EXP 6939: Current Issues In Cognition
Introduction to Cognitive Modeling
Contact Information
Instructor: Stephen Blessing (PSY 86, x2–1970, blessing+@cmu.edu)
Office hours: Monday & Tuesday, 2 – 4 pm
Course web page: http://nersp.nerdc.ufl.edu/~sbless/exp6939/home.html
Prerequisites
No prior knowledge of any particular cognitive model will be assumed. Knowledge of the ideas germane to cognitive modeling, generally those of the information processing point of view, will be assumed. For students not familiar with those ideas, readings will be made available. Furthermore, while no knowledge of a specific programming language will be required, familiarity with programming concepts, and computers in general, will be beneficial.
Course Objective
This course is meant to introduce you to the concept of modeling cognitive skills. A cognitive model is a representation, generally on a computer, of how people solve problems or learn a particular skill. The course is divided into two components. One component takes place in a classroom, and will be an overview of the cognitive modeling field, during which we will discuss the basic idea behind it, early cognitive models, and end with a series of discussions on current cognitive architectures. Some of these cognitive architectures will be made available to you to actually try. The second component is designed to be hands–on. You will learn the fundamentals of how to construct a cognitive model using Anderson’s ACT–R system.
Grading
For the hands–on ACT–R weeks, there is an assignment associated with each lesson. There will be an in–class final at the end of the semester based on the classroom readings and discussions.
Text and Readings
This one required text will be used to support the ACT–R exercises:
Anderson, J. R. (1993). Rules of the Mind. Hillsdale, NJ: Erlbaum.
During the first half of the course, we will be using papers and articles found in various books and journals. These are listed in the course outline below, and will be on reserve. The last part of this syllabus contains a list of additional readings. I will be making reference to these readings as we go through the course, and I provide this list to you in case you are interested in gaining a more in–depth understanding of any particular topic.
Course Outline
Odd numbered weeks will be the classroom component part of the course, where we will meet and discuss some aspect of cognitive modeling. You are expected to have read the readings before class. Even numbered weeks will introduce you to a new part of ACT–R. I will lecture on that new part, and then associated with that lecture will be a new unit within the ACT–R Lessons web page, with an assignment for you to complete within the ACT–R Environment, to be turned in within two weeks (i.e., before the start of the next unit).
Week 1
What is Cognitive Modeling and Why Do It?
No readings. For next week, however, you should work through Unit 0—Interpreting Production Rules, to gain some familiarity with ACT–R.
Week 2
Introduction to ACT–R (Unit 1)
Week 3
The Early Years I
Simon, H. A. (1991). Climbing the mountain: Artificial intelligence achieved. Models of My Life. New York, NY: BasicBooks, 198– 214.
Simon, H. A. (1975). The functional equivalence of problem solving skills. Cognitive Psychology, 7, 268–288.
Chapter 6, Rules of the Mind.
Week 4
Knowledge Representation in ACT–R (Unit 2)
Chapter 2, Rules of the Mind.
Week 5
The Early Years II
Cohen, H. (1973). Parallel to perception: Some notes on the problem of machine–generated art. Computer Studies, 4.
McCorduck, P. (1991). How does Aaron work? Aaron’s Code: Meta–art, Artificial Intelligence, and the Work of Harold Cohen. New York, NY: W. H. Freeman and Company, 201–208.
Neves, D. M. (1978). A computer program that learns algebraic procedures by examining examples and by working test problems in a textbook. Proceedings of the Second National Conference of the Canadian Society for Computational Studies of Intelligence. 191–195.
Week 6
Parameters and Conflict Resolution (Unit 3)
Chapters 3 and 5, Rules of the Mind.
Week 7
EPAM
Simon, H. A., & Feigenbaum, E. A. (1984). EPAM–like models of recognition and learning. Cognitive Science, 8, 305–336.
Simon, H. A. (1972). What is visual imagery? An information–processing interpretation. In L. W. Gregg (Ed.), Cognition in Learning and Memory, New York, NY: Wiley. 183–204.
