Advertisement

Behavior Research Methods

, Volume 41, Issue 1, pp 113–117 | Cite as

NASA TLX: Software for assessing subjective mental workload

  • Alex Cao
  • Keshav K. Chintamani
  • Abhilash K. Pandya
  • R. Darin Ellis
Article

Abstract

The NASA Task Load Index (TLX) is a popular technique for measuring subjective mental workload. It relies on a multidimensional construct to derive an overall workload score based on a weighted average of ratings on six subscales: mental demand, physical demand, temporal demand, performance, effort, and frustration level. A program for implementing a computerized version of the NASA TLX is described. The software version assists in simplifying collection, postprocessing, and storage of raw data. The program collects raw data from the subject and calculates the weighted (or unweighted) workload score, which is output to a text file. The program can also be tailored to a specific experiment using a simple input text file, if desired. The program was designed in Visual Studio 2005 and is capable of running on a Pocket PC with Windows CE or on a PC with Windows 2000 or higher. The NASA TLX program is available for free download.

Keywords

Ergonomics Society Mental Workload Mental Demand Temporal Demand Workload Level 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Battiste, V., & Bortolussi, M. (1988). Transport pilot workload— A comparison between two subjective techniques. In Proceedings of the Human Factors and Ergonomics Society 32nd Annual Meeting (pp. 150–154). Santa Monica, CA: Human Factors & Ergonomics Society.Google Scholar
  2. Baulk, S. D., Kandelaars, K. J., Lamond, N., Roach, G. D., Dawson, D., & Fletcher, A. (2007). Does variation in workload affect fatigue in a regular 12-hour shift system? Sleep & Biological Rhythms, 5, 74–77.CrossRefGoogle Scholar
  3. Byers, J. C., Bittner, A. C., & Hill, S. G. (1989). Traditional and raw task load index (TLX) correlations: Are paired comparisons necessary? In A. Mital (Ed.), Advances in industrial ergonomics & safety (Vol. 1, pp. 481–485). London: Taylor & Francis.Google Scholar
  4. Cha, D., & Park, P. (1997). User required information modality and structure of in-vehicle navigation system focused on the urban commuter. Computers & Industrial Engineering, 33, 517–520.CrossRefGoogle Scholar
  5. Eggemeier, F. T. (1988). Properties of workload assessment techniques. In P. A. Hancock & N. Meshkati (Eds.), Human mental workload (pp. 41–62). Amsterdam: Elsevier.CrossRefGoogle Scholar
  6. Greenwood-Ericksen, A., Oron-Gilad, T., Szalma, J. L., Stafford, S., & Hancock, P. A. (2006). Workload and performance: A field evaluation in a police shooting range. In Proceedings of the Human Factors and Ergonomics Society 50th Annual Meeting (pp. 1953–1957). Santa Monica, CA: Human Factors & Ergonomics Society.Google Scholar
  7. Hart, S. G. (2006). NASA-Task Load Index (NASA-TLX); 20 years later. In Proceedings of the Human Factors and Ergonomics Society 50th Annual Meeting (pp. 904–908). Santa Monica, CA: Human Factors & Ergonomics Society.Google Scholar
  8. Hart, S. G., & Staveland, L. E. (1988). Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research. In P. A. Hancock & N. Meshkati (Eds.), Human mental workload (pp. 139–183). Amsterdam: Elsevier.CrossRefGoogle Scholar
  9. Hill, S. G., Iavecchia, H. P., Byers, J. C., Bittner, A. C., Zaklad, A. L., & Christ, R. E. (1992). Comparison of four subjective workload rating scales. Human Factors, 34, 429–439.Google Scholar
  10. Kaber, D. B., Onal, E., & Endsley, M. R. (2000). Design of automation for telerobots and the effect on performance, operator situation awareness, and subjective workload. Human Factors & Ergonomics in Manufacturing, 10, 409–430.CrossRefGoogle Scholar
  11. Kramer, A. F. (1991). Physiological metrics of mental workload: A review of recent progress. In D. L. Damos (Ed.), Multiple-task performance (pp. 329–360). London: Taylor & Francis.Google Scholar
  12. Mead, A. D., & Drasgow, F. (1993). Equivalence of computerized and paper-and-pencil cognitive ability tests: A meta-analysis. Psychological Bulletin, 114, 449–458.CrossRefGoogle Scholar
  13. Miyake, S. (2001). Multivariate workload evaluation combining physiological and subjective measures. International Journal of Psychophysiology, 40, 233–238.CrossRefPubMedGoogle Scholar
  14. Moroney, W. F., Biers, D. W., Eggemeier, F. T., & Mitchell, J. A. (1992). A comparison of two scoring procedures with the NASA Task Load Index in a simulated flight task. Aerospace and Electronics Conference, 1992. NAECON 1992, Proceedings of the IEEE 1992 National (Vol. 2, pp. 734–740). Dayton, OH: NAECON.Google Scholar
  15. NASA (1986). Task Load Index (TLX): Computerized version (Version 1.0). Moffett Field, CA: Human Research Performance Group, NASA Ames Research Center.Google Scholar
  16. Noyes, J. M., & Bruneau, D. P. J. (2007). A self-analysis of the NASATLX workload measure. Ergonomics, 50, 514–519.CrossRefPubMedGoogle Scholar
  17. Park, P., & Cha, D. (1998, October). Comparison of subjective mental workload assessment techniques for the evaluation of in-vehicle navigation system usability. Paper presented at Session T56 of the 5th World Congress on Intelligent Transport Systems 1998, Seoul.Google Scholar
  18. Reilly, S., Grasha, A. F., Matthews, G., & Schafer, J. (2003). Automatic-controlled information processing and error detection in a simulated pharmacy-verification task. Perceptual & Motor Skills, 97, 151–174.CrossRefGoogle Scholar
  19. Rubio, S., Díaz, E., Martín, J., & Puente, J. M. (2004). Evaluation of subjective mental workload: A comparison of SWAT, NASA-TLX, and workload profile methods. Applied Psychology: An International Review, 53, 61–86.CrossRefGoogle Scholar
  20. Ryu, K., & Myung, R. (2005). Evaluation of mental workload with a combined measure based on physiological indices during a dual task of tracking and mental arithmetic. International Journal of Industrial Ergonomics, 35, 991–1009.CrossRefGoogle Scholar
  21. Turner, C. W., Safar, J. A., & Ramaswamy, K. (2006). The effects of use on acceptance and trust in voice authentication technology. In Proceedings of the Human Factors and Ergonomics Society 50th Annual Meeting (pp. 718–722). Santa Monica, CA: Human Factors & Ergonomics Society.Google Scholar

Copyright information

© Psychonomic Society, Inc. 2009

Authors and Affiliations

  • Alex Cao
    • 1
  • Keshav K. Chintamani
    • 1
  • Abhilash K. Pandya
    • 1
  • R. Darin Ellis
    • 1
  1. 1.Department of Electrical and Computer EngineeringWayne State UniversityDetroit

Personalised recommendations