CSR & Cognitive Science

Computer-supported reasoning (CSR) is a singular method of information visualization that supports human reasoning. CSR enables the user to discover and examine, in small datasets of text data objects, all meaningful relationships by viewing the parametric data and concurrently examining additional displayed information, associated images, and sounds. The perceived information is then manipulated as the user's evolving reasoning suggests.


Information visualization presumes that "visual representations and interaction techniques take advantage of the human eye's broad bandwidth pathway into the mind to allow users to see, explore and understand large amounts of information at once (Thomas, 2005). However, as argued later in CONCEPT, there are limits to the amount of information from which the mind can draw conclusions. Information visualization also relates to visual analytics, described in Wikipedia as "concerned with sensemaking and reasoning." Reasoning as described by Evans (2003) occurs two ways: "System 1 processes are rapid, parallel and automatic in nature; only their final product is posted in consciousness ... System 2 thinking is slow and sequential in nature and makes use of the central working system memory ... Despite its limited capacity and slower speed of operation, System 2 permits abstract hypothetical thinking ..."

Singularity of CSR

Data mining, visual analytics, data visualization, text mining, text analytics, business intelligence, and similar methodologies employ like methods. Using computational processes, they generate, from large quantities of data, information displays from which the user can draw conclusions. Implicit is reliance on the algorithms of the process, and noncritical acceptance of the products. That suggests limitation to System 1 reasoning.

In sharp contrast, computer-supported reasoning (CSR) uses the computer only to generate, from small numbers of text data objects, associated images/sounds all at the user's command. Then using the computer solely to manipulate/model the displays in response to the viewer's dynamic reasoning maximizes use of working memory (WM) and hypothetical thinking. CSR supports System 2 reasoning. About CSR, Heelan (2002) wrote "contextual knowing is the product of the kind of human insight into problems presented in experience but contextually in experience, the contexts for which have to be discovered. What you have done is jumped ahead of the statistical factor analysis which is valuable only on the supposition that the relevant factors are all already given and displayed as already categorized ... What you have done is rightly to assume that the relevant categorical relationships have first to be discovered by act of cognitive insight that are creative and depend for their success on past experience of relevant background data fields that have been successfully resolved theoretically ... the genius of your methodology."


The CSR concept includes a table of text data objects, manually or automatically permuted to enable visual discovery of meaningful groups of parameter values and/or sequences of object names. A virtual stack of associated dialog boxes, manually or automatically shuffled, supplements the parametric values with additional information, and links to related text data items. Concurrent and coordinated access is provided to documents, photos, audio files, internet content, etc. associated with the data objects being examined. In addition to enabling simultaneous perceptions of as much information as possible about viewed data objects, the mind will automatically add to the visual and audible perceptions in WM selective relevant representations from declarative and procedural memory (Baddeley & Wilson, 2002). That provides a broad context for the user's reasoning, leading to rapid and easy manipulation/modeling (edit, color, move, annotate, delete, add) of the displayed data. Thus the term computer-supported reasoning (CSR). Related is the description of working memory in Hassin (2005) as, (using the term "online" as "conscious"):

" an online mechanism that retains items in memory for short periods of time ... however, it does more than retain information: Using its executive functions, it selectively attends to the environment (whether internal or external). Moreover, WM can manipulate the items retained in memory, and it can coordinate use of those representations in complex cognitive processes."

CSR also acknowledges the short term limits of WM (Nairne, 2002a) as well as the field of vision, both of which influence the size of the set of text data objects to be analyzed. Significant also in CSR is the element of surprise that often occurs when the data are manipulated, also addressed by Hassin (2005, p. 204):

"... processes that yield insights do not require conscious awareness ...insights tend to pop up in awareness without prior conscious evidence for their formation." Such human-computer interaction was addressed in the following by Schum (2001). "How well we marshal or organize our existing thoughts and evidence influences how well we are able to generate new ideas in the form of hypotheses, new evidential tests of all hypotheses being considered, and defensible arguments linking our evidence and hypotheses. In other contexts, such as in fact investigation in law, we usually encounter singular, unique, or one-of-a-kind events for which no meaningful statistical analyses are possible. What does seem to be common in discovery in different situations is the need to examine different combinations of existing information. Different combinations or juxtapositions of existing information may, in different ways, suggest new ideas and avenues of inquiry. In this paper I describe a prototype system that allows a person to juxtapose thoughts and evidence in different ways, each of which is helpful in suggesting new ideas, new evidence to gather, and new questions to ask."

