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All Users Are (Not) Equal - The Influence of User Characteristics on Perceived Quality, Modality Choice and Performance

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Proceedings of the Paralinguistic Information and its Integration in Spoken Dialogue Systems Workshop

Abstract

This study investigated if cognitive skills, mood, attitudes and personality traits influence quality perceptions, modality choice (speech vs. touch), and performance. It was shown that attitudes and mood are related to quality perceptions while performance is linked to personality traits. Modality choice is influenced by attitudes and personality. Cognitive abilities had no effect.

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References

  1. Wolters M, Engelbrecht K-P, Gdde F, Möller S, Naumann A, Schleicher R (2010) Making it easier for older people to talk to smart homes: Using help prompts to shape users’ speech. Universal Access in the Information Society, 9(4):311–325

    Article  Google Scholar 

  2. Chalmers PA (2003) The role of cognitive theory in human-computer interface. Computers in Human Behavior 19(5):593–607

    Article  Google Scholar 

  3. Carmichael A (1999) Style guide for the design of interactive television services for elderly viewers. Independent Television Commission, 1: 1–100

    Google Scholar 

  4. Wechsung I, Engelbrecht K-P, Naumann A, Schaffer S, Seebode J, Metze F, Möller S (2009) Predicting the quality of multimodal systems based on judgments of single modalities. In Proc. Interspeech 2009, Brighton, pp 1827–1830

    Google Scholar 

  5. Wechsung I, Naumann A (2009) Evaluating a multimodal remote control: The interplay between user experience and usability. In Proc. IEEE QOMEX 2009, San Diego, pp 19–22

    Google Scholar 

  6. Naumann A, Wechsung I, Hurtienne J (2010) Multimodal interaction: A suitable strategy for including older users? Interacing with Computers, 2010.

    Google Scholar 

  7. Hornbaek K, Law EL (2007) Meta-analysis of correlations among usability measures, In Proc. CHI 2007, pp 617–626

    Google Scholar 

  8. Oviatt SL, Coulston R, Lunsford R (2004) When do we interact multimodally? Cognitive load and multimodal communication patterns. In Proc. ICMI 2004, pp. 129–136

    Google Scholar 

  9. Wechsung I, Engelbrecht K-P, Naumann A,Möller S, Schaffer S, Schleicher R (2010) Investigating modality selection strategies, In: Proc. of IEEE workshop on spoken language technology (SLT 2010), pp 31–36

    Google Scholar 

  10. Chen C, Czerwinski M, Macredie R (2000) Individual differences in virtual environments, Journ of the American Society for Inform. Science, 51(6):499–507

    Google Scholar 

  11. Dillon A,Watson C (1996) User analysis in HCI -the historical lessons from individual differences research. International Journal of Human-Computer Studies 45(6) 619–637

    Article  Google Scholar 

  12. Wolters M, Georgila K, Moore JD, Logie RH, MacPherson SE, Watson M (2009) Reducing working memory load in spoken dialogue systems. Interacing. with Computers, 21(4):276–287

    Article  Google Scholar 

  13. Doolittle PE, Terry KP, Mariano GJ (2009) The effects of working memory capacity on learning and performance in multimedia learning environments. In R. Zheng (Ed.), Cognitive effects of multimedia learning, pp 17–33

    Google Scholar 

  14. Jawahar IM, Elango B (2001) The effect of attitudes, goal setting and selfefficacy on end user performance. Journal of End User Computing, 13(2):40–45

    Article  Google Scholar 

  15. Burnett GE, Ditsikas D (2006) Personality as a criterion for selecting usability testing participants. In In proceedings of IEEE 4th International conference on Information and Communications Technologies

    Google Scholar 

  16. Matilla M, Karjaluoto H, Pento T (2003) Internet banking adoption among mature customers: early majority or laggards? Journal of Services Marketing, 17(5): 514528

    Google Scholar 

  17. Angel A, Hartmann J, Sutcliffe A (2009) The effect of brand on the evaluation of websites. In Proc. INTERACT 09, pp. 638–651

