Abstract
In the chemical industry, highly changeable modular plants allow for system reconfigurations on shortest timescales: a number of processing units can be combined to optimize the plant setup for current demands. As a consequence, human operators are frequently confronted with newly assembled systems that differ from previous ones in some ways while not differing in others. This partial overlap creates a number of challenges with regard to operator performance and learning. Both differentiation and generalization of knowledge are needed, which leads to a goal conflict: on the one hand, operators have to know the specifics of the current system, update their understanding of functional relations between system parameters, and use operation procedures that are tailored to the requirements of the current situation. On the other hand, they need to apply the knowledge they have acquired in previous plant setups to solve problems in a new one. While unwanted carryover must be avoided, appropriate transfer is essential. The present article provides an overview of the challenges and potentials of learning and transfer in changing environments as discussed in the cognitive science and situated cognition literatures. This overview is of prescriptive nature: it presents results and theories that should be considered when analyzing operator performance and designing interfaces or training in modular plants. To this end, the article considers how learning is adapted to the volatility of the environment, how mental representations are updated, how conceptual and procedural knowledge is transferred to new situations, and how learning is shaped by interactions with the environment.
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References
Bakker AB, Demerouti E (2007) The job demands-resources model: state of the art. J Manag Psychol 22:309–328. https://doi.org/10.1108/02683940710733115
Bransford JD, Schwartz DL (1999) Rethinking transfer: a simple proposal with multiple implications. In: Iran-Nejad A, Pearson PD (eds) Review of research in education, vol 24. American Educational Research Association, Washington, DC, pp 61–100
Brown S, Steyvers M (2005) The dynamics of experimentally induced criterion shifts. J Exp Psychol Learn Mem Cogn 31:587–599. https://doi.org/10.1037/0278-7393.31.4.587
Cañas JJ, Antolí A, Fajardo I, Salmerón L (2005) Cognitive inflexibility and the development and use of strategies for solving complex dynamic problems: effects of different types of training. Theor Issues Ergon Sci 6:95–108. https://doi.org/10.1080/14639220512331311599
Carey S, Spelke ES (1994) Domain-specific knowledge and conceptual change. In: Hirschfeld L, Gelman S (eds) Mapping the mind: domain specificity in cognition and culture. Cambridge University Press, Cambridge, pp 169–200
Carraher D, Schliemann AD (2002) The transfer dilemma. J Learn Sci 11:1–24. https://doi.org/10.1207/S15327809JLS1101_1
Chen Z (2002) Analogical problem solving: a hierarchical analysis of procedural similarity. J Exp Psychol Learn Mem Cogn 28:81–98. https://doi.org/10.1037//0278-7393.28.1.81
Chen Z, Mo L (2004) Schema induction in problem solving: a multidimensional analysis. J Exp Psychol Learn Mem Cogn 30:583–600. https://doi.org/10.1037/0278-7393.30.3.583
Chi MTH (2008) Three types of conceptual change: belief revision, mental model transformation, and categorical shift. In: Vosniadou S (ed) International handbook of research on conceptual change. Erlbaum, Hillsdale, pp 61–82
Day SB, Goldstone RL (2012) The import of knowledge export: connecting findings and theories of transfer of learning. Educ Psychol 47:153–176. https://doi.org/10.1080/00461520.2012.696438
