---
_id: '13337'
abstract:
- lang: eng
text: In manufacturing systems with a job shop organization, queues between workstations
create an intermittent process flow, allowing workers to schedule tasks entering
the queue based on their needs and preferences. The resulting scheduling autonomy
of individual workers often leads to inefficiencies in the overall production
process due to the loss of control. Companies are therefore increasingly using
algorithmic scheduling systems to assign task sequences to workers, thereby drastically
reducing their autonomy and negatively affecting their job performance and well-being.
This paper extends the existing flexible job shop scheduling problem by sequencing
preferences (FJSPSP) to incorporate a human-centered perspective by predicting
workers’ task sequencing decisions using learning-to-rank (LTR) methods. By learning
workers’ individual task sequencing preferences, it becomes possible to predict
the processing sequence based on task characteristics. The scheduling algorithm
for the FJSPSP presented in the paper incorporates workers’ learned sequencing
preferences as constraints. Considering workers’ learned task sequencing decisions,
the FJSPSP optimizes only task assignments to maintain workers’ autonomy over
task sequences. The contributions of this paper are fourfold, namely, (1) presenting
an approach to elicit sequencing decision datasets from workers, (2) demonstrating
the successful prediction of humans’ and an actual worker’s task sequencing decisions
with LTR, (3) formulating the FJSPSP variant that integrates workers’ sequencing
preferences as constraints and proving its effectiveness in a simulation study,
and (4) consolidating these steps into an explainable artificial intelligence
(XAI)- and LTR-enabled sociotechnical system design framework. The paper closes
with a discussion of the overall methodology and future research perspectives.
article_type: original
author:
- first_name: Jan-Phillip
full_name: Herrmann, Jan-Phillip
id: '86180'
last_name: Herrmann
- first_name: Sven
full_name: Tackenberg, Sven
id: '71470'
last_name: Tackenberg
- first_name: Tharsika Pakeerathan
full_name: Srirajan, Tharsika Pakeerathan
last_name: Srirajan
- first_name: Verena
full_name: Nitsch, Verena
last_name: Nitsch
citation:
ama: 'Herrmann JP, Tackenberg S, Srirajan TP, Nitsch V. Incorporating scheduling
autonomy of workers into flexible job shop scheduling: Learning and balancing
decentralized task sequencing decisions with overall scheduling performance. Journal
of Manufacturing Systems. 2026;84(2):541-560. doi:10.1016/j.jmsy.2025.12.020'
apa: 'Herrmann, J.-P., Tackenberg, S., Srirajan, T. P., & Nitsch, V. (2026).
Incorporating scheduling autonomy of workers into flexible job shop scheduling:
Learning and balancing decentralized task sequencing decisions with overall scheduling
performance. Journal of Manufacturing Systems, 84(2), 541–560. https://doi.org/10.1016/j.jmsy.2025.12.020'
bjps: 'Herrmann J-P et al. (2026) Incorporating Scheduling Autonomy
of Workers into Flexible Job Shop Scheduling: Learning and Balancing Decentralized
Task Sequencing Decisions with Overall Scheduling Performance. Journal of Manufacturing
Systems 84, 541–560.'
chicago: 'Herrmann, Jan-Phillip, Sven Tackenberg, Tharsika Pakeerathan Srirajan,
and Verena Nitsch. “Incorporating Scheduling Autonomy of Workers into Flexible
Job Shop Scheduling: Learning and Balancing Decentralized Task Sequencing Decisions
with Overall Scheduling Performance.” Journal of Manufacturing Systems
84, no. 2 (2026): 541–60. https://doi.org/10.1016/j.jmsy.2025.12.020.'
chicago-de: 'Herrmann, Jan-Phillip, Sven Tackenberg, Tharsika Pakeerathan Srirajan
und Verena Nitsch. 2026. Incorporating scheduling autonomy of workers into flexible
job shop scheduling: Learning and balancing decentralized task sequencing decisions
with overall scheduling performance. Journal of Manufacturing Systems 84,
Nr. 2: 541–560. doi:10.1016/j.jmsy.2025.12.020,
.'
din1505-2-1: 'Herrmann, Jan-Phillip
; Tackenberg, Sven ; Srirajan,
Tharsika Pakeerathan ; Nitsch, Verena:
Incorporating scheduling autonomy of workers into flexible job shop scheduling:
Learning and balancing decentralized task sequencing decisions with overall scheduling
performance. In: Journal of Manufacturing Systems Bd. 84. Amsterdam, Elsevier
BV (2026), Nr. 2, S. 541–560'
havard: 'J.-P. Herrmann, S. Tackenberg, T.P. Srirajan, V. Nitsch, Incorporating
scheduling autonomy of workers into flexible job shop scheduling: Learning and
balancing decentralized task sequencing decisions with overall scheduling performance,
Journal of Manufacturing Systems. 84 (2026) 541–560.'
ieee: 'J.-P. Herrmann, S. Tackenberg, T. P. Srirajan, and V. Nitsch, “Incorporating
scheduling autonomy of workers into flexible job shop scheduling: Learning and
balancing decentralized task sequencing decisions with overall scheduling performance,”
Journal of Manufacturing Systems, vol. 84, no. 2, pp. 541–560, 2026, doi:
10.1016/j.jmsy.2025.12.020.'
mla: 'Herrmann, Jan-Phillip, et al. “Incorporating Scheduling Autonomy of Workers
into Flexible Job Shop Scheduling: Learning and Balancing Decentralized Task Sequencing
Decisions with Overall Scheduling Performance.” Journal of Manufacturing Systems,
vol. 84, no. 2, 2026, pp. 541–60, https://doi.org/10.1016/j.jmsy.2025.12.020.'
short: J.-P. Herrmann, S. Tackenberg, T.P. Srirajan, V. Nitsch, Journal of Manufacturing
Systems 84 (2026) 541–560.
ufg: 'Herrmann, Jan-Phillip u. a.: Incorporating scheduling autonomy of workers
into flexible job shop scheduling: Learning and balancing decentralized task sequencing
decisions with overall scheduling performance, in: Journal of Manufacturing
Systems 84 (2026), H. 2, S. 541–560.'
van: 'Herrmann JP, Tackenberg S, Srirajan TP, Nitsch V. Incorporating scheduling
autonomy of workers into flexible job shop scheduling: Learning and balancing
decentralized task sequencing decisions with overall scheduling performance. Journal
of Manufacturing Systems. 2026;84(2):541–60.'
date_created: 2026-01-12T08:29:09Z
date_updated: 2026-01-12T08:54:27Z
department:
- _id: DEP7027
doi: 10.1016/j.jmsy.2025.12.020
intvolume: ' 84'
issue: '2'
keyword:
- Human-centered scheduling
- Job autonomy
- Learning-to-rank
- Flexible job shop scheduling
- Human decision-making
- Explainable artificial intelligence
language:
- iso: eng
page: 541-560
place: Amsterdam
publication: Journal of Manufacturing Systems
publication_identifier:
issn:
- 0278-6125
publication_status: published
publisher: Elsevier BV
quality_controlled: '1'
status: public
title: 'Incorporating scheduling autonomy of workers into flexible job shop scheduling:
Learning and balancing decentralized task sequencing decisions with overall scheduling
performance'
type: scientific_journal_article
user_id: '83781'
volume: 84
year: '2026'
...
---
_id: '12009'
abstract:
- lang: eng
text: 'AbstractTraditional work models often need
more flexibility and time autonomy for employees, especially in manufacturing.
Quantitative approaches and Artificial Intelligence (AI) applications offer the
potential to improve work design. However, current research does not entirely
focus on human-centric criteria that enable time autonomy. This paper addresses
this gap by developing a set of criteria to evaluate intelligent personnel planning
approaches based on their ability to enhance time autonomy for employees. Existing
quantitative approaches are not sufficient to fully integrate the developed criteria.Consequently,
a novel model approach is proposed in an attempt to bridge the gap between current
practices and the newly developed criteria. This two-stage planning approach fosters
democratization of time autonomy on the shopfloor, moving beyond traditional top-down
scheduling. The paper concludes by outlining the implementation process and discusses
future developments with respect to AI for this model approach.Practical
Relevance: In order to make working conditions on the shopfloor
in high-wage countries more attractive, an alternative organization of shift work
is needed. Intelligent planning approaches that combine traditional operations
research methods with artificial intelligence approaches can democratize shift
organization regarding time autonomy. Planning that takes both employee and employer
preferences into account in a balanced way will strengthen the long-term competitiveness
of manufacturing companies in high-wage countries and counteract the shortage
of skilled labor.'
author:
- first_name: Benedikt
full_name: Latos, Benedikt
id: '84474'
last_name: Latos
- first_name: Armin
full_name: Buckhorst, Armin
last_name: Buckhorst
- first_name: Peyman
full_name: Kalantar, Peyman
id: '85984'
last_name: Kalantar
- first_name: Dominik
full_name: Bentler, Dominik
last_name: Bentler
- first_name: Stefan
full_name: Gabriel, Stefan
last_name: Gabriel
- first_name: Roman
full_name: Dumitrescu, Roman
last_name: Dumitrescu
- first_name: Michael
full_name: Minge, Michael
id: '78302'
last_name: Minge
orcid: 0000-0003-1930-7064
- first_name: Barbara
full_name: Steinmann, Barbara
id: '77747'
last_name: Steinmann
orcid: 0009-0000-3036-2684
- first_name: Nadine
full_name: Guhr, Nadine
id: '77748'
last_name: Guhr
orcid: 0000-0001-8812-1488
citation:
ama: 'Latos B, Buckhorst A, Kalantar P, et al. Time autonomy in personnel planning:
Requirements and solution approaches in the context of intelligent scheduling
from a holistic organizational perspective . Zeitschrift für Arbeitswissenschaft.
2024;78(3):277-298. doi:10.1007/s41449-024-00432-7'
apa: 'Latos, B., Buckhorst, A., Kalantar, P., Bentler, D., Gabriel, S., Dumitrescu,
R., Minge, M., Steinmann, B., & Guhr, N. (2024). Time autonomy in personnel
planning: Requirements and solution approaches in the context of intelligent scheduling
from a holistic organizational perspective . Zeitschrift Für Arbeitswissenschaft,
78(3), 277–298. https://doi.org/10.1007/s41449-024-00432-7'
bjps: 'Latos B et al. (2024) Time Autonomy in Personnel Planning:
Requirements and Solution Approaches in the Context of Intelligent Scheduling
from a Holistic Organizational Perspective . Zeitschrift für Arbeitswissenschaft
78, 277–298.'
chicago: 'Latos, Benedikt, Armin Buckhorst, Peyman Kalantar, Dominik Bentler, Stefan
Gabriel, Roman Dumitrescu, Michael Minge, Barbara Steinmann, and Nadine Guhr.