    Google Scholar 

  18. Bless H, Schwarz N, Clore GL, Golisano V, Rabe C, WlkM(1996) Mood and the use of scripts: Does being in a happy mood really lead to mindlessness? Journal of Personality and Social Psychology, 71: 665679

    Google Scholar 

  19. Kahneman D (1999) Objective happiness. In: Kahneman D, Diener E, Schwarz N (Eds.) Well-being: Foundations of hedonic psychology, Russell Sage Foundation, New York, pp 3–25

    Google Scholar 

  20. Schupp J, Gerlitz J-Y (2008) BFI-S: Big Five Inventory-SOEP. Zusammenstellung sozialwissenschaftlicher Items und Skalen [collection of socioscientific items and scales]. GESIS, Bonn

    Google Scholar 

  21. Borkenau P, Ostendorf F (1994) Das NEO Fnf-Faktoren-Inventar (NEO-FFI): Handanweisung [The NEO Five-Factor-Inventory: Manual]. Hogrefe, Gttingen.

    Google Scholar 

  22. Karrer K,Glaser C, Clemens C, Bruder C (2009) Technikaffinitt erfassen der Fragebogen TA-EG [Assessing technical affinity - the questionnaire TA-EG]. In Lichtenstein A, Stel C, Clemens C (Eds) Der Mensch als Mittelpunkt technischer Systeme. 8. Berliner Werkstatt Mensch-Maschine-Systeme, VDI Verlag, Dsseldorf, pp 196–201

    Google Scholar 

  23. Andrews FM, Withey SB, (1976). Social indicators of well-being.Plenum, New York.

    Google Scholar 

  24. Hassenzahl M, Monk A (2010) The inference of perceived usability from beauty. Human-Computer Interaction, 25(3):235–260

    Article  Google Scholar 

  25. Hassenzahl,M(2004) The thing and I: understanding the relationship between user and product. In: Blythe MA, Overbeeke K, Monk AF, and Wright PC (Eds.) Funology: From Usability To Enjoyment, Kluwer Academic, Norwell, pp 31–42

    Google Scholar 

  26. Eilers K, Nachreiner F, Ha¨necke K (1986) Entwicklung und U¨ berpru¨fung einer Skala zur Erfassung subjektiv erlebter Antrengung [Development and evaluation of a scale to assess subjectively perceived effort]. Zeitschrift f¨ır Arbeitswissenschaft, 40: 215224

    Google Scholar 

  27. De Waard D (1996) The measurement of drivers’ mental workload. PhD thesis, University of Groningen.

    Google Scholar 

  28. Tewes U (1991) HAWIE-R. Hamburg-Wechsler-Intelligenztest für Erwachsene [Hamburg-Wechsler-intelligence test for adults, Huber, Bern

    Google Scholar 

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Author information

Authors and Affiliations

  1. Quality and Usability Lab, Deutsche Telekom Laboratories, TU Berlin, Ernst-Reuter-Platz 7, 10587, Berlin, Germany

    Ina Wechsung, Matthias Schulz, Klaus-Peter Engelbrecht, Julia Niemann & Sebastian Möller

Authors
  1. Ina Wechsung
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  2. Matthias Schulz
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  3. Klaus-Peter Engelbrecht
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  4. Julia Niemann
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  5. Sebastian Möller
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Corresponding author

Correspondence to Ina Wechsung .

Editor information

Editors and Affiliations

  1. , Dept. of Languages and Computer Systems, University of Granada, Granada, 18071, Spain

    Ramón López-Cózar Delgado

  2. , Dept. of Computer Science & Engineering, Waseda University, Okubo 3-4-1, Tokyo, 169-8555, Japan

    Tetsunori Kobayashi

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Wechsung, I., Schulz, M., Engelbrecht, KP., Niemann, J., Möller, S. (2011). All Users Are (Not) Equal - The Influence of User Characteristics on Perceived Quality, Modality Choice and Performance. In: Delgado, RC., Kobayashi, T. (eds) Proceedings of the Paralinguistic Information and its Integration in Spoken Dialogue Systems Workshop. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1335-6_19

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  • DOI: https://doi.org/10.1007/978-1-4614-1335-6_19

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-1334-9

  • Online ISBN: 978-1-4614-1335-6

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