Friday , April 19 2024

E-Maieutics in Post-industrial Engineering Education

Constantin OPREAN, Claudiu V. KIFOR, Boldur E. BĂRBAT, Dorin D.M. BANCIU
Lucian Blaga University of Sibiu
10 Victoriei Blv., 550024, Sibiu, Romania

“Man cannot remake himself without suffering, for he is both the marble and the sculptor.”

ALEXIS CARREL

Abstract: The paper continues research about adapting engineering education to lifelong learning in a service-based society. Since the solution proposed was based on ‘e-maieutics’, the paper aims at illustrating this new concept by using doctoral studies in Computers and Information Technology as testbench. This target is approached through four sub-objectives: a) Investigating heutagogy and meta-learning as main implementation tools. b) Exploring the role of agent-orientation in lifelong learning within the post-industrial era from three perspectives: non-engineering specialties, engineering education, and IT). c) Illustrating the first attempt to test e-maieutics in a real-world situation. d) Suggesting (by serendipity) the need of easing paradigm shifts by instilling into syllabi elements of transdisciplinary knowledge. After reassessing conclusions of recent research the paper proposes a flexible holistic approach based on heutagogy and meta-learning (for learners) and on simulating e-maieuts through doctoral advisors (for teachers). On this groundwork, some heutagogic guidelines are outlined considering the threefold role of agents, the paradigmatic shifts made urgent by the unprecedented speed of change (due to Moore’s law) as well as some metascience basics and elements of transdisciplinary knowledge, necessary to explore and exploit the transdisciplinary niches entailed by modern post-industrial engineering education. Conclusion: approach and provisional results are promising.

Keywords: E-Maieutics; Knowledge Society (KS); Engineering Education (EE); Lifelong Learning (LL); Agent Orientation (AO).

>>Full text
CITE THIS PAPER AS:
Constantin OPREAN, Claudiu V. KIFOR, Boldur E. BĂRBAT, Dorin D. M. BANCIU, E-Maieutics in Post-industrial Engineering Education, Studies in Informatics and Control, ISSN 1220-1766, vol. 23 (3), pp. 55-66, 2010.

1. Introduction. Why Carrel?

Taking advantage of not being heavily constrained by length restrictions, the paper can afford: a) the minimal redundancy required to be self-contained; b) broadening the scope of ‘transdisciplinary links in agent-orientation’ [31]; c) idem for implementing e-maieutics [3] via heutagogy and meta-learning ; d) giving details about testing and evaluating in January 2010 the first results of this long-term endeavour.

This paper is the sixth from a series of seven describing an undergoing research about ‘Innovating Engineering Education, to Face the Knowledge Society’ (the title of the third paper [30]; the history is abridged in Section 2).

The paper continues the series about adapting engineering education (EE) to lifelong learning (LL) in a service-based society. Since the solution proposed [24] was based on ‘e-maieutics’, the short term target is to explore further this concept using as testbench doctoral studies in Computers and Information Technology. This target is approached through four sub-objectives: a) Investigating heutagogy and meta-learning as main implementation tools. b) Scrutinising the role of agent-orientation (AO) in LL within the post-industrial era from three perspectives: non-engineering specialties, engineering education, and IT. c) Illustrating the first attempt to test e-maieutics in a real-world situation. d) Suggesting (by serendipity) a way of easing paradigmatic shifts by instilling into syllabi metascience basics as well as elements of transdisciplinary knowledge. Thus, the paper suggests a flexible holistic approach based on heutagogy and meta-learning (for students) and on simulating e-maieuts by active teachers (firstly for doctoral advisors).

In this picture, the motto fits in many ways: a) It highlights the difficulty of accepting a rising Zeitgeist. b) Descending from the universal to the particular, it suggests recursion as regards both heuatgogy [27] and meta-learning [1]. c) Though, it avoids self-recursion (as used to in cloning). d) On the contrary, the multivalued hypostatic abstractions linking man’s life (as evolutive process) to sculpture (as artistic endeavour) are inherently holistic and anti-entropic. e) Limiting further the conceptual space to intellectual processes (first of all learning as underpinning of human remake), the motto suggests the pre-eminence of right brain hemisphere features in all complex human-related processes.

To escape the objection that such construals are too stretched out, here follow some key ideas of Alexis Carrel (elaborated upon in [10] or condensed in quotes) showing that he was a remarkable forerunner of the – albeit yet fuzzy depicted – “KS Zeitgeist” this paper is filled with. (The new paradigms for AO are outlined in [15].): a) In man, the things that are not measurable are more important than those that are measurable. b) Science has to be understood in its broadest sense, as a method for comprehending all observable reality, and not merely as an instrument for acquiring specialized knowledge. c) A few observations and much reasoning lead to error; many observations and a little reasoning to truth. d) An absolute can only be given in an intuition, while all the rest has to do with analysis. In fact, in [10] Carrel realised (in both senses of the word) much more: a) Comparing the energy consumption of the brain with that of the biceps, he has foregone Information Theory. b) Likewise, he has foregone the General Systems Theory (e.g.: emphasising the basic role of the endocrine system in any state of mind, he promoted systemic thinking in what is now called psychosomatic medicine). c) Still, vital for EE is his warning against the trend of the industrial era Zeitgeist to favour the simple (reductionist) approach of “exact sciences” instead of encouraging the (albeit more difficult) systemic (holistic) approach not just in medicine but also in all human-related research. (In this regard, Carrel set up the principles of anthropocentrism, decades before artificial intelligence – or even modern computers – were born.)

