Ben Wilbrink

Thinking, of course, is a major theme in philosophy, psychology, the neurosciences, and education. My selection of articles and books simply is: is this article or book relevant to questions of design of achievement test items?

For example, Thorndike's association theory was very influential in educational design in the early twentieth century, especially so in mathematics. His associationism is back again, in the highly sophisticated guise of Parrallel Distributed Processing models of 'thinking' in the later twentieth century.

These PDP-models promise to be adequate to the physical structure of the brain, and therefore to its thinking processes. Let me explain in a few words the issue here. Most models in cognitive psychology in the second half of the twentieth century assume thinking to be a linear process, much like the way programmed computers 'think.' However, it is obvious from a little introspection that the brain does not function like a computer. Literally looking inside the brain reveals a multitude of brain cells, all of them being more or less active all of the time. Something heavily 'parallel' is happening here. Thinking about thinking, it is evident that there is not a little thinking man inside our skull, nor are there replica's of the things and events that might be the 'objects' of our thinking. There simply are no brain cells dedicated to storing and giving back a particular name, picture, event, and not other names, pictures, or events. The question then is, how does the brain function in the process that we somehow observe to be the retrieval of information or the construction of new information on the basis of items of information somehow available to or in the brain? What is happening between 'input' to and 'output' from the brain? Between the two a neural network does the job; the network is able to do theat job because in previous learning its multitude of connections have been tuned to deliver the right output. What is more, the same network also is fine-tuned to deliver adequate output to a lot of other possible inputs. PDP-models are about the mechanisms that make this kind of multiple use of the same connections possible. No homunculus, programmer, genii or god is necessary to make this kind of functioning of neural networks possible. The impact of this kind of theory about thinking on didactics should be enormous, once the educational commuty wakes up to its importance. Carl Bereiter's (2002) book is a wake-up call, for example. Thanks to him, I finally realized that PDP models are not simply fascinating in themselves, but will be highly relevant to instructional science also, complementary--at the micro-level--to much of cognitive psychology's--macro-level--achievements of the seventies and eighties of the last century.

Vision is an area that lends itself to some illustrations of what is happening in this Parallel Distributed Processing.

Frank Werblin and Botond Roska (April 2007). The movies in out eyes. Scientific American, 54-61.

"By encoding each piece of knowledge as a large set of interactions, it is possible to achieve useful properties like content-addressable memory and automatic generalization, and new items can be created without having to create new connections at the hardware level."

Rumelhart & McClelland 1987 p. 108
It is easy to see that the citation given is highly relevant to the learning of categories and concepts, very much the basics of what learning is in life as well as in school. The implication is that the design of achievement test items at the level of instances of concepts etcetera, has to reckon with the characteristics of the underlying hardware, in this case the hardware being the student's brainy neural networks. A special case here undoubtedly will be that of the kind of 'wrong' answers in multiple choice questions; the risc being that the wrong kind of wrongness will teach students wrongness itself. There is indeed recent research documenting adverse effects, see chapter two of 'Toetsvragen ontwerpen' html.

Concepts in their turn figure in artificial intellegence's cognitive schemas. How about using PDP models at the schema-level? Rumelhart and McClelland discuss the possibilities in their chapter 14.

A. N. Whitehead (1911/1961/1965). Wiskunde, basis van het exacte denken. Aula 226. [1911 An introduction to mathematics]De Nederlandse titel is een tikje misleidend, daarom het volgende citaat dat duidelijk maat dat Whitehead hier niet een generiek leren denken bedoelt, maar een wetenschappelijke methode:

Carl Bereiter (2002a). Education and Mind in the Knowledge Age. Erlbaum. questia

Parallel Distributed Processing - Connectionism

How the brain's hardware might handle cognition. Ultimately, achievement testing should be valid to the brain's microprocessing of information given and information asked back. Not many specialists in educational measurement ever even offered this suggestion. Carl Bereiter? He is not especially a 'measurement specialist.' Any readers having suggestions for recent research that might be especially relevant to this issue, please let me know.

David E. Rumelhart, James L. McClelland, and the PDP Research Group (1986). Parallel distributed processing. Explorations into the microstructure of cognition. Volume 1: Foundations, 2: Psychological and biological models.. The MIT Press.

James L. McClelland and David E. Rumelhart (1988). Explorations in parallel distributed processing. A handbook of models, programs, and exercises. The MIT Press.

Rogers, T. T. and McClelland, J. L. (2004). Semantic Cognition: A Parallel Distributed Processing Approach. Cambridge, MA: MIT Press. Not (yet?) in

Paul Grobstein Simple networks, simple rules: Learning and creating categories. Serendip site. html

Christian Lebiere, Marsha Lovett, Paul Munro, Christian Schunn (2004). Proceedings of the Sixth International Conference on Cognitive Modeling: 6th ICCM 2004 Integrating Models, July 30-August 1, 2004, Carnegie Mellon University, University of Pittsburgh, Pittsburgh, Pennsylvania, USA. Erlbaum. questia

Philip T. Quinlan (Ed.) (2003). Connectionist Models of Development. Developmental Processes in Real and Artificial Neural Networks. Psychology Press.. questia

Cognitive psychology

P. N. Johnson-Laird (2004). The history of mental models. In Ken Manktelow and Man Cheung Chung: Psychology of Reasoning. Theoretical and Historical Perspectives. Erlbaum questia

Carey, S. (1992). The origin and evolution of everyday concepts. In R. Giere (ed.), Cognitive Models of Science (Minnesota Studies in the Philosophy of Science, Vol. XV). Minneapolis: University of Minnesota Press, 89-128. pdf

Instruction - Education

Ann L. Brown (1992). Design Experiments: Theoretical and Methodological Challenges in Creating Complex Interventions in Classroom Settings. The Journal of the Learning Sciences, 2, 141-178. pdf

E. Fischbein (1975). The intuitive sources of probabilistic thinking in children. Dordrecht: Reidel. isbn 9027706263

Deanna Kuhn (1991). The skills of argument. Cambridge University Press.