“Time Autonomy in Personnel Planning: Requirements and Solution Approaches in
the Context of Intelligent Scheduling from a Holistic Organizational Perspective
.” Zeitschrift Für Arbeitswissenschaft 78, no. 3 (2024): 277–98. https://doi.org/10.1007/s41449-024-00432-7.'
chicago-de: 'Latos, Benedikt, Armin Buckhorst, Peyman Kalantar, Dominik Bentler,
Stefan Gabriel, Roman Dumitrescu, Michael Minge, Barbara Steinmann und Nadine
Guhr. 2024. Time autonomy in personnel planning: Requirements and solution approaches
in the context of intelligent scheduling from a holistic organizational perspective
. Zeitschrift für Arbeitswissenschaft 78, Nr. 3: 277–298. doi:10.1007/s41449-024-00432-7,
.'
din1505-2-1: 'Latos,
Benedikt ; Buckhorst, Armin
; Kalantar, Peyman ; Bentler,
Dominik ; Gabriel, Stefan
; Dumitrescu, Roman ; Minge,
Michael ; Steinmann, Barbara
; u. a.: Time autonomy in personnel planning: Requirements and solution
approaches in the context of intelligent scheduling from a holistic organizational
perspective . In: Zeitschrift für Arbeitswissenschaft Bd. 78. Heidelberg,
Springer-Verlag GmbH (2024), Nr. 3, S. 277–298'
havard: 'B. Latos, A. Buckhorst, P. Kalantar, D. Bentler, S. Gabriel, R. Dumitrescu,
M. Minge, B. Steinmann, N. Guhr, Time autonomy in personnel planning: Requirements
and solution approaches in the context of intelligent scheduling from a holistic
organizational perspective , Zeitschrift Für Arbeitswissenschaft. 78 (2024) 277–298.'
ieee: 'B. Latos et al., “Time autonomy in personnel planning: Requirements
and solution approaches in the context of intelligent scheduling from a holistic
organizational perspective ,” Zeitschrift für Arbeitswissenschaft, vol.
78, no. 3, pp. 277–298, 2024, doi: 10.1007/s41449-024-00432-7.'
mla: 'Latos, Benedikt, et al. “Time Autonomy in Personnel Planning: Requirements
and Solution Approaches in the Context of Intelligent Scheduling from a Holistic
Organizational Perspective .” Zeitschrift Für Arbeitswissenschaft, vol.
78, no. 3, 2024, pp. 277–98, https://doi.org/10.1007/s41449-024-00432-7.'
short: B. Latos, A. Buckhorst, P. Kalantar, D. Bentler, S. Gabriel, R. Dumitrescu,
M. Minge, B. Steinmann, N. Guhr, Zeitschrift Für Arbeitswissenschaft 78 (2024)
277–298.
ufg: 'Latos, Benedikt u. a.: Time autonomy in personnel planning: Requirements
and solution approaches in the context of intelligent scheduling from a holistic
organizational perspective , in: Zeitschrift für Arbeitswissenschaft 78
(2024), H. 3, S. 277–298.'
van: 'Latos B, Buckhorst A, Kalantar P, Bentler D, Gabriel S, Dumitrescu R, et al.
Time autonomy in personnel planning: Requirements and solution approaches in the
context of intelligent scheduling from a holistic organizational perspective .
Zeitschrift für Arbeitswissenschaft. 2024;78(3):277–98.'
date_created: 2024-10-28T09:08:47Z
date_updated: 2024-10-28T15:09:13Z
department:
- _id: DEP1523
doi: 10.1007/s41449-024-00432-7
intvolume: ' 78'
issue: '3'
keyword:
- Personnel Planning
- Time Autonomy
- Human-Centric Optimization
- Artificial Intelligence
- Manufacturing
language:
- iso: eng
page: 277-298
place: Heidelberg
publication: Zeitschrift für Arbeitswissenschaft
publication_identifier:
eissn:
- 2366-4681
issn:
- 0340-2444
publication_status: published
publisher: Springer-Verlag GmbH
quality_controlled: '1'
status: public
title: 'Time autonomy in personnel planning: Requirements and solution approaches
in the context of intelligent scheduling from a holistic organizational perspective '
type: scientific_journal_article
user_id: '83781'
volume: 78
year: '2024'
...
---
_id: '13169'
abstract:
- lang: eng
text: "KI.BAU is a project being developed and conducted at the Detmold School of
Design, part of the University of Applied Sciences and Arts Ostwestfalen-Lippe.
It focuses on researching the application of artificial intelligence (AI) in architectural
design, modelling, production and management processes, particularly on the communication
between users, processes and the building itself in various development and life-time
phases. Hence the research aims to develop new tools and AI-supported process
chains for the design, production and communication of architecture. This includes
the training and implementing prototypical machine learning algorithms to autonomously
evolve and optimize field-specific processes and workflows.\r\nAs mentioned above,
a critical question KI.BAU explores is how we, as planners, builders and users,
will communicate with architecture in the future, in its phases of creation and
use but also beyond. This also involves, besides virtual interfaces, examining
the physical interaction with a building, its behaviour, responsiveness and adaptation
to certain conditions. \r\nThe primary goal of the research at KI.BAU is to transform
architecture into an intelligent, to some degree self-sustaining, self-reflective
and maybe even evolving ‘ecological system’. This system should be comprehensively
linked with its creators, users, devices, computers, its (biological) environment
and networks. Consequently, a building must be viewed as an organism that communicates,
interacts and adapts to other connected or related organisms and entities.\r\n"
author:
- first_name: Hans
full_name: Sachs, Hans
id: '64589'
last_name: Sachs
citation:
ama: 'Sachs H. KI.BAU Artificial Intelligence in Architecture. In: Kretzer M, AADR
– Art Architecture Design Research, eds. Synthetic Realities: New Frontiers
in AI-Driven Design, Fabrication and Materiality. 1. AADR – Art Architecture
Design Research; 2024:14.'
apa: 'Sachs, H. (2024). KI.BAU Artificial Intelligence in Architecture. In M. Kretzer
& AADR – Art Architecture Design Research (Eds.), Synthetic realities:
New Frontiers in AI-driven Design, Fabrication and Materiality (1., p. 14).
AADR – Art Architecture Design Research.'
bjps: 'Sachs H (2024) KI.BAU Artificial Intelligence in Architecture. In
Kretzer M and AADR – Art Architecture Design Research (eds), Synthetic Realities:
New Frontiers in AI-Driven Design, Fabrication and Materiality, 1. Baunach:
AADR – Art Architecture Design Research, p. 14.'
chicago: 'Sachs, Hans. “KI.BAU Artificial Intelligence in Architecture.” In Synthetic
Realities: New Frontiers in AI-Driven Design, Fabrication and Materiality,
edited by Manuel Kretzer and AADR – Art Architecture Design Research, 1., 14.
Baunach: AADR – Art Architecture Design Research, 2024.'
chicago-de: 'Sachs, Hans. 2024. KI.BAU Artificial Intelligence in Architecture.
In: Synthetic realities: New Frontiers in AI-driven Design, Fabrication and
Materiality, hg. von Manuel Kretzer und AADR – Art Architecture Design Research,
14. 1. Baunach: AADR – Art Architecture Design Research.'
din1505-2-1: 'Sachs, Hans: KI.BAU
Artificial Intelligence in Architecture. In: Kretzer,
M. ; AADR – Art Architecture Design
Research (Hrsg.): Synthetic realities: New Frontiers in AI-driven Design,
Fabrication and Materiality. 1. Baunach : AADR – Art Architecture Design Research,
2024, S. 14'
havard: 'H. Sachs, KI.BAU Artificial Intelligence in Architecture, in: M. Kretzer,
AADR – Art Architecture Design Research (Eds.), Synthetic Realities: New Frontiers
in AI-Driven Design, Fabrication and Materiality, 1., AADR – Art Architecture
Design Research, Baunach, 2024: p. 14.'
ieee: 'H. Sachs, “KI.BAU Artificial Intelligence in Architecture,” in Synthetic
realities: New Frontiers in AI-driven Design, Fabrication and Materiality,
1., M. Kretzer and AADR – Art Architecture Design Research, Eds. Baunach: AADR
– Art Architecture Design Research, 2024, p. 14.'
mla: 'Sachs, Hans. “KI.BAU Artificial Intelligence in Architecture.” Synthetic
Realities: New Frontiers in AI-Driven Design, Fabrication and Materiality,
edited by Manuel Kretzer and AADR – Art Architecture Design Research, 1., AADR
– Art Architecture Design Research, 2024, p. 14.'
short: 'H. Sachs, in: M. Kretzer, AADR – Art Architecture Design Research (Eds.),
Synthetic Realities: New Frontiers in AI-Driven Design, Fabrication and Materiality,
1., AADR – Art Architecture Design Research, Baunach, 2024, p. 14.'
ufg: 'Sachs, Hans: KI.BAU Artificial Intelligence in Architecture, in: Kretzer,
Manuel, AADR – Art Architecture Design Research (Hgg.): Synthetic realities:
New Frontiers in AI-driven Design, Fabrication and Materiality, 1.,
Baunach 2024, S. 14.'
van: 'Sachs H. KI.BAU Artificial Intelligence in Architecture. In: Kretzer M, AADR
– Art Architecture Design Research, editors. Synthetic realities: New Frontiers
in AI-driven Design, Fabrication and Materiality. 1. Baunach: AADR – Art Architecture
Design Research; 2024. p. 14.'
corporate_editor:
- AADR – Art Architecture Design Research
date_created: 2025-09-11T10:50:08Z
date_updated: 2025-10-16T20:54:48Z
department:
- _id: DEP1624
- _id: DEP1055
edition: '1.'
editor:
- first_name: Manuel
full_name: Kretzer, Manuel
last_name: Kretzer
jel:
- A31
keyword:
- AI
- Artificial Intelligence
- Architecture
- Build Environment
- Building Construction
- Ecology of Architecture
language:
- iso: eng
page: '14'
place: Baunach
popular_science: '1'
publication: 'Synthetic realities: New Frontiers in AI-driven Design, Fabrication
and Materiality'
publication_identifier:
isbn:
- 978-3887781088
publication_status: published
publisher: AADR – Art Architecture Design Research
related_material:
link:
- relation: new_edition
url: https://aadr.info/product/synthetic-realities/
status: public
title: KI.BAU Artificial Intelligence in Architecture
type: book_chapter
user_id: '64589'
year: '2024'
...
---
_id: '11402'
abstract:
- lang: eng
text: In diesem Artikel geht es um die Bedeutung von Selbstbildung im Hochschulstudium
und wie Studierende ihre Fähigkeit zur Selbstbildung verbessern können. Der Artikel
diskutiert verschiedene Lehrmethoden und Initiativen, die dazu beitragen können,
die Selbstkompetenzförderung strukturell zu verankern. Es werden auch adaptive,
lernzielorientierte Kurse vorgestellt, die den Einsatz von Algorithmen der künstlichen
Intelligenz nutzen, um Studierenden hochgradig individualisierte Bildungswege
zu ermöglichen. Der Artikel schließt mit einer Diskussion darüber, wie die Hochschuldidaktik
dazu beitragen kann, die Selbstbildungskompetenz der Studierenden zu fördern.
