Forming a method for the integral estimation of interface quality in automated systems based on the quantitative and qualitative indicators

Authors

DOI:

https://doi.org/10.15587/1729-4061.2020.210720

Keywords:

software interface, generalized estimation, Euclidean norms, quantitative and qualitative attributes, spatial-planar trend

Abstract

Informatization is considered an integral part of the functioning of the present-day society, which changes the nature of human-computer interaction and interface. It was substantiated that the interface quality determines the success of software marketing. It was shown that quality is estimated by both quantitative and qualitative indicators. Their calculation is complicated because of the lack of an analytical model of usability. Two Euclidean norms in the form of the root mean square value and the largest value of the modulus of the set of attribute values were proposed for continuous factor attributes. The problem was reduced to a geometric inequality by applying development into the Maclaurin series and a three-level comparator. Expressions of the upper and lower boundaries of the generalized index of interface quality represented through a set of attribute estimates were obtained. Expressions of the maximum possible absolute and relative errors represented by the method of recurrent approximation through the first and second derivative of the trend were substantiated. Representation of data in a plane with one common axis turned by a certain angle was applied which enabled fast viewing of all planes. It was shown that when all attributes have a quantitative dimension, it is sufficient to apply one norm to estimate the generalized index. However, in the case of quantitative and qualitative estimations, consecutive application of norms for the root mean square and the maximum possible value of the module solves the problem of comprehensive generalized estimation of interface quality. Experimental study of estimation of the generalized quality of the user interfaces for the MedInfoService medical information system which covers automation of curative treatment processes in outpatient clinics and hospitals was presented.

Author Biographies

Alexander Trunov, Petro Mohyla Black Sea National University 68 Desantnykiv str., 10, Mykolaiv, Ukraine, 54003

Doctor of Technical Science, Professor, Head of Department

Department of Automation and Computer-Integrated Technologies

Vitalii Koshovyi, Petro Mohyla Black Sea National University 68 Desantnykiv str., 10, Mykolaiv, Ukraine, 54003

