Distributions of air traffic control students’ attitudes towards workload
Abstract
Mental workload is a well-known concept with a long development history. It can be used to examine students’ attitudes at the end of the educational process and compare them in groups or separately. However, building a continuous workload profile across the range of task complexity increase is still an urgent issue. All four groups of methods used to define mental workload have such flaws for the workload profile construction process as significant time requirements, single value processing and post-processing of the received results. Only one of them can be used without modifications to construct the operator’s attitude chart (profile) regarding the workload range and it doesn’t operate with more reliable absolute values. To resolve this problem, a special workload assessment grid was developed, considering the advantages of a subjective group of methods and seven core characteristics. The reasoning for grid axes choice, threshold values, and question formulation were provided. Statistics were calculated for the full sample, different grades, and educational institutions. Comparison of the received responses with referential values, cross-comparison between institutions and different grades were performed. The results contribute to such important aspects of workload, as redlines, workload profiling, and operator’s comparison.
Keyword : human factors, air traffic control, education, workload, self-assessment, Yerkes-Dodson law
How to Cite
Borsuk, S., & Reva, O. (2021). Distributions of air traffic control students’ attitudes towards workload. Aviation, 25(4), 241-251. https://doi.org/10.3846/aviation.2021.15954
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Information Society Technologies (IST). (2006). Adaptive integrated Driver-vehicle interface. Subjective assessment methods for workload. http://www.aide-eu.org/pdf/sp2_deliv_new/aide_d2_2_6.pdf
Iqbal, M. U., Babji, S., & Rajagopalan, S. (2020). Dynamic assessment of control room operator’s cognitive workload using Electroencephalography (EEG). Computers & Chemical Engineering, 141, 106726. https://doi.org/10.1016/j.compchemeng.2020.106726
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Nachreiner, F. (1995). Standards for ergonomics principles relating to the design of work systems and to mental workload. Applied Ergonomics, 26(4), 259–263. https://doi.org/10.1016/0003-6870(95)00029-C
Park, S., Jeong, S., & Myung, R. (2018). Modeling of multiple sources of workload and time pressure effect with ACT-R. International Journal of Industrial Ergonomics, 63, 37–48. https://doi.org/10.1016/j.ergon.2017.07.003
Rahman, S. M. B. A., Borst, C., van Paassen, M. M., & Mulder, M. (2016). Cross-sector transferability of metrics for air traffic controller workload. IFAC-PapersOnLine, 49(19), 313–318. https://doi.org/10.1016/j.ifacol.2016.10.561
Rehmann, A. J. (1995). Handbook of human performance measures and crew requirements for Flightdeck research. Report. Bureau of transportation statistics, U.S. Department of Transportation. https://doi.org/10.1037/e664922007-001
Reva, O. M., Borsuk, S. P., Bala, M. M., & Peyman, M. S. (2016). New approach to determination of main solution taking dominant of air traffic controller during flight level norms violation. In F. Rebelo & M. Soares (Eds.), Proceedings of the AHFE 2016 International Conference on Human Factors in Transportation (pp. 137–147). Springer. https://doi.org/10.1007/978-3-319-41682-3_12
Roscoe, A. H., & Ellis, G. A. (1990). A subjective rating scale of assessing pilot workload in flight: A decade of practical use, a technical report. Procurement Executive, Ministry of Defence Farnborough, Hampshire.
