Publications in Instructional Materials

Wirzberger, M., Borst, J. P., Krems, J. F., & Rey, G. D. (2020). Memory-related cognitive load effects in an interrupted learning task: A model-based explanation. Trends in Neuroscience and Education, 20, 100139. https://doi.org/10.1016/j.tine.2020.100139

Wirzberger, M., & Rey, G. D. (2016). Examining load-inducing factors in instructional design: An ACT-R approach. In D. Reitter, & F. E. Ritter (Eds.). Proceedings of the 14th International Conference on Cognitive Modeling (ICCM 2016) (pp. 223-224). University Park, PA: Penn State.

Lee, H. S. & Anderson, J. R. (2013). Student learning: What has instruction got to do with it? Annual Review of Psychology, 64, 445-469.

Stocco, A., Lebiere, C., O'Reilly, R. C., & Anderson, J. R. (2012). Distinct contributions of the caudate nucleus, rostral prefrontal cortex, and parietal cortex to the execution of instructed tasks. Cognitive, Affective, & Behavioral Neuroscience, 12, 611-628.

Guhe, M., Smaill, A., & Pease, A. (2010). Towards a cognitive model of conceptual blending. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 293-304). Philadelphia, PA: Drexel University.

Stocco, A., Lebiere, C., O'Reilly, R. C., & Anderson, J. R. (2010). The role of the anterior prefrontal-basal ganglia circuit as a biological instruction interpreter. In A. V. Samsonovich, K. R. Jóhannsdóttir, A. Chella, & B. Goertzel (Eds.) Biologically Inspired Cognitive Architectures 2010. Frontiers in Artificial Intelligence and Applications, (pp. 153-162). Amsterdam, The Netherlands: IOS Press.

Huss, D., Taatgen, N. A., & Anderson, J. R. (2006). Instructional Representation in cognitive modeling. In Proceedings of the Seventh International Conference on Cognitive Modeling (pp. 367-368). Trieste, Italy.

Taatgen, N. A., Huss, D., & Anderson, J. R. (2006). How cognitive models can inform the design of instructions. In Proceedings of the Seventh International Conference on Cognitive Modeling (pp. 304-309). Trieste, Italy.

Ritter, F. E. (2004). Choosing and getting started with a cognitive architecture to test and use human-machine interfaces. MMI-Interaktiv-Journal's special issue on Modeling and Simulation in Human-Machine Systems, 7. 17-37.

Anderson, J. R. (2002). Spanning seven orders of magnitude: A challenge for cognitive modeling. Cognitive Science, 26, 85-112

Anderson, J. R. & Schunn, C. D. (2000). Implications of the ACT-R learning theory: No magic bullets. In R. Glaser, (Ed.), Advances in instructional psychology: Educational design and cognitive science (Volume 5), pp. 1-34. Mahwah, NJ: Lawrence Erlbaum Associates.

Anderson, J.R., Reder, L.M., & Simon, H.A. (2000, Summer). Applications and Misapplications of Cognitive Psychology to Mathematics Education. Texas Educational Review

Anderson, J. R., Greeno, J. G., Reder, L. M., & Simon, H. A. (2000). Perspectives on learning, thinking, and activity. Educational Researcher, 29, 11-13.

Anderson, J. R., Reder, L. M. & Simon, H. (1998). Radical constructivism and cognitive psychology. In D. Ravitch (Ed.) Brookings papers on education policy 1998. Washington, DC: Brookings Institute Press.

Anderson, J. R., Simon, H. A., & Reder, L. M. (1997). Rejoiner: Situative versus cognitive perspectives: Form versus substance. Educational Researcher, 26, 18-21.

Anderson, J. R., Simon, H. A., & Reder, L. M. (1996). Situated learning and education. Educational Researcher, 25, 5-11.

Anderson, J. R. (1981). Tuning of search of the problem space for geometry proofs. In Proceedings of IJCAI-81, 97-103.

Copyright © 2002-2013 ACT-R Research Group


Department of Psychology, Carnegie Mellon University