Download Cognitive Science General Exam - Cognitive Science Ph.D. Program

Cognitive Science General Exam
Reading List
Fall 2014
Attached is a copy of the reading list for the Fall 2014 Applied Cognitive Science General Exam. This
exam will take place on two successive days late in the fall semester. The date of the exam will be negotiated
with the students who take the exam that semester. In each session, you will be asked to answer two questions
for a total of 4 questions. Passing the exam requires you to achieve a passing grade on each question. If one or
more answers are not acceptable to the program faculty, you will have to retake part or all of the exam the
following semester. During the test, you will have access to a computer to type your exam responses and a copy
of this reading list, but you will not have access to the internet or other sources of information that could be
used to help you. Thus, you should come prepared.
The questions on the exam will be general and synthetic in nature. Students might expect a question
asking them to compare two theories, to explain how a theory might account for an empirical observation, or to
predict the outcome of an experiment from one or more theoretical perspectives. These are just examples of
the kinds of questions you might expect. You should not anticipate a question that asks about a specific
detail from a particular study. (e.g., “Identify the number of participants per condition in experiment 3 from
paper XXX.”). Your answers will be required to incorporate multiple elements including some or all of the
following (depending on the question): representations, processes, models, and application/implications of the
results.
Be sure to answer ALL parts of each of the questions!
Critical Information:
It is your responsibility to assess your level of understanding of the readings through discussion with
program faculty. With a reading list this broad and covering diverse areas, you may find that you need
additional background to understand the material. The cognitive science faculty are available to provide
additional background readings to help you to achieve the level of understanding necessary to pass the general
exam. You should take advantage of the expertise available to you through meetings with the faculty. Taking
the exam without any discussion with the faculty about the papers in their respective areas is likely a mistake.
We have broken down the reading list into Foundational and Core readings. The first set of readings
provides a foundation upon which the Core readings build. You will be tested on the entire reading list, so be
sure to read and comprehend all of the materials on this list.
Foundational Readings:
1. Anderson, J. R. (2002). Spanning seven orders of magnitude: A challenge for cognitive modeling.
Cognitive Science, 26, 85-112.
2. Anderson, J. R., Bothell, D., Byrne, M. D., Douglass, S., Lebiere, C., & Qin, Y. (2004). An integrated
theory of the mind. Psychological Review 111, 1036-1060.
3. Anderson, J. R., John, B. E., Just, M. A., Carpenter, P. A., Kieras, D. E., & Meyer, D. E. (1995).
Production system models of complex cognition. In Proceedings of the Seventeenth Annual
Conference of the Cognitive Science Society (pp. 9-12). Hillsdale, NJ: Lawrence Erlbaum
Associates.
4. Bjork, R. A. (1992). Interference and memory. In L. R. Squire (Ed.), Encyclopedia of learning and
memory (pp. 283–288). New York: Macmillan.
5. Collins, A.M. & Quillian, M.R. (1969). Retrieval time from semantic memory. Journal of Verbal
Learning and Verbal Behavior, 8, 240-247.
6. Hinton, G.E., McClelland, J.L., & Rumelhart, D.E. (1986). Distributed representations. In D.E.
Rumelhart & J.L. McClelland (Eds.), Parallel Distributed Processing: Explorations in the
Microstructure of Cognition. Cambridge, MA: The MIT Press (pp. 77-109).
7. Hintzman, D. L. (1991). Why are formal models useful in psychology? In W. E. Hockley & S.
Lewandowsky (Eds), Relating theory and data: Essays in honor of Bennet B. Murdock. Hillsdale, NJ:
Erlbaum.
8. Lovett, M. C. (2002). Problem solving. In H. Pashler & D. Medin (Eds.), Steven's handbook of
experimental psychology (3rd ed.), Vol. 2: Memory and cognitive processes. (pp. 317-362).
9. McClelland, J.L., Rumelhart, D.E., & Hinton, G.E. (1986). The appeal of parallel distributed processing.
In Rumelhart, McClelland, and the PDP Research Group (Eds.), Parallel Distributed Processing:
Volume I. Cambridge, MA: The MIT Press.
