Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Towards Sustainable Customization: Bridging Smart Products and Manufacturing Systems |
| Untertitel | Proceedings of the 8th Changeable, Agile, Reconfigurable and Virtual Production Conference (CARV2021) and the 10th World Mass Customization & Personalization Conference (MCPC2021), Aalborg, Denmark, October/November 2021 |
| Herausgeber/-innen | Ann-Louise Andersen, Rasmus Andersen, Thomas Ditlev Brunoe, Maria Stoettrup Schioenning Larsen, Kjeld Nielsen, Alessia Napoleone, Stefan Kjeldgaard |
| Herausgeber (Verlag) | Springer Science and Business Media Deutschland GmbH |
| Seiten | 935-942 |
| Seitenumfang | 8 |
| ISBN (Print) | 9783030906993 |
| Publikationsstatus | Veröffentlicht - 2022 |
| Veranstaltung | 8th Changeable, Agile, Reconfigurable and Virtual Production Conference, CARV 2021 and 10th World Mass Customization and Personalization Conference, MCPC 2021 - Aalborg, Dänemark Dauer: 1 Nov. 2021 → 2 Nov. 2021 |
Publikationsreihe
| Name | Lecture Notes in Mechanical Engineering |
|---|---|
| ISSN (Print) | 2195-4356 |
| ISSN (elektronisch) | 2195-4364 |
Abstract
In the digital era, individualized educational services, e.g. distributed by intelligent tutoring systems, are becoming increasingly popular and important for life-long learning but also during the COVID pandemic as many universities had to switch to distance learning immediately. Intelligent tutoring systems simulate behavior and expertise of physical teachers and support learners individually. In addition to closed questions, which can be modeled simply as if-then statements or decision trees, the use of artificial intelligence enables more and more the implementation of open questions and poorly structured problems, which is of particular importance for e.g. engineering education. In order to make the learning experience authentic, it is important to understand the learners as individuals and to confront them with learning content and in-depth knowledge tailored to their needs and skills. If, e.g., a formative assessment shows that a certain content has not yet been internalized, the tutoring system must detect this and react accordingly. Since this largely corresponds to mass customizing the teaching process, the following article frames digital education with focus on intelligent tutoring systems in context with mass customization. For cracking the code of mass customizing digital education, the three mass customization key competences solution space development, robust process design as well as choice navigation are taken as reference to set up digital educational content.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Fahrzeugbau
- Ingenieurwesen (insg.)
- Luft- und Raumfahrttechnik
- Ingenieurwesen (insg.)
- Maschinenbau
- Chemische Verfahrenstechnik (insg.)
- Fließ- und Transferprozesse von Flüssigkeiten
Zitieren
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- BibTex
- RIS
Towards Sustainable Customization: Bridging Smart Products and Manufacturing Systems: Proceedings of the 8th Changeable, Agile, Reconfigurable and Virtual Production Conference (CARV2021) and the 10th World Mass Customization & Personalization Conference (MCPC2021), Aalborg, Denmark, October/November 2021. Hrsg. / Ann-Louise Andersen; Rasmus Andersen; Thomas Ditlev Brunoe; Maria Stoettrup Schioenning Larsen; Kjeld Nielsen; Alessia Napoleone; Stefan Kjeldgaard. Springer Science and Business Media Deutschland GmbH, 2022. S. 935-942 (Lecture Notes in Mechanical Engineering).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Considering Intelligent Tutoring Systems as Mass Customization of Digital Education
AU - Gembarski, Paul Christoph
AU - Hoppe, Lukas
PY - 2022
Y1 - 2022
N2 - In the digital era, individualized educational services, e.g. distributed by intelligent tutoring systems, are becoming increasingly popular and important for life-long learning but also during the COVID pandemic as many universities had to switch to distance learning immediately. Intelligent tutoring systems simulate behavior and expertise of physical teachers and support learners individually. In addition to closed questions, which can be modeled simply as if-then statements or decision trees, the use of artificial intelligence enables more and more the implementation of open questions and poorly structured problems, which is of particular importance for e.g. engineering education. In order to make the learning experience authentic, it is important to understand the learners as individuals and to confront them with learning content and in-depth knowledge tailored to their needs and skills. If, e.g., a formative assessment shows that a certain content has not yet been internalized, the tutoring system must detect this and react accordingly. Since this largely corresponds to mass customizing the teaching process, the following article frames digital education with focus on intelligent tutoring systems in context with mass customization. For cracking the code of mass customizing digital education, the three mass customization key competences solution space development, robust process design as well as choice navigation are taken as reference to set up digital educational content.
AB - In the digital era, individualized educational services, e.g. distributed by intelligent tutoring systems, are becoming increasingly popular and important for life-long learning but also during the COVID pandemic as many universities had to switch to distance learning immediately. Intelligent tutoring systems simulate behavior and expertise of physical teachers and support learners individually. In addition to closed questions, which can be modeled simply as if-then statements or decision trees, the use of artificial intelligence enables more and more the implementation of open questions and poorly structured problems, which is of particular importance for e.g. engineering education. In order to make the learning experience authentic, it is important to understand the learners as individuals and to confront them with learning content and in-depth knowledge tailored to their needs and skills. If, e.g., a formative assessment shows that a certain content has not yet been internalized, the tutoring system must detect this and react accordingly. Since this largely corresponds to mass customizing the teaching process, the following article frames digital education with focus on intelligent tutoring systems in context with mass customization. For cracking the code of mass customizing digital education, the three mass customization key competences solution space development, robust process design as well as choice navigation are taken as reference to set up digital educational content.
KW - Digital education
KW - eLearning
KW - Intelligent tutoring systems
KW - Mass customization
UR - http://www.scopus.com/inward/record.url?scp=85119420174&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-90700-6_107
DO - 10.1007/978-3-030-90700-6_107
M3 - Conference contribution
AN - SCOPUS:85119420174
SN - 9783030906993
T3 - Lecture Notes in Mechanical Engineering
SP - 935
EP - 942
BT - Towards Sustainable Customization: Bridging Smart Products and Manufacturing Systems
A2 - Andersen, Ann-Louise
A2 - Andersen, Rasmus
A2 - Brunoe, Thomas Ditlev
A2 - Larsen, Maria Stoettrup Schioenning
A2 - Nielsen, Kjeld
A2 - Napoleone, Alessia
A2 - Kjeldgaard, Stefan
PB - Springer Science and Business Media Deutschland GmbH
T2 - 8th Changeable, Agile, Reconfigurable and Virtual Production Conference, CARV 2021 and 10th World Mass Customization and Personalization Conference, MCPC 2021
Y2 - 1 November 2021 through 2 November 2021
ER -