In this paper I begin looking for evidence of a subjective workload curve.
Background:
Results from subjective mental workload assessments are often interpreted linearly. However, I hypothesized that ratings of subjective mental workload increase nonlinearly with unitary increases in working memory load.
Method:
Two studies were conducted. In the first, the participant provided ratings of the mental difficulty of a series of digit span recall tasks. In the second study, participants provided ratings of mental difficulty associated with recall of visual patterns. The results of the second study were then examined using a mathematical model of working memory.
Results:
An S curve, predicted a priori, was found in the results of both the digit span and visual pattern studies. A mathematical model showed a tight fit between workload ratings and levels of working memory activation.
Conclusion:
This effort provides good initial evidence for the existence of a workload curve. The results support further study in applied settings and other facets of workload (e.g., temporal workload).
Application:
Measures of subjective workload are used across a wide variety of domains and applications. These results bear on their interpretation, particularly as they relate to workload thresholds.
AltmannE. M.SchunnC. D. (2002). Integrating decay and interference: A new look at an old interaction. In GrayW.SchunnS. (Eds.), Proceedings of the 24th Annual Conference of the Cognitive Science Society (pp. 65–70). Fairfax, VA: Cognitive Science Society.
2.
AltmannE. M.TraftonJ. G. (2002). Memory for goals: An activation-based model. Cognitive Science, 26, 39–83.
3.
AmichettiN.StanleyR.WhiteA.WingfieldA. (2013). Monitoring the capacity of working memory: Executive control and effects of listening effort. Memory & Cognition, 41, 839–849.
4.
AndersonJ. (2007). How can the mind occur in the physical universe?New York, NY: Oxford University Press.
5.
AndersonJ.RederL.LebiereC. (1996). Working memory: Activation limitations on retrieval. Cognitive Psychology, 30, 221–256.
6.
BachelderB. (2000). The magical number 4 = 7: Span theory on capacity limitations. Behavioral and Brain Sciences, 24, 87–185.
7.
BaddeleyA. (1975). Word length and the structure of short-term memory. Journal of Verbal Learning and Verbal Behavior, 14, 575–589.
8.
BaddeleyA. (2007). Working memory, thought, and action. New York, NY: Oxford University Press.
9.
BarrouilletP.BernardinS.CamosV. (2004). Time constraints and resource sharing in adults’ working memory spans. Journal of Experimental Psychology: General, 133, 83–100.
10.
BaudM. (1993). Data analysis, mathematical modeling. In MasseyeffR. F.AlbertW.StainesN. A. (Eds.), Methods of immunological analysis: Vol. 1. Fundamentals (pp. 656–671). New York, NY: VCH.
11.
BerkaC.LevendowskiD. J.LumicaoM. N.YauA.DavisG.ZivkovicV. T.OlmsteadR. E.TremouletP. D.CravenP. L. (2007). EEG correlates of task engagement and mental workload in vigilance, learning, and memory tasks. Aviation, Space, and Environmental Medicine, 78, 231–244.
12.
BöhmU.MehlhornK. (2009). The influence of spreading activation on memory retrieval in sequential diagnostic reasoning. In HowesA.PeeblesD.CooperR. (Eds.), Proceedings of the 9th International Conference on Cognitive Modeling (pp. 188–193). Manchester, UK.
13.
BrownJ. (1958). Some tests of the decay theory of immediate memory. Quarterly Journal of Experimental Psychology, 10, 12–21.
14.
BunnellJ.BakenD.Richards-WardL. (1999). The effect of age on metamemory for working memory. New Zealand Journal of Psychology, 28, 23–29.
ByrneM.BovairS. (1997). A working memory model of a common procedural error. Cognitive Science, 21, 31–61.
17.
CardS.MoranT.NewellA. (1983). The psychology of human computer interaction. Hillsdale, NJ: Lawrence Erlbaum.
18.
ClearyM.PisoniD. B.GeersA. E. (2001). Some measures of verbal and spatial working memory in eight- and nine-year-old hearing-impaired children with cochlear implants. Ear & Hearing, 22, 395–411.
19.
CohenJ. (1988). Statistical power analysis for the behavioral sciences. Hillsdale, NJ: Lawrence Erlbaum.
20.
CooperG.HarperR. (1969). The use of pilot rating in the evaluation of aircraft handling qualities (Tech. Rep. TN D-5153). Washington, DC: NASA.
21.