10. Memory, Stanford Encyclopedia of Philosophy, SU2004.
http://plato.stanford.edu/archives/sum2004/entries/memory/
11. Roediger, H.L., & Guynn, M.J. (1996). Retrieval processes. In E.L. Bjork & R.A. Bjork (Eds.), Human
memory (pp. 197-236). San Diego: Academic Press.
12. Tulving E. 2007. Coding and representation: Searching for a home in the brain. In (Eds. Roediger HL
I.I.I., Dudai Y. & Fitzpatrick S.M.), Science of Memory: Concepts (pp. 65-68). New York, NY: Oxford
University Press.
13. McClelland, J. L. (2009). The Place of Modeling in Cognitive Science. Topics in Cognitive Science,
1(1), 11–38. doi:10.1111/j.1756-8765.2008.01003.x
Core Readings:
1. Ackerman, P. L. (1988). Determinants of individual differences during skill acquisition: Cognitive
abilities and information processing. Journal of Experimental Psychology: General, 117, 288-318.
2. Anderson, J.R. (1982). Acquisition of cognitive skill. Psychological Review, 89, 369- 406.
3. Aizawa, K. (1994). “Representations without Rules, Connectionism and the Syntactic Argument,”
Synthese, 101: 465–492.
4. Altmann, E. M., & Gray, W. D. (2008). An integrated model of cognitive control in task switching.
Psychological Review, 115, 602-639.
5. Anderson, J.R. (2010). Cognitive Psychology and Its Implications (7th edition). New York: Worth
Publishers. Chapter 12, Language Structure
6. Budiu, R., & Anderson, J.R. (2004). Interpretation-based processing: a unified theory of semantic
sentence comprehension. Cognitive Science, 28, 1-44.
7. Chase, W., & Simon, H. (1973). Perception in chess. Cognitive Psychology, 4, 55-81.
8. Elman, J. L. (1991). “Distributed Representations, Simple Recurrent Networks, and Grammatical
Structure,” in Touretzky (1991), 91–122.
9. Ericsson, K. A., & Kintsch, W. (1995). Long-term working memory. Psychological Review, 102,
211-245.
10. Fitts, P. M., & Posner, M. I. (1967). Human performance. Belmont, CA: Brooks/Cole. (Chapters 13).
11. Fleishman, E. A. (1972). On the relation between abilities, learning, and human performance.
American Psychologist, 27, 1017-1032.
12. Fodor, J., and Pylyshyn, Z. (1988). “Connectionism and Cognitive Architecture: a Critical
Analysis,” Cognition, 28: 3–71.
13. Forbus, K. D., Gentner, D., & Law, K. (1995). MAC/FAC: A model of similarity-based retrieval.
Cognitive Science: A Multidisciplinary Journal, 19(2), 141–205.
14. Gillund, G., & Shiffrin, R. Bm. (1984). A retrieval model of both recognition and recall.
Psychological Reviews, 91, 1-67.
15. Gobet, F. (1998). Expert memory: A comparison of four theories. Cognition , 66, 115-152.
16. Goldstone, R.L. (1998). Perceptual Learning. Annual Review of Psychology, 585-612.
17. Hintzman, D. L. (1984). MINERVA 2: A simulation model of human memory. Behavior Research
Methods, 16, 96-101.
18. Hintzman, D. L. (1988). Judgments of frequency and recognition memory in a multiple-trace
memory model. Psychological Review, 95, 528-551.
19. Hummel, J. E., & Holyoak, K. J. (1997). Distributed representations of structure: A theory of
analogical access and mapping. Psychological Review, 104 (3), 427–466.
20. Jeffries, R., Polson, P. G., Razran, L., & Atwood, M. E. (1977). A process model for missionariescannibals and other river-crossing problems. Cognitive Psychology, 9(4), 412–440.
21. Logan, G. (2002). An instance theory of attention and memory. Psychological Review, 109, 376400.
22. Metcalfe, J. (1990). Composite holographic associative recall model (CHARM) and blended
memories in eyewitness testimony. Journal of Experimental Psychology: General, 119, 145-160.
23. Metcalfe, J. (1991). Recognition failure and the composite memory trace in CHARM. Psychological
Review, 98, 529-553.