(Autor); This article is about the importance of self-education in higher education
and how students can improve their ability to self-educate. The article discusses
various teaching methods and initiatives that can help to structurally embed self-education.
It also presents adaptive learning goal-oriented courses that leverage the use
of artificial intelligence algorithms to provide students with highly individualized
educational pathways. The article concludes with a discussion of how higher education
didactics can help promote students’ self-education skills.
author:
- first_name: Tobias
full_name: Schmohl, Tobias
id: '71782'
last_name: Schmohl
orcid: https://orcid.org/0000-0002-7043-5582
- first_name: Stefanie
full_name: Go, Stefanie
id: '81255'
last_name: Go
citation:
ama: 'Schmohl T, Go S. Selbstbildung als Proprium akademischer Didaktik? Ein kritischer
Zwischenruf. In: Haberer M, Günther D, Köhler J, eds. (Selbst-)Lernkompetenzen
Studierender stärken: Unterstützungsangebote – Beratung – Lernräume. Sammelband
zur Fachtagung “(Selbst-)Lernunterstützung an Hochschulen – wieso noch mal?” am
15. und 16.10.2020 an der Technischen Universität Kaiserslautern. Rheinland-Pfälzische
Technische Universität Kaiserslautern-Landau, Zentrum für Innovation und Digitalisierung
in Studium und Lehre (ZIDiS) ; 2023:35-45. doi:https://doi.org/10.25656/01:27948'
apa: 'Schmohl, T., & Go, S. (2023). Selbstbildung als Proprium akademischer
Didaktik? Ein kritischer Zwischenruf. In M. Haberer, D. Günther, & J. Köhler (Eds.),
(Selbst-)Lernkompetenzen Studierender stärken: Unterstützungsangebote – Beratung
– Lernräume. Sammelband zur Fachtagung “(Selbst-)Lernunterstützung an Hochschulen
– wieso noch mal?” am 15. und 16.10.2020 an der Technischen Universität Kaiserslautern
(pp. 35–45). Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau,
Zentrum für Innovation und Digitalisierung in Studium und Lehre (ZIDiS) . https://doi.org/10.25656/01:27948'
bjps: 'Schmohl T and Go S (2023) Selbstbildung als Proprium akademischer
Didaktik? Ein kritischer Zwischenruf. In Haberer M, Günther D and Köhler J (eds),
(Selbst-)Lernkompetenzen Studierender stärken: Unterstützungsangebote – Beratung
– Lernräume. Sammelband zur Fachtagung ‘(Selbst-)Lernunterstützung an Hochschulen
– wieso noch mal?’ am 15. und 16.10.2020 an der Technischen Universität Kaiserslautern.
Kaiserslautern-Landau: Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau,
Zentrum für Innovation und Digitalisierung in Studium und Lehre (ZIDiS) , pp.
35–45.'
chicago: 'Schmohl, Tobias, and Stefanie Go. “Selbstbildung als Proprium akademischer
Didaktik? Ein kritischer Zwischenruf.” In (Selbst-)Lernkompetenzen Studierender
stärken: Unterstützungsangebote – Beratung – Lernräume. Sammelband zur Fachtagung
“(Selbst-)Lernunterstützung an Hochschulen – wieso noch mal?” am 15. und 16.10.2020
an der Technischen Universität Kaiserslautern, edited by Monika Haberer,
Dorit Günther, and Janina Köhler , 35–45. Kaiserslautern-Landau: Rheinland-Pfälzische
Technische Universität Kaiserslautern-Landau, Zentrum für Innovation und Digitalisierung
in Studium und Lehre (ZIDiS) , 2023. https://doi.org/10.25656/01:27948.'
chicago-de: 'Schmohl, Tobias und Stefanie Go. 2023. Selbstbildung als Proprium akademischer
Didaktik? Ein kritischer Zwischenruf. In: (Selbst-)Lernkompetenzen Studierender
stärken: Unterstützungsangebote – Beratung – Lernräume. Sammelband zur Fachtagung
„(Selbst-)Lernunterstützung an Hochschulen – wieso noch mal?“ am 15. und 16.10.2020
an der Technischen Universität Kaiserslautern, hg. von Monika Haberer, Dorit Günther,
und Janina Köhler , 35–45. Kaiserslautern-Landau: Rheinland-Pfälzische Technische
Universität Kaiserslautern-Landau, Zentrum für Innovation und Digitalisierung
in Studium und Lehre (ZIDiS) . doi:https://doi.org/10.25656/01:27948,
.'
din1505-2-1: 'Schmohl, Tobias ; Go, Stefanie: Selbstbildung als Proprium
akademischer Didaktik? Ein kritischer Zwischenruf. In: Haberer,
M. ; Günther, D. ; Köhler , J. (Hrsg.): (Selbst-)Lernkompetenzen
Studierender stärken: Unterstützungsangebote – Beratung – Lernräume. Sammelband
zur Fachtagung „(Selbst-)Lernunterstützung an Hochschulen – wieso noch mal?“ am
15. und 16.10.2020 an der Technischen Universität Kaiserslautern. Kaiserslautern-Landau :
Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau, Zentrum für
Innovation und Digitalisierung in Studium und Lehre (ZIDiS) , 2023, S. 35–45'
havard: 'T. Schmohl, S. Go, Selbstbildung als Proprium akademischer Didaktik? Ein
kritischer Zwischenruf, in: M. Haberer, D. Günther, J. Köhler (Eds.), (Selbst-)Lernkompetenzen
Studierender stärken: Unterstützungsangebote – Beratung – Lernräume. Sammelband
zur Fachtagung “(Selbst-)Lernunterstützung an Hochschulen – wieso noch mal?” am
15. und 16.10.2020 an der Technischen Universität Kaiserslautern, Rheinland-Pfälzische
Technische Universität Kaiserslautern-Landau, Zentrum für Innovation und Digitalisierung
in Studium und Lehre (ZIDiS) , Kaiserslautern-Landau, 2023: pp. 35–45.'
ieee: 'T. Schmohl and S. Go, “Selbstbildung als Proprium akademischer Didaktik?
Ein kritischer Zwischenruf,” in (Selbst-)Lernkompetenzen Studierender stärken:
Unterstützungsangebote – Beratung – Lernräume. Sammelband zur Fachtagung “(Selbst-)Lernunterstützung
an Hochschulen – wieso noch mal?” am 15. und 16.10.2020 an der Technischen Universität
Kaiserslautern, M. Haberer, D. Günther, and J. Köhler , Eds. Kaiserslautern-Landau:
Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau, Zentrum für
Innovation und Digitalisierung in Studium und Lehre (ZIDiS) , 2023, pp. 35–45.
doi: https://doi.org/10.25656/01:27948.'
mla: 'Schmohl, Tobias, and Stefanie Go. “Selbstbildung als Proprium akademischer
Didaktik? Ein kritischer Zwischenruf.” (Selbst-)Lernkompetenzen Studierender
stärken: Unterstützungsangebote – Beratung – Lernräume. Sammelband zur Fachtagung
“(Selbst-)Lernunterstützung an Hochschulen – wieso noch mal?” am 15. und 16.10.2020
an der Technischen Universität Kaiserslautern, edited by Monika Haberer et
al., Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau, Zentrum
für Innovation und Digitalisierung in Studium und Lehre (ZIDiS) , 2023, pp. 35–45,
https://doi.org/10.25656/01:27948.'
short: 'T. Schmohl, S. Go, in: M. Haberer, D. Günther, J. Köhler (Eds.), (Selbst-)Lernkompetenzen
Studierender stärken: Unterstützungsangebote – Beratung – Lernräume. Sammelband
zur Fachtagung “(Selbst-)Lernunterstützung an Hochschulen – wieso noch mal?” am
15. und 16.10.2020 an der Technischen Universität Kaiserslautern, Rheinland-Pfälzische
Technische Universität Kaiserslautern-Landau, Zentrum für Innovation und Digitalisierung
in Studium und Lehre (ZIDiS) , Kaiserslautern-Landau, 2023, pp. 35–45.'
ufg: 'Schmohl, Tobias/Go, Stefanie: Selbstbildung als Proprium akademischer
Didaktik? Ein kritischer Zwischenruf, in: Haberer, Monika/Günther, Dorit/Köhler
, Janina (Hgg.): (Selbst-)Lernkompetenzen Studierender stärken: Unterstützungsangebote
– Beratung – Lernräume. Sammelband zur Fachtagung „(Selbst-)Lernunterstützung
an Hochschulen – wieso noch mal?“ am 15. und 16.10.2020 an der Technischen Universität
Kaiserslautern, Kaiserslautern-Landau 2023, S. 35–45.'
van: 'Schmohl T, Go S. Selbstbildung als Proprium akademischer Didaktik? Ein kritischer
Zwischenruf. In: Haberer M, Günther D, Köhler J, editors. (Selbst-)Lernkompetenzen
Studierender stärken: Unterstützungsangebote – Beratung – Lernräume Sammelband
zur Fachtagung “(Selbst-)Lernunterstützung an Hochschulen – wieso noch mal?” am
15 und 16102020 an der Technischen Universität Kaiserslautern. Kaiserslautern-Landau:
Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau, Zentrum für
Innovation und Digitalisierung in Studium und Lehre (ZIDiS) ; 2023. p. 35–45.'
date_created: 2024-04-30T18:11:12Z
date_updated: 2024-05-15T12:31:49Z
department:
- _id: DEP2000
doi: https://doi.org/10.25656/01:27948
editor:
- first_name: 'Monika '
full_name: 'Haberer, Monika '
last_name: Haberer
- first_name: 'Dorit '
full_name: 'Günther, Dorit '
last_name: Günther
- first_name: 'Janina '
full_name: 'Köhler , Janina '
last_name: 'Köhler '
keyword:
- Selbstbildung
- Studium
- Selbstkompetenz
- Lehrmethode
- Adaptiver Unterricht
- Künstliche Intelligenz
- Hochschuldidaktik
- Lerngegenstand
- Wissen
- Bildungsbiografie
- Hochschule
- Student
- Self-education
- Academic studies
- Teaching method
- Artificial intelligence
- University didactics
- Knowledge
- School career
- Higher education institute
- Male student
language:
- iso: ger
page: 35-45
place: Kaiserslautern-Landau
publication: '(Selbst-)Lernkompetenzen Studierender stärken: Unterstützungsangebote
– Beratung – Lernräume. Sammelband zur Fachtagung "(Selbst-)Lernunterstützung an
Hochschulen – wieso noch mal?" am 15. und 16.10.2020 an der Technischen Universität
Kaiserslautern'
publication_status: published
publisher: 'Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau, Zentrum
für Innovation und Digitalisierung in Studium und Lehre (ZIDiS) '
quality_controlled: '1'
status: public
title: Selbstbildung als Proprium akademischer Didaktik? Ein kritischer Zwischenruf
type: book_chapter
user_id: '83781'
year: '2023'
...
