PSCH 457 is the graduate course I will be teaching this Spring (2004). It is our 4th required course for Cognitive students that rounds out the coverage of cognitive topics in our graduate curriculum. (The correct course number is 457, but I guess students will need to register for 494 since that is what is listed in the timetable.) Registration is limited to graduate students in the Cognitive Division, or consent of the instructor. PLEASE REGISTER FOR 3 CREDITS.
The purpose of this course is to familiarize students with cognitive research on learning, including skill acquisition, concepts & categories, concept acquisition and development, and conceptual change processes. The course approaches learning from a variety of cognitive perspectives. The instruction is organized around discussions of original empirical and theoretical journal articles. Evaluation will be based on writing assignments designed to assess students' ability to critically evaluate and understand cognitive theories of categorization, skill and concept acquisition, and learning.
Here is the working list of topics to be covered that gives an idea
of the content and structure of the course.
This is a work in progress -- I promise to get the readings down to
2 per week most weeks!
Jan 15 Week 1: Organizational Meeting
Part I: Concepts & Categorization
Jan 22 Week 2: Introduction to Concept & Categories
Overview and Classical View Research
Bruner, J.S., Goodnow,
J.J., & Austin, G.A. (1956). A study of thinking. New York: Wiley.
Chapters
1 & 5
Family Resemblance and Basic Levels
Rosch,
E. & Mervis, C. (1975). Family resemblances: Studies in the internal
structures of categories.
Cognitive Psychology, 7,
573-605.
Jan 29 Week 3: Typicality, Prototype and Exemplar Theories
Medin
& Schwanenflugel
Medin, D. L., & Schwanenflugel, P. J. (1981). Linear separability
in classification learning. Journal of Experimental Psychology: Human Learning
and Memory, 7, 355--368.
McCloskey
& Glucksburg
McCloskey, M.E. and Glucksberg, S. (1978). Natural categories: Well
defined or fuzzy sets? Memory and Cognition, 6(4), 462-472.
Posner
& Keele
Posner, MI, & Keele, SW (1968). On the genesis of abstract ideas.
Journal of Experimental Psychology, 77, 353-363
(Stimuli from Posner, Goldsmith & Welton, 1967)
Feb 5 Week 4: Explanation or Theory-Based Approches
Murphy
& Medin, 1985
Murphy, G. L., & Medin, D. L. (1985). The role of theories in conceptual
coherence. Psychological Review, 92, 289-316.
Rips, 1989
Rips, L. J. (1989). Similarity, typicality, and categorization. In
S. Vosniadou & A. Ortony (Eds.), Similarity and Analogical Reasoning
(pp. 21-59). Cambridge, MA: Cambridge University Press.
Feb 12 Week 5: Goals and Contexts
Barsalou,
1985
Barsalou, L. W. (1985). Ideals, central tendency, and frequency of
instantiation as determinants of graded structure in categories. Journal
of Experimental Psychology: Learning, Memory, and Cognition, 11, 629654.
Markman
& Ross, 2003
Markman, AB, & Ross, BH (2003). Category use and category learning.
Psychological
Bulletin, 129(4), 592-615.
Feb 19 Week 6: Test
on Part I
Read this article and discuss its experiments and results in relation
to the classical view of categories, family resemblance theories,
protoype models, linear separability, and theory-based approaches to categorization.
Your papers should be around 7 pages, not including references (which should
be present). Reminder: this is an open book, closed mouth test.
Part II: Acquisition
Feb 26 Week 7: Acquisition of Skills (with Jim Pellegrino)
Anderson,
J. R. (1982). Acquisition of cognitive skill. Psychological Review, 89,
369-403.
Newell & Rosenbloom (1981)
Mar 4 Week 8: Skill Acquisition (continued)
Logan,
G. D. (1988). Towards an instance theory of automatization. Psychological
Review, 95, 492-527.
Ackerman, P. L. (1988). Determinants of individual differences during skill acquisition: cognitive abilities and information processing. Journal of Experimental Psychology: General, 117, 288-318.
