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Teaching ill-defined problems in engineering

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Abstract

Ill-defined problems are found in many real-world situations and involve both technical and societal issues. Thus, engineering education must prepare students to address such problems. This paper presents a methodology that combines a metacognitive model with question-prompts to guide students in defining and solving ill-defined engineering problems. The proposed methodology is based on the concept of Weltanschauung, a term that pertains to the view through which the world is perceived, i.e., the "worldview." Three case studies illustrate the methodology. The first case study focuses on an engineering economics problem; the second focuses on a business reengineering problem, and the third focuses on product design. In all three cases, the participating students were able to define the problem with little or no instructor help. The findings suggested that the students could more easily connect the problem domain with other learning. Also, results showed that the approach led to an increased engagement level, ignited student curiosity, and enabled them to acquire new skills or knowledge, expanding their creativity and innovation.

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Notes

  1. Activities are also referred to as process in the Object-Process Methodology standard [28]

  2. As defined in [28], possible individuals are entities that exist in space and time, including physical objects like a table or imaginary individuals like Spiderman.

References

  1. Savery, J.: Overview of problem-based learning: definitions and distinctions. Interdiscip. J. Prob. Based Learn. 1(1), 9–20 (2006)

    Google Scholar 

  2. Nichols, M., Cator, K., Torres, M.: Challenge Based Learner User Guide. Digital Promise, Redwood City, CA (2016)

    Google Scholar 

  3. Laxman, K.: A conceptual framework mapping the application of information search. Comput. Educ. 55, 513–526 (2010)

    Article  Google Scholar 

  4. DaVia Rubenstein, L., Callan, G., SpeirsNeumeister, K., Ridgley, L.: Finding the problem: how students approach problem identification. Think. Skills Creat. 35, 100635 (2020)

    Article  Google Scholar 

  5. Jonassen, D.: Toward a design theory of problem solving. Educ. Tech. Res. Dev. 48(4), 63–85 (2000)

    Article  Google Scholar 

  6. Greenwald, L.: Learning from problems. Sci. Teach. 67(4), 28–32 (2000)

  7. Hew, K., Knapczyk, D.: Analysis of ill-structured problem solving, mentoring functions, and perceptions of practicum teachers and mentors toward online mentoring in a field-based practicum. Instr. Sci. 35, 1–40 (2007)

    Article  Google Scholar 

  8. Rittel, H., Webber, M.: Dilemmas in a general tehory of planning. Policy Sci. 4, 155–169 (1973)

    Article  Google Scholar 

  9. Lönngren, J., Adawi, T., Svanström, M.: Wicked problems and assessment in engineering education: Developing and evaluating an analytic rubric. In: Proceedings of the 7th Research in Engineering Education Symposium, Bogota, Colombia (2017)

  10. Kitchener, K.: Cognition, metacognition, and epistemic cognition: a three-level model of cognitive processing. Hum. Dev. 26(4), 222–232 (1983)

    Article  Google Scholar 

  11. Murphy, E.: Identifying and measuring ill-structured problem formulation and resolution in online asynchronous discussions. Can. J. Learn. Technol. 30(1), 5–20 (2004)

    Article  Google Scholar 

  12. Sinnott, J.: A model for Solution of Ill-Structured Problems: Implications for Everyday and Abstract Problem Solving. Praeger, New York (1989)

    Google Scholar 

  13. Ge, X., Land, S.: Scaffolding students’ problem solving processes in an ill-structured task using question prompts and peer interactions. Educ. Tech. Res. Dev. 51(1), 21–38 (2003)

    Article  Google Scholar 

  14. Wood, D., Bruner, J., Ross, G.: The role of tutoring in problem solving. J. Child Psychol. Psychiatry Appl. Discip. 17, 89–100 (1976)

    Article  Google Scholar 

  15. Grohs, J., Kirk, G., Soledad, M., Knight, D.: Assessing systems thinking: a tool to measure complex reasoning through Ill-structured problems. Think. Skills Creat. 28, 110–130 (2018)

    Article  Google Scholar 

  16. Tawfik, A.: Do cases teach themselves? A comparison of case library prompts in supporting problem-solving during argumentation. J. Comput. High. Educ. 29(2), 267–285 (2017)

    Article  Google Scholar 

  17. Rourke, A., Sweller, J.: The worked-example effect using ill-defined problems: learning to recognise designers’ styles. Learn. Instr. 19, 185–199 (2009)

