Logo PTI Logo FedCSIS

Proceedings of the 17th Conference on Computer Science and Intelligence Systems

Annals of Computer Science and Information Systems, Volume 30

User Experience and Multimodal Usability for Navigation Systems

,

DOI: http://dx.doi.org/10.15439/2022F252

Citation: Proceedings of the 17th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 30, pages 213216 ()

Full text

Abstract. User experience as a concept of human-computer interaction is a crucial concept in the evaluation of systems and applications, particularly when considering that as a field it focuses on issues such as usability, cognitive load, affective experiences, mental demand, efficiency. Every new generation of navigational systems provides new features and extended functionality, which has additional functions that can oftentimes confuse on the primary information of the system's functionality. The conducted experiment analyses and observes available navigation systems such as Garmin Drive 50 and/or TomTom, which are available and with certain advantages on features, although not as widely used as the most traditional available Maps. The paper presents the selected aspects regarding the implementation, design, environment, recruitment, tests and evaluation of navigation systems.

References

  1. P. Zalewski and B. Muczynski, Extended Framework for Usability Testing in e-Navigation Systems, TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 10, pp. 43–48, 2016.
  2. G. Papatzanis, Evaluating usability evaluation methods for location-aware interactive systems in contextually rich environment, https://qmro.qmul.ac.uk/xmlui/handle/123456789/1275, 2011.
  3. R.L. Charles and J. Nixon, Measuring mental workload using physiological measures: A systematic review, Applied Ergonomics, Vol. 74, pp. 221–232, 2019.
  4. C. Marchand, J.B. De Graaf and N. Jarrasse, Measuring mental workload in assistive wearable devices: a review, J NeuroEngineering Rehabil, Vol 18(10), pp. 160, 2021.
  5. C.M. Barnum, Preparing for usability testing, in Usability Testing Essentials, Ed. Morgan Kaufmann, 2nd edition, 2021.
  6. P. Laubheimer, Beyond the NPS: Measuring Perceived Usability with the SUS, NASA-TLX, and the Single Ease Question After Tasks and Usability Tests, Nielsen Norman Group, https://www.nngroup.com/articles/measuring-perceived-usability/, 2018.
  7. A.J. Lazard, J.S.B. Brennen and S.P. Belina, App Designs and Interactive Features to Increase mHealth Adoption: User Expectation Survey and Experiment, JMIR Mhealth Uhealth, Vol. 9(11), pp. e29815, 2021.
  8. R. Minelli, A. Mocci and M. Lanza, Measuring Navigation Efficiency in the IDE, 7th International Workshop on Empirical Software Engineering in Practice (IWESEP), pp. 1–6, 2016.
  9. M.H. Phan, J.R. Keebler and B.S. Chaparro, The Development and Validation of the Game User Experience Satisfaction Scale (GUESS), Human Factors, Vol. 58(8), pp. 1217–1247, 2021.
  10. J. Sauro, Measuring Usability with the System Usability Scale (SUS), MeasuringU, 2011.
  11. S. Radmard, A.J. Moon and E.A. Croft, Interface design and usability analysis for a robotic telepresence platform, Proceedings of 24th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), pp. 511–516, 2015.
  12. M. Schrepp, A. Hinderks and J. Thomaschewski, User Experience mit Fragebögen evaluieren – Tipps und Tricks für Datenerhebung, Auswertung und Präsentation der Ergebnisse, UP 2016, Gesellschaft für Informatik e.V. und die German UPA e.V., 2016.
  13. K. Tcha-Tokey, O. Christmann, E. Loup-Escande and S. Richir, Proposition and Validation of a Questionnaire to Measure the User Experience in Immersive Virtual Environments, IJVR, Vol. 16(1), 2016.
  14. B. Borowska, Learning Competitive Swarm Optimization, Entropy, Vol. 24(2), 283, MDPI, ISSN 1099-4300, pp. 1–17, 2022.
  15. T. Galaj, F. Pietrusiak, M. Galewski, R. Ledzion and A. Wojciechowski, Hybrid Integration Method for Sunlight Atmospheric Scattering, IEEE Access, Vol. 9, Publisher IEEE, ISSN 2169-3536, pp. 40681–40694, 2021.
  16. S. Zakrzewski, B. Stasiak, T. Klepaczka and A. Wojciechowski, VR-oriented EEG signal classification of motor imagery tasks, Human Technology, Vol 18 (1), ISSN 1795-6889, pp. 29–44, 2022.
  17. F. Paas, J. E. Tuovinen, H. Tabbers and P. W. M. Van Gerven, Cognitive Load Measurement as a Means to Advance Cognitive Load Theory, Educational Psychologist, vol. 38(1), pp. 63–71, Jan. 2003.
  18. K. Whitenton, Minimize Cognitive Load to Maximize Usability, Nielsen Norman Group. https://www.nngroup.com/articles/minimize-cognitive-load/ (accessed Jul. 14, 2022).