Senior Lecturer

Department of Intelligent Information Systems

References

  1. Wixon, D., Wilson, C. (1997). The Usability Engineering Framework for Product Design and Evaluation. Handbook of Human-Computer Interaction, 653–688. doi: https://doi.org/10.1016/b978-044481862-1.50093-5
  2. ISO 9241-210:2019(en) Ergonomics of human-system interaction – Part 210: Human-centred design for interactive systems. Available at: https://www.iso.org/obp/ui/#iso:std:iso:9241:-210:ed-2:v1:en
  3. ISO 9241-112:2017(en) Ergonomics of human-system interaction – Part 112: Principles for the presentation of information. Available at: https://www.iso.org/obp/ui/#iso:std:iso:9241:-112:ed-1:v1:en
  4. Mandel, T. (2001). Razrabotka pol'zovatel'skogo interfeysa. Moscow: DMK Press, 416.
  5. Unger, R., Chendler, K. (2011). Dizayn: Prakticheskoe rukovodstvo po testirovaniyu opyta vzaimodeystviya. Sankt-Peterburg: Simvol-Plyus, 336.
  6. Scriven, M. B. (1967). The methodology of evaluation. Perspectives of Curriculum Evaluation. Chicago, 39–83.
  7. Adelman, L., Riedel, S. L. (1997). Handbook for Evaluating Knowledge-Based Systems. Springer. doi: https://doi.org/10.1007/978-1-4615-6171-2
  8. Hix, D., Hartson, H. R. (1993). Developing user interfaces: Ensuring usability through product and process. John Wiley & Sons.
  9. Nielsen, J., Molich, R. (1990). Heuristic evaluation of user interfaces. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems Empowering People - CHI ’90. doi: https://doi.org/10.1145/97243.97281
  10. Whitefield, A., Wilson, F., Dowell, J. (1991). A framework for human factors evaluation. Behaviour & Information Technology, 10 (1), 65–79. doi: https://doi.org/10.1080/01449299108924272
  11. Nielsen, J., Mack, R. (1994). Usability Inspection Methods. John Wiley & Sons, Inc., 337.
  12. Nielsen, J. (1993). Usability Engineering. Morgan Kaufmann, 362. doi: https://doi.org/10.1016/c2009-0-21512-1
  13. Dumas, J. S., Redish, J. (1993). A Practical Guide to Usability Testing. Norwood: Ablex, 367.
  14. Nielsen, J., Mack, R. (Eds.) (1994). Usability Inspection Methods. John Wiley and Sons, 448.
  15. Wharton, C., Rieman, J., Lewis, C., Polson, P. (1994). The cognitive walkthrough method: a practitioner's guide: Usability Inspection Methods. Wiley, 105–140.
  16. Ines, G., Makram, S., Mabrouka, C., Mourad, A. (2017). Evaluation of Mobile Interfaces as an Optimization Problem. Procedia Computer Science, 112, 235–248. doi: https://doi.org/10.1016/j.procs.2017.08.234
  17. Wong, C. Y., Khong, C. W., Chu, K. (2012). Interface Design Practice and Education Towards Mobile Apps Development. Procedia - Social and Behavioral Sciences, 51, 698–702. doi: https://doi.org/10.1016/j.sbspro.2012.08.227
  18. Díaz-Bossini, J.-M., Moreno, L. (2014). Accessibility to Mobile Interfaces for Older People. Procedia Computer Science, 27, 57–66. doi: https://doi.org/10.1016/j.procs.2014.02.008
  19. Zhitnikov, V. P., Sheryhalina, N. M. (1999). Otsenka dostovernosti chislennyh rezul'tatov pri nalichii neskol'kih metodov resheniya zadachi. Vychislitel'nye tehnologii, 4 (6), 77–87.
  20. Jason, B., Calitz, A., Greyling, J. (2010). The evaluation of an adaptive user interface model. Proceedings of the 2010 Annual Research Conference of the South African Institute of Computer Scientists and Information Technologists on - SAICSIT ’10. doi: https://doi.org/10.1145/1899503.1899518
  21. Kovalchuk, A. M., Levytskyi, V. H. (2002). Rozrobka adaptyvnoho interfeisu korystuvacha prohramnoi systemy chyselnoho analizu matematychnykh zadach. Visnyk ZhITI, 20, 111–119.
  22. Bias, R. (1994). The Pluralistic Usability Walkthrough: Coordinated Empathies. Usability Inspection Methods. John Wiley.
  23. Petrov, K. E., Kryuchkovskiy, V. V. (2009). Komparatornaya strukturno-parametricheskaya identifikatsiya modeley skalyarnogo mnogofaktornogo otsenivaniya. Kherson: Oldi-plyus, 294.
  24. Trunov, A., Beglytsia, V. (2019). Synthesis of a trend’s integral estimate based on a totality of indicators for a time series data. Eastern-European Journal of Enterprise Technologies, 2 (4 (98)), 48–56. doi: https://doi.org/10.15587/1729-4061.2019.163922
  25. Trunov, A. (2015). An adequacy criterion in evaluating the effectiveness of a model design process. Eastern-European Journal of Enterprise Technologies, 1 (4 (73)), 36–41. doi: https://doi.org/10.15587/1729-4061.2015.37204
  26. Trunov, A. (2017). Recurrent Approximation in the Tasks of the Neural Network Synthesis for the Control of Process of Phototherapy. computer systems for healthcare and medicine, 213–248.
  27. Shchelkalin, V. (2015). A systematic approach to the synthesis of forecasting mathematical models for interrelated non-stationary time series. Eastern-European Journal of Enterprise Technologies, 2 (4 (74)), 21–35. doi: https://doi.org/10.15587/1729-4061.2015.40065

Downloads

Published

2020-08-31

How to Cite

Trunov, A., & Koshovyi, V. (2020). Forming a method for the integral estimation of interface quality in automated systems based on the quantitative and qualitative indicators. Eastern-European Journal of Enterprise Technologies, 4(4 (106), 47–53. https://doi.org/10.15587/1729-4061.2020.210720

Issue

Section

Mathematics and Cybernetics - applied aspects