---
_id: '11445'
abstract:
- lang: eng
text: Predicting human decisions is a central challenge for planning and controlling
production with weakly structured processes. Thus, workers’ decisions regarding
the processing strategies and the temporal sequence of tasks to be processed are
to be determined prospectively. Accordingly, there is a need to review methods
for preference elicitation to develop individual predictive decision models. This
paper presents a systematic literature review and discussion of 42 publications
on predictive decision models and decision attributes. Methods for eliciting decision-making
knowledge from manufacturing workers as part of the modeling process and decision
model validation methods are reviewed and discussed in light of their predictive
validity for individual task selection. The article synthesizes the recent literature
for predicting human decision-making in manufacturing using artificial intelligence
methods. Along with the review results, a future research agenda is proposed for
modeling and simulating human decision-making in manufacturing. Knowledge about
human preferences and the successful prediction of workers’ decision-making in
manufacturing helps companies predict manufacturing objectives and derive organizational
and work design measures.
author:
- first_name: Jan-Phillip
full_name: Herrmann, Jan-Phillip
id: '75846'
last_name: Herrmann
- first_name: Sven
full_name: Tackenberg, Sven
id: '71470'
last_name: Tackenberg
- first_name: Verena
full_name: Nitsch, Verena
last_name: Nitsch
citation:
ama: 'Herrmann JP, Tackenberg S, Nitsch V. Predicting Human Decision-Making for
Task Selection in Manufacturing: A Systematic Literature Review. IEEE Access.
2023;11:141172-141191. doi:10.1109/access.2023.3340626'
apa: 'Herrmann, J.-P., Tackenberg, S., & Nitsch, V. (2023). Predicting Human
Decision-Making for Task Selection in Manufacturing: A Systematic Literature Review.
IEEE Access, 11, 141172–141191. https://doi.org/10.1109/access.2023.3340626'
bjps: 'Herrmann J-P, Tackenberg S and Nitsch V (2023) Predicting Human Decision-Making
for Task Selection in Manufacturing: A Systematic Literature Review. IEEE Access
11, 141172–141191.'
chicago: 'Herrmann, Jan-Phillip, Sven Tackenberg, and Verena Nitsch. “Predicting
Human Decision-Making for Task Selection in Manufacturing: A Systematic Literature
Review.” IEEE Access 11 (2023): 141172–91. https://doi.org/10.1109/access.2023.3340626.'
chicago-de: 'Herrmann, Jan-Phillip, Sven Tackenberg und Verena Nitsch. 2023. Predicting
Human Decision-Making for Task Selection in Manufacturing: A Systematic Literature
Review. IEEE Access 11: 141172–141191. doi:10.1109/access.2023.3340626,
.'
din1505-2-1: 'Herrmann, Jan-Phillip
; Tackenberg, Sven ; Nitsch,
Verena: Predicting Human Decision-Making for Task Selection in Manufacturing:
A Systematic Literature Review. In: IEEE Access Bd. 11. New York, NY, IEEE
(2023), S. 141172–141191'
havard: 'J.-P. Herrmann, S. Tackenberg, V. Nitsch, Predicting Human Decision-Making
for Task Selection in Manufacturing: A Systematic Literature Review, IEEE Access.
11 (2023) 141172–141191.'
ieee: 'J.-P. Herrmann, S. Tackenberg, and V. Nitsch, “Predicting Human Decision-Making
for Task Selection in Manufacturing: A Systematic Literature Review,” IEEE
Access, vol. 11, pp. 141172–141191, 2023, doi: 10.1109/access.2023.3340626.'
mla: 'Herrmann, Jan-Phillip, et al. “Predicting Human Decision-Making for Task Selection
in Manufacturing: A Systematic Literature Review.” IEEE Access, vol. 11,
2023, pp. 141172–91, https://doi.org/10.1109/access.2023.3340626.'
short: J.-P. Herrmann, S. Tackenberg, V. Nitsch, IEEE Access 11 (2023) 141172–141191.
ufg: 'Herrmann, Jan-Phillip/Tackenberg, Sven/Nitsch, Verena: Predicting Human
Decision-Making for Task Selection in Manufacturing: A Systematic Literature Review,
in: IEEE Access 11 (2023), S. 141172–141191.'
van: 'Herrmann JP, Tackenberg S, Nitsch V. Predicting Human Decision-Making for
Task Selection in Manufacturing: A Systematic Literature Review. IEEE Access.
2023;11:141172–91.'
date_created: 2024-05-10T11:48:50Z
date_updated: 2025-06-26T07:53:23Z
department:
- _id: DEP7000
- _id: DEP7020
doi: 10.1109/access.2023.3340626
external_id:
isi:
- '001130254900001'
intvolume: ' 11'
isi: '1'
keyword:
- Artificial intelligence
- assistance system
- human decision-making
- manufacturing
language:
- iso: eng
page: 141172-141191
place: New York, NY
publication: IEEE Access
publication_identifier:
eissn:
- 2169-3536
publication_status: published
publisher: IEEE
status: public
title: 'Predicting Human Decision-Making for Task Selection in Manufacturing: A Systematic
Literature Review'
type: scientific_journal_article
user_id: '83781'
volume: 11
year: '2023'
...
---
_id: '13010'
abstract:
- lang: eng
text: Especially in highly interdisciplinary fields such as automation engineering,
contemporary programming education with tailored assignments and individual feedback
is a major challenge for educational institutions due to the increasing number
of students per teacher and the ever-increasing demand for computer science professionals.
To address this gap, we present ”KIAAA” an AI Assistant for Automation Engineering
Teaching, a work-in-progress approach for an integrated, customized, and AI-based
learning support system for automation and programming courses based on instructor-defined
course objectives. Thereby in the KIAAA system, the individual knowledge level
of the students is determined and individually tailored virtual learning scenarios
are generated based on the knowledge and learning profile of the students. These
are iteratively adapted based on the answers given. To achieve this, KIAAA uses
several AI components, a hybrid rule-based scenario generation component, a Help-DKT-based
cognitive model, and a solution assessor that uses a combination of traditional
code analysis methods and AI-based analyses methods for automated programming
task assessment. These components are the main parts of KIAAA to generate customized
programming scenarios as well as visualization and simulation based on a modern
game and physics engine.
author:
- first_name: Sebastian
full_name: Eilermann, Sebastian
last_name: Eilermann
- first_name: Leon
full_name: Wehmeier, Leon
id: '81257'
last_name: Wehmeier
- first_name: Oliver
full_name: Niggemann, Oliver
last_name: Niggemann
- first_name: Andreas
full_name: Deuter, Andreas
id: '62088'
last_name: Deuter
orcid: 0000-0002-6529-6215
citation:
ama: 'Eilermann S, Wehmeier L, Niggemann O, Deuter A. KIAAA: An AI Assistant
for Teaching Programming in the Field of Automation. (Jasperneite J, IEEE
International Conference on Industrial Informatics , Institute of Electrical and
Electronics Engineers, eds.). IEEE; 2023. doi:10.1109/indin51400.2023.10218157'
apa: 'Eilermann, S., Wehmeier, L., Niggemann, O., & Deuter, A. (2023). KIAAA:
An AI Assistant for Teaching Programming in the Field of Automation. In J. Jasperneite,
IEEE International Conference on Industrial Informatics , & Institute of Electrical
and Electronics Engineers (Eds.), 2023 IEEE 21st International Conference on
Industrial Informatics (INDIN). IEEE. https://doi.org/10.1109/indin51400.2023.10218157'
bjps: 'Eilermann S et al. (2023) KIAAA: An AI Assistant for Teaching
Programming in the Field of Automation, Jasperneite J, IEEE International
Conference on Industrial Informatics , and Institute of Electrical and Electronics
Engineers (eds). [Piscataway, NJ]: IEEE.'
chicago: 'Eilermann, Sebastian, Leon Wehmeier, Oliver Niggemann, and Andreas Deuter.
KIAAA: An AI Assistant for Teaching Programming in the Field of Automation.
Edited by Jürgen Jasperneite, IEEE International Conference on Industrial Informatics
, and Institute of Electrical and Electronics Engineers. 2023 IEEE 21st International
Conference on Industrial Informatics (INDIN). [Piscataway, NJ]: IEEE, 2023.
https://doi.org/10.1109/indin51400.2023.10218157.'
chicago-de: 'Eilermann, Sebastian, Leon Wehmeier, Oliver Niggemann und Andreas Deuter.
2023. KIAAA: An AI Assistant for Teaching Programming in the Field of Automation.
Hg. von Jürgen Jasperneite, IEEE International Conference on Industrial Informatics
, und Institute of Electrical and Electronics Engineers. 2023 IEEE 21st International
Conference on Industrial Informatics (INDIN). [Piscataway, NJ]: IEEE. doi:10.1109/indin51400.2023.10218157,
.'
din1505-2-1: 'Eilermann, Sebastian
; Wehmeier, Leon ; Niggemann,
Oliver ; Deuter, Andreas
; Jasperneite, J. ; IEEE
International Conference on Industrial Informatics ; Institute
of Electrical and Electronics Engineers (Hrsg.): KIAAA: An AI Assistant
for Teaching Programming in the Field of Automation. [Piscataway, NJ] : IEEE,
2023'
havard: 'S. Eilermann, L. Wehmeier, O. Niggemann, A. Deuter, KIAAA: An AI Assistant
for Teaching Programming in the Field of Automation, IEEE, [Piscataway, NJ], 2023.'
ieee: 'S. Eilermann, L. Wehmeier, O. Niggemann, and A. Deuter, KIAAA: An AI Assistant
for Teaching Programming in the Field of Automation. [Piscataway, NJ]: IEEE,
2023. doi: 10.1109/indin51400.2023.10218157.'
mla: 'Eilermann, Sebastian, et al. “KIAAA: An AI Assistant for Teaching Programming
in the Field of Automation.” 2023 IEEE 21st International Conference on Industrial
Informatics (INDIN), edited by Jürgen Jasperneite et al., IEEE, 2023, https://doi.org/10.1109/indin51400.2023.10218157.'
short: 'S. Eilermann, L. Wehmeier, O. Niggemann, A. Deuter, KIAAA: An AI Assistant
for Teaching Programming in the Field of Automation, IEEE, [Piscataway, NJ], 2023.'
ufg: 'Eilermann, Sebastian u. a.: KIAAA: An AI Assistant for Teaching Programming
in the Field of Automation, hg. von Jasperneite, Jürgen/IEEE International Conference
on Industrial Informatics , Institute of Electrical and Electronics Engineers,
[Piscataway, NJ] 2023.'
van: 'Eilermann S, Wehmeier L, Niggemann O, Deuter A. KIAAA: An AI Assistant for
Teaching Programming in the Field of Automation. Jasperneite J, IEEE International
Conference on Industrial Informatics , Institute of Electrical and Electronics
Engineers, editors. 2023 IEEE 21st International Conference on Industrial Informatics
(INDIN). [Piscataway, NJ]: IEEE; 2023.'
conference:
end_date: 2023-07-20
location: Lemgo
name: 21st International Conference on Industrial Informatics (INDIN)
start_date: 2023-07-18
corporate_editor:
- 'IEEE International Conference on Industrial Informatics '
- Institute of Electrical and Electronics Engineers
date_created: 2025-06-24T09:24:47Z
date_updated: 2025-06-24T09:38:24Z
department:
- _id: DEP7022
- _id: DEP1306
- _id: DEP7001
doi: 10.1109/indin51400.2023.10218157
editor:
- first_name: Jürgen
full_name: Jasperneite, Jürgen
id: '1899'
last_name: Jasperneite
keyword:
- Visualization
- Automation
- Education
- Games
- Hybrid power systems
- Task analysis
- Artificial intelligence
language:
- iso: eng
place: '[Piscataway, NJ]'
publication: 2023 IEEE 21st International Conference on Industrial Informatics (INDIN)
publication_identifier:
eisbn:
- 978-1-6654-9313-0
isbn:
- 978-1-6654-9314-7
publication_status: published
publisher: IEEE
quality_controlled: '1'
status: public
title: 'KIAAA: An AI Assistant for Teaching Programming in the Field of Automation'
type: conference_editor_article
user_id: '83781'
year: '2023'
...