Week 8
Activation and Latency (Unit 4)
Chapter 3, Rules of the Mind.
Week 9
PDP
McClelland, J. L., Rumelhart, D. E., & Hinton, G. E. (1986). The appeal of parallel destributed processing. Parallel Distributed Processing: Explorations in the Microstructure of Cognition (Vol. 1). Cambridge, MA: The MIT Press. 3–45.
Rumelhart, D. E. & McClelland, J. L. (1986). PDP models and general issues in cognitive science. Parallel Distributed Processing: Explorations in the Microstructure of Cognition (Vol. 1). Cambridge, MA: The MIT Press. 110–146.
Week 10 (Nov. 5, 5:30 pm)
Partial Matching and Accuracy (Unit 5)
Week 11 (Nov. 7)
Soar
Newell, A. (1990). Symbolic processing for intelligence. Unified Theories of Cognition. Cambridge, MA: Harvard University Press. 158–234.
Howes, A., Young, R. M. (1996). Learning consistent, interactive, and meaningful task–action mappings: A computational model. Cognitive Science, 20, 301–356.
Week 12 (Nov. 14)
Learning Activation Parameters (Unit 6)
Chapter 4 (first half), Rules of the Mind.
Week 13 (Nov. 21)
ACT–R
Anderson, J. R. (1996). ACT: A simple thoery of complex congition. American Psychologist, 51, 355–365.
Anderson, J. R., Reder, L. M., & Lebiere, C. (in press). Working memory: Activation limitations on retrieval. Cognitive Psychology.
Anderson, J. R., & Fincham, J. M. (1994). Acquisition of procedural skills from examples. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20(6), 1322–1340.
Week 14 (Dec. 5)
Learning by Analogy (Unit 8)
Chapter 4 (second half), Rules of the Mind.
Week 15 (Dec. 10)
The ACT Tutors and Wrap–Up
Anderson, J. R. (1995). The cognitive tutors: lessons learned. Journal of the Learning Sciences, Vol. 4(2), 167–207.
Davidson, J. (1996). PUMPing students through the math pipeline. Carnegie Mellon Alumni Magazine, Fall 1996.
Chapter 10, Rules of the Mind.
Additional Readings
Information Processing Psychology
Simon, H. A., (1978). Information–processing theory of human problem solving. In W. K. Estes (Ed.) Handbook of learning and cognitive processes (Vol. 5). Hillsdale, NJ: Erlbaum.
Newell, A., & Simon, H. A. (1972). Human problem solving. Englewood Cliffs, NJ: Prentice–Hall. [This is The Book on IPS. I suggest Chapters 2 and 14.]
Miscellaneous Models
Klahr, D., Langley, P., & Neches, R. (1987). Production System Models of Learning and Development. Cambridge, MA: The MIT Press.
Simon, H. A. (1979). Models of Thought: Volumes 1 and 2. NewHaven, CT: Yale University Press.
Simon, H. A., & Siklóssy, L. (1972), Representation and Meaning. Englewood Cliffs, NJ: Prentice–Hall.
EPAM
Both the 1979 and 1989 Simon volumes listed above have articles with EPAM models and discussions.
Richman, H., & Simon, H. A. (1989). Context effects in letter perception: Comparison of two theories. Pscyhological Review, 96, 417–432.
PDP
Plaut, D. C., & Shallice, T. (1994). Word reading in damaged connectionist networks: Computational and neuropsychological implications. In R. J. Mammone (Ed.), Artificial Neural Networks for Speech and Vision, London: Chapman & Hall, 294–323
Plaut, D. C., McClelland, J. L., Seidenberg, M. S., & Patterson, K. (1995). Understanding normal and impaired word reading: Computational Principles in quasi–regular domains. Psychological Review, ?, ???–???.
Seidenberg, M. S., & McClelland, J. L. (1989). A distributed, developmental model of word recognition and naming. Psychological Review, 96, 523–568.
