Skillab - A Multimodal Augmented Reality Environment for Learning Manual Tasks

Ambika Shahu; Sonja Dorfbauer; Philipp Wintersberger; Florian Michahelles

doi:10.1007/978-3-031-42286-7_33

Skillab - A Multimodal Augmented Reality Environment for Learning Manual Tasks

Ambika Shahu, Sonja Dorfbauer, Philipp Wintersberger, Florian Michahelles

Publikation: Beitrag in Buch/Bericht/Tagungsband › Konferenzbeitrag › Begutachtung

Abstract

The paper investigates the usage of AR-based systems in teaching manual skills. We propose Skillab, a novel AR-based scaffolding system. It aids in the learning of manual work and functions as a multimodal immersive tool for feedback, including muscle actuation. As our initial investigation, we made a floor lamination tutorial. We evaluated our system’s performance and user experience in comparison to traditional paper instructions. With 20 participants, we conducted a between-group user study and obtained both qualitative and quantitative data. In terms of task performance, learnability, and overall user experience, Skillab significantly outperformed conventional paper instructions. In contrast to learning from paper instructions, Skillab training demonstrated a significant improvement in the systematic rating on the quality of the performed task. We believe that by demonstrating the potential of immersive multi-modal feedback technology for skill-building, researchers would be motivated to explore this area further.

Originalsprache	Englisch
Titel	Human-Computer Interaction – INTERACT 2023 - 19th IFIP TC13 International Conference, Proceedings
Redakteure/-innen	José Abdelnour Nocera, Marta Kristín Lárusdóttir, Helen Petrie, Antonio Piccinno, Marco Winckler
Herausgeber (Verlag)	Springer
Seiten	588-607
Seitenumfang	20
ISBN (Print)	9783031422850
DOIs	https://doi.org/10.1007/978-3-031-42286-7_33
Publikationsstatus	Veröffentlicht - 2023
Veranstaltung	19th IFIP TC 13 International Conference on Human-Computer Interaction, INTERACT 2023 - York, Großbritannien/Vereinigtes Königreich Dauer: 28 Aug. 2023 → 1 Sep. 2023

Publikationsreihe

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band	14144 LNCS
ISSN (Print)	0302-9743
ISSN (elektronisch)	1611-3349

Konferenz

Konferenz	19th IFIP TC 13 International Conference on Human-Computer Interaction, INTERACT 2023
Land/Gebiet	Großbritannien/Vereinigtes Königreich
Ort	York
Zeitraum	28.08.2023 → 01.09.2023

UN SDGs

Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung

Zugriff auf Dokument

10.1007/978-3-031-42286-7_33

Andere Dateien und Links

Link zur Publikation in Scopus

Zitieren

Shahu, A., Dorfbauer, S., Wintersberger, P., & Michahelles, F. (2023). Skillab - A Multimodal Augmented Reality Environment for Learning Manual Tasks. in J. Abdelnour Nocera, M. Kristín Lárusdóttir, H. Petrie, A. Piccinno, & M. Winckler (Hrsg.), Human-Computer Interaction – INTERACT 2023 - 19th IFIP TC13 International Conference, Proceedings (S. 588-607). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 14144 LNCS). Springer. https://doi.org/10.1007/978-3-031-42286-7_33

Shahu, Ambika ; Dorfbauer, Sonja ; Wintersberger, Philipp et al. / Skillab - A Multimodal Augmented Reality Environment for Learning Manual Tasks. Human-Computer Interaction – INTERACT 2023 - 19th IFIP TC13 International Conference, Proceedings. Hrsg. / José Abdelnour Nocera ; Marta Kristín Lárusdóttir ; Helen Petrie ; Antonio Piccinno ; Marco Winckler. Springer, 2023. S. 588-607 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "The paper investigates the usage of AR-based systems in teaching manual skills. We propose Skillab, a novel AR-based scaffolding system. It aids in the learning of manual work and functions as a multimodal immersive tool for feedback, including muscle actuation. As our initial investigation, we made a floor lamination tutorial. We evaluated our system{\textquoteright}s performance and user experience in comparison to traditional paper instructions. With 20 participants, we conducted a between-group user study and obtained both qualitative and quantitative data. In terms of task performance, learnability, and overall user experience, Skillab significantly outperformed conventional paper instructions. In contrast to learning from paper instructions, Skillab training demonstrated a significant improvement in the systematic rating on the quality of the performed task. We believe that by demonstrating the potential of immersive multi-modal feedback technology for skill-building, researchers would be motivated to explore this area further.",

