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Age-Differentiated Analysis of the Influence of Task Descriptions on Learning Sensorimotor Tasks

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Advances in Ergonomic Design of Systems, Products and Processes

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.

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Notes

  1. 1.

    Compared to (Kuhlenbäumer et al. 2016a), one male participant in AG II was replaced, because he was identified as an outlier in later analyses. An analysis without this participant (59 participants) can be found in (Kuhlenbäumer et al. 2016b).

References

  • Ackermann KF (2010) Alter als Kernaufgabe. Personal 06:12–14

    Google Scholar 

  • Daft RL, Lengel RH (1986) Organizational information requirements, media richness and structural design. Manage Sci 32:554–571

    Article  Google Scholar 

  • de Greiff M (1999) Prognose von Lernkurven in der manuellen und teilmechanisierten Montage. REFA-Nachrichten 6:19–26

    Google Scholar 

  • De Greiff M (2001) Die Prognose von Lernkurven in der manuellen Montage unter besonderer Berücksichtigung der Lernkurven von Grundbewegungen. VDI, Düsseldorf

    Google Scholar 

  • de Jong JR (1960) Die Auswirkungen zunehmender Fertigkeiten. REFA Nachrichten 13(1):155–161

    Google Scholar 

  • 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

    Google Scholar 

  • Field A (2009) Discovering statistics using SPSS, 3rd edn. Sage, London

    MATH  Google Scholar 

  • 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

    Google Scholar 

  • Fleishman EA, Ellison GD (1962) A factor analysis of fine manipulative performance. J Appl Psychol 46:96–105

    Article  Google Scholar 

  • Görlich Y, Schuler H (2007) Arbeitsprobe zur berufsbezogenen Intelligenz. Technische und handwerkliche Tätigkeiten; AZUBI-TH. Hogrefe, Göttingen, Vienna

    Google Scholar 

  • Hamster W (1980) Die Motorische Leistungsserie – MLS. Handanweisung. Dr. G. Schuhfried, Mödling

    Google Scholar 

  • 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

    Google Scholar 

  • Hieber WL (1991) Lern- und Erfahrungskurveneffekte und ihre Bestimmung in der flexibel automatisierten Produktion. Vahlen, Munich

    Google Scholar 

  • Jeske T (2013) Entwicklung einer Methode zur Prognose der Anlernzeit sensumotorischer Tätigkeiten. In: Schlick CM (ed) Industrial engineering and ergonomics. Shaker, Aachen

    Google Scholar 

  • 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

    Google Scholar 

  • 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

    Chapter  Google Scholar 

  • 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

    Google Scholar 

  • 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

    Google Scholar 

  • 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

    Google Scholar 

  • Laarmann A (2005) Lerneffekte in der Produktion. Deutscher Universitäts-Verlag, Wiesbaden

    Book  Google Scholar 

  • Liepmann D (2007) Intelligenz-Struktur-Test 2000 R. I-S-T 2000 R, 2nd edn. Hogrefe, Göttingen

    Google Scholar 

  • 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

    Article  Google Scholar 

  • Rohmert W, Rutenfranz J, Ulrich E (1974) Das Erlernen sensumotorischer Fertigkeiten. Institut für Arbeitswissenschaft, TU Darmstadt. Europäische Verlagsanstalt, Frankfurt a.M.

    Google Scholar 

  • Schoppe KJ (1974) Das MLS-Gerät: ein neuer Testapparat zur Messung feinmotorischer Leistungen. Diagnostica 20:43–47

    Google Scholar 

  • Stanić S (2010) Fahrzeugmontage – Herausforderungen für den demografischen Wandel. In: Sträter O, Frieling E (eds) Schriftenreihe Personal- und Organisationsentwicklung, 8

    Google Scholar 

  • Wright TP (1936) Factors affecting the cost of airplanes. J Aeronaut Sci 3(4):122–128

    Article  Google Scholar 

  • Yaber MY (2011) Learning curves: theory, models, and applications. CRC Press, Boca Raton, FL

    Google Scholar 

  • Yelle LE (1979) The learning curve: historical review and comprehensive survey. Decis Sci 10(2):302–328

    Article  Google Scholar 

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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.

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Correspondence to Francoise Kuhlenbäumer .

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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

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  • DOI: https://doi.org/10.1007/978-3-662-53305-5_12

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