Cognitive Science 737: Topics and Methodologies
in Cognitive Science (Proseminar in Cognitive Science)
Spring 1997 Course Information
Class Time/Place: | Monday 3:30-5:30 DL 298 (Dreese Lab) |
Call Numbers: | CIS 04680-5, ISE 09823-9, Ling 10160-1, Philosophy 13274-8 , Psych 14938-4 , SHS 16187-4 |
Credit: | 2 credit hours |
Required Texts: | • (FCS) Posner, M. I. (Ed.). (1989). Foundations of Cognitive Science. Cambridge, MA: The MIT Press. • (ROM) Anderson, J. R. (1993). Rules of the Mind. Hillsdale, NJ: Lawrence Erlbaum. • (TUT) The Web-Based Act-R Tutorial, available at http://rome.medinfo.ohio-state.edu. If this server is not responding, you can try the Act-R Tutorial server at CMU. • (ACT) Anderson, J. R. and Lebiere, C. (1997) The Atomic Components of Thought. Unpublished manuscript. (ACT is available at Grade A Notes in the OSU bookstore.) • Additional assigned articles will be distributed in class. |
Prerequisites: | A total of 12 cr hrs from at least two of the following areas: computer science, linguistics, philosophy, and psychology. |
Professor: | Todd R. Johnson (johnson.25@osu.edu) |
Office Hours: | TR 2:30-3:30 or by appointment Dreese Lab 258, 292-3284 Mailbox: 395 Dreese Lab |
Description
Cognitive Science is the the study of mind from an information-processing perspective. This course provides an overview of cognitive science as a distinct discipline, but also shows how the component fields fit in and contribute to cognitive science. The course reviews the central research methodology, including experimental methods and computational modeling. In addition, the course covers a wide range of cognitive science topics, including knowledge representation, problem solving, learning, and visual cognition. To introduce students to the variety of research being conducted at OSU, several of the topics are presented in the context of original research by faculty guest lecturers. Through lectures, reading assignments, and hands-on modeling exercises (using the Act-R cognitive architecture), students become familiar with many of the issues and methods central to cognitive science.
Prerequisites
Psych/ISE/CIS/Ling/Phil 612 (Introduction to Cognitive Science) or equivalent. This class assumes that you are familiar with the basic concepts introduced in 612, including declarative and procedural knowledge, state-space analysis, semantic networks, and basic theories of memory, categorization, problem solving, and skill-acquisition. Basic knowledge of computer programming will be helpful, but is not necessary. The class does assume that you know how to use computers and the world-wide-web. Students who have not taken 612 or an equivalent may take the course with permission from the instructor.
Evaluation
There is no midterm or final exam.
Modeling Assignments (8): 56%
Discussion Preparation: 25%
Class Participation: 19%
Modeling Assignments
The syllabus (given below) details all due dates for the modeling assignments. Although the Act-R tutorial contains several exercises, you need only hand in those specified in the syllabus. You should read through the entire tutorial, not just the sections pertaining to the assigned exercises. All modeling assignments are due in class on the assigned due date. Hand in a Mac or PC floppy disk containing the code and a trace of the running program (sufficient to show that you have completed the assignment) to the instructor. At times, I will also ask you to answer one or more questions about some of the projects. Place your answers to these questions in a file on your floppy disk. You can use either plain text (produced by Simpletext on the Mac, or notepad on the PC) or Word (any version). Late assignments will be assessed a 5% penalty per day.
Computer Accounts and Act-R Software
Act-R has been installed on the Macs in 345 Central Classroom (The OSU Bookstore), which is a public computing lab. You can use these Macs any time the lab is open, though you might have to wait for a seat. Based on your schedules, I will reserve the Macs for your exclusive use for at least one 2 hour block each week, at which time I will show up in the lab to help you with your projects.