---
_id: '12796'
abstract:
- lang: eng
text: 'This Design-Based Research (DBR) project aims to develop an intelligent tutoring
system (ITS) for higher education. The system will collect teaching and learning
materials in audio and video formats (e.g., podcasts, lecture recordings, screencasts,
and explainer videos), and store them on a learning experience platform (LXP).
Then, the ITS will process them with the help of speech recognition to gain data
which, in turn, will be used to power further applications: Using artificial intelligence
(AI), the platform will allow users to search the materials, automatically compiling
them according to criteria like lesson subject, language, medium, or required
prior knowledge. By the end of the last DBR cycle, the ITS will also provide a
more active form of support: It will automatically generate exercises based on
predefined patterns and teaching materials, thus allowing learners to check up
on their learning progress autonomously. In order to closely match the ITS''s
features to the needs and learning habits of students in higher education, the
development of this AI-based tutoring system is accompanied by an interdisciplinary
team which will continuously re-evaluate and adapt the concept over the course
of several DBR cycles. Our goal is to derive implications for the system''s technical
development by collecting and evaluating educational research data (mixed methods
design; primary and secondary research methods).'
author:
- first_name: Tobias
full_name: Schmohl, Tobias
id: '71782'
last_name: Schmohl
orcid: https://orcid.org/0000-0002-7043-5582
- first_name: Kathrin
full_name: Schelling, Kathrin
id: '81212'
last_name: Schelling
- first_name: Stefanie
full_name: Go, Stefanie
id: '86007'
last_name: Go
- first_name: Katrin Jana
full_name: Thaler, Katrin Jana
id: '74178'
last_name: Thaler
- first_name: Alice
full_name: Watanabe, Alice
id: '76856'
last_name: Watanabe
citation:
ama: 'Schmohl T, Schelling K, Go S, Thaler KJ, Watanabe A. Development, Implementation
and Acceptance of an AI-Based Tutoring System: A Research-Led Methodology.
(Cukurova M, Rummel N, Gillet D, McLaren B, Uhomoibhi J, eds.). SCITEPRESS - Science
and Technology Publications; 2022:179-186. doi:10.5220/0011068500003182'
apa: 'Schmohl, T., Schelling, K., Go, S., Thaler, K. J., & Watanabe, A. (2022).
Development, Implementation and Acceptance of an AI-based Tutoring System: A Research-Led
Methodology. In M. Cukurova, N. Rummel, D. Gillet, B. McLaren, & J. Uhomoibhi
(Eds.), Proceedings of the 14th International Conference on Computer Supported
Education - Vol. 2 (pp. 179–186). SCITEPRESS - Science and Technology Publications.
https://doi.org/10.5220/0011068500003182'
bjps: 'Schmohl T et al. (2022) Development, Implementation and
Acceptance of an AI-Based Tutoring System: A Research-Led Methodology, Cukurova
M et al. (eds). SCITEPRESS - Science and Technology Publications.'
chicago: 'Schmohl, Tobias, Kathrin Schelling, Stefanie Go, Katrin Jana Thaler, and
Alice Watanabe. Development, Implementation and Acceptance of an AI-Based Tutoring
System: A Research-Led Methodology. Edited by Mutlu Cukurova, Nikol Rummel,
Denis Gillet, Bruce McLaren, and James Uhomoibhi. Proceedings of the 14th
International Conference on Computer Supported Education - Vol. 2. SCITEPRESS
- Science and Technology Publications, 2022. https://doi.org/10.5220/0011068500003182.'
chicago-de: 'Schmohl, Tobias, Kathrin Schelling, Stefanie Go, Katrin Jana Thaler
und Alice Watanabe. 2022. Development, Implementation and Acceptance of an
AI-based Tutoring System: A Research-Led Methodology. Hg. von Mutlu Cukurova,
Nikol Rummel, Denis Gillet, Bruce McLaren, und James Uhomoibhi. Proceedings
of the 14th International Conference on Computer Supported Education - Vol. 2.
SCITEPRESS - Science and Technology Publications. doi:10.5220/0011068500003182,
.'
din1505-2-1: 'Schmohl, Tobias ; Schelling, Kathrin ; Go,
Stefanie ; Thaler, Katrin Jana
; Watanabe, Alice ; Cukurova,
M. ; Rummel, N. ; Gillet,
D. ; McLaren, B. ; Uhomoibhi, J. (Hrsg.): Development,
Implementation and Acceptance of an AI-based Tutoring System: A Research-Led Methodology :
SCITEPRESS - Science and Technology Publications, 2022'
havard: 'T. Schmohl, K. Schelling, S. Go, K.J. Thaler, A. Watanabe, Development,
Implementation and Acceptance of an AI-based Tutoring System: A Research-Led Methodology,
SCITEPRESS - Science and Technology Publications, 2022.'
ieee: 'T. Schmohl, K. Schelling, S. Go, K. J. Thaler, and A. Watanabe, Development,
Implementation and Acceptance of an AI-based Tutoring System: A Research-Led Methodology.
SCITEPRESS - Science and Technology Publications, 2022, pp. 179–186. doi: 10.5220/0011068500003182.'
mla: 'Schmohl, Tobias, et al. “Development, Implementation and Acceptance of an
AI-Based Tutoring System: A Research-Led Methodology.” Proceedings of the 14th
International Conference on Computer Supported Education - Vol. 2, edited
by Mutlu Cukurova et al., SCITEPRESS - Science and Technology Publications, 2022,
pp. 179–86, https://doi.org/10.5220/0011068500003182.'
short: 'T. Schmohl, K. Schelling, S. Go, K.J. Thaler, A. Watanabe, Development,
Implementation and Acceptance of an AI-Based Tutoring System: A Research-Led Methodology,
SCITEPRESS - Science and Technology Publications, 2022.'
ufg: 'Schmohl, Tobias u. a.: Development, Implementation and Acceptance of
an AI-based Tutoring System: A Research-Led Methodology, hg. von Cukurova, Mutlu
u. a., o. O. 2022.'
van: 'Schmohl T, Schelling K, Go S, Thaler KJ, Watanabe A. Development, Implementation
and Acceptance of an AI-based Tutoring System: A Research-Led Methodology. Cukurova
M, Rummel N, Gillet D, McLaren B, Uhomoibhi J, editors. Proceedings of the 14th
International Conference on Computer Supported Education - Vol. 2. SCITEPRESS
- Science and Technology Publications; 2022.'
conference:
end_date: 2022-04-24
location: Online
name: 14th International Conference on Computer Supported Education (CSEDU)
start_date: 2022-04-22
date_created: 2025-04-15T12:23:55Z
date_updated: 2025-06-26T13:40:15Z
doi: 10.5220/0011068500003182
editor:
- first_name: 'Mutlu '
full_name: 'Cukurova, Mutlu '
last_name: Cukurova
- first_name: 'Nikol '
full_name: 'Rummel, Nikol '
last_name: Rummel
- first_name: 'Denis '
full_name: 'Gillet, Denis '
last_name: Gillet
- first_name: 'Bruce '
full_name: 'McLaren, Bruce '
last_name: McLaren
- first_name: 'James '
full_name: 'Uhomoibhi, James '
last_name: Uhomoibhi
keyword:
- Artificial Intelligence in Higher Education
- Design-based Research
- Intelligent Tutoring System
- Participatory Technology Design
- Scoping Review
language:
- iso: eng
page: 179-186
publication: Proceedings of the 14th International Conference on Computer Supported
Education - Vol. 2
publication_identifier:
eisbn:
- 978-989-758-562-3
publication_status: published
publisher: SCITEPRESS - Science and Technology Publications
status: public
title: 'Development, Implementation and Acceptance of an AI-based Tutoring System:
A Research-Led Methodology'
type: conference_editor_article
user_id: '83781'
year: '2022'
...
---
_id: '6908'
abstract:
- lang: eng
text: Es liegt auf der Hand, dass eine digitale Unterstützung von Planungs- und
Beteiligungsverfahren in vielfacher Hinsicht enorme Vorteile bietet. So können
mittels moderner, digitaler Partizpationsplattformen Prozessbeteiligte orts- und
zeitunabhängig an städtebaulichen Ideenfindungs- und Bewertungsverfahren teilnehmen
und ihre Gedanken, Meinungen und Vorschläge mit anderen teilen und diskutieren.
Seit einigen Jahren stehen hierfür eine Reihe adaptierbarer Softwareprodukte zur
Verfügung, z. B. Consul, ein community-basiertes Opensource-Projekt der Consul
Democracy Foundation auf GitHub, die proprietäre Software citizenLab des gleichnamigen
belgischen Unternehmens, oder dem neuseeländischen Pendant Loomio der Loomio Cooperative
Ltd. und viele weitere. Der webbasierte Zugang ermöglicht dabei nicht nur eine
potenzielle Reichweitensteigerung an Teilnehmenden und die schnelle Verlinkung
zu anderen digitalen Inhalten bzw. Medien, sondern erleichtert auch die statistische
Informationsauswertung und die mediale wie inhaltliche Dokumentation des Gesamtprozesses.