Mar 11 Week 9: Acquisition of Expertise
Ericsson,
K. A., R. Th. Krampe, and C. Tesch-Römer, 1993, ‘The role of
deliberate practice in the acquisition of expert performance.’ Psychological
Review, 100: 363-406.
Medin, DL, Lynch, EB Coley, JD, Altran, SA (1997) Categorization and reasoning among tree experts: Do all roads lead to Rome? Cognitive Psychology: 32, 49-96
Chi, M. T., Hutchinson, J. E. & Robin.A. F. (1989). How inferences about novel domain-related concepts can be constrained by structured knowledge. Merrill-Palmer Quarterly 35:27-62.
Mar 18 Week 10: Theories of Children's Learning
Siegler, R. (1996) Emerging minds : the process of change in children's thinking
Chapters 1,
3, 4,
and 7.
Chapter 1 serves as an overview of developmental theories, Chapters
3 & 4 offer many examples of variability ** pay special attention to
the examples from addition (the most data is offered to illustrate these,
and we will focus our discussion on the addition studies)** you can just
scan over the other examples, Chapter 7 provides an overview of microgenetic
methods and how they may be used to sutdy learning.
Week 11: Test on Part II: what is the learning curve?
(please answer these questions in a 7-9 page paper).
What is the learning curve?
What have different theorists suggested as the determinants of the
learning curve?
i.e., Describe, compare and contrast the accounts of Anderson, Newell
& Rosenbloom, Logan & Ackerman (4-6 pages)
Then (in 3-4 pages) describe and map on Ericsson's and Siegler's theories:
i.e., How do Ericsson's and Siegler's approaches to skill acquisition
relate to or extend these other theories?
Part III: Knowledge Acquisition/Conceptual Change
April 1 Week 12:
Vosniadou,
S., and W. F. Brewer. (1987). "Theories of knowledge restructuring
in development." Review of Educational Research 57:51–67.
Background reading on schema theory: Brewer
& Nakamura
Short article on learning: Rumelhart
& Norman
April 8 Week 13: Models and Studies of Conceptual Change
Vosniadou, S. & Brewer, WF (1992). Mental models of the earth: A study of conceptual change in childhood. Cognitive Psychology, 24, 535-585
Chi, M. T. H. (1992). Conceptual change within and across ontological categories: examples from learning and discovery in science. Cognitive models of science. R. N. Giere. Minneapolis, University of Minnesota Press: 129-186.
Couldn't find an original di Sessa or Thagard that I liked so we will read Doug's paper that discusses their viewpoints....
Clark, D. B. (submitted). Longitudinal analysis of student conceptual change in thermodynamics: Theories or pieces?
here's a diSessa that I found too late to assign, but you can read this instead of the Clark if you want
April 15 Week 14: AERA no class
April 22 Week 15 Transfer
Barnett, S. M. & Ceci, S. J. (2002). When and Where do we apply what we learn? A taxonomy for far transfer. Psychological Bulletin, Vol. 128(4), 612-637.
Goldstone, R. L & Sakamoto, Y. (2003) The transfer of abstract principles governing complex adaptive systems. Cognitive Psychology, 46(4), 414-466.
Final week: Attend MPA Knowledge Acquisition and Analogy paper session 10-12 Thursday
We will discuss papers and the Gentner 1983 article at 5pm. Meet in lobby.
Gentner, D. (1983) Structure Mapping: A theoretical framework for analogy. Cognitive Science, 7, 155-170.
Final Examination on Part III
The paradox of learning is, if we need old knowledge to integrate with
new knowledge, how do we ever learn anything fundamentally new? We
have read articles from 3 traditions: schema theory, conceptual change,
and learning via transfer/analogy. What are the mechanisms that each
suggests underlie the acquisition of new information? You should
discuss this general question in the context of an article by Halpern,
Hansen & Riefer (1990) J Ed Psych (pdf available through Pschinfo)
which compares learning from passages which contain no analogy (literal
explanation), a near analogy, or a far analogy. According to each
theoretical approach, which condition might be predicted to generate the
best learning? Why might analogies help or hurt learning? And
in particular, in terms of the articles we read, discuss why far analogies
might lead to better learning outcomes or conceptual change.