You can also run Act-R on your own Mac or Windows PC. The PowerMac version is the complete Act-R system containing Act-R 4.0 with the Tutor, visual system, and a graphical development environment. The Windows version supports only the basic Act-R 4.0 architecture without the tutor or the graphical development environment. The tutor is used for tutorial Units 1 and 2. The visual system is used with Unit 9. I recommend that you use the Mac version for these units, because without the tutor (or visual system) you will likely find the projects too difficult (or impossible). The other units do not use the tutor, so you should do fine using the PC version for those.
The Act-R environment is for use only by officially enrolled 737 students. To uncompress these files you must use the password given in class.
Notes on Act-R Versions and the Readings
The latest publically available version of Act-R is 3.0. We will be using Act-R 4.0, which is an alpha release of the latest version of Act-R. This version is described in ACT, the first four chapters of a book due out in 1998, and TUT, the Act-R web-based tutorial. ROM describes Act-R 2.0, which differs in many significant ways from 4.0. You should focus your reading on ACT and TUT and use ROM as a reference to clarify points that might be confusing in ACT. In addition, ROM contains interesting information and examples that are not in ACT. In particular, ROM Chapter 12-12.4 provides an excellent introduction on creating production system models.
Discussion Preparation
Two students will be semi-randomly assigned to each paper/presentation listed in the discussion sections. These students are responsible for presenting and leading the discussion for that paper. If you are the discussants for a standard paper, prepare a set of transparancies that covers the main points or arguments of the paper. If you are a discussant for a guest speaker presentation/paper, prepare a list of questions to ask the speaker. Turn your transparancies or questions in as a basis for grading.The presentation/discussion portion of class willl last approximately 1 hour for lectures without a guest speaker.
Lecture and Assignment Schedule
Note: Readings (except those for the first class) should be completed before the dates listed below.
Lecture slides, in Adobe Acrobat 2.1 format, are available by clicking on the lecture titles. To view or print these files, you need the free Adobe Acrobat reader.
Wk | Date | Topic(s) | Readings | Discussion | Assignment | Due |
1 | 31-Mar | Cognitive Architectures I: Symbolic Approaches & Intro to Act-R | ACT 1, FCS 1; ; ROM 1, 2 -2.2.3,12.1-12.4 |
| TUT Unit 0: Interpreting Production Rules Tut Unit 1: Introduction to Act-R |
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2 | 7-Apr | Cognitive Science Methodology & Goals and Subgoals in Act-R | FCS 7 | FCS 2, 3 Iyer, Cadmus Patterson, Bhandari |
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3 | 14-Apr | Cognitive Architectures II: Neural Approaches Guest Lecturer: Dr. In Jae Myung, Psychology | FCS 4, 8 | Guest Lecture | TUT Unit 2: Knowledge Representation in Act-R | Unit 1 Exercise 1.4: Reproducing Protocols in the TOH |
4 | 21-Apr | Problem Solving & Conflict Resolution in Act-R | ACT 2-2.1 | FCS 14 Ranson, Christoffersen | TUT Unit 3: Parameters and Conflict Resolution | Unit 2 Exercise 2.1: Solving Algebra Problems |
5 | 28-Apr | Memory Activation, Latency, and Partial Matching | ACT 2.2-2.4 | FCS 17 Gray | TUT Unit 4: Activation and Latency | Unit 3 Exercise: 8 Puzzle |
6 | 5-May | Reasoning Guest lecturer: Dr. Vladimir Sloutsky, Education | FCS 12 | Guest Paper | TUT Unit 5: Partial Matching and Accuracy | Unit 4 Exercise: Fan Effect |
7 | 12-May | Learning | ACT 3 | TBA Wu | TUT Unit 6: Learning Activation Parameters | Unit 5 Exercise: Error Modeling in Simple Addition |
8 | 19-May | Language Guest lecturer: Dr. Rick Lewis, Computer and Information Science | FCS 5, 9 | Guest Paper Martin | TUT Unit 7: Learning Conflict Resolution Parameters | Unit 6 Exercise: Alphabet Arithmetic |
9 | 26-May | Memorial Day - No Classes |
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10 | 2-Jun | Visual Cognition | ACT 4 | FCS 16, TBA Chuah | TUT Unit 8: Learning by Analogy | Unit 7 Exercise: Building Sticks Task |
11 | 12-Jun | Finals Week - No Class |
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| Unit 8 Exercise: Algebraic Transformations (Due by 5:00 Thursday) |
Other References
Ericsson, K., & Simon, H. (1993). Protocol Analysis: Verbal Reports as Data. (Revised ed.). Cambridge, MA: MIT Press.
