Journal of Science Education and Technology

, Volume 20, Issue 2, pp 146–155 | Cite as

Why School is not Easy: An Analytical Perspective

Article

Abstract

An overarching theory that enables a systematic study of learning recently has been developed. Motivation, for example, is something we all think weknow when we see. It was an important step to recognize that motivation can be conceptualized in terms of allocating working memory and especially attention to a learning task. The unified learning model (ULM) was synthesized from the literature with this in mind. Using the ULM as a basis for analysis, it is possible to consider all aspects of learning. A good place to begin concerns schools in general and why, in particular, school is not thought of as being easy. The ULM explains that allocating working memory often requires effort, and any exertion of such effort may be perceived as being hard. This paper is an analysis of school learning and especially science learning (STEM learning) in terms of the ULM.

Keywords

Learning Teaching Attention Motivation STEM Schools Working memory 

References

  1. Baddeley AD (1992) Working memory. Science 255:556–559CrossRefGoogle Scholar
  2. Baddeley AD, Hitch GJ (1974) Working memory. The psychology of learning and motivation, vol VIII. G. Bower, Academic Press, New York, pp 47–90Google Scholar
  3. Bandura A (1986) Social foundations of thought and action: a social cognitive theory. Prentice-Hall, Englewood CliffsGoogle Scholar
  4. Bloom BS (ed) (1956) Taxonomy of educational objectives: the classification of educational goals. D. McKay, New YorkGoogle Scholar
  5. Bloom B, Sosniak L (1985) Developing talent in young people. Ballantine Books, New YorkGoogle Scholar
  6. Brooks DW, Shell DF (2006) Working memory, motivation, and teacher-initiated learning. J Sci Educ Technol 15(1):17–30CrossRefGoogle Scholar
  7. Casner-Lotto J, Barrington L (2006) Are they really ready to work? Employers’ perspectives on the basic knowledge and applied skills of new entrants to the 21st century US workforce. The Conference Board, New YorkGoogle Scholar
  8. Cave paintings (2010) Wikipedia: the free encyclopedia. Wikimedia Foundation, Inc., Florida. Retrieved 2 Feb 2010, from http://www.wikipedia.org
  9. Colvin G (2008) Talent is overrated: what really separates world-class performers from everybody else. Penguin Group, New YorkGoogle Scholar
  10. Cosmelli D (2008) Attending to the stream of consciousness: a methodological challenge. In: Aboitiz F, Cosmelli D (eds) From attention to goal-directed behavior: neurodynamical, methodological and clinical trends. Springer, Dordrecht, pp 83–103Google Scholar
  11. Cowan N (1999) An embedded process model of working memory. In: Miyake A, Shah P (eds) Models of working memory. Cambridge University Press, Cambridge, pp 62–101Google Scholar
  12. Cowan N (2005) Working memory capacity. Psychology Press, New YorkCrossRefGoogle Scholar
  13. Coyle D (2009) The talent code. Greatness isn’t born. It’s grown. Here’s how. Random House, New YorkGoogle Scholar
  14. Emergence (2010) Wikipedia: the free encyclopedia. Wikimedia Foundation, Inc., Florida. Retrieved 2 Feb 2010, from http://www.wikipedia.org
  15. Episodic memory (2010) Wikipedia: the free encyclopedia. Wikimedia Foundation, Inc., Florida. Retrieved 2 Feb 2010, from http://www.wikipedia.org
  16. Ericsson KA, Krampe RT, Tesch-Römer C (1993) The role of deliberate practice in the Acquisition of expert performance. Psychol Rev 100(3):363–406CrossRefGoogle Scholar