Deanna Kuhn (2005). Education for thinking. Harvard University Press.

Marlene Scardamalia (2002). Collective Cognitive Responsibility for the Advancement of Knowledge. In Barry Smith: Liberal Education in a Knowledge Society. Open Court. [" This volume looks at the thinking of educational theorist Carl Bereiter, who has tackled the problem of the liberal education canon in a new way."] pdf

Rupert Wegerif, Li Li & James C. Kaufman (Eds.) (2015). The Routledge International Handbook of Research on Teaching Thinking. Taylor & Francis. [als eBook in KB] info

Jordan P. Lippman, Trina C. Kershaw, James W. Pellegrino & Stellan Ohlsson (2008). Beyond Standard Lectures: Supporting the Development of Critical Thinking in Cognitive Psychology Courses. Chapter 16 in Dana S. Dunn, Jane S. Halonen & Randolph A. Smith (Eds.) (2008). Teaching critical thinking in psychology: a handbook of best practices. Wiley-Blackwell. [niet in UB Leiden] [als eBook in KB] book info, chapter:

Dana S. Dunn, Jane S. Halonen & Randolph A. Smith (Eds.) (2008). Teaching critical thinking in psychology: a handbook of best practices. Wiley-Blackwell. [niet in UB Leiden] [als eBook in KB] book info

Corinne Zimmerman (2007). The development of scientific thinking skills in elementary and middle school. Developmental Review, 27, 172-223. pdf

Jessica Dewey & Janet Bento (2009). Activating children's thinking skills (ACTS): The effect of an infusion approach to teaching thinking in primary schools. British Journal of Educational Psychology, 79, 329-351. fc korter paper

Robert J. Sternberg & Li-Fang Zhang (Eds) (2001) Perspectives on Thinking, Learning, and Cognitive Styles. Erlbaum.

Thinking & Reasoning. Elektronisch tijdschrift ISSN:  1464-0708 Inloggen op ULCN account, wat is dat? 05928635 wil

Herbert A. Simon (Ed.) (1979). Models of thought. New Haven: Yale University Press. isbn 0300024320

Johnson, Donald M. (1972). Systematic introduction to the psychology of thinking. New York: Harper and Row. sbn 060433310

Johnson-Laird, P.N., A taxonomy of thinking. In Sternberg, R.J. (Ed.) The psychology of human thought. Cambridge UP: 1988.

Deanna Kuhn, Eric Amsel & Michael O'Loughlin (1988). The development of scientific thinking skills. Academic Press; 1988; [UB Leiden: PEDAG. 29.e.10] info

Keith J. Holyoak & Barbara A. Spellman (1993). Thinking. Annual Review of Psychology, 44, abstract

Robert J. Sternberg (1997). Thinking styles. Cambridge University Press. isbn 0521553164 info

Austin J. Freeley and David L. Steinberg (2000, 10th). Argumentation and debate. Critical thinking for reasoned decision making. Wadsworth.

Johnson-Laird, P. N. Johnson-Laird & Ruth M. J. Byrne(1991). Deduction. Erlbaum. isbn 0863771483

Karl Duncker (1935/1963 Neudruck). Zur Psychologie des produktiven Denkens. Berlin: Springer. lccc 35-35396 info

'Landmark in the history of cognitive psychology' (Newell, 1985)

Kenneth M. Ford & Patrick J. Hayes (Eds.) (1991). Reasoning Agents in a Dynamic World: The Frame problem. Jai Press. isbn 1559380829

Intriguing. How to solve problems in the real world?

Scott B. Shadrick and James W. Lussier (2009). Training Complex Cognitive Skills: A Theme-Based Approach to the Development of Battlefield Skills. In K. Anders Ericsson (Ed.) (2009). Development of professional expertise: Toward measurement of expert performance and design of optimal Learning Environments (286-311). Cambridge University Press. isbn 9780521740081

  • Richard A. Talaska (Ed.) (1992). Critical reasoning in contemporary culture. SUNY. isbn 0791409805 info

    Eugene J. Meehan (1993). Kritisch leren denken. Aula.

    Kritisch denken, ja ja, geen enkele bron genoemd! Hij is zo overtuigd van zijn eigen denkkracht, dat hij niet op de schouders van reuzen hoeft te gaan staan? Alleen in het voorwoord enige verwijzingen: naar eigen boeken. Weggegooid, dus. (ook absurde repetitievragen aan het eind van ieder hoofdstukje: alleen te beantwoordenals je dat hoofdstukje hebt lezen. Geweldig kritisch, dus. )

    David P. Ausubel (1963). The psychology of meaningful verbal learning. An introduction to school learning. New York: Grune & Stratton.

    Keith E. Stanovich (2009). What intelligence tests miss. The psychology of rational thought. Yale University Press. isbn 9780300123852

    Jonathan St. B. T. Evans (1989). Bias in human reasoning; causes and consequences. Hove, East Sussex: Erlbaum. isbn 0863771068 reviewed

    Barbara Koslowski (1996). Theory and evidence. The development of scientific reasoning. MIT Press. isbn 0262112094

    Bekende thematiek: wetenschappelijk redeneren vaak onderzocht in ‘kennisvrije’ situaties, maar dat redeneren kan natuurlijk niet los worden gekoppeld van disciplinaire kennis. Daarom kan dit wel eens een inspirerend boek zijn. Zie ook

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