Hostname: page-component-7bb8b95d7b-cx56b Total loading time: 0 Render date: 2024-09-11T21:15:29.836Z Has data issue: false hasContentIssue false
  • English
  • Français

HELICAL Learning Model Applied in a Nanotechnology for Science and Engineering Course

Published online by Cambridge University Press:  01 February 2011

Eric Peterson ,
Morgan Reed ,
Jewel Gomes  and
David L. Cocke
Eric Peterson
Affiliation:
texas2eric@yahoo.com, Lamar University, Chemical Engineering, MLK Blvd, Beaumont, TX, 77710, United States
Morgan Reed
Affiliation:
mreed51@yahoo.com, Lamar University, Chemical Engineering, PO Box 10053, Beaumont, TX, 77710, United States
Jewel Gomes
Affiliation:
jaggomes2002@yahoo.com, Lamar University, Chemical Engineering, PO Box 10053, Beaumont, TX, 77710, United States
David L. Cocke
Affiliation:
deltagco@hotmail.com, Lamar University, Chemical Engineering, PO Box 10053, Beaumont, TX, 77710, United States
Get access

Abstract

In education, a popular model employed to represent the learning process is typically portrayed as a four-stage process signified by a cycle in a two-dimensional circular path. This cycle can be repeated by revisiting topics at increasing levels of sophistication in order to produce what is known as a spiral curriculum.

In this presentation, a variation of Kolb's two-dimensional learning cycle model is offered that represents the learning cycle as if it were a three-dimensional spiral or helix, with successive turns associated with increases in Bloom's Taxonomic level. This representation is explored and developed, with a specific example from a chemical engineering course offered in Industrial Electrochemistry. This more comprehensive concept-centered model for the learning cycle explicitly includes higher order thinking skills to promote creative thinking, through the application of concepts and can be used to develop more effective curricula and course instruction. Specifically, our sample class consists of four teams, each of which is responsible for becoming expert in the concepts associated with an area of science and another of application. Transfer of content is student driven while topics are explored. Students teaching each other allows for synergistic enhanced motivation to explore, with concurrent ultimate improvement in the retention of core concepts by the entire course population.

Keywords

educationnanoscalenanostructure
Type
Research Article
Information
MRS Online Proceedings Library (OPL) , Volume 1046: Symposium W – Forum on Materials Science and Engineering Education for 2020 , 2007 , 1046-W03-04
Copyright
Copyright © Materials Research Society 2008

