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@PHDTHESIS{Neumann:1004360,
author = {Neumann, Alexander Tobias},
othercontributors = {Decker, Stefan Josef and Spaniol, Marc},
title = {{C}hatbots as professional companions in large-scale
community information systems: integrating chatbots in
educational ecosystems},
school = {RWTH Aachen University},
type = {Dissertation},
address = {Aachen},
publisher = {RWTH Aachen University},
reportid = {RWTH-2025-01385},
pages = {1 Online-Ressource : Illustrationen},
year = {2024},
note = {Veröffentlicht auf dem Publikationsserver der RWTH Aachen
University 2025; Dissertation, RWTH Aachen University, 2024},
abstract = {Online communities are fundamental for knowledge sharing,
collaboration, and professional development in our digital
age. However, challenges like information overload and low
engagement hinder their effectiveness. New members often
struggle to find accurate information from multiple sources.
Chatbots with natural language understanding and automation
capabilities can solve these challenges. By providing
personalized guidance, improving efficiency, and integrating
with external knowledge bases, chatbots enhance the user
experience in online communities. Unfortunately, community
members often lack the necessary resources or expertise to
create bots that optimize their practices. This dissertation
follows a design science approach that empowers communities
to create and maintain customized chatbots collaboratively.
We introduce a model-driven Social Bot Framework that allows
community members to participate in bot creation and
evaluation. This framework incorporates process mining
techniques and leverages Large Language Models (LLMs) to
enhance bot performance. The dissertation also presents a
catalog of success factors for bots, providing a
multi-dimensional model for assessing chatbot effectiveness
within communities of practice. Through a co-design process
involving real-world use cases, we have produced,
demonstrated, and evaluated chatbots as artifacts,
showcasing their impact and usefulness. Our research
explores the application of chatbots in Technology Enhanced
Learning (TEL). We developed a series of mentoring bots that
address various aspects of the educational process. These
include systems for collaborative knowledge building,
providing personalized feedback on writing tasks, and
facilitating quiz-based learning. We also investigated the
integration of gamification elements to enhance user
engagement and motivation in educational contexts.
Furthermore, we leveraged LLMs to provide more
sophisticated, personalized learning support. The
evaluations, conducted through user studies, surveys, and
performance metrics, demonstrate the effectiveness and user
acceptance of our developed chatbots. Our research promotes
the democratization of bot-building, enabling communities to
leverage chatbot potential. This represents a significant
advancement in the self-governance and development of online
communities in response to changing needs and opportunities.
Ultimately, this work pushes the boundaries of current
community practices, opening up new horizons where bots are
professional companions supporting the success of online
communities.},
cin = {124510 / 120000},
ddc = {004},
cid = {$I:(DE-82)124510_20160614$ / $I:(DE-82)120000_20140620$},
pnm = {BMBF 16DHB2213 - Verbundprojekt: Personalisierte
Kompetenzentwicklung und hybrides KI-Mentoring -
tech4compKI; Teilvorhaben: Verteilte Datenanalyse zur
Bestimmung von Personmerkmalen (16DHB2213)},
pid = {G:(BMBF)16DHB2213},
typ = {PUB:(DE-HGF)11},
doi = {10.18154/RWTH-2025-01385},
url = {https://publications.rwth-aachen.de/record/1004360},
}
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