  17. Euston DR, Tatsuno M, McNaughton BL (2007) Fast-forward playback of recent memory sequences in prefrontal cortex during sleep. Science 318:1147–1150CrossRefGoogle Scholar
  18. Exploratorium (1998) Common cents. Retrieved 2 Feb 2010, from http://www.exploratorium.edu/exhibits/common_cents/index.html
  19. Franklin B (1750) Paper on the academy. Retrieved 2 Feb 2010, from http://www.archives.upenn.edu/histy/features/1700s/bfacadpaper1750.html
  20. Geary D (2005) The origin of mind: evolution of brain, cognition, and general intelligence. American Psychological Association, Washington, DCCrossRefGoogle Scholar
  21. Geary DC (2008) An evolutionarily informed education science. Educ Psychol 43(4):179–195CrossRefGoogle Scholar
  22. Gladwell M (2008) Outliers: the story of success. Little, Brown, and Company, New YorkGoogle Scholar
  23. Gopnik A, Tenenbaum J (2007) Bayesian networks, Bayesian learning and cognitive development. Dev Sci 10(3):281–287CrossRefGoogle Scholar
  24. Hazy T, Frank M, O’Reilly R (2007) Towards an executive without a homunculus: computational models of the prefrontal cortex/basal ganglia system. Philos Trans Royal Soc B: Biol Sci 362(1485):1601CrossRefGoogle Scholar
  25. Hebbian learning (2010) Wikipedia: the free encyclopedia. Wikimedia Foundation, Inc., Florida. Retrieved 2 Feb 2010, from http://www.wikipedia.org
  26. Influenza A virus subtype H1N1 (2010) Wikipedia: the free encyclopedia. Wikimedia Foundation, Inc., Florida. Retrieved 2 Feb 2010, from http://www.wikipedia.org
  27. Inquiry-based learning (2010) Wikipedia: the free encyclopedia. Wikimedia Foundation, Inc., Florida. Retrieved 2 Feb 2010, from http://www.wikipedia.org
  28. Jilk D, Lebiere C et al (2008) SAL: an explicitly pluralistic cognitive architecture. J Exp Theor Artif Intell 20(3):197–218CrossRefGoogle Scholar
  29. Jung-Beeman M, Bowden EM, Haberman J, Frymiare JL, Arambel-Liu S, Greenblatt R et al (2004) Neural activity when people solve verbal problems with insight. PLoS Biol 2(4). Retrieved from doi: 10.1371/journal.pbio.0020097
  30. Kandel ER (2006) In search of memory: the emergence of a new science of mind. Norton, New YorkGoogle Scholar
  31. Kandel E, Frazier W, Waziri R, Coggeshall R (1967) Direct and common connections among identified neurons in Aplysia. J Neurophysiol 30:1352–1376Google Scholar
  32. Keil FC, Lockhart KL, Schlegel E (2010) A bump on a bump? Emerging intuitions concerning the relative difficulty of the sciences. J Exp Psychol Gen 139(1):1–15CrossRefGoogle Scholar
  33. Kroodsma D (2005) The singing life of birds. Houghton Mifflin, BostonGoogle Scholar
  34. Kuhl PK, Andruski JE, Chistovich IA, Chistovich LA, Kozhevnikova EV, Ryskina VL et al (1997) Cross-language analysis of phonetic units in language addressed to infants. Science 277:684–686CrossRefGoogle Scholar
  35. Loftus EF (1993) Made in memory: distortions in memory after misleading communications. In: Bower G (ed) The psychology of learning and motivation: advances in research and theory, vol 30. Academic Press, San Diego, pp 187–215Google Scholar
  36. McClelland J, Thompson R (2007) Using domain-general principles to explain children’s causal reasoning abilities. Dev Sci 10(3):333CrossRefGoogle Scholar
  37. Mellon R (2009) Superstitious perception: Response-independent reinforcement and punishment as determinants of recurring eccentric interpretations. Behav Res Ther 47(10):868–875CrossRefGoogle Scholar
  38. Michelsen A, Andersen B, Storm J, Kirchner W, Lindauer M (1992) How honeybees perceive communication dances, studied by means of a mechanical model. Behav Ecol Sociobiol 30(3):143–150CrossRefGoogle Scholar
