Abstract
This chapter discusses the design of a curriculum with main focus on human-oriented scientific knowledge and how this can be exploited to develop support for humans by means of advanced smart devices in the daily environment. The aim for this curriculum was to offer a study path for those students with exact talents but with an interest mainly in human processes and society. The curriculum was designed from a problem-oriented perspective in relation to societal problem areas. From human-oriented disciplines scientific knowledge for human processes in such problem areas was obtained. Computational modeling for such human processes plays a central role as an integrating factor in the curriculum. Elements from Ambient Intelligence, Artificial Intelligence, and Informatics are included for design of smart support systems.
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R. Ashby, Design for a Brain (Chapman and Hall, London, 1952)
M.H. Ashcraft, Cognition (Prentice Hall, Upper Saddle River, 2005)
R.D. Beer, A dynamical systems perspective on agent-environment interactions. Artif. Intell. 72, 173–215 (1995a)
T. Bosse, C.M. Jonker, L. van der Meij, J. Treur, A language and environment for analysis of dynamics by simulation. Int. J. Artif. Intell. Tools 16, 435–464 (2007)
T. Bosse, C.M. Jonker, L. van der Meij, A. Sharpanskykh, J. Treur, Specification and verification of dynamics in agent models. Int. J. Coop. Inf. Syst. 18, 167–193 (2009)
T. Bosse, M. Hoogendoorn, M.C.A. Klein, J. Treur, A three-dimensional abstraction framework to compare multi-agent system models, in Proceedings of the Second International Conference on Computational Collective Intelligence, ICCCI’10, Part I. Lecture Notes in Artificial Intelligence, vol. 6421 (Springer, 2010), pp. 306–319
T. Bosse, C.G. Gerritsen, M. Hoogendoorn, S.W. Jaffry, J. Treur, Agent-based versus population-based simulation of displacement of crime: a comparative study. Web Intell. Agent Syst. J. 9, 147–160 (2011a)
T. Bosse, M. Hoogendoorn, M.C.A. Klein, R.M. van Lambalgen, P.P. vanMaanen, J. Treur, Incorporating human aspects in ambient intelligence and smart environments, in Handbook of Research on Ambient Intelligence and Smart Environments: Trends and Perspectives, eds. by N.Y. Chong, F. Mastrogiovanni (IGI Global, 2011b), pp. 128–164
T. Bosse, M. Hoogendoorn, M.C.A. Klein, J. Treur, An ambient agent model for monitoring and analysing dynamics of complex human behaviour. J. Ambient Intell. Smart Environ. 3, 283–303 (2011c)
T. Bosse, S.W. Jaffry, G. Siddiqui, J. Treur, Comparative analysis of agent-based and population-based modelling in epidemics and economics. Multi-Agent Grid Syst. J. 8, 223–255 (2012)
J.R. Busemeyer, J.R. Diederich, Cognitive Modeling (SAGE Publications, 2010)
S.P. Fraser, A.M. Bosanquet, The curriculum? That’s just a unit outline, isn’t it? Stud. High. Educ. 31, 269–284 (2006)
H. Gleitman, A.J. Fridlund, D. Reisberg, Psychology, 6th edn. (Norton & Company Inc, New York, 2004)
G. Hamstra et al., Haalbaarheidsonderzoek Human Ambience (Right Marktonderzoek en Advies B.V, 2007)
Joint Quality Initiative Group, Shared ‘Dublin’ descriptors for short cycle, first cycle, second cycle and third cycle awards (2004). www.jointquality.org/content/descriptors/CompletesetDublinDescriptors.doc
M. Mäkinen, J. Annala, Meanings behind curriculum development in higher education. Prime 4, 1744–2494 (2010)
L. Mears, M. Omar, T.R. Kurfess, Automotive engineering curriculum development: case study for Clemson University. J. Intell. Manuf. 22, 693–708 (2011). doi:10.1007/s10845-009-0329-z
