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.
- "The retina processes information much more than anyone has ever imagined, sending a dozen different movies to the brain."
- film of images being sent to the brain. The remarkable thing is that the 'images' almost literally 'sent to the brain' are extremely coarse, meaning the brain's neural networks have to work very hard to construct the images the rabbit 'sees.' Humans are related to rabbits, remember? The hard work of the brain = Parallel Distributed Processing. The film is about several different images being sent to different parts of the brain, take a peak. Somehow or other the brain gathers that distributed information together again, producing the wonderful world we think we see 'directly.' You do not believe this? Try looking through a stereoscopic viewer to some old fashioned stereoscopic photographs of the Liberty Statue or whatever: it is not easy to 'see' only one picture in depth, but suddenly it is there! In a split second the brain's neural networks have figured it out! Nothing 'you' can do about it!
Of course, in the case of vision, the retinal receptors take the input, the world you 'see' is the output of the neural network or the parrallel distributed processing in between. Some of this brainy hardware must already come pre-programmed at birth, but most of the delicate structures of this neural network have been 'learned' or 'tuned' during your lifetime.
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.
"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
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 archive.org]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:
p. 8: The object of the following Chapters is not to teach mathematics, but to enable students from the very beginning of their course to know what the science is about, and why it is necessarily the foundation of exact thought as applied to natural phenomena. [my emphasis, b.w.]
Whitehead (1924, p. 61): It is a profoundly erroneous truism, repeated by all copy-books and by eminent people when they are making speeches, that we should cultivate the habit of thinking of what we are doing. The precise opposite is the case. Civilization advances by extending the number of important operations which we can perform without thinking about them. Operations of thought are like cavalry charges in a battle| they are strictly limited in number, they require fresh horses, and must only be made at decisive moments.
Carl Bereiter (2002a). Education and Mind in the Knowledge Age. Erlbaum. questia
- My summary and annotations in a special page
- Een sterk statement over de stand van zaken in wat cognitieve wetenschappen en hedendaagse filosofie over de inrichting van de leeromgeving te melden hebben.
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 questia.com
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
- a.o. Yasuaki Sakamoto, Toshihiko Matsuka and Bradley C. Love: Dimension-Wide vs. Exemplar-Specific Attention in Category Learning and Recognition - David Danks: Constraint-Based Human Causal Learning - Helmar Gust, Kai-Uwe Kuhnberger and Ute Schmid: Ontological Aspects of Computing Analogies - Alexei Samsonovich and Kenneth DeJong: A General-Purpose Computational Model of the Conscious Mind - Lael J. Schooler and Ralph Hertwig: How Forgetting Fosters Heuristic Inference - M. Afzal Upal: A Computational Model for Acquisition of Counterintuitive Concepts
Philip T. Quinlan (Ed.) (2003). Connectionist Models of Development. Developmental Processes in Real and Artificial Neural Networks. Psychology Press.. questia
a.o. Steven R. Quartz: Learning and brain development: A neural constructivist perspective
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
- The story of a personal tour of discovery. Introduction to the literature on thinking in education. Use its title to find more recent expositions. Use its list of references to locate the classics in the field.
E. Fischbein (1975). The intuitive sources of probabilistic thinking in children. Dordrecht: Reidel. isbn 9027706263
- Jane M. Watson and Jonathan B. Moritz (2002). School students' reasoning about conjunction and conditional events. International Journal of Mathematical Education in Science and Technology
- Jenni Way (2003). The development of young children's notions of probability. European Research in Mathematics Education III Proceedings of the Third Conference of the European Society for Research in Mathematics Education 28 February - 3 March 2003pdf
Deanna Kuhn (1991). The skills of argument. Cambridge University Press.
Deanna Kuhn (2005). Education for thinking. Harvard University Press.
- This is an exposition of what thinking in education should be. Use it to find out what the shortcomings are of the many attempts to introduce 'thinking' in education. Do not be mistaken about this text: it is evidence based, and the evidence in the book itself consists of highly revealing reports of classical teaching of 'thinking' as it typically is practiced by teachers everywhere in the U.S., or the world, for that matter. I my opninion, this is a key publication on education for the early twentyfirst century. I will use it to lay a secure fundament under my design technology for achievement test items.
- My summary and annotations in a special page
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
- Teaching for Thinking: Ethical Reasoning. Robert J. Sternberg
- A Recent History of Teaching Thinking. Steve Higgins
- Teaching Thinking: An Ideological Perspective. Yoram Harpaz
- How to improve thinking. P.N. Johnson-Laird
- Teaching for Successful Intellectual Styles. Li-fang Zhang.
- Using an Informed Understanding of Styles to Enhance Learning and Teaching in 21st century Learning Environments. Carol Evans and Michael Waring.
- Thinking about metacognition improves thinking. Marcel V.J. Veenman.
- Do They Really Work? Evidence For The Efficacy Of Thinking Skills Approaches In Affecting Learning Outcomes: The Need For A Broader Perspective. Robert Burden.
- Assessing Critical Thinking in Our Students. Heather A. Butler.
- Assessing Creative Thinking: Practical Applications. Haiying Long and Jonathan A. Plucker.