CowanN. (2001). The magical number 4 in short-term memory: A reconsideration of mental storage capacity. Behavioral and Brain Sciences, 24, 87–114.
22.
DaryanianB. (1980). Subjective scaling of mental workload multi-task environment (Unpublished master’s thesis). Massachusetts Institute of Technology, Cambridge.
23.
DijksterhuisC.de WaardD.BrookhuisK.MulderB.de JongR. (2013). Classifying visuomotor workload in a driving simulator using subject specific spatial brain patterns. Frontiers in Neuroscience, 7(149). Retrieved from http://journal.frontiersin.org/article/10.3389/fnins.2013.00149/full
24.
EggemeierF. T.CrabtreeM. S.ReidG. B. (1982). Subjective workload assessment in a memory update task. In Proceedings of the Human Factors and Ergonomics Society 26th Annual Meeting (pp. 643–647). Santa Monica, CA: Human Factors and Ergonomics Society.
25.
EggemeierF. T.WilsonG. F. (1991). Performance-based and subjective assessment of workload in multi-task environments. In DamosD. L. (Ed.), Multiple-task performance (pp. 217–278). London, UK: Taylor & Francis.
26.
EricssonK. A.SimonH. A. (1980). Verbal reports as data. Psychological Review, 87, 215–251.
27.
FittsP. (1954). The information capacity of the human motor system in controlling the amplitude of movement. Journal of Experimental Psychology, 47, 381–391.
28.
GawronV. J. (2008). Human performance, workload, and situational awareness measures handbook. Boca Raton, Florida: CRC.
29.
GendleM.RansomM. (2006). Use of the electronic game Simon as a measure of working memory span in college age adults. Journal of Behavioral and Neuroscience Research, 4, 1–7.
30.
GopherD.BrauneR. (1984). On the psychophysics of workload: Why bother with subjective measures?Human Factors, 26, 519–532.
31.
HalamishV.McGillivrayS.CastelA. (2011). Monitoring one’s own forgetting in younger and older adults. Psychology and Aging, 26, 631–635.
32.
HartS. G. (2006). NASA–Task Load Index (NASA-TLX); 20 years later. In Proceedings of the Human Factors and Ergonomics Society 26th Annual Meeting (pp. 904–908). Santa Monica, CA: Human Factors and Ergonomics Society.
33.
HartS. G.StavelandL. E. (1988). Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research. In HancockP. A.MeshkatiN. (Eds.), Human mental workload (pp. 139–183). Amsterdam, Netherlands: North-Holland.
34.
HassinR. R.BarghJ. A.EngellA.McCulluchK. C. (2009). Implicit working memory. Consciousness and Cognition, 189, 665–678.
35.
HauserJ. R.ChildressM. E.HartS. G. (1982). Rating consistency and component salience in subjective workload estimation. In GeorgeF. (Ed.), Proceedings of the 18th Annual Conference on Manual Control (pp. 127–149). Washington, DC: NASA.
36.
HessR. (1971). The use of a nonadjectival, nonordinal, linear rating scale in a single axis compensatory tracking task (Unpublished master’s thesis). Naval Postgraduate School, Monterey, CA
37.
HickW. E. (1952). On the rate of gain of information. Quarterly Journal of Experimental Psychology, 4, 11–26.
38.
HumesL.FloydS. (2005). Measures of working memory, sequence learning, and speech recognition in the elderly. Journal of Speech, Language, and Hearing Research, 48, 224–235.
39.
JevonsW. S. (1871). The power of numerical discrimination. Nature, 3, 281–282.
40.
JustM. A.CarpenterP. A. (1992). A capacity theory of comprehension: Individual differences in working memory. Psychological Review, 99, 122–149.
41.
KahanaM. (2012). Foundations of human memory. New York, NY: Oxford University Press.
42.
KornellN.RhodesM.CastelA.TauberS. (2011). The ease-of-processing heuristic and stability bias: Dissociating memory, memory beliefs, and memory judgments. Psychological Science, 22, 787–794.
43.
MillerG. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63, 81–97.
44.
MorayN.JohansenJ.PewR. W.RasmussenJ.SandersA. F.WickensC. D. (1979). Mental workload: Its theory and measurement. New York, NY: Plenum Press.
45.
MuellerS.KrawitzA. (2009). Reconsidering the two-second decay hypothesis in verbal working memory. Journal of Mathematical Psychology, 53, 14–25.
46.