Rusnock, C. F., & Borghetti, B. J. (2018). Workload profiles: A continuous measure of mental workload. International Journal of Industrial Ergonomics, 63, 49–64. https://doi.org/10.1016/j.ergon.2016.09.003
Socha, V., Hanakova, L., Valenta, V., Socha, L., Abela, R., Kušmirek, S., Pilmannova, T., & Tecl, J. (2020). Workload assessment of air traffic controllers. Transportation Research Procedia, 51, 243–251. https://doi.org/10.1016/j.trpro.2020.11.027
Stanton, N. A. (2005). Handbook of human factors and ergonomics methods. CRC Press. https://doi.org/10.1201/9780203489925
Tattersall, A. J., & Foord, S. (1996). An experimental evaluation of instantaneous self assessment as a measure of workload. Ergonomics, 39(5), 740–748. https://doi.org/10.1080/00140139608964495
Teigen, K. H. (1994). Yerkes-Dodson: A law for all seasons. Theory & Psychology, 4(4), 525–547. https://doi.org/10.1177/0959354394044004
Tsang, P., & Velazquez, V. (1996). Diagnosticity and multidimensional subjective workload ratings. Ergonomics, 39(3), 358–381. https://doi.org/10.1080/00140139608964470
Tsang, P. S., & Vidulich, M. A. (2012). Mental workload and situation awareness. In G. Salvendy (Ed.), Handbook of human factors and ergonomics (pp. 243–268). John Wiley & Sons, Inc. https://doi.org/10.1002/0470048204.ch9
Valdehita, S., Ramiro, E., Garcia, J., & Puente, J. (2004). Evaluation of subjective mental workload: a comparison of SWAT, NASA-TLX, and workload profile methods. Applied Psychology, 53(1), 61–86. https://doi.org/10.1111/j.1464-0597.2004.00161.x
Vidulich, M. A., Ward, G. F., & Schueren, J. (1991). Using the Subjective Workload Dominance (SWORD) technique for projective workload assessment. Human Factors, 33(6), 677–691. https://doi.org/10.1177/001872089103300605
Wang, P., Fang, W., & Guo, B. (2020). A measure of mental workload during multitasking: Using performance-based Timed Petri Nets. International Journal of Industrial Ergonomics, 75, 102877. https://doi.org/10.1016/j.ergon.2019.102877
Weeda, C., & Zeilstra, M. (2013). Prediction of mental workload of monitoring tasks. In N. Dadashi, A. Scott, J. R. Wilson, & A. Mills (Eds.), Rail human factors: Supporting reliability, safety and cost reduction (pp. 633–640). CRC Press. https://doi.org/10.1201/b13827-83
Wickens, C. (2002). Multiple resources and performance prediction. Theoretical Issues in Ergonomic Science, 3(2), 159–177. https://doi.org/10.1080/14639220210123806
Wickens, C. (2008). Multiple resources and mental workload. Human Factors, 50(3), 449–455. https://doi.org/10.1518/001872008X288394
Yan, S., Wei, Y., & Trana, C. C. (2019). Evaluation and prediction mental workload in user interface of maritime operations using eye response. International Journal of Industrial Ergonomics, 71, 117–127. https://doi.org/10.1016/j.ergon.2019.03.002
Young, M. S., Brookhuis, K. A., Wickens, C. D., & Hancock, P. A. (2015). State of science: Mental workload in ergonomics. Ergonomics, 58(1), 1–17. https://doi.org/10.1080/00140139.2014.956151
Zeier, H. (1994). Workload and psychophysiological stress reactions in air traffic controllers. Ergonomics, 37, 525–539. https://doi.org/10.1080/00140139408963668
Bommer, S. (2016). A theoretical framework for evaluating mental workload resources in Human Systems design for manufacturing operations. Wright State University, Dayton, Ohio, US.
Borsuk, S. (2017). New methods for air traffic controller main solution taking dominant determination concerning their attitude to risk. Logistics and Transport, 1(33), 25–29.
Braarud, P. O. (2020). An efficient screening technique for acceptable mental workload based on the NASA Task Load Index – development and application to control room validation. International Journal of Industrial Ergonomics, 76, 102904. https://doi.org/10.1016/j.ergon.2019.102904
Chiappe, D., Morgan, C. A., Kraut, J., Ziccardi, J., Sturre, L., Strybel, T. Z., & Vu, K.-P. L. (2016). Evaluating probe techniques and a situated theory of situation awareness. Journal of Experimental Psychology: Applied, 22(4), 436–454. https://doi.org/10.1037/xap0000097
Cowan, N., Morey, C. C., & Chen, Z. (2007). The legend of the Magical Number Seven. In S. Della Sala (Ed.), Tall tales about the mind and brain: Separating fact from fiction (pp. 45–59). Oxford University Press. https://doi.org/10.1093/acprof:oso/9780198568773.003.0005
De Waard, D. (1996). The measurement of drivers’ mental workload. University of Groningen.