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author = "Ambika Shahu and Sonja Dorfbauer and Philipp Wintersberger and Florian Michahelles",

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Shahu, A, Dorfbauer, S, Wintersberger, P & Michahelles, F 2023, Skillab - A Multimodal Augmented Reality Environment for Learning Manual Tasks. in J Abdelnour Nocera, M Kristín Lárusdóttir, H Petrie, A Piccinno & M Winckler (Hrsg.), Human-Computer Interaction – INTERACT 2023 - 19th IFIP TC13 International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bd. 14144 LNCS, Springer, S. 588-607, 19th IFIP TC 13 International Conference on Human-Computer Interaction, INTERACT 2023, York, Großbritannien/Vereinigtes Königreich, 28.08.2023. https://doi.org/10.1007/978-3-031-42286-7_33

Skillab - A Multimodal Augmented Reality Environment for Learning Manual Tasks. / Shahu, Ambika; Dorfbauer, Sonja; Wintersberger, Philipp et al.
Human-Computer Interaction – INTERACT 2023 - 19th IFIP TC13 International Conference, Proceedings. Hrsg. / José Abdelnour Nocera; Marta Kristín Lárusdóttir; Helen Petrie; Antonio Piccinno; Marco Winckler. Springer, 2023. S. 588-607 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 14144 LNCS).

Publikation: Beitrag in Buch/Bericht/Tagungsband › Konferenzbeitrag › Begutachtung

TY - GEN

T1 - Skillab - A Multimodal Augmented Reality Environment for Learning Manual Tasks

AU - Shahu, Ambika

AU - Dorfbauer, Sonja

AU - Wintersberger, Philipp

AU - Michahelles, Florian

PY - 2023

Y1 - 2023

N2 - The paper investigates the usage of AR-based systems in teaching manual skills. We propose Skillab, a novel AR-based scaffolding system. It aids in the learning of manual work and functions as a multimodal immersive tool for feedback, including muscle actuation. As our initial investigation, we made a floor lamination tutorial. We evaluated our system’s performance and user experience in comparison to traditional paper instructions. With 20 participants, we conducted a between-group user study and obtained both qualitative and quantitative data. In terms of task performance, learnability, and overall user experience, Skillab significantly outperformed conventional paper instructions. In contrast to learning from paper instructions, Skillab training demonstrated a significant improvement in the systematic rating on the quality of the performed task. We believe that by demonstrating the potential of immersive multi-modal feedback technology for skill-building, researchers would be motivated to explore this area further.

AB - The paper investigates the usage of AR-based systems in teaching manual skills. We propose Skillab, a novel AR-based scaffolding system. It aids in the learning of manual work and functions as a multimodal immersive tool for feedback, including muscle actuation. As our initial investigation, we made a floor lamination tutorial. We evaluated our system’s performance and user experience in comparison to traditional paper instructions. With 20 participants, we conducted a between-group user study and obtained both qualitative and quantitative data. In terms of task performance, learnability, and overall user experience, Skillab significantly outperformed conventional paper instructions. In contrast to learning from paper instructions, Skillab training demonstrated a significant improvement in the systematic rating on the quality of the performed task. We believe that by demonstrating the potential of immersive multi-modal feedback technology for skill-building, researchers would be motivated to explore this area further.

KW - Augmented Reality

KW - Immersiveness

KW - Muscle Actuation

KW - Skill Building

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U2 - 10.1007/978-3-031-42286-7_33

DO - 10.1007/978-3-031-42286-7_33

M3 - Conference contribution

AN - SCOPUS:85173057545

SN - 9783031422850

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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EP - 607

BT - Human-Computer Interaction – INTERACT 2023 - 19th IFIP TC13 International Conference, Proceedings

A2 - Abdelnour Nocera, José

A2 - Kristín Lárusdóttir, Marta

A2 - Petrie, Helen

A2 - Piccinno, Antonio

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PB - Springer

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Y2 - 28 August 2023 through 1 September 2023

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Shahu A, Dorfbauer S, Wintersberger P, Michahelles F. Skillab - A Multimodal Augmented Reality Environment for Learning Manual Tasks. in Abdelnour Nocera J, Kristín Lárusdóttir M, Petrie H, Piccinno A, Winckler M, Hrsg., Human-Computer Interaction – INTERACT 2023 - 19th IFIP TC13 International Conference, Proceedings. Springer. 2023. S. 588-607. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-42286-7_33