A gamified and adaptive learning system for neurodivergent workers in electronic assembling tasks
Open accessAbstract
Learning and work-oriented assistive systems are often designed to fit the workflow of neurotypical workers. Neurodivergent workers and individuals with learning disabilities often present cognitive and sensorimotor characteristics that are better accommodated with personalized learning and working processes. Therefore, we designed an adaptive learning system that combines an augmented interaction space with user-sensitive virtual assistance to support step-by-step guidance for neurodivergent workers in electronic assembling tasks. Gamified learning elements were also included in the interface to provide self-motivation and praise whenever users progress in their learning and work achievements.
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Across HCI studies, there is a tendency to design systems that address perceived neurodivergent behaviours from an external viewpoint without adequately considering internal struggles.
“Across a number of studies [9, 29, 30, 39, 54, 55, 64, 74, 81, 90, 93], there is a noticeable tendency to design systems that address perceived neurodivergent behaviours, often from an external viewpoint, without adequately considering the internal struggles experienced by neurodivergent individuals.”
From Burnout by Design: How Digital Systems Overburden Neurodivergent Students in Higher Education (2025) · cites this paper as [39]
The Introduction and §2.3 describe a system that guides neurodivergent workers through assembly tasks, supporting its use as an example of this kind of HCI design. But §2.3 explicitly considers cognitive overload, frustration, sensory sensitivity, and individual preferences, while §2.4 says neurodivergent workers co-designed its badges. The paper therefore does not support characterizing this system as designed solely from an external viewpoint without adequate consideration of internal experiences. The indexed passages provide section labels but no page numbers. (LLM, conf=0.83)
Experimental — accuracy not yet measuredThere is an emerging body of work that involves neurodivergent adults in knowledge creation such as co-design and acknowledges the importance of neurodivergent perspectives in technology design.
“However, there is an emerging body of work that involves neurodivergent adults in knowledge creation such as co-design and acknowledges the importance of neurodivergent perspectives in technology design [39, 64], such as a 2019 study, which relevantly investigated why existing digital time management tools remain inadequate for ADHD adults [29].”
From Burnout by Design: How Digital Systems Overburden Neurodivergent Students in Higher Education (2025) · cites this paper as [39]
The gap investigated by this work lies at the intersection of HCI work that actively involves neurodivergent subjects and literature investigating neurodivergent individuals in higher education and broad accessibility of universities and their systems.
“The gap investigated by this work lies at the intersection of the mentioned HCI work which actively involves its neurodivergent subjects [21, 29, 39, 64, 64, 93], and the body of literature which investigates the experience of these neurodivergent individuals in higher education [4, 14, 15, 51, 57, 70], as well as work investigatigating the broad accessibility of universities and their systems [3,”
From Burnout by Design: How Digital Systems Overburden Neurodivergent Students in Higher Education (2025) · cites this paper as [39]
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References 13 · Cited by 24
Research works printed but not linked: 11
- Alyssa Alcorn, Helen Pain, Gnanathusharan Rajendran, Tim Smith, Oliver Lemon, Kaska Porayska-Pomsta, Mary Ellen Foster, Katerina Avramides, Christopher Frauenberger, and Sara Bernardini. 2011. Social communication between virtual characters and children with autism. In Proceedings of the 15th international conference on Artificial intelligence in education (AIED'11), Gautam Biswas, Susan Bull, Judy Kay, and Antonija Mitrovic (Eds.). Springer -Verlag, Berlin, Heidelberg, 7 -14.
- Cynthia Putnam and Lorna Chong. 2008. Software and technologies designed for people with autism: what do users want? In Proceedings of the 10th international ACM SIGACCESS conference on Computers and accessibility (Assets '08). ACM, New York, NY, USA, 3-10.
- Ganit Richter, Daphne R. Raban, Sheizaf Rafaeli. 2015. Studying Gamification: The Effects of Rewards and Incentives on Motivation. In: T. Reiners, L. Wood (eds) Gamification in Education and Business. Springer.
- Ian Glover. 2013. Play as You Learn: Gamification as a Technique for Motivating Learners. In Proceedings of EdMedia 2013 -Conference on Educational Media and Technology. AACE, Victoria, Canada.
- Markus Funk, Andreas Bächler, Liane Bächler, Oliver Korn, Christoph Krieger, Thomas Heidenreich, and Albrecht Schmidt. 2015. Comparing projected in-situ feedback at the manual assembly workplace with impaired workers. In Proceedings of the 8th ACM International Conference on PErvasive Technologies Related to Assistive Environments (PETRA '15). ACM, New York, NY, USA, Article 1, 1-8.
- Oliver Korn, Albrecht Schmidt, and Thomas Hörz. 2013. The potentials of in- situ-projection for augmented workplaces in production: a study with impaired persons. In CHI '13 Extended Abstracts on Human Factors in Computing Systems (CHI EA '13). ACM, New York, NY, USA, 979-984.
- Oliver Korn, Markus Funk, and Albrecht Schmidt. 2015. Towards a gamification of industrial production: a comparative study in sheltered work environments. In Proceedings of the 7th ACM SIGCHI Symposium on Engineering Interactive Computing Systems (EICS '15). ACM, New York, NY, USA, 84-93.
- Oliver Korn. 2012. Industrial playgrounds: how gamification helps to enrich work for elderly or impaired persons in production. In Proceedings of the 4th ACM SIGCHI symposium on Engineering interactive computing systems (EICS '12). ACM, New York, NY, USA, 313-316.
- Ramin Yaghoubzadeh, Marcel Kramer, Karola Pitsch, and Stefan Kopp. 2013. Virtual agents as daily assistants for elderly or cognitively impaired people: Studies on acceptance and interaction feasibility. In Proceedings of the International Workshop on Intelligent Virtual Agents (IVA 2013). Lecture Notes in Computer Science, vol 8108, 79-91. Springer, Berlin, Heidelberg.
- Sarah Parsons and Peter Mitchell. 2002. The potential of virtual reality in social skills training for people with autistic spectrum disorders. Journal of Intellectual Disability Research. 46, 5, 430-443.
- Tina R. Goldsmith and Linda A. LeBlanc. 2004. Use of technology in interventions for children with autism. Journal of Early and Intensive Behavior Intervention. 1, 2, 166-178.
- Authors
- Grund, J., Umfahrer, M., Buchweitz, L., Gay, J., Theil, A., & Korn, O.
- Affiliations
- Offenburg University of Applied Sciences (DE)
- Venue
- Proceedings of Mensch und Computer 2020
- Publisher
- ACM
- Published
- 2020-09-06
- Pages
- 491-494
- OpenAlex
- W3090795567
- Cited by
- 24
- References
- 13
- Citations by year
- 2026: 3 · 2025: 7 · 2024: 4 · 2023: 6 · 2022: 3 · 2021: 1
- FWCI
- 3.38
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Mensch und Computer (MuC) (publishedVersion, cc-by-sa)
- Opus-HSO (Offenburg University of Applied Sciences) (submittedVersion)
- Funders
- Bundesministerium für Bildung und Forschung (01PE17001D)
- Topics
- Social Sciences › Human Factors and Ergonomics › Digital Accessibility for Disabilities
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Augmented Reality Applications
- Keywords
- adaptive learning systems, gamification, electronics assembly, assistive technology, personalized learning, virtual assistance, learning disabilities, step-by-step guidance, self-motivation
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