In line with these ideas, after abridging the series history and updating related work in Section 2, the paper proposes in Section 3 a flexible holistic approach focusing on heutagogy AND meta-learning – as implementation mechanisms for e-maieutics. Section 4 explains the threefold role of agents in higher education preparing for LL, while Section 5 presents doctoral studies in artificial intelligence as testbench for the proposed approach (during the academic year 2009-2010). Some guidelines and examples of applying transdisciplinarity are offered in Section 6, via the metaphor of Computer-Aided Mercator. Section 7 evaluates and closes the paper.

REFERENCES

  1. ANDERSON. M. L., T. OATES, A Review of Recent Research in Metareasoning and Meta-learning, AI Magazine, aaai.org, 2007.
  2. BĂRBAT, B. E., From e-Learning to e-Nursing, Applying Non-Algorithmic Paths, Medinf 2007 Workshop: E-Learning aspects in medicine and nursing. 29th Int. Conf. of the Romanian Medical Informatics Society, Sibiu, 2007. (On CD.)
  1. BĂRBAT, B. E., E-Maieutics. Rationale and Approach, Int. J. of Computers, Communications & Control, 3, Suppl. S, (http://www.britannica.com/bps/additionalcontent/18/33373698/Emaieutics-Rationale-and-Approach),
    2008, pp. 40-54.
  2. BĂRBAT, B. E., Interface Agents for Transcultural Communication: A Framework, The good, the Bad and the Challenging: The user and the Future of Information and Communication Technologies (B. Sapio et al, Eds.), Conf. Proc. Copenhagen, COST Office, Brussels, Vol. 2, 2009, pp. 666-674.
  3. BĂRBAT, B. E., R. D. FABIAN, C. BRUMAR, R. S. MUNTEAN, Bounded Rationality and Approximation in Modern Artificial Intelligence, Proc. of the Int. Workshop New Approaches, Algorithms and Advanced Computational Techniques in Approximation Theory and its Applications (D. Simian, D. F. Sofonea, Eds.) , 2007, pp. 64-76.
  4. BĂRBAT, B. E., A. MOICEANU, I, Agent, The good, the Bad and the Unexpected: The User and the Future of Information and communication Technologies (B. Sapio et al, Eds.), Conf. Proc. Moscow, COST Office, Brussels, 1, 2007, pp. 357-365.
  5. BĂRBAT, B. E., A. MOICEANU, H. ANGHELESCU, Enabling Humans to Control the Ethical Behaviour of Persuasive Agents, Chap. 13 in E. Loos, et al (Eds.), The Social Dynamics of Information and Communication Technology, Ashgate, Aldershot, UK, 2008, pp. 191-203.
  6. BĂRBAT, B. E., S. C. NEGULESCU, From Algorithms to (Sub-)Symbolic Inferences in Multi-Agent Systems, Int. J. of Computers, Communications & Control, 1, 3, 2006, 5-12.
  7. BRAŞOVEANU, A., A. MANOLESCU, R. URZICEANU, Generic Multimodal Ontologies (Accepted for ICCCC), 2010.
  8. CARREL, A., Man, The Unknown (translated from L’homme, cet inconnu), New York and London, Harper and Brothers, 1935.
  9. COLLINS, J., Lifelong Learning in the 21st Century and Beyond, RadioGraphics, 29, March, 2009, pp. 613-622.
  10. CONNER, M. L., Andragogy and Pedagogy, retrived, from Ageless Learner, 1997-2004: http://agelesslearner. com/intros/andragogy.html, 2009.
  11. COOK, M., From the Editor www.MercatorNet.com, Dec. 2, 2009.
  12. DENNETT, D. C., The Part of Cognitive Science That Is Philosophy, Topics in Cognitive Science 1, 2009, 231-236.
  13. DZIŢAC, I., B. E. B?RBAT, Artificial Intelligence + Distributed Systems = Agents, Int. J. of Computers, Communications & Control, IV, 1, 17-26, (http:/www.britannica.com/bps/additionalcontent/18/36182542/Artificial-Intelligence–Distributed-Systems –Agents), 2009.
  14. ESPOSITO, A., et al (Eds.), Multimodal Signals: Cognitive and Algorithmic Issues, LNAI 5398, Springer Verlag Berlin Heidelberg, 2009.
  15. FABIAN, R. D., M.-J. MANOLESCU, G. BOLOGA, Bounded Rationality, through the Sieve of the Lisbon Objectives (Accepted for ICCCC), 2010.
  16. GIRAUD-CARRIER, C., Meta-learning – A Tutorial, (www.icmla-conference.org /icmla08/slides2.pdf), 2008.
