John Robert Anderson (psychologist)

John Robert Anderson
Born (1947-08-27) August 27, 1947
Fields Educational psychology
Cognitive psychology (mathematics education)
Institutions Carnegie Mellon University
Alma mater University of British Columbia (B.A.)
Stanford University (Ph.D.)
Thesis A Stochastic model of sentence memory (1972)
Doctoral advisor Gordon Bower
Notable students Kenneth Koedinger
Neil Heffernan
Known for Intelligent tutoring systems
Cognitive tutors
Rational analysis

John Robert Anderson (born August 27, 1947) is a Canadian-born American psychologist. He is currently professor of Psychology and Computer Science at Carnegie Mellon University.


Anderson obtained a B.A. from the University of British Columbia in 1968, and a Ph.D. in Psychology from Stanford in 1972. He became an assistant professor at Yale in 1972. He moved to the University of Michigan in 1973 as a Junior Fellow (and married Lynne Reder who was a graduate student there) and returned to Yale in 1976 with tenure. He was promoted to full professor at Yale in 1977 but moved to Carnegie Mellon University in 1978. From 1988 to 1989, he served as president of the Cognitive Science Society. He has elected to the American Academy of Arts and Sciences and the National Academy of Sciences and has received a series of awards:


In cognitive psychology, John Anderson is widely known for his cognitive architecture ACT-R[6][7] and rational analysis.[8][9] He has published many papers on cognitive psychology, including recent criticism of unjustified claims in mathematics education that lack experimental warrant and sometimes (in extreme cases) contradict known findings in cognitive psychology.[10]

He was also an early leader in research on intelligent tutoring systems, such as cognitive tutors, and many of Anderson's former students, such as Kenneth Koedinger and Neil Heffernan, have become leaders in that area.

Intelligent tutoring systems

Anderson's research has used fMRI brain imaging to study how students learn with intelligent tutoring systems.[11] Most of his studies have looked at neural processes of students while they are solving algebraic equations or proofs.

Anderson and colleagues generated a cognitive model that predicted that while students were learning an algebra proof, neuroimages showed decreased activation in a lateral inferior prefrontal region and a predefined fusiform region. This decrease in activity showed an increased fluency in retrieving declarative information, as students required less activity in these regions to solve the problems.[11]

Cognitive stages when solving mathematical problems

In a 2012 study, Anderson and Fincham (a Carnegie Mellon University colleague) conducted a study that looked at the cognitive stages participants engaged in when solving mathematical problems. These stages included encoding, planning, solving, and response. The study determined how much time participants spent in each problem solving stage when presented with a mathematical problem. Multi-voxel pattern recognition techniques and Hidden Markov models were used to determine participants' problem solving stages.

Results of the study showed that the time spent in the planning stage was dependent on the novelty of the problem. The time spent in the solving stage was dependent on the amount of computation required for the particular problem. Lastly, the time spent in the response stage was dependent on the complexity of the response required by the problem.[12]

Decomposition Hypothesis

In another study, Anderson and colleagues used a video game task to test the Decomposition Hypothesis, or the idea that a complex cognitive task can be broken down into a set of information processing components. The combination of these components remains the same across different tasks. The study used a cognitive model that predicted behavioral and activation patterns for specific regions in the brain.

The predictions involved both tonic activation, which remained stable across brain regions during game play, and phasic activation, which was present only when there was resource competition. The study's results supported the Decomposition Hypothesis. Individual differences were also found in participants' learning gains, which indicated that learning a complex skill is dependent on cognitive capacity limits.[13]'



  1. National Academy of Sciences: Anderson, John R.
  2. "Book of Members, 1780–2010: Chapter A" (PDF). American Academy of Arts and Sciences. Retrieved April 18, 2011.
  3. See the list of Rumelhart prize winners on the Cognitive Science Society website.
  4. See the list of prize winners at the Heineken Prize page website.
  5. "Benjamin Franklin Medal in Computer and Cognitive Science". Franklin Institute. 2011. Retrieved December 23, 2011.
  6. Anderson, J. R. & Lebiere, C. (1998). The atomic components of thought. Mahwah, NJ: Lawrence Erlbaum Associates
  7. Anderson, J. R. (2007). How can the human mind occur in the physical universe? New York: Oxford University Press
  8. Anderson, J. R. (1991). Is human cognition adaptive? Behavioral and Brain Sciences 14, 471–517.
  9. Anderson, J. R. (1990). "The adaptive character of thought". Hillsdale, NJ: Lawrence Erlbaum Associates.
  10. Anderson, John R.; Reder, Lynne M.; Simon, Herbert A.; K. Anders Ericsson; Robert Glaser (1998). Diane Ravitch, ed. "Radical constructivism and cognitive psychology". Brookings Papers on Education Policy. 6 (1): 227–278..
  11. 1 2

External links

This article is issued from Wikipedia - version of the 3/24/2016. The text is available under the Creative Commons Attribution/Share Alike but additional terms may apply for the media files.