The following anthology contain a broad range of papers introducing many areas of research in Cognitive Science.
Osherson, Daniel N. and Howard Lasnik. An Invitation to cognitive science. Cambridge, MA: MIT Press, 1990.
• Vol. 1. Language;
• Vol. 2. Visual cognition and action;
• Vol. 3. Thinking.
The following philosophy of science book develops a definition of cognitive science as a shared research framework. The book treats Cognitive Science as a distinct, but multidisciplinary, field and clarifies the relationship between Cognitive Science and the component fields.
Von Eckardt, B. (1993). What is Cognitive Science?. Cambridge, MA: MIT Press.
As Cognitive Science is by definition an interdisciplinary field, relevant research is presented in many different journals and conferences from particular disciplines. However, there are also two journals with a particular focus on cognitive science:
• Cognitive Science, which is oriented toward computational issues, and is received in the Engineering library at OSU.
• Cognition, which is oriented toward psychological issues, and is received in the Education library at OSU.
You might want to consult the following sources for additional information on Act-R, including the justification for each theoretical distinction in Act-R and the phenomena that motivated the design of Act-R.
Anderson, J. R. (1983). The Architecture of Cognition. Cambridge: Harvard.
Anderson, J. R. (1990). The Adaptive Character of Thought. Hillsdale, NJ: Lawrence Erlbaum Associates.
Anderson, J. R. (1995). Learning and Memory: An Integrated Approach. New York: John Wiley & Sons.
The following books are good sources of information on cognitive modeling.
Newell, A., & Simon, H. A. (1972). Human Problem Solving. Englewood Cliffs. N.J.: Prentice-Hall.
Newell, A. (1990). Unified Theories of Cognition. Cambridge, MA: Harvard University Press.
Notes for Cognitive Modeling Class
Fall 1996
Tony Simon & Ashwin Ram - September 11, 1997
Introduction to Production Systems
1) BPS
Start with standard BPS excercise 1 WeekClass: BPS Exercise & start of trace
Lab etc: Finish trace, write and test missing production
Aims: Introduction to Representation/Processing Issues
Issues: Procedural/Declarative distinction, Goal Stacks & Context Dependency, Conflict Resolution, "Where the Smarts Are" (repn vs proc)
Reqs: Read R.O.M. Chapter 1 (so start on Tues of Week 2)
To Dos: Read Chapter 2 of R.O.M.
2) ACT-R - Simple TOH Hands-On intro to ACT-R 1-2 Weeks
Class: Chapter 2 Hypercard stack & some exercises
Lab etc: Complete above
Aims: Getting used to ACT-R syntax etc
Issues: Procedural/Declarative distinction (productions/chunks), using MCL
Reqs: Read R.O.M. Chapter 2
Convert BPS into ACT-R
Class: Begin translation process - decide on common representations
Lab etc: Complete & test translation
Aims: Faithful reproduction of BPS code (goal recursive strategy) in ACT-R
Issues: Beware that conflict res without R.A. will create random selection of 1st rule
Reqs: R.O.M. Chapter 2 To Dos: Read Chapter 3 of R.O.M.
Cognitive Modeling Issues in Production Systems
3) ACT-R - Conflict Res. & Activation in TOH 1 Week
Introducing "cognitive" components of ACT-R
Class: Chapter 3 Hypercard stack & discussion of CR
Lab etc: Rewrite 1st rule into specific proposals & set parameters to simulate expert strategy of picking large disk first.
Aims: Cognitive models of conflict resolution
Issues: Why Rational Analysis vs Impasses in Soar for e.g.