De Keyser V, Woods DD (1990) Fixation errors: failures to revise situation assessment in dynamic and risky systems. In: Colombo AG, De Bustamante AS (eds) Systems reliability assessment. Springer, Dordrecht, pp 231–251. https://doi.org/10.1007/978-94-009-0649-5_11
Doane SM, Alderton DL, Sohn YW, Pellegrino JW (1996) Acquisition and transfer of skilled performance: are visual discrimination skills stimulus specific? J Exp Psychol Hum Percept Perform 22:1218–1248. https://doi.org/10.1037/0096-1523.22.5.1218
Dweck CS (1986) Motivational processes affecting learning. Am Psychol 41:1040–1048. https://doi.org/10.1037/0003-066X.41.10.1040
Earley PC, Connolly T, Ekegren G (1989) Goals, strategy development, and task performance: some limits on the efficacy of goal setting. J Appl Psychol 74:24–33. https://doi.org/10.1037/0021-9010.74.1.24
Ellis AB (2011) Generalizing-promoting actions: how classroom collaborations can support students’ mathematical generalizations. J Res Math Educ 42:308–345. https://doi.org/10.5951/jresematheduc.42.4.0308
Engle RA (2006) Framing interactions to foster generative learning: a situative explanation of transfer in a community of learners classroom. J Learn Sci 15:451–498. https://doi.org/10.1207/s15327809jls1504_2
Gentner D, Rattermann MJ, Forbus KD (1993) The roles of similarity in transfer: separating retrievability from inferential soundness. Cogn Psychol 25:524–575. https://doi.org/10.1006/cogp.1993.1013
George DN, Kruschke JK (2012) Contextual modulation of attention in human category learning. Learn Behav 40:530–541. https://doi.org/10.3758/s13420-012-0072-8
Gick ML, Holyoak KJ (1983) Schema induction and analogical transfer. Cogn Psychol 15:1–38
GMA 7.20 (2013) Cyber-physical systems: chancen und Nutzen aus Sicht der Automation. GMA
Goldstone RL, Wilensky U (2008) Promoting transfer by grounding complex systems principles. J Learn Sci 17:465–516. https://doi.org/10.1080/10508400802394898
Gonzalez C, Lerch JF, Lebiere C (2003) Instance-based learning in dynamic decision making. Cogn Sci 27
Goschke T (2013) Volition in action: Intentions, control dilemmas and the dynamic regulation of intentional control. In: Prinz W, Beisert A, Herwig A (eds) Action science. Foundations of an emerging discipline. MIT Press, Cambridge
Greeno JG, Moore JL, Smith DR (1993) Transfer of situated learning. In: Detterman DK, Sternberg RJ (eds) Transfer on trial: intelligence, cognition, and instruction. Ablex Publishing, Westport, pp 99–167
Grote G, Weichbrodt JC, Günter H, Zala-Mezö E, Künzle B (2009) Coordination in high-risk organizations: the need for flexible routines. Cogn Technol Work 11:17–27. https://doi.org/10.1007/s10111-008-0119-y
Hackman JR, Oldham GR (1975) Development of the job diagnostic survey. J Appl Psychol 60:159–170. https://doi.org/10.1037/h0076546
Hajdukiewicz JR, Vicente KJ (2002) Designing for adaptation to novelty and change: functional information, emergent feature graphics, and higher-level control. Hum Factors 44:592–610. https://doi.org/10.1518/0018720024496980
Helsdingen AS, Van Gog T, Van Merriënboer JJ (2011) The effects of practice schedule on learning a complex judgment task. Learn Instr 21:126–136. https://doi.org/10.1016/j.learninstruc.2009.12.001
Hirsch-Kreinsen H (2014) Wandel von Produktionsarbeit—Industrie 4.0. WSI Mitteilungen 6:421–429
Hmelo-Silver CE, Marathe S, Liu L (2007) Fish swim, rocks sit, and lungs breathe: expert-novice understanding of complex systems. J Learn Sci 16:307–331. https://doi.org/10.1080/10508400701413401
Hoffman AB, Rehder B (2010) The costs of supervised classification: the effect of learning task on conceptual flexibility. J Exp Psychol Gen 139:319–340. https://doi.org/10.1037/a0019042
Holyoak KJ, Koh K (1987) Surface and structural similarity in analogical transfer. Mem Cogn 15:332–340. https://doi.org/10.3758/BF03197035
