Dergiler / Gazi University Journal of Science / 2014 / Cilt: 27 - Sayı: 4

USING OUTPUTS OF NASA-TLX FOR BUILDING A MENTAL WORKLOAD EXPERT SYSTEM

Sayfa
1131–1142
Yayın Tarihi
2014-03-26
DOI
—
🏛️Bu makalenin bibliyografik verileri ve tam metin bağlantısı DergiPark üzerinden sağlanmıştır.
DergiPark Kaydı ↗
✨

Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

In the second phase of the study, output of NASA-TLX is used by AHP (Analytic Hierarchy Process) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solutions) methods to construct an expert system for choosing an executive expert from TEYDEB’s expert pool.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:In this study, we evaluate the effect of demographic factors such as age, gender, marital status, and education level on mental workload of TEYDEB’s (Technology & Innovation Grant Programs Directorate) experts working in basic stages of R&D projects evaluation activities.
📊
Temel Bulgular & Veri:We make statistical analyses to measure the effectiveness of 6 scales used in NASA-TLX for evaluating the subjective mental workload of TEYDEB’s experts.
💡
Sonuç & Katkı:In the second phase of the study, output of NASA-TLX is used by AHP (Analytic Hierarchy Process) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solutions) methods to construct an expert system for choosing an executive expert from TEYDEB’s expert pool.
🔬Tür:Laboratuvar & Saha Deneyi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Mental workload · NASA-TLX · AHP

Abstract

In this study, we evaluate the effect of demographic factors such as age, gender, marital status, and education level on mental workload of TEYDEB’s (Technology & Innovation Grant Programs Directorate) experts working in basic stages of R&D projects evaluation activities. One of the workload measurement techniques, NASA-TLX is chosen since it is the most convenient measurement technique for the experiment groups used in this study. We make statistical analyses to measure the effectiveness of 6 scales used in NASA-TLX for evaluating the subjective mental workload of TEYDEB’s experts. In the second phase of the study, output of NASA-TLX is used by AHP (Analytic Hierarchy Process) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solutions) methods to construct an expert system for choosing an executive expert from TEYDEB’s expert pool.

🔖

Bu Makaleye Atıf Yap

ŞEKER, A., SEKER, A. (2014). USING OUTPUTS OF NASA-TLX FOR BUILDING A MENTAL WORKLOAD EXPERT SYSTEM. Gazi University Journal of Science, Cilt: 27 - Sayı: 4, 1131–1142. https://ajindex.com/articles/255158

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (14)

  1. Aidan, B., Tweed, N. and Halligan, C., "A pilot study of the mental workload of objective structured clinical examination examiners." Medical education 48(3): 262- 267, (2014).
  2. Bhushan, N., and Kanwal, R., Strategic Decision Making: Applying the Analytic Hierarchy Process, Springer-Verlag, London, (2004).
  3. Ericsson, K. A., Simon, H. A., “Verbal reports as data”, Psychological Review, 87(3): 215-251, (1980).
  4. Finomore, S., et al. "Viewing the Workload of Vigilance Through the Lenses of the NASA-TLX and the MRQ." Human Factors: The Journal of the Human Factors and Ergonomics Society 55(6):1044-1063 (2013).
  5. George, L. et al. “Combining Brain-Computer Interfaces and Haptics: Detecting Mental Workload to Adapt Haptic Assistance”, Lecture Notes in Computer Science, 7282: 124-135, (2012).
  6. Hart, S.C., Staveland, L.E. Development of a multi- dimensional workload rating scale: result of empirical and theoretical research, Handcock, P.A., Meshkati, N. (Ed.), Human Mental Workload, Elseiver, Netherlands, (1988).
  7. Hart, S. G. “NASA-Task Load Index (NASA-TLX); 20 Years Later”. In Human Factor and Ergonomics Society Annual 50(9):904–908, (2006).
  8. General sessions Hertzum, M., Holmegaard, K.D., “Perceived Time as a Measure of Mental Workload: Effects of Time Constraints and Task Success”, International Journal of Human-Computer Interaction, 29(1): 26-39, (2013).
  9. Hill, S.G., Byers, J.C., Zaklad, A.L., & Christ, R.E. Subjective workload assessment during 48 continuous hours of LOS – F – H operations. In Proceedings of the Human Factors Society 33rd Annual Meeting, 1129– 1133, Santa Monica, USA. (1992).
  10. Hwang, C.L., Lai, Y.J., Liu, T.Y., “A new approach for multiple objective decision making”, Computers and Operational Research, 20: 889–899, (1993).
  11. Kajiwara, S., "Evaluation of driver’s mental workload by facial temperature and electrodermal activity under simulated driving conditions." International Journal of Automotive Technology 15(1): 65-70 (2014).
  12. Maior, Horia A., et al. "Continuous Detection of Workload Contemporary Ergonomics and Human Factors 2014: Proceedings of the international conference on Ergonomics & Human Factors 2014,
  13. Southampton, UK, 7-10 April 2014. CRC Press, (2014).
  14. Approach." Nisbett, R. E., Wilson T. D., “Telling more than we can know: Verbal Psychological Review, 84(3): 231-259, (1977). on mental processes”, Rubio et al., S. Rubio, E. Díaz, J. Martín, “Evaluation of subjective mental workload: a comparison of SWAT, NASA-TLX, and workload profile methods”