Reqs: R.O.M. Chapter 2 To Dos: Read R.O.M. Chapter 4
4) ACT-R - Learning Parameters in TOH 1 Week
How does learning affect performance (Representation & Processing)
Class: Chapter 4 Hypercard stack & discussion of learning?
Lab etc: Complete Exercise?
Aims: Effect of past performance of future repn's & proc
Issues: Comparison to other learning mechs.
Reqs: R.O.M. Chapter 4
To Dos: Read R.O.M Chapters & details of experiments (Santa, Sternberg, etc)
5) ACT-R Models of Psych Experiments Modeling experimental data 1 Week
6) Other Models of Cognitive Processes 2-3 Weeks
Other approaches to modeling other reasoning/thinking/problem-solving/learning
7) Project Presentations 1 Week
PSYC768: Advanced Seminar in Cognitive Science
Sp97: Under the hood: Cognitive theory underlying selected Human Factors phenomena.
Instructor Information: Wayne Gray; (703) 993-1357; gray@gmu.edu; DK 2052
Office Hours: Mon: 3:00-4:00; Thur: 3:00 to 5:00
listserver: HFAC-GRAY@GMU.EDU
Class Time: Thur. 7:20-10pm.
Class Location: Rob. B134
Description (new graduate catalog entry)
This advanced topics series emphasizes current research in cognitive science. Topics may include computational cognitive models, the nature of expertise, diagrammatic reasoning, display-based problem solving, visual attention, decision-making, goal-based versus event-based cognition, and situated action. May be repeated for credit.
Spring 97 description
We will explore the current issues in Human Factors that have (or should have) their bases in cognitive theory. On the Human Factors side, the topics are referred to as display-based problem solving; and situation awareness (one of the "hotter" topics at HFES'96 conference, the new darling of the Aviation Psych and Cognitive Engineering crowd). The cognitive science issues that these topics evoke include; event-driven cognition, visual attention; computational models of display-based performance, control of attention, workload, cognitive load, multiple-resource theory, working memory capacity limits, and what makes tasks hard?
Why theory? How theory?
Newell, A. (1973). You can't play 20 questions wtih nature and win: Projective comments on the papers of this symposium. In W. G. Chase (Ed.), Visual information processing, (pp. 283-308). New York: Academic Press.
Event-driven cognition
Read both of these (57 pp):
Vera, A. H., & Simon, H. A. (1993). Situated action: A symbolic interpretation. Cognitive Science, 17(1), 7-48.
Vera, A. H., & Simon, H. A. (1993). Situated action: Reply to William Clancey. Cognitive Science, 17(1), 117-133.
Visual Attention
Read all three (67 pages)
Posner, M. I. (1980). Orienting of attention. Quarterly Journal of Experimental Psychology, 32, 3-25.
Treisman, A. M., & Sato, S. (1990). Conjunction search revisited. Journal of Experimental Psychology: Human Perception and Performance, 16, 459-478.
Wolfe, J. M. (1994). Guided search 2.0: A revised model of visual search. Psychonomic Bulletin & Review, 1, 202-238.
Display-based problem solving
Read all (64 pp.)
Theory
Larkin, J. H. (1989). Display-based problem solving. In D. Klahr & K. Kotovsky (Eds.), Complex information processing: The impact of Herbert A. Simon, (pp. 319-341). Hillsdale, NJ: Erlbaum.
Studies of display-based skill within HCI
Briggs, P. (1990). Do they know what they're doing? an evaluation of word-processor users' implicit and explicit task-relevant knowledge, and its role in self-directed learning. International Journal of Man-Machine Studies, 32(4), 385-398.
Mayes, J. T., Draper, S. W., McGregor, A. M., & Oatley, K. (1988). information flow in a user interface: the effect of experience and context on the recall of macwrite screens. In D. M. Jones & R. Winder (Eds.), People and Computers IV, (pp. 275-289). New York: Cambridge University Press.
Payne, S. J. (1991). Display-based action at the user interface. International Journal of Man-Machine Studies, 35, 275-289.