Humphrey SE, Nahrgang JD, Morgeson FP (2007) Integrating motivational, social, and contextual work design features: a meta-analytic summary and theoretical extension of the work design literature. J Appl Psychol 92:1332–1356. https://doi.org/10.1037/0021-9010.92.5.1332
Jacobson MJ (2000) Problem solving about complex systems: differences between experts and novices. In: Fishman B, O’Connor-Divelbiss S (eds) Proceedings of the fourth international conference of the learning sciences, Mahwah, NJ, Erlbaum, pp 14–21
Jamieson BA, Rogers WA (2000) Age-related effects of blocked and random practice schedules on learning a new technology. J Gerontol Ser B Psychol Sci Soc Sci 55:P343–P353. https://doi.org/10.1093/geronb/55.6.P343
Jonassen DH (2000) Toward a design theory of problem solving. Educ Technol Res Dev 48:63–85. https://doi.org/10.1007/BF02300500
Jornet A, Roth W-M, Krange I (2016) A transactional approach to transfer episodes. J Learn Sci 25:285–330. https://doi.org/10.1080/10508406.2016.1147449
Jurow AS (2004) Generalizing in interaction: middle school mathematics students making mathematical generalizations in a population-modeling project. Mind Cult Act 11:279–300. https://doi.org/10.1207/s15327884mca1104_4
Kanfer R, Ackerman PL (1989) Motivation and cognitive abilities: an integrative/aptitude-treatment interaction approach to skill acquisition. J Appl Psychol 74:657–690. https://doi.org/10.1037/0021-9010.74.4.657
Karasek RA (1979) Job demands, job decision latitude, and mental strain: implications for job redesign. Adm Sci Q 24:285–308. https://doi.org/10.2307/2392498
Kindsmüller MC (2006) Trend-Literacy—zur Interpretation von Kurvendarstellungen in der Prozessführung. Shaker Verlag, Aachen
Kluge A, Ritzmann S, Burkolter D, Sauer J (2011) The interaction of drill and practice and error training with individual differences. Cogn Technol Work 13:103–120. https://doi.org/10.1007/s10111-010-0158-z
Kluge A, Nazir S, Manca D (2014) Advanced applications in process control and training needs of field and control room operators. IIE Trans Occup Ergon Hum Factors 2:121–136. https://doi.org/10.1080/21577323.2014.920437
Krems JF (1995) Cognitive flexibility and complex problem solving. In: Frensch PA, Funke J (eds) Complex problem solving: the European perspective (Chap. 8). Lawrence Erlbaum Associates, Hillsdale
Kruschke JK (2005) Category learning. In: Lamberts K, Goldstone RL (eds) The handbook of cognition. Sage, London, pp 183–201
Lai Q, Shea CH, Wulf G, Wright DL (2000) Optimizing generalized motor program and parameter learning. Res Q Exerc Sport 71:10–24. https://doi.org/10.1080/02701367.2000.10608876
Lau N, Jamieson GA, Skraaning G Jr (2012) Situation awareness in process control: a fresh look. In: Paper presented at the 8th American Nuclear Society International Topical Meeting on Nuclear Plant Instrumentation & Control and Human-Machine Interface Technologies (NPIC & HMIT), San Diego, CA, USA
Lave J (1988) Cognition in practice: mind, mathematics and culture in everyday life. Cambridge University Press, Cambridge
Lave J (2009) The practice of learning. In: Illeris K (ed) Contemporary theories of learning: learning theorists… in their own words. Routledge, New York, pp 200–208
Law N, Ogborn J (1994) Students as expert system developers: a means of eliciting and understanding commonsense reasoning. J Res Comput Educ 26:497–513. https://doi.org/10.1080/08886504.1994.10782106
Lobato J (2003) How design experiments can inform a rethinking of transfer and vice versa. Educ Res 32:17–20. https://doi.org/10.3102/0013189X032001017
Lobato J (2006) Alternative perspectives on the transfer of learning: history, issues, and challenges for future research. J Learn Sci 15:431–449. https://doi.org/10.1207/s15327809jls1504_1
Lobato J, Siebert D (2002) Quantitative reasoning in a reconceived view of transfer. J Math Behav 21:87–116. https://doi.org/10.1016/S0732-3123(02)00105-0