24. Meyer, D. E., & Kieras, D. E. (1997). A computational theory of executive cognitive processes and
multiple-task performance: Part I. Basic mechanisms. Psychological Review, 104(1), 3-65.
doi:10.1037/0033-295X.104.1.3
25. Meyer, D. E., & Kieras, D. E. (1997). A computational theory of executive cognitive processes and
multiple-task performance: Part 2. Accounts of psychological refractory-period phenomena.
Psychological Review, 104(4), 749-791. doi:10.1037/0033-295X.104.4.749
26. Newell, A. (1973). You can’t play twenty questions with nature and win. Visual information
processing, 283–308.
27. Newell, A., & Rosenbloom, P. S. (1981). Mechanisms of skill acquisition and the power law of
practice. In J. R. Anderson (Ed.), Cognitive skills and their acquisition (pp. 1-55). Hillsdale, NJ:
Lawrence Erlbaum.
28. Newell, A., & Simon, H. A. (1980). The theory of human problem solving. In AM Collins & EE
Smith (Eds.), Readings in cognitive science: A perspective for psychology and artificial intelligence.
San Mateo, CA: Kaufmann.
29. Pinker, S., and Prince, A. (1988). “On Language and Connectionism: Analysis of a Parallel
Distributed Processing Model of Language Acquisition,” Cognition, 23: 73–193.
30. Raaijmakers, J. G. W., & Shiffrin, R.M. (1981). Search of associative memory. Psychological
Review, 88, 93-134.
31. Roberts, S., & Pashler, H. (2000). How persuasive is a good fit? A comment on theory testing.
Psychological Review, 107, 358-367.
32. Roediger, H. L. (1974). Inhibiting effects of recall. Memory and Cognition, 2, 261-196.
33. Rogers, T.T., & McClelland, J.L. (2008). Précis of Semantic Cognition: A Parallel Distributed
Processing Approach. Behavioral and Brain Sciences, 31, 681-749.
34. Rumelhart, D.E., & Norman, D. A. (1985). Representation of knowledge. In A.M. Aitkenhead &
J.M. Slack (Eds.), Issues in cognitive modeling. London:Erlbaum.
35. Salvucci, D. D., & Taatgen, N. A. (2008). Threaded cognition: An integrated theory of concurrent
multitasking. Psychological Review, 115(1), 101–130.
36. Schank, R. C. (1995). The Structure of Episodes in Memory. In George F. Luger (Ed.) Computation
and Intelligence: Collected Readings. Menlo Park, CA: AAAI Press/The MIT Press (pp. 236259).
37. Schneider, W., & Shiffrin, R. M. (1977). Controlled and automatic human information processing: 2.
Perceptual learning, automatic attending, and a general theory. Psychological Review, 84, 127-190
38. Simon, H. A. (1968). On judging the plausibility of theories. In B. van Roostelaar & J. F. Staal
(Eds.), Logic, methodology and philosophy of sciences III (Vol. 3, pp. 439-459). Amsterdam: NorthHolland.
39. Simon, H. A. (1992). What is an 'explanation' of behavior? Psychological Science, 3, 150-161.
40. Simon, H.A., Langley, P.W., & Bradshaw, G.L. (1981). Scientific discovery as problem solving.
Synthese, 47, 1-27.
41. Singley, M. K., & Anderson, J. R. (1989). The transfer of cognitive skill. Cambridge, MA: Harvard
Press. (Chapters 1-2)
42. Taatgen, N. A. (2013). The nature and transfer of cognitive skills. Psychological Review, 120(3),
439–471.
43. Taatgen, N. A., Huss, D., Dickison, D., & Anderson, J. R. (2008). The acquisition of robust and
flexible cognitive skills. Journal of Experimental Psychology: General, 137(3), 548–565.
44. Thagard, P (1988). Explanatory coherence. Behavioral and Brain Sciences, 12, 435-502.
45. Thagard, P., & Litt, A. (2008). Models of scientific explanation. In R. Sun (Ed.), The Cambridge
handbook of computational psychology (pp 549-564). Cambridge: Cambridge University Press.
46. Tulving, E. (2002). Episodic memory: From mind to brain. Annual Review of Psychology, 53, 125.
Approved: 5/12/2014