Efthymiou, M., Fichert, F., & Lantzsch, O. (2019). Workload perception of air traffic control officers and pilots during continuous descent operations approach procedures. Aviation Psychology and Applied Human Factors, 9(1), 2–11. https://doi.org/10.1027/2192-0923/a000154
Gao, Q., Wang, Y., Song, F., Li, Z., & Dong, X. (2013). Mental workload measurement for emergency operating procedures in digital nuclear power plants. Ergonomics, 56(7), 1070–1085. https://doi.org/10.1080/00140139.2013.790483
Goillau, P. J. & Kelly, C. J. (1997). MAlvern Capacity Estimate (MACE) – A proposed cognitive measure for complex systems. In D. Harris (Ed.), Engineering psychology and cognitive ergonomics, Vol. 1: Transportation Systems (pp. 219–225). Routledge. https://doi.org/10.4324/9781315094496-22
Hamilton, K. M., & Landry, L. N. (1993). Measuring subjective workload: When is one scale better than many? Human Factors, 35, 579–601. https://doi.org/10.1177/001872089303500401
Hopkin, V. D. (1995). Human factors in air traffic control. Taylor & Francis.
Information Society Technologies (IST). (2006). Adaptive integrated Driver-vehicle interface. Subjective assessment methods for workload. http://www.aide-eu.org/pdf/sp2_deliv_new/aide_d2_2_6.pdf
Iqbal, M. U., Babji, S., & Rajagopalan, S. (2020). Dynamic assessment of control room operator’s cognitive workload using Electroencephalography (EEG). Computers & Chemical Engineering, 141, 106726. https://doi.org/10.1016/j.compchemeng.2020.106726
Jordan, C. S. (1992). Experimental study of the effect of an instantaneous self assessment workload recorder on task performance. DRA Technical Memorandum (CAD5). DRA Maritime Command Control Division.
Kirwan, B., Evans, A., Donohoe, L., Kilner, A., Lamoureux, T., Atkinson, T., & MacKendrick, H. (1997). Human factors in the ATM system design life cycle. In FAA/Eurocontrol ATM R&D Seminar (pp. 16–20). Paris, France.
Kostenko, A., Rauffet, P., Chauvin, C., & Coppin, G. (2016). A dynamic closed-looped and multidimensional model for Mental Workload evaluation. IFAC-PapersOnLine, 49(19), 549–554. https://doi.org/10.1016/j.ifacol.2016.10.621
Leveson, N. (2004). A new accident model for engineering safer systems. Safety Science, 42(4), 237–270. https://doi.org/10.1016/S0925-7535(03)00047-X
Marinescu, A. C., Sharples, S., Ritchie, A. C., Lopez, T. S., McDowell, M., & Morvan, H. P. (2017). Physiological parameter response to variation of mental workload. Human Factors, 60(1), 31–56. https://doi.org/10.1177/0018720817733101
Miller, S. (2001). Literature review. Workload measures. National Advanced Driving Simulator, The University of Iowa.
Nachreiner, F. (1995). Standards for ergonomics principles relating to the design of work systems and to mental workload. Applied Ergonomics, 26(4), 259–263. https://doi.org/10.1016/0003-6870(95)00029-C
Park, S., Jeong, S., & Myung, R. (2018). Modeling of multiple sources of workload and time pressure effect with ACT-R. International Journal of Industrial Ergonomics, 63, 37–48. https://doi.org/10.1016/j.ergon.2017.07.003
Rahman, S. M. B. A., Borst, C., van Paassen, M. M., & Mulder, M. (2016). Cross-sector transferability of metrics for air traffic controller workload. IFAC-PapersOnLine, 49(19), 313–318. https://doi.org/10.1016/j.ifacol.2016.10.561
Rehmann, A. J. (1995). Handbook of human performance measures and crew requirements for Flightdeck research. Report. Bureau of transportation statistics, U.S. Department of Transportation. https://doi.org/10.1037/e664922007-001
Reva, O. M., Borsuk, S. P., Bala, M. M., & Peyman, M. S. (2016). New approach to determination of main solution taking dominant of air traffic controller during flight level norms violation. In F. Rebelo & M. Soares (Eds.), Proceedings of the AHFE 2016 International Conference on Human Factors in Transportation (pp. 137–147). Springer. https://doi.org/10.1007/978-3-319-41682-3_12
Roscoe, A. H., & Ellis, G. A. (1990). A subjective rating scale of assessing pilot workload in flight: A decade of practical use, a technical report. Procurement Executive, Ministry of Defence Farnborough, Hampshire.
