Bijan Khosrawi-RadTechnische Universität Braunschweig · Institut für Wirtschaftsinformatik
Bijan Khosrawi-Rad
Master of Science
Design-oriented research on Game-based Learning, Pedagogical Conversational Agents, and Virtual Companionship
About
14
Publications
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18
Citations
Citations since 2017
Publications
Publications (14)
Conversational agents (CAs) are getting smarter thanks to advances in artificial intelligence, which opens the potential to use them in educational contexts to support (working) students. In addition, CAs are turning toward relationship-oriented virtual companions (e.g., Replika). Synthesizing these trends, we derive the virtual learning companion...
Zusammenfassung
Startups verfolgen in ihrer Anfangsphase das Ziel, schnell zu wachsen, um sich einen großen Kundenstamm aufzubauen und sich langfristig am Markt behaupten zu können. Während die Digitalisierung einen schnellen Markteinstieg ermöglicht, ist es in der New Economy für junge Unternehmen mit begrenzten Ressourcen jedoch schwierig, von po...
Dieser Beitrag hat zum Ziel, eine problemzentrierte Taxonomie für das selbstregulierte Lernen zu entwickeln. Das Vorgehen nach Nickerson zur Taxonomie-Entwicklung und wissenschaftliche Literatur aus der Lernpsychologie und Pädagogik fungieren zusammen mit der Kerntheorie des selbstgesteuerten Lernens als Wissensbasis. Das resultierende Artefakt, un...
Personalisiertes Lernen ermöglicht es Lernenden, nach ihren eigenen Lernpräferenzen und-stilen zu lernen. Conversational Agents (CAs) bieten eine vielversprechende Möglichkeit zur Unterstützung der Lernenden. CAs können Lernstile im Dialog mit den Nutzer:innen erkennen sowie passende Lern-Empfehlungen bereitstellen. Eine Herausforderung besteht jed...
Many people globally experience the feeling of loneliness and struggle with its consequences. A modern way to deal with this loneliness and lack of companionship is to use empathetic and emotional conversational agents. Often referred to as virtual companions, these agents can engage in human-like conversations with their users and build relationsh...
Pedagogical Conversational Agents (PCAs) offer the potential to increase educational equity worldwide by making learning accessible to all as a service for good, often enabled by artificial intelligence (AI). Yet, there are ethical challenges to the design and use of PCAs that hinder the achievement of individual and social goals. However, in addit...
Due to significant technological progress in the field of artificial intelligence, conversational agents have the potential to become smarter, deepen the interaction with their users, and overcome a function of merely assisting. Since humans often treat computers as social actors, theories on interpersonal relationships can be applied to human-mach...
International students often have difficulties in getting connected with other students (from their host country), or in fully understanding the lectures due to barriers such as interacting in a foreign language or adjusting to a new campus. eLearning Companions (eLCs) act as virtual friends, accompany students with dialog-based support for learnin...
Learners are faced with the challenge of processing a large amount of knowledge. However, they often lack individual support, and teaching is not tailored to their learning styles. Conversational Agents (CAs) could be a way to identify personal learning styles through a dialog between the CA and the learner, and to support him/her accordingly. This...
Conversational Agents (CAs) are widely spread in a variety of domains, such as health and customer service. There is a recent trend of increasing publications and implementations of CAs in education. We conduct a systematic literature review to identify common methodologies, pedagogical CA roles, addressed target groups, the technologies and theori...
Zusammenfassung
Begünstigt durch die wachsende Relevanz digitaler Unterstützungsangebote für das Lehren und Lernen, bspw. in Schulen und Universitäten, gewinnt der Forschungszweig der Conversational Agents im Bildungskontext an Bedeutung. Sogenannte Lern-Companions, also virtuelle Lern-Gefährten, bieten das Potenzial einer nutzeradaptiven sowie ört...
Questions
Question (1)
Hello everyone,
I've got a question regarding within-subject experiments, in which two or more variants of a prototype (e.g., chatbot) are evaluated with respect to different constructs, I.e. classic A/B testing experiments of different design options. For both versions, the same items are used for comparability.
Before the final data analysis, I plan to perform tests for validity, reliability and factor analysis. Does anyone know if I need to calculate the corresponding criteria (e.g., Cronbach's alpha, factor loadings, KMO values) for both versions separately, or only once aggregated for the respective constructs? And how would I proceed with the exclusion of items? Especially when there are a lot of control conditions, it might be difficult to decide whether to exclude an item if it is below a certain criterion.
In reviewing the literature of papers with a similar experiment design, I couldn't identify a consistent approach so far.
Thank you very much for your help! If anyone has any recommendations for tools or tutorials, I would also appreciate it as well.
Projects
Projects (5)
Mit dem Innovationswettbewerb INVITE (Digitale Plattform berufliche Weiterbildung) soll ein Beitrag zur Optimierung eines innovativen digitalen und sicheren Bildungsraums der berufsbezogenen Weiterbildung geleistet werden (https://www.bibb.de/de/120851.php).
Arbeiten Sie in einem der 35 geförderten Einzelprojekte? Dann treten Sie diesem Projekt gerne bei.
Bitte fügen Sie im INVITE-Kontext entstandene Publikationen dem Projekt hinzu.
In an increasingly digitalized and flexible world, lifelong learning tailored to one's own needs is becoming more and more important for professional success. The funded project StudyBuddy is a collaborative project with the main goal of designing a virtual learning companion to support learners. The aim is to identify and eliminate gaps in knowledge and understanding at an early stage and to tailor knowledge transfer to the individual learner. In the long term, this should increase learning success and reduce the dropout rate in professional development programs.
For more information, go to: https://study-buddy-research.de/
Derivation of design guidelines for digital game-based learning applications