  17. GUARINO, N. The Ontological Level: Revisiting 30 Years of Knowledge Representation (A. Borgida et al, Eds.), Conceptual Modelling: Foundations and Applications, Springer Verlag, (http://www.loacnr.it/Papers/OntologicalLevelRevisited), 2009, pp. 52-67.
  18. HAMBRUSCH, S., et al, A Multidisciplinary Approach towards Computational Thinking for Science Majors, ACM SIGCSE Bulletin archive Vol. 41, (1) SIGCSE ’09 SESSION: Computational Thinking Across Disciplines, 2009, pp. 183-187.
  19. HASE, S., C. KENYON, Heutagogy: A Child of Complexity Theory, Complicity: An International Journal of Complexity and Education, 4, 1, 2007, pp. 111-118.
  20. HERRERA, F., Genetic Fuzzy Systems: Taxonomy, Current Research Trends and Prospects, Evol. Intel., 1, 2008, pp. 27-46.
  21. KEIFF, L., Dialogical Logic, The Stanford Encyclopedia of Philosophy, Edward N. Zalta (ed.), http://plato.stanfo rd.edu/entries/logicdialogical, 2009.
  22. KIFOR, C. V., et al., Engineering Education: Dense Teaching for Lifelong Learning, Proc. Balkan Reg. Conf. on Eng. and Bus. Edu. & Int. Conf. on Eng. and Bus. Edu., Sibiu, 2009, pp. 659-665.
  23. KLAMMA, R., et al, Social Software for Lifelong Learning, Educational Technology & Society, 10 (3), 2007, pp. 72-83.
  24. LASCU, A. E., A. V. GEORGESCU, From Extensity to Protensity in CAS: Adding Sounds to Icons, 16, 2009, pp. 130-136.
  25. MCAULIFFE, M., D. HARGREAVES, A. WINTER, G. CHADWICK, Does pedagogy still rule? Institution of Engineers Australia, Australasian J. of Eng. Education, 15, 1, 2009, pp. 13-17.
  26. OPREAN, C. A Bumpy Ride towards Reform: Higher Education Challenges Journeying from Sibiu to Lisbon via Bologna, EUprofile, Public Service Review: European Union, 18, 1-2, 2009.
  27. OPREAN, C. et al, Knowledge-Based Approach to Affordable Technological Innovation, Proc. 6th Int. Conf. on Manag. of Tech. Changes (C. Rusu, Ed.), Alexandroupolis, 2009, pp. 161-165.
  28. OPREAN, C., S. C. NEGULESCU, C. V. KIFOR, B. E. BĂRBAT, Innovating Engineering Education, to Face the Knowledge Society, Proc. of Balkan Reg. Conf. on Eng. and Bus. Edu. & Int. Conf. on Eng. and Bus. Edu., Sibiu, 2009, pp. 80- 85.
  29. OPREAN, C., C. V. KIFOR, S. C. NEGULESCU, B. E. BĂRBAT, Paradigm Shift in Eng. Edu., World Conf. on Educational Sciences, Bahçeşehir Univ., Istanbul), Feb. 2010.
  30. OPREAN, C., C. V. KIFOR, B. E. BĂRBAT, R. D. FABIAN, Bounded Rationality in Computer Science Curricula (submitted to the 2010 World Congress in Computer Science, Computer Eng., and Applied Computing, Las Vegas).
  31. PRUDÊNCIO, R. B. C., T. B. LUDERMIR, Active Meta-Learning with Uncertainty Sampling and Outlier Detection, Int. Joint Conf. on Neural Networks, Hong Kong, (http://www.cin.ufpe.br/~rbcp/papers/ijcnn-2008-final.pdf), 2008.
  32. SILVA, N. S. A., G. J. M. COSTA, S. ROGERSON, M. PRIOR, Knowledge or Content? The Philosophical Boundaries in e-Learning Pedagogical Theories, Research, Reflections and Innovations in Integrating ICT in Education, De Montfort University, Leicester, 2009, pp. 221-225.
  33. SMART, P., et al, Development of a Controlled Natural Language Interface for Semantic MediaWiki, Proc. of W-shop on Controlled Natural Language, Springer-Verlag, Heidelberg, 2010. (In Press.)
  34. WINTER, A., M. MCAULIFFE, D. HARGREAVES, G. CHADWICK, The Transition to Academagogy, Philosophy of Education Society of Australasia (PESA) Conf. 2008, QUT, Brisbane, Queensland (eprints. qut.edu.au/17367/1/17367.pdf), 2009.
  35. WINTER, A., M. MCAULIFFE, G. CHADWICK, D. HARGREAVES, Implementing Academagogy: The First Case Study, 20th Australasian Association for Engineering Education Conference, Book of Abstracts, University of Adelaide, 2009, p. 35.
  36. ZADEH, L. A., et al. (Eds.), From Natural Language to Soft Computing: New Paradigms in Artificial Intelligence, Romanian Academy Publishing House, 2008.

https://doi.org/10.24846/v19i1y201006