Aktuelle Softwarelösungen sind dabei als anwenderfreundliches Baukastensystem
konzipiert, das je nach Anwendungsfall individuell, modular und ohne Programmierkenntnisse
zusammengesetzt werden kann. Die zuschaltbaren Module reichen von einfachen Formularmasken
über interaktive Karten-Tools, MindMaps und Umfragen bis hin zu integrierten Video-Chat-Funktionen
und kollaborativen Whiteboards. Zukünftig ist davon auszugehen, dass die modulare
Struktur und die enorm vielfältigen Einsatzgebiete dieser Softwarelösungen zunehmend
auch KI-gestützte Funktionen als neue Features enthalten werden bzw. im Baukasten
bestehende Module optimieren oder ablösen werden. Die Gründe hierfür liegen größtenteils
im disruptiven Fortschritt der Softwarentwicklung. Andererseits darf aber auch
erwogen werden, ob nicht doch häufig beobachtete Hemmnisse oder Probleme bisheriger
Partizipationsverfahren ggf. durch den unterstützenden Einsatz von KI auch abgebaut
oder verringert werden könnten. Beide Perspektiven stellen für sich genommen schon
sehr breite Grundlagenforschungsfelder dar, die insbesondere durch die noch hinzukommenden
Aspekte der Technologieakzeptanz enorm komplex werden können. Da aber die technologische
Hürde zur Umsetzung einfacher Software-Prototypen durch die Vielzahl zur Verfügung
stehender Opensource-Tools sehr niedrig ist, entwickelte der Forschungsschwerpunkt
nextPlace der Technischen Hochschule Ostwestfalen-Lippe zunächst eine allererste,
prototypische Hardware-Software-Applikation, um - im Sinne eines Proof-of-Concept
– die Relevanz und Aufwände tiefergehender Forschungs- und Entwicklungsarbeiten
abschätzen zu können. Folglich stellen die nachfolgenden Ausführungen einen technischen
Erfahrungsbericht der ersten Entwicklungsschritte dar, um einen einfachen, kostengünstigen
und experimentellen Zugang in dieses noch recht junge Forschungsfeld nachvollziehbar
zu machen.
author:
- first_name: Carsten
full_name: Oldenburg, Carsten
id: '75372'
last_name: Oldenburg
- first_name: Axel
full_name: Häusler, Axel
id: '61520'
last_name: Häusler
orcid: 0009-0001-8565-8199
citation:
ama: 'Oldenburg C, Häusler A. KI-gestützter Wordcloud-Generator für Beteiligungsprozesse.
In: Schrenk M, Popovich VV, Zeile P, et al., eds. REAL CORP 2021: Cities
20.50, Creating Habitats for the 3rd Millennium, Smart - Sustainable - Climate
Neutral : Proceedings of 26th International Conference on Urban Planning, Regional
Development and Information Society. ; 2021:481-487. doi:10.48494/REALCORP2021.1116'
apa: 'Oldenburg, C., & Häusler, A. (2021). KI-gestützter Wordcloud-Generator
für Beteiligungsprozesse. In M. Schrenk, V. V. Popovich, P. Zeile, P. Elisei,
C. Beyer, J. Ryser, G. Stöglehner, & CORP – Competence Center of Urban and
Regional Planning (Eds.), REAL CORP 2021: Cities 20.50, creating habitats
for the 3rd millennium, smart - sustainable - climate neutral : proceedings of
26th International Conference on Urban Planning, Regional Development and Information
Society (pp. 481–487). https://doi.org/10.48494/REALCORP2021.1116'
bjps: 'Oldenburg C and Häusler A (2021) KI-Gestützter Wordcloud-Generator
Für Beteiligungsprozesse. In Schrenk M et al. (eds), REAL CORP 2021: Cities
20.50, Creating Habitats for the 3rd Millennium, Smart - Sustainable - Climate
Neutral : Proceedings of 26th International Conference on Urban Planning, Regional
Development and Information Society. Wien, pp. 481–487.'
chicago: 'Oldenburg, Carsten, and Axel Häusler. “KI-Gestützter Wordcloud-Generator
Für Beteiligungsprozesse.” In REAL CORP 2021: Cities 20.50, Creating Habitats
for the 3rd Millennium, Smart - Sustainable - Climate Neutral : Proceedings of
26th International Conference on Urban Planning, Regional Development and Information
Society, edited by Mnafred Schrenk, Vasily V. Popovich, Peter Zeile, Pietro
Elisei, Clemens Beyer, Judith Ryser, Gernot Stöglehner, and CORP – Competence
Center of Urban and Regional Planning, 481–87. Wien, 2021. https://doi.org/10.48494/REALCORP2021.1116.'
chicago-de: 'Oldenburg, Carsten und Axel Häusler. 2021. KI-gestützter Wordcloud-Generator
für Beteiligungsprozesse. In: REAL CORP 2021: Cities 20.50, creating habitats
for the 3rd millennium, smart - sustainable - climate neutral : proceedings of
26th International Conference on Urban Planning, Regional Development and Information
Society, hg. von Mnafred Schrenk, Vasily V. Popovich, Peter Zeile, Pietro
Elisei, Clemens Beyer, Judith Ryser, Gernot Stöglehner, und CORP – Competence
Center of Urban and Regional Planning, 481–487. Wien. doi:10.48494/REALCORP2021.1116,
.'
din1505-2-1: 'Oldenburg, Carsten ;
Häusler, Axel: KI-gestützter Wordcloud-Generator
für Beteiligungsprozesse. In: Schrenk,
M. ; Popovich, V. V. ; Zeile, P. ; Elisei,
P. ; Beyer, C. ; Ryser,
J. ; Stöglehner, G. ; CORP – Competence Center of Urban and Regional
Planning (Hrsg.): REAL CORP 2021: Cities 20.50, creating habitats
for the 3rd millennium, smart - sustainable - climate neutral : proceedings of
26th International Conference on Urban Planning, Regional Development and Information
Society. Wien, 2021, S. 481–487'
havard: 'C. Oldenburg, A. Häusler, KI-gestützter Wordcloud-Generator für Beteiligungsprozesse,
in: M. Schrenk, V.V. Popovich, P. Zeile, P. Elisei, C. Beyer, J. Ryser, G. Stöglehner,
CORP – Competence Center of Urban and Regional Planning (Eds.), REAL CORP 2021:
Cities 20.50, Creating Habitats for the 3rd Millennium, Smart - Sustainable -
Climate Neutral : Proceedings of 26th International Conference on Urban Planning,
Regional Development and Information Society, Wien, 2021: pp. 481–487.'
ieee: 'C. Oldenburg and A. Häusler, “KI-gestützter Wordcloud-Generator für Beteiligungsprozesse,”
in REAL CORP 2021: Cities 20.50, creating habitats for the 3rd millennium,
smart - sustainable - climate neutral : proceedings of 26th International Conference
on Urban Planning, Regional Development and Information Society, M. Schrenk,
V. V. Popovich, P. Zeile, P. Elisei, C. Beyer, J. Ryser, G. Stöglehner, and CORP
– Competence Center of Urban and Regional Planning, Eds. Wien, 2021, pp. 481–487.
doi: 10.48494/REALCORP2021.1116.'
mla: 'Oldenburg, Carsten, and Axel Häusler. “KI-Gestützter Wordcloud-Generator Für
Beteiligungsprozesse.” REAL CORP 2021: Cities 20.50, Creating Habitats for
the 3rd Millennium, Smart - Sustainable - Climate Neutral : Proceedings of 26th
International Conference on Urban Planning, Regional Development and Information
Society, edited by Mnafred Schrenk et al., 2021, pp. 481–87, https://doi.org/10.48494/REALCORP2021.1116.'
short: 'C. Oldenburg, A. Häusler, in: M. Schrenk, V.V. Popovich, P. Zeile, P. Elisei,
C. Beyer, J. Ryser, G. Stöglehner, CORP – Competence Center of Urban and Regional
Planning (Eds.), REAL CORP 2021: Cities 20.50, Creating Habitats for the 3rd
Millennium, Smart - Sustainable - Climate Neutral : Proceedings of 26th International
Conference on Urban Planning, Regional Development and Information Society, Wien,
2021, pp. 481–487.'
ufg: 'Oldenburg, Carsten/Häusler, Axel: KI-gestützter Wordcloud-Generator
für Beteiligungsprozesse, in: Schrenk, Mnafred u. a. (Hgg.): REAL CORP
2021: Cities 20.50, creating habitats for the 3rd millennium, smart - sustainable
- climate neutral : proceedings of 26th International Conference on Urban Planning,
Regional Development and Information Society, Wien 2021, S. 481–487.'
van: 'Oldenburg C, Häusler A. KI-gestützter Wordcloud-Generator für Beteiligungsprozesse.
In: Schrenk M, Popovich VV, Zeile P, Elisei P, Beyer C, Ryser J, et al., editors.
REAL CORP 2021: Cities 2050, creating habitats for the 3rd millennium, smart
- sustainable - climate neutral : proceedings of 26th International Conference
on Urban Planning, Regional Development and Information Society. Wien; 2021. p.
481–7.'
conference:
end_date: 2021-10-10
location: Wien
name: 26. REAL CORP - International Conference on Urban Planning and Regional Development
in the Information Society
start_date: 2021-10-07
corporate_editor:
- CORP – Competence Center of Urban and Regional Planning
date_created: 2021-12-16T10:47:01Z
date_updated: 2024-12-04T12:56:15Z
department:
- _id: DEP1055
- _id: DEP1028
doi: 10.48494/REALCORP2021.1116
editor:
- first_name: Mnafred
full_name: Schrenk, Mnafred
last_name: Schrenk
- first_name: Vasily V.
full_name: Popovich, Vasily V.
last_name: Popovich
- first_name: Peter
full_name: Zeile, Peter
last_name: Zeile
- first_name: Pietro
full_name: Elisei, Pietro
last_name: Elisei
- first_name: Clemens
full_name: Beyer, Clemens
last_name: Beyer
- first_name: Judith
full_name: Ryser, Judith
last_name: Ryser
- first_name: Gernot
full_name: Stöglehner, Gernot
last_name: Stöglehner
keyword:
- Data Visualisation
- Participation
- Speech Recognition
- Artificial Intelligence
- Internet of Things
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.corp.at/archive/CORP2021_116.pdf
oa: '1'
page: 481-487
place: Wien
publication: "\t REAL CORP 2021: Cities 20.50, creating habitats for the 3rd millennium,
smart - sustainable - climate neutral : proceedings of 26th International Conference
on Urban Planning, Regional Development and Information Society"
publication_identifier:
isbn:
- 978-3-9504945-0-1
publication_status: published
quality_controlled: '1'
related_material:
link:
- relation: confirmation
url: https://www.corp.at/archive/CORP2021_116.pdf
status: public
title: KI-gestützter Wordcloud-Generator für Beteiligungsprozesse
type: book_chapter
user_id: '83781'
year: '2021'
...
---
_id: '4100'
author:
- first_name: Tobias
full_name: Schmohl, Tobias
id: '71782'
last_name: Schmohl
orcid: https://orcid.org/0000-0002-7043-5582
- first_name: Susanne
full_name: Schwickert, Susanne
id: '27269'
last_name: Schwickert
- first_name: Oliver
full_name: Glahn, Oliver
id: '76018'
last_name: Glahn
citation:
ama: 'Schmohl T, Schwickert S, Glahn O. Conceptual Design of an AI-Based Learning
Assistant . Bologna: Libreriauniversitaria.it; 2020:309-313. doi:10.26352/E618_2384-9509'
apa: 'Schmohl, T., Schwickert, S., & Glahn, O. (2020). Conceptual Design
of an AI-Based Learning Assistant . The Future of Education (pp. 309–313).