    Article  Google Scholar 

  18. Kim, J., Lim, K.: Promoting learning in online, ill-structured problem solving: the effects of scaffolding type and metacognition level. Comput. Educ. 138, 116–129 (2019)

    Article  Google Scholar 

  19. Middleton, H.: Complex problem solving in a workplace setting. Int. J. Educ. Res. 37, 67–84 (2002)

    Article  Google Scholar 

  20. Lamp, J.: Using Petri Nets to Model Weltanschauung Alternatives. In: Soft Systems Methodology Australian Conference on Requirements Engineering, pp. 91–100 (1998)

  21. Chandrasekaran, B.: AI in design: review and prospects. AIChE Symp. Ser. 92(132), 175–183 (1996)

    Google Scholar 

  22. Klir, G.: Architecture of Systems Problem Solving. Plenum Press, New York (1985)

    Book  Google Scholar 

  23. Marquardt, W.: An object-oriented representation of structured process models. Comput. Chem. Eng. 16, S329–S336 (1992)

    Article  Google Scholar 

  24. Bogusch, R., Marquardt, W.: A formal representation of process model equations. Comput. Chem. Eng. 21(10), 1105–1115 (1997)

    Article  Google Scholar 

  25. Object Management Group: OMG Systems Modeling Language 16th edn. (2019). Available at: https://www.omg.org/spec/SysML/1.6/PDF

  26. Batres, R., Naka, Y., Lu, M.-L.: A multidimensional design framework and its implementation in an engineering design environment. Concurr. Eng. 7(1), 43–54 (1999)

    Article  Google Scholar 

  27. Batres, R., West, M., Leal, D., Price, D., Masaki, K., Shimada, Y., Fuchino, T., Naka, Y.: An upper ontology based on ISO 15926. Comput. Chem. Eng. 31(5–6), 519–534 (2007)

    Article  Google Scholar 

  28. Dori, D.: Object-Process Methodology. Springer-Verlag, Berlin Heidelberg (2002)

    Book  Google Scholar 

  29. Subramaniam, G., Gosavi, A.: Simulation-based optimisation for material dispatching in Vendor-Managed Inventory systems. Int. J. Simul. Process Model. 3, 238–245 (2007)

    Article  Google Scholar 

  30. Fey, V., Rivin, E.: Innovation on Demand, 4th edn. Cambridge University Press, New York (2011)

    Google Scholar 

  31. Gero, J., Kannengiesser, U.: A function–behavior–structure ontology of processes. Artif. Intell. Eng. Des. Anal. Manuf. 21, 379–391 (2007)

    Article  Google Scholar 

  32. McCarthy, B.: Using the 4MAT system to bring learning styles to schools. Educ. Leadersh. 48(2), 31–37 (1990)

    Google Scholar 

  33. Sterman, J.: Business Dynamics. McGraw-Hill, Boston (2000)

    Google Scholar 

  34. Savoia, A.: Pretotype It. In: Pretotyping. Available at: https://www.pretotyping.org/uploads/1/4/0/9/14099067/pretotype_it_2nd_pretotype_edition-2.pdf

  35. Council, S.: Supply Chain Operations Reference Model, Version 9.0 ISBN 0-615-20259-4. (2008)

  36. E. J. Barkmeyer (editor): SIMA Reference Architecture Part 1: Activity Models, The National Institute of Standards and Technology, Internal Report 5939, Gaithersburg, Maryland (1996). Available at: https://nvlpubs.nist.gov/nistpubs/Legacy/IR/nistir5939.pdf

  37. Santiago Acosta, R. D., Quezada Batalla, M. L., Hernández Medina, A., Hernández Cooper, E. M.: Challenge based learning physics and mathematics teaching. In: 10th International Conference on Education and New Learning Technologies (EduLearn), Palma, Spain, pp. 8303–8310 (2018)

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Acknowledgements

The author would like to acknowledge the financial and technical support of Writing Lab, Institute for the Future of Education, Tecnologico de Monterrey, Mexico, in the production of this work.

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Writing Lab, Tecnologico de Monterrey.

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  1. School of Engineering and Sciences, Tecnologico de Monterrey, Epigmenio González 500, San Pablo, 76130, Santiago de Querétaro, Mexico

    Rafael Batres

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Correspondence to Rafael Batres.

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Batres, R. Teaching ill-defined problems in engineering. Int J Interact Des Manuf 16, 1321–1336 (2022). https://doi.org/10.1007/s12008-022-00978-y

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