How’s Your Sewing? Investigating Metrics to Automatically Assess Sewing Expertise
Authors: 
Marcel Lahaye, 
Ricarda Rahm, Andreas Dymek, Adrian Wagner, Judith Ernstberger, 
Jan BorchersAuthors Info & Claims
Marcel Lahaye, Ricarda Rahm, Andreas Dymek, Adrian Wagner, Judith Ernstberger, Jan BorchersAuthors Info & ClaimsArticle No.: 190, Pages 1 - 7
Abstract
Makers must regularly assess their expertise when planning projects or selecting tutorials. However, personal bias makes this assessment prone to error, potentially leading to frustration, loss of materials, and discouragement. Additionally, hobbyists have limited feedback possibilities to refine their skills, unlike, for example, apprentice artisans who receive continuous instructor feedback. To address these issues, automated expertise assessment systems could help makers assess their skills and progress. However, such systems require assessment metrics, which have been studied little in the maker context so far. We derived such metrics for sewing from semi-structured interviews with ten sewing-related instructors about their evaluation process. Additionally, we showed them a sewn object and asked them to assess the creator’s expertise. From our findings, we derive criteria to use in future automated sewing expertise assessment systems. For one criterion, seam allowance, we present a functional demonstrator that automatically assesses related measurements.
Supplemental Material
- Download
- 8.97 MB
- Transcript
- Download
- 38.82 MB
- Transcript
References
[1]
Michelle Annett, Tovi Grossman, Daniel Wigdor, and George Fitzmaurice. 2019. Exploring and Understanding the Role of Workshop Environments in Personal Fabrication Processes. ACM Transactions on Computer-Human Interaction 26, 2, Article 10 (mar 2019), 43 pages. https://doi.org/10.1145/3301420
[2]
Christiane Attig, Ester Then, and Josef F. Krems. 2019. Show Me How You Click, and I’ll Tell You What You Can: Predicting User Competence and Performance by Mouse Interaction Parameters. In Intelligent Human Systems Integration 2019, Waldemar Karwowski and Tareq Ahram (Eds.). Springer International Publishing, Cham, 801–806.
[3]
Marc Bächlin, Kilian Förster, and Gerhard Tröster. 2009. SwimMaster: A Wearable Assistant for Swimmer. In Proceedings of the 11th International Conference on Ubiquitous Computing(UbiComp ’09). Association for Computing Machinery, New York, NY, USA, 215–224. https://doi.org/10.1145/1620545.1620578
[4]
P.J. Besl and Neil D. McKay. 1992. A Method for Registration of 3-D Shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence 14, 2 (1992), 239–256. https://doi.org/10.1109/34.121791
[5]
David Buckley, Ke Chen, and Joshua Knowles. 2017. Rapid Skill Capture in a First-Person Shooter. IEEE Transactions on Computational Intelligence and AI in Games 9 (2017), 63–75. https://doi.org/10.1109/TCIAIG.2015.2494849
[6]
David N. Chin. 1989. KNOME: Modeling What the User Knows in UC. In User Models in Dialog Systems, Alfred Kobsa and Wolfgang Wahlster (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 74–107.
[7]
Victoria Clarke and Virginia Braun. 2017. Thematic Analysis. The Journal of Positive Psychology 12, 3 (2017), 297–298. https://doi.org/10.1080/17439760.2016.1262613 arXiv:https://doi.org/10.1080/17439760.2016.1262613
[8]
Michel C. Desmarais and Jiming Liu. 1993. Exploring the Applications of User-Expertise Assessment for Intelligent Interfaces. In Proceedings of the INTERACT ’93 and CHI ’93 Conference on Human Factors in Computing Systems(CHI ’93). Association for Computing Machinery, New York, NY, USA, 308–313. https://doi.org/10.1145/169059.169243
[9]
Arin Ghazarian and S Majid Noorhosseini. 2010. Automatic detection of users’ skill levels using high-frequency user interface events. User Modeling and User-Adapted Interaction 20 (2010), 109–146.