Those thoughts of Schum obviously relate to System 2 reasoning. They relate also to critical thinking, as it is defined by Halpern (2003, p.6):

"Critical thinking is the use of those cognitive skills and strategies that increase the probability of a desirable outcome. It is used to describe thinking that is purposeful, reasoned, and goal directed - the kind of thinking involved in solving problems, formulating inferences, calculating likelihoods, and making decisions, when the thinker is using skills that are thoughtful and effective for the particular context and type of thinking task."

Concept Materialized

CSR software is described in detail in six patents. Embodiment will result in up to 5 scalable and movable windows displaying: (1) a virtual stack of the dialog boxes that define text data objects ("items"), i.e.. parametric values - and more, (2) a dynamic table listing parametric values of selected data items; (3) a list of queries, i.e. varying specifications of items for analysis, (4) images and/or sounds associated with those items, and (5) fields for "tags", brief user statements of the significance of selected items. Envisioned are 3 versions of an application, the first comprised of (1), (2), and (3), the second adding (4), and the third adding (5).

Such software is a general purpose thinking tool usable by almost anyone who must personally plan, track and/or analyze a number of things of any type. Relevant occupations include intelligence analysis, law investigation, archeology, management (CEO to supervisor), investigation of aircraft accidents, and many more.

The value of CSR is limited, as with spreadsheets, only by the imagination of the user. CSR software engages the user's reasoning throughout the process. The product of the operation is in the user's mind, the result of the user's reasoning that controls the process rather than becoming engaged after the computer has generated a product.


Baddeley, A.D. & Wilson, B. (2002). Prose recall and amnesia; Implications for the structure of working memory. Neuropsychologia, 40. 1737-1743.

Evans, J. St. B. T (2003). In two minds: Dual processing accounts of reasoning. Trends in Cognitive Science, 7.454-459

Halpern, D.F. (2003). Thought and Knowledge, Mahwah, NJ: Lawrence Erlbaum Associates.

Hassin, R.R. (2005. Nonconscious Control and Implicit Working Memory. In Hassan et al (Eds.). The New Unconscious. New York: Oxford University Press. 196-222

Heelan, P.A. (2002). Email message to CDM inventor. The Georgetown University.

Miller, G. A. (1956). Psychological Review 63 (2), 81-97.

Nairne, J.S. (2002a). Remembering the short term: The case against the standard model. Annual Review of Psychology, 53-81

Schum, David (2001). Evidence Marshaling for Imaginative Fact Investigation, Artificial Intelligence and Law, The Netherlands: Klumer Academic Publishers. 165

Thomas, James and Cook, Kristin (Ed.) (2005). Illuminating the Path: The R&D Agenda for Visual Analytics. National Visualization and Analytics Center. 30


Closely related to the above is the following excerpt from the essay "On Free Will" (Harper's, September, 2014) written by Edward O. Wilson, the eminent biologist, researcher, theorist, naturalist and author:

"Our minds consist of storytelling. In each instant, a flood of information flows into our senses, more than the brain can process. To augment the fraction of this information, we summon the stories of past events for context and meaning. We compare the past and the present and apply the decisions that were made previously, variously right or wrong. Then we look forward, creating - not just recalling this time - multiple competing scenarios. These are weighed against one another by the suppressing or intensifying effect imposed by aroused emotional centers. A choice is made in the unconscious centers of the brain, recent studies tell us, several seconds before the decision arrives in the conscious part."

That affirms, I believe, the need for analytics firms to consider the cognitive aspects of what occurs in the minds of those using their products, as well as how many users there can be in almost any type of enterprise.

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© 2020 Execware, LLC