Abstract
This paper presents a study into the validity of a self-developed method to predict the learning time of sensorimotor tasks that was originally developed for young adults (age group AG I) for persons aged between 52 and 67 (age group AG II). For this purpose, a laboratory study was conducted with an age-differentiated sample of 60 participants. The participants’ task was to repeatedly assemble a carburetor with the help of one of three task descriptions, which differed in regard to format (textual, text- & figure-based, animated). Execution times and numbers of assembly errors were measured to evaluate human performance. Additionally, the cumulative viewing time of the task description was measured in each trial to analyze participants’ usage of the task description. Data analysis with respect to the age group and the format of the task descriptions indicates significant effects (α = 0.05). Thus, participants who had the support of a textual task description achieved greater performance improvement than participants who used the animated task description. Concerning the age group, participants in AG I show better performance and lower observation times concerning to participants in AG II. Furthermore, nonlinear curve fittings were carry out and root mean square errors calculated in order to investigate the accuracy of the prediction method. The results show that the prediction method is less accurate for older adults.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ackermann KF (2010) Alter als Kernaufgabe. Personal 06:12–14
Daft RL, Lengel RH (1986) Organizational information requirements, media richness and structural design. Manage Sci 32:554–571
de Greiff M (1999) Prognose von Lernkurven in der manuellen und teilmechanisierten Montage. REFA-Nachrichten 6:19–26
De Greiff M (2001) Die Prognose von Lernkurven in der manuellen Montage unter besonderer Berücksichtigung der Lernkurven von Grundbewegungen. VDI, Düsseldorf
de Jong JR (1960) Die Auswirkungen zunehmender Fertigkeiten. REFA Nachrichten 13(1):155–161
Dombrowski U, Mielke T (2012) Entwicklungspfade zur Lösung des Demografieproblems in Deutschland. In: Müller E (ed) Demografischer Wandel: Herausforderungen für die Arbeits- und Betriebsorganisation der Zukunft. Gito mbH Verlag, Berlin, pp 55–80
Field A (2009) Discovering statistics using SPSS, 3rd edn. Sage, London
Fleishman EA (1962) The description and prediction of perceptual motor skill learning. In: Glaser R (ed) Training research and education. University of Pittsburgh Press, Pittsburgh, PA, pp 137–175
Fleishman EA, Ellison GD (1962) A factor analysis of fine manipulative performance. J Appl Psychol 46:96–105
Görlich Y, Schuler H (2007) Arbeitsprobe zur berufsbezogenen Intelligenz. Technische und handwerkliche Tätigkeiten; AZUBI-TH. Hogrefe, Göttingen, Vienna
Hamster W (1980) Die Motorische Leistungsserie – MLS. Handanweisung. Dr. G. Schuhfried, Mödling
Hart S, Staveland LE (1988) Development of NASA-TLX (Task Load Index): results of empirical and theoretical research. In: Hancock PA, Meshkati N (eds) Human mental workload. North-Holland Press, Amsterdam, pp 239–250
Hieber WL (1991) Lern- und Erfahrungskurveneffekte und ihre Bestimmung in der flexibel automatisierten Produktion. Vahlen, Munich
Jeske T (2013) Entwicklung einer Methode zur Prognose der Anlernzeit sensumotorischer Tätigkeiten. In: Schlick CM (ed) Industrial engineering and ergonomics. Shaker, Aachen
Jeske T, Schlick CM (2011) Influence of task complexity on learning times of sensorimotor tasks in assembly systems. In: Spath D, Ilg R, Krause T (eds) Innovation in product and production – conference proceedings. 21st International Conference on Production Research (ICPR 21), Stuttgart, CD-ROM
Jeske T, Schlick CM (2012) A new method for forecasting the learning time of sensorimotor task. In: Trzcieliński S, Karwowski W (eds) Advances in ergonomics in manufacturing. CRC Press, Boca Raton, FL, pp 241–250
Jeske T, Hasenau K, Schlick CM (2011) Influence of task descriptions on learning sensorimotor tasks. In: Göbel M, Christie C, Zschernack S, Todd A, Mattison M (eds) Human factors in organisational design and management – X, vol 1. IEA Press, Santa Monica, CA, pp 343–348
Kuhlenbäumer F, Duckwitz S, Schlick CM (2016a) Altersdifferenzierte Untersuchung zur Prognose der Anlernzeit von sensumotorischen Arbeitsaufgaben. In: Gesellschaft für Arbeitswissenschaft e.V. (ed) Arbeit in komplexen Systemen – Digital, vernetzt, human?! 62nd Kongress der Gesellschaft für Arbeitswissenschaft of March 2 to 4, 2016. GfA-Press, Dortmund
Kuhlenbäumer F, Duckwitz S, Schlick CM (2016b) Age-differentiated modeling and prediction of the learning time of sensorimotor tasks. In: Schlick CM, Trzcieliński S (eds) Advances in ergonomics of manufacturing: managing the enterprise of the future: Proceedings of the AHFE2016 international conference on human aspects of advanced manufacturing, July 27–31, Walt Disney World R, Florida, USA
Laarmann A (2005) Lerneffekte in der Produktion. Deutscher Universitäts-Verlag, Wiesbaden
Liepmann D (2007) Intelligenz-Struktur-Test 2000 R. I-S-T 2000 R, 2nd edn. Hogrefe, Göttingen
Morrell R, Park DC (1993) The effects of age, illustrations, and task variables on the performance of procedural assembly tasks. Psychol Aging 8(3):389–399
Rohmert W, Rutenfranz J, Ulrich E (1974) Das Erlernen sensumotorischer Fertigkeiten. Institut für Arbeitswissenschaft, TU Darmstadt. Europäische Verlagsanstalt, Frankfurt a.M.
Schoppe KJ (1974) Das MLS-Gerät: ein neuer Testapparat zur Messung feinmotorischer Leistungen. Diagnostica 20:43–47
Stanić S (2010) Fahrzeugmontage – Herausforderungen für den demografischen Wandel. In: Sträter O, Frieling E (eds) Schriftenreihe Personal- und Organisationsentwicklung, 8
Wright TP (1936) Factors affecting the cost of airplanes. J Aeronaut Sci 3(4):122–128
Yaber MY (2011) Learning curves: theory, models, and applications. CRC Press, Boca Raton, FL
Yelle LE (1979) The learning curve: historical review and comprehensive survey. Decis Sci 10(2):302–328
Acknowledgements
This study is part of the research project “Coping with Aging in Manual Assembly Systems: Age-differentiated Analyses and Mathematical Modeling for Predicting the Time Structure of Sensorimotor-skill Acquisition for Assembly in Series Production with Numerous Product Variants” (SCHL 1805/9-1), which is funded by Deutsche Forschungsgemeinschaft.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer-Verlag GmbH Germany
About this paper
Cite this paper
Kuhlenbäumer, F., Przybysz, P., Mütze-Niewöhner, S., Schlick, C.M. (2017). Age-Differentiated Analysis of the Influence of Task Descriptions on Learning Sensorimotor Tasks. In: Schlick, C., et al. Advances in Ergonomic Design of Systems, Products and Processes. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-53305-5_12
Download citation
DOI: https://doi.org/10.1007/978-3-662-53305-5_12
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-53304-8
Online ISBN: 978-3-662-53305-5
eBook Packages: EngineeringEngineering (R0)