Models of display-based skill and its acquisition in HCI
Read Howes & Young and Bauer & John (62 pp), or Kitajima & Polson and Altmann (55 pp)
Altmann, E. M. (August 1996). Thesis summary: Episodic memory for external information.
Bauer, M. I., & John, B. E. (1995). Modeling time-constrained learning in a highly interactive task. In I. R. Katz, R. Mack, L. Marks, M. B. Rosson, & J. Nielsen (Eds.), ACM CHI'95 Conference on Human Factors in Computing Systems, (pp. 19-26). New York: ACM Press.
Howes, A., & Young, R. M. (1996). Learning consistent, interactive and meaningful device methods: a computation model. Cognitive Science, 20(3), 301-356.
Kitajima, M. & Polson, P. G. (1995). A Comprehension based model of correct and errors in skilled, display-based, human-computer interaction. International Journal of Human-Computer Studies, 43, 65-99.
What is Situation awareness?
Read all (70 pp)
Endsley, M. R. (1995). Toward a theory of situation awareness in dynamic systems. Human Factors, 37(1), 32-64.
Adams, Tenney, & Pew (1995). Situation awareness and the cognitive management of complex systems. Human Factors, 37(1), 85-104.
Smith & Hancock (1995). Situation awareness is adaptive, externally directed consciousness. Human Factors, 37(1), 137-148.
Flach, J. M. (1995). Situation awareness: Proceed with caution. Human Factors, 37(1), 149-157.
Dynamic control of attention
Read Allport et al. and Gopher et al. (49 pp), and either Gopher (1993) or Rogers & Monsell (assign students, those in 530 cannot elect Gopher).
Gopher, D. (1993). The skill of attention control: Acquisition and execution of attention strategies. In D. E. Meyer & S. Kornblum (Eds.), Attention and performance XIV: Synergies in experimental psychology, artificial intelligence, and cognitive neuroscience, (pp. 299-322). Cambridge, MA: The MIT Press.
Gopher, D., Weil, M., & Bareket, T. (1994). Transfer of skill from a computer game trainer to flight. Human Factors, 36(3), 387-405.
Rogers, R. D., & Monsell, S. (1995). Costs of a predictable switch between simple cognitive tasks. Journal of Experimental Psychology: General, 124(2), 207-231.
Allport, A., Styles, E. A., & Hsieh, S. (1994). Shifting intentional set: Exploring the dynamic control of tasks. In C. Umilta & M. Moscovitch (Eds.), Attention and performance IV, (pp. 421-452). Cambridge, MA: MIT Press.
What makes tasks hard?
Read Zhang & Norman plus one of the others. (75-80 pp)
Kotovsky, K., Hayes, J. R., & Simon, H. A. (1985). Why are some problems hard? Evidence from tower of hanoi. Cognitive Psychology, 17, 248-294.
Kotovsky, K. & Simon, H. A. (1990). What makes some problems really hard: Explorations in the problem space of difficulty. Cognitive Psychology, 22, 143-183.
Zhang, J. & Norman, D. A. (1994). Representations in distributed cognitive tasks. Cognitive Science, 18, 87-122.
Workload 1--The HF side of things
Read Wierwille et al. and Gopher & Donchin, plus one of the Hancock ones (69-74)
Wierwille, W. W., Rahimi, M., & Casali, J. G. (1985). Evaluation of 16 measures of mental workload using a simulated flight task emphasizing mediational activity. Human Factors, 27(5), 489-502.
Gopher, D., & Donchin, E. (1986). Workload: An examination of the concept. In K. R. Boff, L. Kaufmann, & J. P. Thomas (Eds.), Handbook of perception and human performance, (Vol. II, pp. 41.1-41.49). New York: Wiley.
Hancock, P. A. (1989). The effect of performance failure and task demand on perception of mental workload. Applied Ergonomics, 20(3), 197-205.
Hancock, P. A., & Caird, J. K. (1993). Experimental evaluation of a model of mental workload. Human Factors,
5(3), 413-429.