Bologna: Libreriauniversitaria.it. https://doi.org/10.26352/E618_2384-9509'
bjps: 'Schmohl T, Schwickert S and Glahn O (2020) Conceptual Design of
an AI-Based Learning Assistant . Bologna: Libreriauniversitaria.it.'
chicago: 'Schmohl, Tobias, Susanne Schwickert, and Oliver Glahn. Conceptual Design
of an AI-Based Learning Assistant . The Future of Education. Bologna:
Libreriauniversitaria.it, 2020. https://doi.org/10.26352/E618_2384-9509.'
chicago-de: 'Schmohl, Tobias, Susanne Schwickert und Oliver Glahn. 2020. Conceptual
Design of an AI-Based Learning Assistant . The Future of Education.
Bologna: Libreriauniversitaria.it. doi:10.26352/E618_2384-9509,
.'
din1505-2-1: 'Schmohl, Tobias ; Schwickert, Susanne ; Glahn,
Oliver: Conceptual Design of an AI-Based Learning Assistant . Bologna :
Libreriauniversitaria.it, 2020'
havard: T. Schmohl, S. Schwickert, O. Glahn, Conceptual Design of an AI-Based Learning
Assistant , Libreriauniversitaria.it, Bologna, 2020.
ieee: 'T. Schmohl, S. Schwickert, and O. Glahn, Conceptual Design of an AI-Based
Learning Assistant . Bologna: Libreriauniversitaria.it, 2020, pp. 309–313.'
mla: Schmohl, Tobias, et al. “Conceptual Design of an AI-Based Learning Assistant
.” The Future of Education, Libreriauniversitaria.it, 2020, pp. 309–13,
doi:10.26352/E618_2384-9509.
short: T. Schmohl, S. Schwickert, O. Glahn, Conceptual Design of an AI-Based Learning
Assistant , Libreriauniversitaria.it, Bologna, 2020.
ufg: 'Schmohl, Tobias et. al. (2020): Conceptual Design of an AI-Based Learning
Assistant , Bologna.'
van: 'Schmohl T, Schwickert S, Glahn O. Conceptual Design of an AI-Based Learning
Assistant . The Future of Education. Bologna: Libreriauniversitaria.it; 2020.'
conference:
end_date: 2020-07-19
location: Florenz
name: ' 10 th International Conference The Future of Education '
start_date: 2020-07-18
date_created: 2020-11-27T08:28:18Z
date_updated: 2023-03-15T13:49:50Z
department:
- _id: DEP1022
- _id: DEP2000
doi: 10.26352/E618_2384-9509
keyword:
- Artificial Intelligence
- intelligent tutoring system
- reflection
- project-based learning
- online-learning
- interactive video
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.academia.edu/43653971/The_Future_of_Education_Conference_Proceedings_2020
oa: '1'
page: 309-313
place: Bologna
publication: The Future of Education
publication_identifier:
eisbn:
- 978-88-85813-87-8
publication_status: published
publisher: Libreriauniversitaria.it
quality_controlled: '1'
status: public
title: 'Conceptual Design of an AI-Based Learning Assistant '
type: conference_editor_article
user_id: '79260'
year: 2020
...
---
_id: '4518'
abstract:
- lang: eng
text: This paper introduces CAAI, a novel cognitive architecture for artificial
intelligence in cyber-physical production systems. The goal of the architecture
is to reduce the implementation effort for the usage of artificial intelligence
algorithms. The core of the CAAI is a cognitive module that processes the user's
declarative goals, selects suitable models and algorithms, and creates a configuration
for the execution of a processing pipeline on a big data platform. Constant observation
and evaluation against performance criteria assess the performance of pipelines
for many and different use cases. Based on these evaluations, the pipelines are
automatically adapted if necessary. The modular design with well-defined interfaces
enables the reusability and extensibility of pipeline components. A big data platform
implements this modular design supported by technologies such as Docker, Kubernetes,
and Kafka for virtualization and orchestration of the individual components and
their communication. The implementation of the architecture is evaluated using
a real-world use case. The prototypic implementation is accessible on GitHub and
contains a demonstration.
author:
- first_name: Andreas
full_name: Fischbach, Andreas
last_name: Fischbach
- first_name: Jan
full_name: Strohschein, Jan
last_name: Strohschein
- first_name: Andreas
full_name: Bunte, Andreas
id: '58885'
last_name: Bunte
- first_name: Jörg
full_name: Stork, Jörg
last_name: Stork
- first_name: Heide
full_name: Faeskorn-Woyke, Heide
last_name: Faeskorn-Woyke
- first_name: Natalia
full_name: Moriz, Natalia
id: '44238'
last_name: Moriz
- first_name: Thomas
full_name: Bartz-Beielstein, Thomas
last_name: Bartz-Beielstein
citation:
ama: Fischbach A, Strohschein J, Bunte A, et al. CAAI -- A Cognitive Architecture
to Introduce Artificial Intelligence in Cyber-Physical Production Systems. The
International Journal of Advanced Manufacturing Technology. 2020;111(1/2):609-626.
doi:10.1007/s00170-020-06094-z
apa: Fischbach, A., Strohschein, J., Bunte, A., Stork, J., Faeskorn-Woyke, H., Moriz,
N., & Bartz-Beielstein, T. (2020). CAAI -- A Cognitive Architecture to Introduce
Artificial Intelligence in Cyber-Physical Production Systems. The International
Journal of Advanced Manufacturing Technology, 111(1/2), 609–626. https://doi.org/10.1007/s00170-020-06094-z
bjps: Fischbach A et al. (2020) CAAI -- A Cognitive Architecture to
Introduce Artificial Intelligence in Cyber-Physical Production Systems. The
International Journal of Advanced Manufacturing Technology 111, 609–626.
chicago: 'Fischbach, Andreas, Jan Strohschein, Andreas Bunte, Jörg Stork, Heide
Faeskorn-Woyke, Natalia Moriz, and Thomas Bartz-Beielstein. “CAAI -- A Cognitive
Architecture to Introduce Artificial Intelligence in Cyber-Physical Production
Systems.” The International Journal of Advanced Manufacturing Technology
111, no. 1/2 (2020): 609–26. https://doi.org/10.1007/s00170-020-06094-z.'
chicago-de: 'Fischbach, Andreas, Jan Strohschein, Andreas Bunte, Jörg Stork, Heide
Faeskorn-Woyke, Natalia Moriz und Thomas Bartz-Beielstein. 2020. CAAI -- A Cognitive
Architecture to Introduce Artificial Intelligence in Cyber-Physical Production
Systems. The International Journal of Advanced Manufacturing Technology
111, Nr. 1/2: 609–626. doi:10.1007/s00170-020-06094-z,
.'
din1505-2-1: 'Fischbach, Andreas ;
Strohschein, Jan ; Bunte,
Andreas ; Stork, Jörg ; Faeskorn-Woyke, Heide ; Moriz,
Natalia ; Bartz-Beielstein, Thomas:
CAAI -- A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical
Production Systems. In: The International Journal of Advanced Manufacturing
Technology Bd. 111, Springer (2020), Nr. 1/2, S. 609–626'
havard: A. Fischbach, J. Strohschein, A. Bunte, J. Stork, H. Faeskorn-Woyke, N.
Moriz, T. Bartz-Beielstein, CAAI -- A Cognitive Architecture to Introduce Artificial
Intelligence in Cyber-Physical Production Systems, The International Journal of
Advanced Manufacturing Technology. 111 (2020) 609–626.
ieee: 'A. Fischbach et al., “CAAI -- A Cognitive Architecture to Introduce
Artificial Intelligence in Cyber-Physical Production Systems,” The International
Journal of Advanced Manufacturing Technology, vol. 111, no. 1/2, pp. 609–626,
2020, doi: 10.1007/s00170-020-06094-z.'
mla: Fischbach, Andreas, et al. “CAAI -- A Cognitive Architecture to Introduce Artificial
Intelligence in Cyber-Physical Production Systems.” The International Journal
of Advanced Manufacturing Technology, vol. 111, no. 1/2, 2020, pp. 609–26,
https://doi.org/10.1007/s00170-020-06094-z.
short: A. Fischbach, J. Strohschein, A. Bunte, J. Stork, H. Faeskorn-Woyke, N. Moriz,
T. Bartz-Beielstein, The International Journal of Advanced Manufacturing Technology
111 (2020) 609–626.
ufg: 'Fischbach, Andreas u. a.: CAAI -- A Cognitive Architecture to Introduce
Artificial Intelligence in Cyber-Physical Production Systems, in: The International
Journal of Advanced Manufacturing Technology 111 (2020), H. 1/2, S. 609–626.'
van: Fischbach A, Strohschein J, Bunte A, Stork J, Faeskorn-Woyke H, Moriz N, et
al. CAAI -- A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical
Production Systems. The International Journal of Advanced Manufacturing Technology.
2020;111(1/2):609–26.
date_created: 2021-01-26T12:24:10Z
date_updated: 2025-06-26T13:38:24Z
department:
- _id: DEP5023
doi: 10.1007/s00170-020-06094-z
external_id:
isi:
- '000574389900002'
intvolume: ' 111'
isi: '1'
issue: 1/2
keyword:
- CPPS
- Artificial intelligence
- Industry 40
- Reference architecture
- Optimization
- SMBO
- Cognition
- Big data platform
- Modularization
- AutoML
language:
- iso: eng
page: 609-626
publication: The International Journal of Advanced Manufacturing Technology
publication_identifier:
eissn:
- 1433-3015
issn:
- 0268-3768
publication_status: published
publisher: Springer
status: public
title: CAAI -- A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical
Production Systems
type: journal_article
user_id: '83781'
volume: 111
year: '2020'
...
---
_id: '4312'
abstract:
- lang: eng
text: Computer-aided assistance systems are entering the world of work and production.
Such systems utilize augmented- and virtual-reality for operator training and
live guidance as well as mobile maintenance and support. This is particularly
important in the modern production reality of ever-changing products and `lot
size one' customization of production.This paper focuses on the application of
machine learning approach to extend the functionality of assistance systems. Machine
learning provides tools to analyse large amounts of data and extract meaningful
information. The goal here is to recognize the movement of an operator which would
enable automatic display of instructions relevant to them.We present the challenges
facing machine learning applications in human-centered assistance systems and
a framework to assess machine learning approaches feasible for this scenario.
The approach is assessed on a historical data set and then deployed in a work
station for live testing. The post-hoc, or historical, analysis yields promising
results. The ad-hoc, or live, analysis is a complex task and the results are affected
by multiple factors, most of which are introduced by the human influence.The contribution
of this paper is an approach to adapt state- of-the-art machine learning to operator
movement recognition with a special focus on approaches to spatial time series
data pre-processing. Presented experiment results validate the approach and show
that it performs well in a real-world scenario.
author:
- first_name: Marta
full_name: Fullen, Marta
last_name: Fullen
- first_name: Alexander
full_name: Maier, Alexander
id: '11158'
last_name: Maier
- first_name: Arthur
full_name: Nazarenko, Arthur
last_name: Nazarenko
- first_name: Sascha
full_name: Jenderny, Sascha
last_name: Jenderny
- first_name: Carsten
full_name: Röcker, Carsten
id: '61525'
last_name: Röcker
citation:
ama: 'Fullen M, Maier A, Nazarenko A, Jenderny S, Röcker C. Machine Learning for
Assistance Systems: Pattern-Based Approach to Online Step Recognition. In: IEEE,
ed. 2019 IEEE 17th International Conference on Industrial Informatics (INDIN).