NewellA. (1973). You can’t play 20 questions with nature and win: Projective comments on the papers of this symposium. In ChaseW. G. (Ed.), Visual information processing (pp. 283–308). New York, NY: Academic Press.
47.
NewellA.RosenbloomP. S. (1981). Mechanisms of skill acquisition and the law of practice. In AndersonJ. R. (Ed.), Cognitive skills and their acquisition (pp. 1–55). Hillsdale, NJ: Lawrence Erlbaum.
48.
OberauerK.LewandowskyS.FarrellS.JarroldC.GreavesM. (2012). Modeling working memory: An interference model of complex span. Psychonomic Bulletin & Review, 19, 779–819.
49.
PapeN.UrbasL. (2008). A model of time-estimation considering working memory demands. In Proceedings of the 30th Annual Cognitive Science Society (pp. 1543–1548). Austin, TX: Cognitive Science Society.
50.
ReidG. B.NygrenT. E. (1988). The subjective workload assessment technique: A scaling procedure for measuring mental workload. In HancockP. A.MeshkatiN. (Eds.), Human mental workload (pp. 185–218). Amsterdam, Netherlands: Elsevier.
51.
RubioS.DiazE.MartinJ.PuenteJ. M. (2004) Evaluation of subjective mental workload: A comparison of SWAT, NASA-TLX, and Workload Profile. Applied Psychology: An International Review, 53, 61–86.
52.
SchunnC. D.WallachD. (2005). Evaluating goodness-of-fit in comparison of models to data. In TackW. (Ed.), Psychologie der Kognition: Reden and Vorträge anlässlich der Emeritierung von Werner Tack (pp. 115–154). Saarbrueken, Germany: University of Saarland Press.
53.
SheridanT. B.SimpsonR. W. (1979). Toward the definition and measurement of the mental workload of transport pilots (Tech. Rep. No. R 79-4). Cambridge, MA: MIT Flight Transportation Laboratory.
54.
SimonH. A. (1969). The sciences of the artificial. Cambridge, MA: MIT Press.
55.
SohnM. H.AndersonJ. R.RederL. M.GoodeA. (2004) Differential fan effect and attentional focus. Psychonomic Bulletin and Review, 11, 729–734.
56.
StevensS. S. (1957). On the psychophysical law. Psychological Review, 64, 153–181.
57.
TaatgenN. (2000). Dispelling the magic: Towards memory without capacity. Behavioral and Brain Sciences, 24, 87–185.
58.
TryonW. (2001). Evaluating statistical difference, equivalence, and indeterminacy using inferential confidence intervals: An integrated alternative method of conducting null hypothesis statistical tests. Psychological Methods, 6, 371–386.
59.
TulgaM. K.SheridanT. B. (1980). Dynamics decision and workload in multitask supervisory control. IEEE Transactions on Systems, Man, and Cybernetics, SMC-10, 217–231.
60.
VidulichM. A. (1988). The cognitive psychology of subjective mental workload. In HancockP. A.MeshkatiN. (Eds.), Human mental workload (pp. 219–229). New York, NY: Elsevier.
61.
VidulichM. A.TsangP. (1985). Assessing subjective workload assessment: A comparison of SWAT and the NASA-bipolar methods. In Proceedings of the Human Factors and Ergonomics Society 29th Annual Meeting (pp. 71–75). Santa Monica, CA: Human Factors and Ergonomics Society.
62.
WickensC. D. (2008). Multiple resources and mental workload. Human Factors, 50, 449–455.
63.
WierwilleW. W.CasaliJ. G. (1983). A validated rating scale for global mental workload measurement applications. In Proceedings of the Human Factors and Ergonomics Society 27th Annual Meeting (pp. 129–133). Santa Monica, CA: Human Factors and Ergonomics Society.
64.
WierwilleW. W.WilligesR. C. (1978). Survey and analysis of operator workload assessment techniques (Tech. Rep. No. S-78-101). Systemetrics, Inc.
65.
YehY. Y.WickensC. D. (1988). Dissociation of performance and subjective measures of workload. Human Factors, 30, 111–120.
66.
YerkesR.DodsonJ. (1908). The relation of strength of stimulus to rapidity of habit-formation. Journal of Comparative Neurology and Psychology, 18, 459–482.
67.
YoungM. S.BrookhuisK. A.WickensC. D.HancockP. A. (2015). State of science: Mental workload in ergonomics. Ergonomics, 58, 1–17.