Workload 2--Cognitive load, goal specificity, Sweller!!!
Read all (53 pp)
Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12, 257-285.
Vollmeyer, R., Burns, B. D., & Holyoak, K. J. (1996). The impact of goal specificity on strategy use and the acquisition of problem structure. Cognitive Science, 20(1), 75-100.
Situation awareness/workload/attention: Multiple-resource theory
Read all (52 pp)
Navon, D. (1984). Resources--A theoretical stone soup? Psychological Review, 91, 216-234.
Hirst, W., & Kalmar, D. (1987). Characterizing attentional resources. Journal of Experimental Psychology: General, 116(1), 68-81.
Wickens, C. D. (1990). Resource management and time-sharing. In J. I. Elkind, S. K. Card, J. Hochberg, & B. M. Huey (Eds.), Human performance models for computer-aided engineerng, (pp. 181-202). Orlando, FL: Academic Press.
Workload 3--Capacity limits?
Read all (45 Psyc Rev pp + manuscript)
Just, M. A., & Carpenter, P. A. (1992). A capacity theory of comprehension: Individual differences in working memory. Psychological Review, 99, 122-149.
Waters, G. S., & Caplan, D. (1996). The capacity theory of sentence comprehension: Critique of Just and Carpenter (1992). Psychological Review, 103(4), 761-772.
Just, M. A., Carpenter, P. A., & Keller, T. A. (1996). The capacity theory of comprehension: New frontiers of evidence and arguments. Psychological Review, 103(4), 773-780.
Huguenard, B. R., Lerch, F. J., Junker, B. W., Patz, R. J., & Kass, R. E. (in press). Working memory failure in phone-based interaction. ACM Transactions on Computer-Human Interaction.
New architectures: EPIC
Read all (?? pp)
The two Psych Rev papers:
Kieras & Meyers
Meyers & Kieras
more on visual attention
Logan, G. D. (1996). The CODE theory of visual attention: An integration of space-based and object-based attention. Psychological Review, 103(4), 603-649.
Is spatial knowledge acquired automatically?
Andrade, J., & Meudell, P. (1993). Is spatial information encoded automatically in memory. Quarterly Journal of Experimental Psychology: Section A -- Human Experimental Psychology, 46, 365-375.
Lansdale, M. W. (1991). Remembering about documents: memory for appearance, format, and location. Ergonomics, 34(8), 1161-1178.
Expectations and course requirements
Each week,each student will be responsible for reading all assigned papers and producing a 2-3 screen email discussion and critique (500-750 words total per week) that will be distributed to class members a minimum of 24 hours before class. Prior to the class, all students will be expected to have read all email correspondence. One student will be responsible for leading the class each week. All students are expected to participate in each week's classroom discussion. All material (assigned papers as well as all email from all students) is fair game for classroom discussion.
In addition to the weekly assignments, each student is responsible for producing a 20 page (max) research proposal. The proposal is due the last day of class (May 8th); drafts received on or before April 24th will be reviewed and returned to the student for revision (N.B., THIS IS OPTIONAL). Other than with regard to figures and tables (which should be inserted in the text rather than at the end) a strict APA format must be followed. The research question pursued should be a refinement of one or more of the topics discussed in class. In addition to the seminar readings and discussion that are relevant to the topic, I expect the papers to demonstrate a command of all published and easily available sources of information as of May 8, 1997. Such sources include journal articles, books, email correspondence with researchers (as appropriate), as well as technical reports and drafts available from web sites or from the authors (as appropriate).
Grading
Grades will be based upon class participation (80%) and term paper (20%).
All weekly activities are considered as in-class participation. These activities include the email discussions and critiques; in-class discussions, as well as leading the in-class discussion.
Ten percent of your in-class grade will be determined by other students. By 5/9, each student is expected to send to me (via email) a rank-ordered list of all students in the class (excluding yourself). This list is for my eyes only and it will be considered confidential and destroyed after I assign grades. Additional information on the procedurals involved will be sent to all class members before 5/8/97.