Lobato J, Rhodehamel B, Hohensee C (2012) “Noticing” as an alternative transfer of learning process. J Learn Sci 21:433–482. https://doi.org/10.1080/10508406.2012.682189
Locke EA, Latham GP (2002) Building a practically useful theory of goal setting and task motivation: a 35-year odyssey. Am Psychol 57:705–717. https://doi.org/10.1037/0003-066X.57.9.705
Ma R, Kaber DB (2007) Situation awareness and driving performance in a simulated navigation task. Ergonomics 50:1351–1364. https://doi.org/10.1080/00140130701318913
McGuire JT, Nassar MR, Gold JI, Kable JW (2014) Functionally dissociable influences on learning rate in a dynamic environment. Neuron 84:870–881. https://doi.org/10.1016/j.neuron.2014.10.013
McNeese MD (2000) Socio-cognitive factors in the acquisition and transfer of knowledge. Cogn Technol Work 2:164–177. https://doi.org/10.1007/PL00011499
Müller R, Urbas L (2017) Cognitive challenges of changeability: multi-level flexibility for operating a modular chemical plant. Chem Ing Tech. https://doi.org/10.1002/cite.201700029
Mumaw RJ, Roth EM, Vicente KJ, Burns CM (2000) There is more to monitoring a nuclear power plant than meets the eye. Hum Factors 42:36–55. https://doi.org/10.1518/001872000779656651
Nemirovsky R (2002) On guessing the essential thing. In: Gravemeijer K, Lehrer R, van Oers B, Verschaffel L (eds) Symbolizing, modeling and tool use in mathematics education. Springer, Dordrecht, pp 233–256
Nyhuis P et al (2008) Wandlungsfähige Produktionssysteme—Fit sein für die Produktion von morgen. Zeitschrift für wirtschaftlichen Fabrikbetrieb 103:333–337
O’Reilly JX (2013) Making predictions in a changing world—inference, uncertainty, and learning. Front Neurosci 7:1–10. https://doi.org/10.3389/fnins.2013.00105
Oppelt M (2016) Towards an integrated use of simulation within the life-cycle of a process plant. Shaker Verlag GmbH, Aachen
Rasmussen J (1983) Skills, rules, and knowledge; signals, signs, and symbols, and other distinctions in human performance models. IEEE Trans Syst Man Cybern SMC 13:257–266. https://doi.org/10.1109/TSMC.1983.6313160
Rasmussen J (1986) Information processing and human machine interaction: an approach to cognitive engineering. North-Holland, New York
Rasmussen J, Pejtersen AM, Goodstein LP (1994) Cognitive systems engineering. Wiley, New York
Reiner M, Slotta JD, Chi MTH, Resnick LB (2000) Naive physics reasoning: a commitment to substance-based conceptions. Cogn Instr 18:1–34. https://doi.org/10.1207/S1532690XCI1801_01
Roth W-M, Jornet A (2013) Situated cognition. Wiley Interdiscip Rev Cogn Sci 4:463–478. https://doi.org/10.1002/wcs.1242
Roth W-M, Mavin TJ, Munro I (2015) How a cockpit forgets speeds (and speed-related events): toward a kinetic description of joint cognitive systems. Cogn Technol Work 17:279–299. https://doi.org/10.1007/s10111-014-0292-0
Sarter NB, Woods DD (1992) Mode error in supervisory control of automated systems. Proc Hum Factors Ergon Soc Annu Meet 36:26–29. https://doi.org/10.1177/154193129203600108
Schoultz J, Säljö R, Wyndhamn J (2001) Heavenly talk: discourse, artifacts, and children’s understanding of elementary astronomy. Hum Dev 44:103–118. https://doi.org/10.1159/000057050
Scribner S (1986) Thinking in action: some characteristics of practical thought. In: Sternberg RJ, Wagner RK (eds) Practical intelligence: nature and origins of competence in the everyday world. Cambridge University Press, Cambridge, pp 13–30
Sheridan TB (2011) Adaptive automation, level of automation, allocation authority, supervisory control, and adaptive control: distinctions and modes of adaptation. IEEE Trans Syst Man Cybern Part A Syst Hum 41:662–667 https://doi.org/10.1109/TSMCA.2010.2093888