[10]
Jun Gong, Fraser Anderson, George Fitzmaurice, and Tovi Grossman. 2019. Instrumenting and Analyzing Fabrication Activities, Users, and Expertise. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems(CHI ’19). Association for Computing Machinery, New York, NY, USA, 1–14. https://doi.org/10.1145/3290605.3300554
[11]
Jodi S Goodman. 1998. The Interactive Effects of Task and External Feedback on Practice Performance and Learning. Organizational Behavior and Human Decision Processes 76, 3 (1998), 223–252.
[12]
Robert D Grober. 2010. An Accelerometer Based Instrumentation of the Golf Club: Measurement and Signal Analysis.
[13]
Tovi Grossman and George Fitzmaurice. 2015. An Investigation of Metrics for the In Situ Detection of Software Expertise. Human–Computer Interaction 30 (2015), 64–102. https://doi.org/10.1080/07370024.2014.881668
[14]
Pamela J Hinds. 1999. The Curse of Expertise: The Effects of Expertise and Debiasing Methods on Predictions of Novice Performance. Journal of Experimental Psychology: Applied 5 (1999), 205.
[15]
Pamela J Hinds, Michael Patterson, and Jeffrey Pfeffer. 2001. Bothered by Abstraction: The Effect of Expertise on Knowledge Transfer and Subsequent Novice Performance. Journal of Applied Psychology 86 (2001), 1232.
[16]
Amy Hurst, Scott E. Hudson, and Jennifer Mankoff. 2007. Dynamic Detection of Novice vs. Skilled Use Without a Task Model. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems(CHI ’07). Association for Computing Machinery, New York, NY, USA, 271–280. https://doi.org/10.1145/1240624.1240669
[17]
Aftab Khan, Sebastian Mellor, Eugen Berlin, Robin Thompson, Roisin McNaney, Patrick Olivier, and Thomas Plötz. 2015. Beyond Activity Recognition: Skill Assessment from Accelerometer Data. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing(UbiComp ’15). Association for Computing Machinery, New York, NY, USA, 1155–1166. https://doi.org/10.1145/2750858.2807534
[18]
Stacey Kuznetsov and Eric Paulos. 2010. Rise of the Expert Amateur: DIY Projects, Communities, and Cultures. In Proceedings of the 6th Nordic Conference on Human-Computer Interaction: Extending Boundaries(NordiCHI ’10). Association for Computing Machinery, New York, NY, USA, 295–304. https://doi.org/10.1145/1868914.1868950
[19]
Cassim Ladha, Nils Y. Hammerla, Patrick Olivier, and Thomas Plötz. 2013. ClimbAX: Skill Assessment for Climbing Enthusiasts. In Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing(UbiComp ’13). Association for Computing Machinery, New York, NY, USA, 235–244. https://doi.org/10.1145/2493432.2493492
[20]
Mackenzie Leake, Kathryn Jin, Abe Davis, and Stefanie Mueller. 2023. InStitches: Augmenting Sewing Patterns with Personalized Material-Efficient Practice. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Hamburg, Germany) (CHI ’23). Association for Computing Machinery, New York, NY, USA, Article 267, 14 pages. https://doi.org/10.1145/3544548.3581499
[21]
Edwin A Locke and Gary P Latham. 2002. Building a Practically Useful Theory of Goal Setting and Task Motivation: A 35-Year Odyssey. American Psychologist 57 (2002), 705.
[22]
Richard E Mayer and Roxana Moreno. 2003. Nine Ways to Reduce Cognitive Load in Multimedia Leaming. Educational Psychologist 38 (2003), 43–52.
[23]
Richard E Nisbett and Timothy D Wilson. 1977. Telling More Than We Can Know: Verbal Reports on Mental Processes. Psychological Review 84 (1977), 231.
[24]
Donald A Norman. 2013. The Design of Everyday Things: Revised and expanded edition. Basic Books, New York City, USA.
[25]
Fred Paas, Alexander Renkl, and John Sweller. 2003. Cognitive Load Theory and Instructional Design: Recent Developments. Educational Psychologist 38 (2003), 1–4.