Rusnock, C. F., & Borghetti, B. J. (2018). Workload profiles: A continuous measure of mental workload. International Journal of Industrial Ergonomics, 63, 49–64. https://doi.org/10.1016/j.ergon.2016.09.003
Socha, V., Hanakova, L., Valenta, V., Socha, L., Abela, R., Kušmirek, S., Pilmannova, T., & Tecl, J. (2020). Workload assessment of air traffic controllers. Transportation Research Procedia, 51, 243–251. https://doi.org/10.1016/j.trpro.2020.11.027
Stanton, N. A. (2005). Handbook of human factors and ergonomics methods. CRC Press. https://doi.org/10.1201/9780203489925
Tattersall, A. J., & Foord, S. (1996). An experimental evaluation of instantaneous self assessment as a measure of workload. Ergonomics, 39(5), 740–748. https://doi.org/10.1080/00140139608964495
Teigen, K. H. (1994). Yerkes-Dodson: A law for all seasons. Theory & Psychology, 4(4), 525–547. https://doi.org/10.1177/0959354394044004
Tsang, P., & Velazquez, V. (1996). Diagnosticity and multidimensional subjective workload ratings. Ergonomics, 39(3), 358–381. https://doi.org/10.1080/00140139608964470
Tsang, P. S., & Vidulich, M. A. (2012). Mental workload and situation awareness. In G. Salvendy (Ed.), Handbook of human factors and ergonomics (pp. 243–268). John Wiley & Sons, Inc. https://doi.org/10.1002/0470048204.ch9
Valdehita, S., Ramiro, E., Garcia, J., & Puente, J. (2004). Evaluation of subjective mental workload: a comparison of SWAT, NASA-TLX, and workload profile methods. Applied Psychology, 53(1), 61–86. https://doi.org/10.1111/j.1464-0597.2004.00161.x
Vidulich, M. A., Ward, G. F., & Schueren, J. (1991). Using the Subjective Workload Dominance (SWORD) technique for projective workload assessment. Human Factors, 33(6), 677–691. https://doi.org/10.1177/001872089103300605
Wang, P., Fang, W., & Guo, B. (2020). A measure of mental workload during multitasking: Using performance-based Timed Petri Nets. International Journal of Industrial Ergonomics, 75, 102877. https://doi.org/10.1016/j.ergon.2019.102877
Weeda, C., & Zeilstra, M. (2013). Prediction of mental workload of monitoring tasks. In N. Dadashi, A. Scott, J. R. Wilson, & A. Mills (Eds.), Rail human factors: Supporting reliability, safety and cost reduction (pp. 633–640). CRC Press. https://doi.org/10.1201/b13827-83
Wickens, C. (2002). Multiple resources and performance prediction. Theoretical Issues in Ergonomic Science, 3(2), 159–177. https://doi.org/10.1080/14639220210123806
Wickens, C. (2008). Multiple resources and mental workload. Human Factors, 50(3), 449–455. https://doi.org/10.1518/001872008X288394
Yan, S., Wei, Y., & Trana, C. C. (2019). Evaluation and prediction mental workload in user interface of maritime operations using eye response. International Journal of Industrial Ergonomics, 71, 117–127. https://doi.org/10.1016/j.ergon.2019.03.002
Young, M. S., Brookhuis, K. A., Wickens, C. D., & Hancock, P. A. (2015). State of science: Mental workload in ergonomics. Ergonomics, 58(1), 1–17. https://doi.org/10.1080/00140139.2014.956151
Zeier, H. (1994). Workload and psychophysiological stress reactions in air traffic controllers. Ergonomics, 37, 525–539. https://doi.org/10.1080/00140139408963668