  39. Miller GA (1956) The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychol Rev 63:81–97CrossRefGoogle Scholar
  40. Myelin (2010) Wikipedia: the free encyclopedia. Wikimedia Foundation, Inc., Florida. Retrieved 2 Feb 2010, from http://www.wikipedia.org
  41. National Academies Press (1996) National science education standards. Retrieved 2 Feb 2010, from http://www.nap.edu/catalog.php?record_id=4962
  42. Nickerson RS, Adams MJ (1979) Long-term memory for a common object. Cogn Psychol 11(3):287–307CrossRefGoogle Scholar
  43. Oberauer K, Bialkova S (2009) Accessing information in working memory: can the focus of attention grasp two elements at the same time? J Exp Psychol Gen 138(1):64–87CrossRefGoogle Scholar
  44. Parker E, Cahill L, McGaugh J (2006) A case of unusual autobiographical remembering. Neurocase 12(1):35–49CrossRefGoogle Scholar
  45. Pashler H, McDaniel M, Rohrer D, Bjork R (2009) Learning styles: concepts and evidence. Psychol Sci Public Interest 9(3):105–119Google Scholar
  46. Posner M, Rothbart M (2006) Research on attention networks as a model for the integration of psychological science. Ann Rev Psychol 58:1–23CrossRefGoogle Scholar
  47. Rohrer D, Pashler H (2010) Recent research on human learning challenges conventional instructional strategies. Educ Res 39(5):406–411CrossRefGoogle Scholar
  48. Ross PE (2006) The expert mind. Sci Am August:64–71CrossRefGoogle Scholar
  49. Schraw G, Lehman S (2001) Situational interest: a review of the literature and directions for future research. Educ Psychol Rev 13(1):23–52CrossRefGoogle Scholar
  50. Schraw G, Brooks DW, Crippen KJ (2005) Improving chemistry instruction using an interactive, compensatory model of learning. J Chem Educ 82(4):637–640CrossRefGoogle Scholar
  51. Shakhashiri BZ (2010) Science is fun. Retrieved 2 Feb 2010, from http://scifun.chem.wisc.edu/
  52. Shell DF, Brooks DW, Trainin G, Wilson KM, Kauffman DF, Herr LM (2010) The unified learning model: how motivational, cognitive, and neurobiological sciences inform best teaching practices. Springer, DordrechtGoogle Scholar
  53. Smallwood J, Schooler J (2006) The restless mind. Psychol Bull 132(6):946CrossRefGoogle Scholar
  54. Stanovich KE (1986) Matthew effects in reading: some consequences of individual differences in the acquisition of literacy. Read Res Q 21:340–406Google Scholar
  55. Strayer D, Drews F, Johnston W (2003) Cell phone-induced failures of visual attention during simulated driving. J Exp Psychol Appl 9(1):23–32CrossRefGoogle Scholar
  56. Sweller J, van Merrienboer JJG, Paas FGWC (1998) Cognitive architecture and instructional design. Educ Psychol Rev 10(3):251–296CrossRefGoogle Scholar
  57. Tan P (2010) Towards a culturally sensitive and deeper understanding of “Rote Learning” and memorization of adult learners. J Stud Int Educ. 1028315309357940v1028315309357941Google Scholar
  58. US Patent 3763422, Macphee J, Mowbray J, Noonan D, Remillard J, Scott R, Deceased D et al (1973) Method and apparatus for electrochemical analysis of small samples of bloodGoogle Scholar
  59. Wamsley EJ, Tucker M, Payne JD, Benavides JA, Stickgold R (2010) Dreaming of a learning task is associated with enhanced sleep-dependent memory consolidation. Curr Biol 20:1–6CrossRefGoogle Scholar
  60. Watson JM, Strayer DL (2010) Supertaskers: profiles in extraordinary multitasking ability. Psychon Bull Rev (in press; http://parentheses.atelier.fr/upload/2010/03/supertaskers.pdf)

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Department of Teaching, Learning, and Teacher EducationUniversity of NebraskaLincolnUSA

Personalised recommendations