[26]
C Richards, J Rosen, B Hannaford, C Pellegrini, and M Sinanan. 2000. Skills evaluation in minimally invasive surgery using force/torque signatures. Surgical Endoscopy 14 (2000), 791–798.
[27]
J. Rosen, B. Hannaford, C.G. Richards, and M.N. Sinanan. 2001. Markov Modeling of Minimally Invasive Surgery Based on Tool/Tissue Interaction and Force/Torque Signatures for Evaluating Surgical Skills. IEEE Transactions on Biomedical Engineering 48 (2001), 579–591. https://doi.org/10.1109/10.918597
[28]
S. Rusinkiewicz and M. Levoy. 2001. Efficient Variants of the ICP algorithm. In Proceedings Third International Conference on 3-D Digital Imaging and Modeling. IEEE, Piscataway, USA, 145–152. https://doi.org/10.1109/IM.2001.924423
[29]
Shahed Anzarus Sabab, Adnan Khan, Parmit K. Chilana, Joanna McGrenere, and Andrea Bunt. 2020. An Automated Approach to Assessing an Application Tutorial’s Difficulty. In 2020 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC). IEEE, Piscataway, USA, 1–10. https://doi.org/10.1109/VL/HCC50065.2020.9127271
[30]
Johnny Saldaña. 2013. The Coding Manual for Qualitative Researchers. sage, London.
[31]
Nick Taylor, Ursula Hurley, and Philip Connolly. 2016. Making Community: The Wider Role of Makerspaces in Public Life. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (San Jose, California, USA) (CHI ’16). Association for Computing Machinery, New York, NY, USA, 1415–1425. https://doi.org/10.1145/2858036.2858073
[32]
Cristen Torrey, Elizabeth F. Churchill, and David W. McDonald. 2009. Learning How: The Search for Craft Knowledge on the Internet. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems(CHI ’09). Association for Computing Machinery, New York, NY, USA, 1371–1380. https://doi.org/10.1145/1518701.1518908
[33]
Marco Wolf and Shaun McQuitty. 2011. Understanding the do-it-yourself consumer: DIY motivations and outcomes. AMS Review 1 (2011), 154–170.
[34]
Gabriele Wulf, Charles Shea, and Rebecca Lewthwaite. 2010. Motor skill learning and performance: A review of influential factors. Medical education 44, 1 (2010), 75–84.
[35]
Gabriele Wulf, Charles H Shea, and Sabine Matschiner. 1998. Frequent Feedback Enhances Complex Motor Skill Learning. Journal of Motor Behavior 30, 2 (1998), 180–192.
Index Terms
- How’s Your Sewing? Investigating Metrics to Automatically Assess Sewing Expertise
Recommendations
InStitches: Augmenting Sewing Patterns with Personalized Material-Efficient Practice
CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing SystemsThere is a rapidly growing group of people learning to sew online. Without hands-on instruction, these learners are often left to discover the challenges and pitfalls of sewing through trial and error, which can be a frustrating and wasteful process. We ...
Expertise transfer and complex problems
Special issue: 1969-1999, the 30th anniversaryAcquiring knowledge from a human expert is a major problem when building a knowledge-based system. Aquinas, an expanded version of the Expertise Transfer System (ETS), is a knowledge-acquisition workbench that combines ideas from psychology and ...
Comments
Information & Contributors
Information
Published In
May 2024
4761 pages
ISBN:9798400703317
DOI:10.1145/3613905
Copyright © 2024 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 11 May 2024
Check for updates
Author Tags
Qualifiers
- Work in progress
- Research
- Refereed limited
Conference
Acceptance Rates
Overall Acceptance Rate 6,164 of 23,696 submissions, 26%
Upcoming Conference
CHI 2025
- Sponsor:
- sigchi
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 288Total Downloads
- Downloads (Last 12 months)288
- Downloads (Last 6 weeks)99
Reflects downloads up to 08 Mar 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderFull Text
View this article in Full Text.
Full TextHTML Format
View this article in HTML Format.
HTML Format