- A Model for the Assessment of Rational Thought and its Potential Operationalization. Richard F. West Keith E. Stanovich
- STEM Education and Problem-Based Learning Areej M. Adel El Sayary, Sufian A. Forawi, and Nasser Mansour
- The Teaching and Learning of Probabilistic Thinking: Heuristic, Informal and Fallacious Reasoning. Egan J Chernoff and Bharath Sriraman.
- Epistemic practices and thinking in science: fostering teachers' development in scientific argumentation. Sibel Erduran and Merce Garcia-Mila.
- Teaching Mathematics Creatively. Ai-Girl Tan
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: researchgate.net
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
- Recent interest in the teaching of thinking skills within education has led to an increase in thinking skills packages available to schools. However many of these are not based on scientific evaluation (DfEE, 1999). This paper endeavours to examine the effectiveness of one approach, that of infusion, to teaching thinking.
Robert J. Sternberg & Li-Fang Zhang (Eds) (2001) Perspectives on Thinking, Learning, and Cognitive Styles. Erlbaum.
- Robert J. Sternberg and Elena L. Grigorenko: A Capsule History of Theory and Research on Styles - Joseph S. Renzulli and David Yun Dai: Abilities, Interests, and Styles as Aptitudes for Learning: A Person-Situation Interaction Perspective - Richard Riding: The Nature and Effects of Cognitive Style - John Biggs: Enhancing Learning: A Matter of Style or Approach? - Noel Entwistle, Velda McCune, and Paul Walker: Conceptions, Styles, and Approaches Within Higher Education: Analytical Abstractions and Everyday Experience - Gillian M. Boulton-Lewis, Ference Marton, and Lynn A. Wilss: The Lived Space of Learning: An Inquiry into Indigenous Australian University Students' Experiences of Studying - David Watkins: Correlates of Approaches to Learning: A Cross-Cultural Meta-Analysis - Li-fang Zhang and Robert J. Sternberg: Thinking Styles across Cultures: Their Relationships with Student Learning - David A. Kolb, Richard E. Boyatzis, and Charalampos Mainemelis: Experiential Learning Theory: Previous Research and New Directions - Robert J. Sternberg: Epilogue: Another Mysterious Affair at Styles
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
The controversies over methods of instruction are somewhat similar in shape and intensity, nevertheless, to controversies over theories of learning. And one of the most persistent of these, which may be phrased as rote learning versus meaningful learning, or drill versus understanding, applies with equal emphasis to problem solving. A second controversy, overlapping the first, is that between discovery and expository learning. Is it better to let a student make errors and discover the solution by himself or to explain to him how to solve a problem? This is an active topic of discussion even though there is some uncertainty about the meaning of discovey
in this context (Shulman and Keislar, 1966). But one thing is clear. There is no magic formula for teaching people how to solve problems. Research will not prove that one method is right and the others wrong.
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]
D. Kuhn, Introduction.The Development of Scientific Thinking.Related Work.D. Kuhn and E. Amsel with the assistance of L. Schauble, The Evaluation of Evidence.The Interpretation of Covariation and Noncovariation Evidence.The Influence of Theory on Evaluation of Evidence.The Reconstruction of Theory and Evidence.D. Kuhn and M. O'Loughlin with the assistance of W. Yotive, The Coordination of Theory and Evidence.Replication: The Evaluation of Evidence.The Interpretation of Insufficient and Mixed Evidence.The Coordination of Evidence with Multiple Theories.The Generation of Evidence to Evaluate Theories.The Development of Skills in Coordinating Theory and Evidence.D. Kuhn and B. Leadbeater, The Connection of Theory and Evidence.The Interpretation of Divergent Evidence.D. Kuhn, Conclusion.Summary and Conclusions.
Keith J. Holyoak & Barbara A. Spellman (1993). Thinking. Annual Review of Psychology, 44,
Robert J. Sternberg (1997). Thinking styles. Cambridge University Press. isbn 0521553164
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.
Robert H. Ennis: Conflicting views on teaching critical reasoning
John E. McPeck: Teaching Critical Reasoning through the Disciplines: Content versus Process
Ralph H. Johnson: Critical Reasoning and Informal Logic
Harvey Siegel: Education and the Fostering of Rationality
Robert J. Sternberg: Creativity, critical reasoning, and the problem of content-oriented education
Michael Scriven: Evaluation and critical reasoning: Logic's last frontier?
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.
Another way in which educators have evaded responsibility for programing the content of instruction has been by hiding behind the slogan that the function of the school is to “teach children how to think—not what to think.” This slogan also states a false dichotomy since the two functions are by no means mutually exclusive. Actually, as will be argued later, the transmission of subject matter can be considered the primary function of the school. Most of the thinking that goes on in school is and should be supplementary to the process of reception learning, that is, concerned with having students assimilate subject-matter content in a more active, integrative, and critical fashion. Development of thinking or problem-solving ability can also be considered an objective of schooling in its own right, although it is a lesser objective than the learning of subject matter and is only partly teachable; but under no circumstances is it a proper substitute for reception learning or a feasible primary means of imparting subject-matter knowledge.
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
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 http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.330.8346&rep=rep1&type=pdf
Michelene Chi's publications