Smith P, Blandford A, Back J (2009) Questioning, exploring, narrating and playing in the control room to maintain system safety. Cogn Technol Work 11:279–291. https://doi.org/10.1007/s10111-008-0116-1
Soo K, Mavin TJ, Roth W-M (2016) Mixed-fleet flying in commercial aviation: a joint cognitive systems perspective. Cogn Technol Work 18:449–463. https://doi.org/10.1007/s10111-016-0381-3
Speekenbrink M, Shanks DR (2010) Learning in a changing environment. J Exp Psychol Gen 139:266–298. https://doi.org/10.1037/a0018620
Spiro RJ, Vispoel WP, Schmitz JG, Samarapungavan A, Boerger AE (1987) Knowledge acquisition for application: cognitive flexibility and transfer in complex content domains. In: Britton BK, Glynn SM (eds) Executive control processes in reading. Erlbaum, Hillsdale, pp 177–199
Stokes PD, Lai B, Holtz D, Rigsbee E, Cherrick D (2008) Effects of practice on variability, effects of variability on transfer. J Exp Psychol Hum Percept Perform 34:640–659. https://doi.org/10.1037/0096-1523.34.3.640
Urbas L, Doherr F, Krause A, Obst M (2012) Modularisierung und Prozessführung. Chem Ing Tech 84:615–623. https://doi.org/10.1002/cite.201200034
VandeWalle D, Brown SP, Cron WL, Slocum JWJ (1999) The influence of goal orientation and self-regulation tactics on sales performance: a longitudinal field test. J Appl Psychol 84:249–259. https://doi.org/10.1037/0021-9010.84.2.249
Vicente KJ, Burns CM (1996) Evidence for direct perception from cognition in the wild. Ecol Psychol 8:269–280. https://doi.org/10.1207/s15326969eco0803_5
Vollmeyer R, Burns BD, Holyoak KJ (1996) The impact of goal specificity on strategy use and the acquisition of problem structure. Cogn Sci 20:75–100. https://doi.org/10.1207/s15516709cog2001_3
Vosniadou S, Brewer WF (1992) Mental models of the earth: a study of conceptual change in childhood. Cogn Psychol 24:535–585. https://doi.org/10.1016/0010-0285(92)90018-W
Vosniadou S, Mason L (2012) Conceptual change induced by instruction: a complex interplay of multiple factors. In: Harris KR, Graham S, Urdan T, Graham S, Royer JM, Zeidner M (eds) APA educational psychology handbook, vol 2: individual differences and cultural and contextual factors. American Psychological Association, Washington, DC, pp 221–246
Wenger E (2010) Communities of practice and social learning systems: the career of a concept. In: Blackmore C (ed) Social learning systems and communities of practice. Springer, London, pp 179–198
Wenger E, Trayner B, de Laat M (2011) Promoting and assessing value creation in communities and networks: a conceptual framework. Ruud de Moor Centrum, Open Universiteit, Heerlen
Winters D, Latham GP (1996) The effect of learning versus outcome goals on a simple versus a complex task. Group Organ Manag 21:236–250. https://doi.org/10.1177/1059601196212007
Wiser M (1986) The differentiation of heat and temperature: an evaluation of the effect of microcomputer teaching on students’ misconceptions. Technical Report 87-5. Educational Technology Center, Cambridge, MA
Acknowledgements
Parts of this work were supported by a grant of the German Research Foundation (PA 1232/6-1). I am especially thankful to Leon Urbas for providing lots of inspiration over the last years, for many valuable discussions about modular plants and the associated operator requirements, and for support in constructing some of the modular plant examples used in this article. Moreover, I want to thank two anonymous reviewers for their valuable feedback on an earlier version of the manuscript.
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Müller, R. Cognitive challenges of changeability: adjustment to system changes and transfer of knowledge in modular chemical plants. Cogn Tech Work 21, 113–131 (2019). https://doi.org/10.1007/s10111-018-0489-8
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DOI: https://doi.org/10.1007/s10111-018-0489-8