organizations: Analyzing Social Loafing Tendencies and Responsibility Attribution
VL - 24
ER -
TY - JOUR
AB - AbstractArtificial intelligence (AI) is being increasingly integrated into enterprises to foster collaboration within humanmachine teams and assist employees with work-related tasks. However, introducing AI may negatively impact employees’ identifications with their jobs as AI is expected to fundamentally change workplaces and professions, feeding into individuals’ fears of being replaced. To broaden the understanding of the AI identity threat, the findings of this study reveal three central predictors for AI identity threat in the workplace: changes to work, loss of status position, and AI identity predicting AI identity threat in the workplace. This study enriches information systems literature by extending our understanding of collaboration with AI in the workplace to drive future research in this field. Researchers and practitioners understand the implications of employees’ identity when collaborating with AI and comprehend which factors are relevant when introducing AI in the workplace.
AU - Mirbabaie, Milad
AU - Brünker, Felix
AU - Möllmann Frick, Nicholas R. J.
AU - Stieglitz, Stefan
ID - 37144
IS - 1
JF - Electronic Markets
KW - Management of Technology and Innovation
KW - Marketing
KW - Computer Science Applications
KW - Economics and Econometrics
KW - Business and International Management
SN - 1019-6781
TI - The rise of artificial intelligence – understanding the AI identity threat at the workplace
VL - 32
ER -
TY - JOUR
AB - The application of artificial intelligence (AI) not only yields in advantages for healthcare but raises several ethical questions. Extant research on ethical considerations of AI in digital health is quite sparse and a holistic overview is lacking. A systematic literature review searching across 853 peer-reviewed journals and conferences yielded in 50 relevant articles categorized in five major ethical principles: beneficence, non-maleficence, autonomy, justice, and explicability. The ethical landscape of AI in digital health is portrayed including a snapshot guiding future development. The status quo highlights potential areas with little empirical but required research. Less explored areas with remaining ethical questions are validated and guide scholars’ efforts by outlining an overview of addressed ethical principles and intensity of studies including correlations. Practitioners understand novel questions AI raises eventually leading to properly regulated implementations and further comprehend that society is on its way from supporting technologies to autonomous decision-making systems.
AU - Möllmann, Nicholas RJ
AU - Mirbabaie, Milad
AU - Stieglitz, Stefan
ID - 37154
IS - 4
JF - Health Informatics Journal
KW - Health Informatics
SN - 1460-4582
TI - Is it alright to use artificial intelligence in digital health? A systematic literature review on ethical considerations
VL - 27
ER -
TY - JOUR
AB - Artificial intelligence (AI) has moved beyond the planning phase in many organisations and it is often accompanied by uncertainties and fears of job loss among employees. It is crucial to manage employees{\textquoteright} attitudes towards the deployment of an AI-based technology effectively and counteract possible resistance behaviour. We present lessons learned from an industry case where we conducted interviews with affected employees. We evaluated our results with managers across industries and found that that the deployment of AI-based technologies does not differ from other IT, but that the change is perceived differently due to misguided expectations.
AU - Stieglitz, Stefan
AU - Möllmann (Frick), Nicholas R. J.
AU - Mirbabaie, Milad
AU - Hofeditz, Lennart
AU - Ross, Björn
ID - 37155
JF - International Journal of Management Practice
KW - Artificial Intelligence
KW - Change Management
KW - Resistance
KW - AI-Driven Change
KW - AI Deployment
KW - AI Perception
SN - 1477-9064
TI - Recommendations for Managing AI-Driven Change Processes: When Expectations Meet Reality
ER -
TY - DATA
AU - Grebe, Christian
AU - Schürmann, Mirko
AU - Latteck, Änne-Dörte
ID - 37234
TI - Die Health Professionals Competence Scales (HePCoS) zur Kompetenzerfassung in den Gesundheitsfachberufen. Technical Report
ER -
TY - CONF
AB - Social media have become a valuable source for extracting data about societal crises and an important outlet to disseminate official information. Government agencies are increasingly turning to social media to use it as a mouthpiece in times of crisis. Gaining intelligence through social media analytics, however, remains a challenge for government agencies, e.g. due to a lack of training and instruments. To mitigate this shortcoming, government agencies need tools that support them in analysing social media data for the public good. This paper presents a design science research approach that guides the development of a social media analytics dashboard for a regional government agency. Preliminary results from a workshop and the resulting design of a first prototype are reported. A user-friendly and responsive design that is secure, flexible, and quick in use could identified as requirements, as well as information display of regional discussion statistics, sentiment, and emerging topics.
AU - Basyurt, Ali Sercan
AU - Marx, Julian
AU - Stieglitz, Stefan
AU - Mirbabaie, Milad
ID - 37174
T2 - ACIS 2021 Proceedings
TI - Designing a Social Media Analytics Dashboard for Government Agency Crisis Communications
ER -
TY - CONF
AB - So-called 'fast fashion' consumption, amplified through cost-effective e-commerce, constitutes a major factor negatively impacting climate change. A recently noted strategy to motivate consumers to more sustainable decisions is digital nudging. This paper explores the capability of digital nudging in the context of green fashion e-commerce. To do so, digital default and social norm nudges are tested in an experimental setting of green fashion purchases. An online experiment (n=320) was conducted, simulating an online retail scenario. Results failed to show statistically significant relationships between nudging strategies and purchase decisions. However, explorative analyses show a backfiring effect for the combination of nudges and thus, reveal a hitherto neglected impact of participants' identification on the effectiveness of the digital nudging strategies. Consequently, this study contributes to digital nudging literature and informs practice with new insights on effective choice architectures in e-commerce.
AU - Mirbabaie, Milad
AU - Marx, Julian
AU - Germies, Johanna
ID - 37175
T2 - ACIS 2021 Proceedings
TI - Conscious Commerce - Digital Nudging and Sustainable E-commerce Purchase Decisions
ER -
TY - CONF
AU - Marx, Julian
AU - Stieglitz, Stefan
AU - Mirbabaie, Milad
AU - Sauer, Tabea
AU - Frowerk, Janice
ID - 37142
T2 - ICIS Proceedings
TI - The Identity of Born Virtual Organizations: Exploring the Role of ICT
ER -
TY - JOUR
AB - Verification of software and processor hardware usually proceeds separately, software analysis relying on the correctness of processors executing machine instructions. This assumption is valid as long as the software runs on standard CPUs that have been extensively validated and are in wide use. However, for processors exploiting custom instruction set extensions to meet performance and energy constraints the validation might be less extensive, challenging the correctness assumption. In this paper we present a novel formal approach for hardware/software co-verification targeting processors with custom instruction set extensions. We detail two different approaches for checking whether the hardware fulfills the requirements expected by the software analysis. The approaches are designed to explore a trade-off between generality of the verification and computational effort. Then, we describe the integration of software and hardware analyses for both techniques and describe a fully automated tool chain implementing the approaches. Finally, we demonstrate and compare the two approaches on example source code with custom instructions, using state-of-the-art software analysis and hardware verification techniques.
AU - Jakobs, Marie-Christine
AU - Pauck, Felix
AU - Platzner, Marco
AU - Wehrheim, Heike
AU - Wiersema, Tobias
ID - 27841
JF - IEEE Access
KW - Software Analysis
KW - Abstract Interpretation
KW - Custom Instruction
KW - Hardware Verification
TI - Software/Hardware Co-Verification for Custom Instruction Set Processors
ER -