J.R. Michelcic, J.C. Crittenden, M.J. Small, D.R. Shonnard, D.R. Hokanson, Q. Zhang, H. Chen, S.A. Sorby, V.U. James, J.W. Sutherland, J.L. Schnoor, Sustainability science and engineering: the emergence of a new metadiscipline. Environ. Sci. Technol. 37, 5314–5324 (2003)
J.H. Miller, S.E. Page, Complex Adaptive Systems: An Introduction to Computational Models of Social Life (Princeton Studies in Complexity, 2007)
S. Nolen-Hoeksema, Abnormal Psychology (McGraw-Hill, 2005)
R. Port, T. van Gelder, Mind as Motion: Explorations in the Dynamics of Cognition (MIT/Bradford, 1995)
A. Sharpanskykh, J. Treur, Group Abstraction for Large-Scale Agent-Based Social Diffusion Models, in Proceedings of the Third International Conference on Social Computing, SocialCom’11, eds. by J. Zhan, M. Pantic, A. Vinciarelli (IEEE Computer Society Press, 2011), pp. 830–837
A. Sharpanskykh, J. Treur, Abstraction relations between internal and behavioural agent models for collective decision making. Web Intell. Agent Syst. J. 10, 465–484 (2012a)
A. Sharpanskykh, J. Treur, An ambient agent architecture exploiting automated cognitive analysis. J. Ambient Intell. Humaniz. Comput. 3, 219–237 (2012b)
S. Shay, Curriculum formation: a case study from history. Stud. High. Educ. 36, 315–329 (2011)
A.B. Shiflet, G.W. Shiflet, Introduction to Computational Science: Modeling and Simulation for the Sciences (Princeton University Press, 2006)
E.R. Smith, T.M. Mackie, Social Psychology (Worth Publishers, New York, 1999)
J. Treur, Bachelor Study Human Ambience (in Dutch). Report (VU University Amsterdam, Department of Computer Science, Amsterdam, 2007), p. 83
J. Treur, On human aspects in ambient intelligence, in Proceedings of the First International Workshop on Human Aspects in Ambient Intelligence, HAI’07. Published in: Communications in Computer and Information Science (CCIS), vol. 11 (Springer, 2008), pp. 262–267
J. Treur, On the use of reduction relations to relate different types of agent models. Web Intell. Agent Syst. J. 9, 81–95 (2011a)
J. Treur, Specification of interlevel relations for agent models in multiple abstraction dimensions, in Proceedings of the 24th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE’11, Part II, ed. by K.G. Mehrotra et al. Lecture Notes in Artificial Intelligence, vol. 6704 (Springer, 2011b), pp. 542–555 (Extended version in: International Journal of Modeling, Simulation, and Scientific Computing, vol. 4(1), 1250026, 2013, pp. 1–27)
J. Treur, Designing a problem-oriented multi-disciplinary academic curriculum: integrating biomedical, psychological, and social sciences with ambient intelligence, artificial intelligence and informatics, in Proceedings of the Third World Conference on Learning, Teaching and Educational Leadership, WCLTA’12, ed. by H.F. Odabasi. Procedia Social and Behavioral Sciences, vol. 93 (Elsevier, 2013), pp. 258–265
E.P. Widmaier, H. Raff, K.T. Strang, Vander, Sherman en Luciano’s Human Physiology (MacGraw Hill, 2004)
Acknowledgments
The author is grateful to a large number of colleagues, who have, during discussions, deepened his insight into this area, and provided encouragement to go ahead with the challenging enterprise, among whom are Tibor Bosse, Frank van Harmelen, Mark Hoogendoorn, Johan Hoorn, Michel Klein, Peter-Paul van Maanen, Andre Spijkervet, Maarten van Steen, Gerrit van der Veer, Chris Verhoef, and Natalie van der Wal.
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Treur, J. (2016). Multidisciplinary Education. In: Network-Oriented Modeling. Understanding Complex Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-45213-5_17
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DOI: https://doi.org/10.1007/978-3-319-45213-5_17
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