Piscataway, NJ : IEEE; 2019:296-302. doi:10.1109/INDIN41052.2019.8972122'
apa: 'Fullen, M., Maier, A., Nazarenko, A., Jenderny, S., & Röcker, C. (2019).
Machine Learning for Assistance Systems: Pattern-Based Approach to Online Step
Recognition. In IEEE (Ed.), 2019 IEEE 17th International Conference on Industrial
Informatics (INDIN) (pp. 296–302). Piscataway, NJ : IEEE. https://doi.org/10.1109/INDIN41052.2019.8972122'
bjps: 'Fullen M et al. (2019) Machine Learning for Assistance Systems:
Pattern-Based Approach to Online Step Recognition. In IEEE (ed.), 2019 IEEE
17th International Conference on Industrial Informatics (INDIN). Piscataway,
NJ : IEEE, pp. 296–302.'
chicago: 'Fullen, Marta, Alexander Maier, Arthur Nazarenko, Sascha Jenderny, and
Carsten Röcker. “Machine Learning for Assistance Systems: Pattern-Based Approach
to Online Step Recognition.” In 2019 IEEE 17th International Conference on
Industrial Informatics (INDIN), edited by IEEE, 296–302. Piscataway, NJ :
IEEE, 2019. https://doi.org/10.1109/INDIN41052.2019.8972122.'
chicago-de: 'Fullen, Marta, Alexander Maier, Arthur Nazarenko, Sascha Jenderny und
Carsten Röcker. 2019. Machine Learning for Assistance Systems: Pattern-Based Approach
to Online Step Recognition. In: 2019 IEEE 17th International Conference on
Industrial Informatics (INDIN), hg. von IEEE, 296–302. Piscataway, NJ : IEEE.
doi:10.1109/INDIN41052.2019.8972122,
.'
din1505-2-1: 'Fullen, Marta ; Maier, Alexander ; Nazarenko,
Arthur ; Jenderny, Sascha
; Röcker, Carsten: Machine Learning
for Assistance Systems: Pattern-Based Approach to Online Step Recognition. In:
IEEE (Hrsg.): 2019 IEEE 17th
International Conference on Industrial Informatics (INDIN). Piscataway, NJ
: IEEE, 2019, S. 296–302'
havard: 'M. Fullen, A. Maier, A. Nazarenko, S. Jenderny, C. Röcker, Machine Learning
for Assistance Systems: Pattern-Based Approach to Online Step Recognition, in:
IEEE (Ed.), 2019 IEEE 17th International Conference on Industrial Informatics
(INDIN), IEEE, Piscataway, NJ , 2019: pp. 296–302.'
ieee: 'M. Fullen, A. Maier, A. Nazarenko, S. Jenderny, and C. Röcker, “Machine Learning
for Assistance Systems: Pattern-Based Approach to Online Step Recognition,” in
2019 IEEE 17th International Conference on Industrial Informatics (INDIN),
IEEE, Ed. Piscataway, NJ : IEEE, 2019, pp. 296–302.'
mla: 'Fullen, Marta, et al. “Machine Learning for Assistance Systems: Pattern-Based
Approach to Online Step Recognition.” 2019 IEEE 17th International Conference
on Industrial Informatics (INDIN), edited by IEEE, IEEE, 2019, pp. 296–302,
doi:10.1109/INDIN41052.2019.8972122.'
short: 'M. Fullen, A. Maier, A. Nazarenko, S. Jenderny, C. Röcker, in: IEEE (Ed.),
2019 IEEE 17th International Conference on Industrial Informatics (INDIN), IEEE,
Piscataway, NJ , 2019, pp. 296–302.'
ufg: 'Fullen, Marta et. al. (2019): Machine Learning for Assistance Systems:
Pattern-Based Approach to Online Step Recognition, in: IEEE (Hg.): 2019 IEEE
17th International Conference on Industrial Informatics (INDIN), Piscataway,
NJ , S. 296–302.'
van: 'Fullen M, Maier A, Nazarenko A, Jenderny S, Röcker C. Machine Learning for
Assistance Systems: Pattern-Based Approach to Online Step Recognition. In: IEEE,
editor. 2019 IEEE 17th International Conference on Industrial Informatics (INDIN).
Piscataway, NJ : IEEE; 2019. p. 296–302.'
conference:
end_date: 2019-07-25
location: Helsinki, Finland,
name: 17th International Conference on Industrial Informatics (INDIN)
start_date: 2019-07-22
corporate_editor:
- IEEE
date_created: 2021-01-06T13:59:10Z
date_updated: 2023-03-15T13:49:51Z
department:
- _id: DEP5023
doi: 10.1109/INDIN41052.2019.8972122
keyword:
- augmented reality
- computer based training
- data handling
- industrial training
- learning (artificial intelligence)
- time series
language:
- iso: eng
page: 296 - 302
place: 'Piscataway, NJ '
publication: 2019 IEEE 17th International Conference on Industrial Informatics (INDIN)
publication_identifier:
isbn:
- 978-1-7281-2927-3
issn:
- 2378-363X
publication_status: published
publisher: IEEE
status: public
title: 'Machine Learning for Assistance Systems: Pattern-Based Approach to Online
Step Recognition'
type: book_chapter
user_id: '15514'
year: 2019
...
---
_id: '2087'
abstract:
- lang: eng
text: It is likely in real-world applications that only little data isavailable
for training a knowledge-based system. We present a method forautomatically training
the knowledge-representing membership functionsof a Fuzzy-Pattern-Classification
system that works also when only littledata is available and the universal set
is described insufficiently. Actually,this paper presents how the Modified-Fuzzy-Pattern-Classifier’s
member-ship functions are trained using probability distribution functions.
author:
- first_name: Uwe
full_name: Mönks, Uwe
id: '1825'
last_name: Mönks
- first_name: Volker
full_name: Lohweg, Volker
id: '1804'
last_name: Lohweg
orcid: 0000-0002-3325-7887
- first_name: Denis
full_name: Petker, Denis
last_name: Petker
citation:
ama: 'Mönks U, Lohweg V, Petker D. Fuzzy-Pattern-Classifier Training with Small
Data Sets. In: IPMU 2010 - International Conference on Information Processing
and Management of Uncertainty in Knowledge Based Systems. 28 Jun 2010 - 02
July 2010, Dortmund, Germany; 2010.'
apa: Mönks, U., Lohweg, V., & Petker, D. (2010). Fuzzy-Pattern-Classifier Training
with Small Data Sets. In IPMU 2010 - International Conference on Information
Processing and Management of Uncertainty in Knowledge Based Systems. 28 Jun
2010 - 02 July 2010, Dortmund, Germany.
bjps: Mönks U, Lohweg V and Petker D (2010) Fuzzy-Pattern-Classifier Training
with Small Data Sets. IPMU 2010 - International Conference on Information Processing
and Management of Uncertainty in Knowledge Based Systems. 28 Jun 2010 - 02
July 2010, Dortmund, Germany.
chicago: Mönks, Uwe, Volker Lohweg, and Denis Petker. “Fuzzy-Pattern-Classifier
Training with Small Data Sets.” In IPMU 2010 - International Conference on
Information Processing and Management of Uncertainty in Knowledge Based Systems.
28 Jun 2010 - 02 July 2010, Dortmund, Germany, 2010.
chicago-de: 'Mönks, Uwe, Volker Lohweg und Denis Petker. 2010. Fuzzy-Pattern-Classifier
Training with Small Data Sets. In: IPMU 2010 - International Conference on
Information Processing and Management of Uncertainty in Knowledge Based Systems.
28 Jun 2010 - 02 July 2010, Dortmund, Germany.'
din1505-2-1: 'Mönks, Uwe ; Lohweg,
Volker ; Petker, Denis: Fuzzy-Pattern-Classifier
Training with Small Data Sets. In: IPMU 2010 - International Conference on
Information Processing and Management of Uncertainty in Knowledge Based Systems :
28 Jun 2010 - 02 July 2010, Dortmund, Germany, 2010'
havard: 'U. Mönks, V. Lohweg, D. Petker, Fuzzy-Pattern-Classifier Training with
Small Data Sets, in: IPMU 2010 - International Conference on Information Processing
and Management of Uncertainty in Knowledge Based Systems, 28 Jun 2010 - 02 July
2010, Dortmund, Germany, 2010.'
ieee: U. Mönks, V. Lohweg, and D. Petker, “Fuzzy-Pattern-Classifier Training with
Small Data Sets,” in IPMU 2010 - International Conference on Information Processing
and Management of Uncertainty in Knowledge Based Systems, 2010.
mla: Mönks, Uwe, et al. “Fuzzy-Pattern-Classifier Training with Small Data Sets.”
IPMU 2010 - International Conference on Information Processing and Management
of Uncertainty in Knowledge Based Systems, 28 Jun 2010 - 02 July 2010, Dortmund,
Germany, 2010.
short: 'U. Mönks, V. Lohweg, D. Petker, in: IPMU 2010 - International Conference
on Information Processing and Management of Uncertainty in Knowledge Based Systems,
28 Jun 2010 - 02 July 2010, Dortmund, Germany, 2010.'
ufg: 'Mönks, Uwe et. al. (2010): Fuzzy-Pattern-Classifier Training with Small
Data Sets, in: IPMU 2010 - International Conference on Information Processing
and Management of Uncertainty in Knowledge Based Systems.'
van: 'Mönks U, Lohweg V, Petker D. Fuzzy-Pattern-Classifier Training with Small
Data Sets. In: IPMU 2010 - International Conference on Information Processing
and Management of Uncertainty in Knowledge Based Systems. 28 Jun 2010 - 02 July
2010, Dortmund, Germany; 2010.'
date_created: 2019-12-02T08:15:18Z
date_updated: 2023-03-15T13:49:38Z
department:
- _id: DEP5023
keyword:
- Fuzzy Logic
- Probability Theory
- Fuzzy-Pattern-Classification
- Machine Learning
- Artificial Intelligence
- Pattern Recognition
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.th-owl.de/init/uploads/tx_initdb/00800426_01.pdf
oa: '1'
publication: IPMU 2010 - International Conference on Information Processing and Management
of Uncertainty in Knowledge Based Systems
publication_status: published
publisher: 28 Jun 2010 - 02 July 2010, Dortmund, Germany
status: public
title: Fuzzy-Pattern-Classifier Training with Small Data Sets
type: conference
user_id: '45673'
year: 2010
...