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Meisen, Axel, Developing Global Perspectives for Engineering Students: A North American View, 2003 ECI Conference on Enhancement of the Global Perspective for Engineering Students by Providing an International Experience, Tomar, Portugal, Editors: McHargue, Carl and Baum, Eleanor 2004, Paper 4Google Scholar
2. Leung, Peter, Ishii, Kosuke and Benson, Jan “MODULARIZATION OF WORK TASKS FOR GLOBAL ENGINEERING” Proceedings of IMECE2005 2005 ASME International Mechanical Engineering Congress and Exposition November 5-11, 2005, Orlando, Florida USA Google Scholar
3.2006-2007 Criteria for Accrediting Engineering Programs, p.2, ABET, Inc., Baltimore, MD, 2006Google Scholar
4. Cocke, D.L., Gomes, J.A.G., Moreno, H., Peterson, E., (2006), “Unified Teaching Strategy of Air Chemistry in Engineering, Proceedings ASEE Gulf-Southwest Annual Conference, Baton Rouge, LA 2006 Google Scholar
5. O'Connor, J., Peterson, E., Gomes, J.A.G., Moreno, H., Cocke, D.L., (2006), Helical Learning Model, Modeling in Physics and Physics Education, 20 - 25 August 2006, AMSTEL institute, Faculty of Science, University of Amsterdam, NetherlandsGoogle Scholar
6. Bruner, J., The Process of Education, Harvard University Press, Cambridge, MA, 1960 Google Scholar
7.Enquiry-based learning, cognitive acceleration and the spiral curriculum: Jerome Bruner's constructivist view of teaching and learning, http://www.gtce.org.uk/policyandresearch/research/ROMtopics/brunerROM/studyGoogle Scholar
8. Collura, M.A., Bouzid, A., Daniels, S., Nocito-Gobel, J., (2004), “Development of a Multidisciplinary Engineering Foundation Spiral”, 2004 ASEE Annual Conference ProceedingsGoogle Scholar
9.Work in Progress - Spiral Curriculum Approach to Reformulate Engineering Curriculum Lohani, Vinod K., Mallikarjunan, Kumar, Wolfe, Mary Leigh, Wildman, Terry, Connor, Jeff, Muffo, John, Lo, Jenny1, Knott, Tamara W., Loganathan, G. V., Goff, Richard, Chang, Mike, Cundiff, John, Adel, Greg, Agblevor, Foster, Gregg, Mike, Vaughan, David, Fox, Ed, Griffin, Hayden, Mostaghimi, Saied, 2005 IEEE October 19 – 22, 2005, Indianapolis, IN 35th ASEE/IEEE Frontiers in Education Conference.Google Scholar
10.Stanford Center for Innovations in Learning, http://sll.stanford.edu/pubs/jeepark/pblsite/skipintro.htmGoogle Scholar
11. Rogers, C.R. & Freiberg, H.J. (1994). Freedom to Learn (3rd Ed). Columbus, OH: Merrill/Macmillan.Google Scholar
12. Bloom, B. S. (1956). Taxonomy of Educational Objectives, Handbook I: The Cognitive Domain. New York: David McKay Co Inc Google Scholar
13. Kolb, D. A. (1984). Experiential Learning: Experience as the Source of Learning & Development. Englewood Cliffs, NJ, Prentice-Hall Google Scholar
14. Felder, R.M. and Silverman, L.K., Learning and teaching styles in engineering education. J. of Eng. Ed., 78, 7, 674–681 (1988)Google Scholar
15. Arons, A., “A Guide to Introductory Physics Teaching”, John Wiley & Sons, 1990 Google Scholar
16. McDermott, L.C., (1991), Millikan Lecture 1990- “What we teach and what is learned- Closing the gap”, American Journal of Physics V. 59, pp. 301–315 Google Scholar
17. Harb, , Terry, , Hurt, , and Williamson, , “Teaching Through the Cycle – Application of Learning Style Theory to Engineering Education at Brigham Young University”, BYU Press, Provo, Utah, 1991 Google Scholar
18. Terry, and Harb, , “Kolb, Bloom, Creativity, and Engineering Design”, Proceedings the American Society of Engineering Education, Annual Conference, 1993Google Scholar
19. Redish, E.F., (1996), “New Models of Physics Instruction Based on Physics Education Research”, Proceedings of the Deustchen Physikalischen Gesellschaft Jena ConferenceGoogle Scholar
20. Tella, S. & Mononen-Aaltonen, M. (2000), Towards Network-Based Education: A Multidimensional Model for Principles of Planning and Evaluation. In Tella, S. (ed.) Media, Mediation, Time and Communication: Emphases in Network-Based Media Education. Media Education Centre. Department of Teacher Education. University of Helsinki. Media Education Publications 9, 1-58.Google Scholar
21. Novak, J. D. (1965). A model for the interpretation and analysis of concept formation. Journal of Research in Science Teaching, 3: 72–83.Google Scholar
22. Inelmen, , Erol, , Re-inventing engineering education: a new challenge, World Transactions on Engineering and Technology Education 2002 UICEE, Vol.1, No.1, 2002.Google Scholar
23. Hoz, R., and Gonik, N. The use of concept mapping for knowledge-oriented evaluation in nursing education. Evaluation and Research in Education. 15(4): 207–227, 2001.Google Scholar
24.Concept Maps: Theory, Methodology, Technology, Proc. of the First Int. Conference on Concept Mapping, Cañas, A.J., Novak, J. D., González, F. M., Eds., Pamplona, Spain 2004.Google Scholar
25. Lanzing, , Jan, , The Concept Mapping Homepage, http://users.edte.utwente.nl/lanzing/cm_home.htmGoogle Scholar
26. Cocke, D., , Li, -Y., K., and Hopper, Jack, 2000, “Computer-Aided Modeling and Simulation to Improve Undergraduate Chemical Engineering Education”, NSF Award #9981152, June 1, 2000 to May 31, 2003.Google Scholar
27. Cornwell, P.J., “Concept Maps in the Mechanical Engineering Curriculum”, Proceedings of the 1996 ASEE Annual Conference, Washington D.C., June 1996.Google Scholar
28.Formal Concept Analysis Foundations and Applications Series: Lecture Notes in Computer Science Subseries:Lecture Notes in Artificial Intelligence, Vol. 3626 Ganter, , Bernhard, ; Stumme, , Gerd, ; Wille, , Rudolf, (Eds.).Google Scholar
29. Stutt, A. (1997) Knowledge Engineering Ontologies, Constructivist Epistemology, Computer Rhetoric: A Trivium for the Knowledge Age. Proceedings of Ed-Media-97, June 1997, Calgary, Canada.Google Scholar
30. Kolb, D., and Fry, R., 1975, “Towards an applied theory of experiential learning”, In Theories of group processes, ed. Copper, C.L., pp. 33–58, John Wiley, London.Google Scholar
31. Manahan, S.E., 1991, Environmental Chemistry, p. 2, Lewis Publishers, Inc., MI.Google Scholar
32. Peterson, E., O'Connor, J., Gomes, J.A.G., Moreno, H., Reed, M., Cocke, D.L., (2007), HELICAL Learning Model Applied in an Industrial Engineering Course, 114th Annual ASEE Conference & Exposition, June 24-27, Honolulu, HI 2007.Google Scholar