Posts Tagged: representation

representational issues, framing

Chapter: The cognitive basis of arithmetic

The truths about numbers are in us; but still we learn them.
G.W. Leibniz (1765), Nouveaux essais sur l’entendement humain, p. 85

[Copyright neth.de, 2010]:

Helen De Cruz, Hans Neth, Dirk Schlimm (2010). The cognitive basis of arithmetic.

Helen De Cruz, Hansjörg Neth, Dirk Schlimm

The cognitive basis of arithmetic

Overview:  Arithmetic is the theory of the natural numbers and one of the oldest areas of mathematics.  Since almost all other mathematical theories make use of numbers in some way or other, arithmetic is also one of the most fundamental theories of mathematics.  But numbers are not just abstract entities that are subject to mathematical ruminations — they are represented, used, embodied, and manipulated in order to achieve many different goals, e.g., to count or denote the size of a collection of objects, to trade goods, to balance bank accounts, or to play the lottery. Consequently, numbers are both abstract and intimately connected to language and to our interactions with the world.  In the present paper we provide an overview of research that has addressed the question of how animals and humans learn, represent, and process numbers.

Paper: Feedback design for controlling a dynamic multitasking system


If an organism is confronted with the problem of behaving approximately rationally,
or adaptively, in a particular environment, the kinds of simplifications that are suitable
may depend not only on the characteristics—sensory, neural, and other—of the organism,
but equally on the nature of the environment.
H.A. Simon (1956), Rational choice and the structure of the environment, p. 130

[Copyright neth.de, 2008]:

Hans Neth, Sunny Khemlani, Wayne Gray (2008)

Feedback design for the control of a dynamic multitasking system: Dissociating outcome feedback from control feedback. Human Factors Journal, 2008.

Hansjörg Neth, Sangeet S. Khemlani, Wayne D. Gray

Feedback design for the control of a dynamic multitasking system: Dissociating outcome feedback from control feedback

Objective: We distinguish outcome feedback from control feedback to show that suboptimal performance in a dynamic multitasking system may be caused by limits inherent to the information provided rather than human resource limits.

Paper: A taxonomy of (practical vs. theoretical) actions

The solution to a problem changes the problem.
Peer’s Law

[Copyright neth.de, 2008]:

Hans Neth and Thomas Mueller (2008). Thinking by doing and doing by thinking: A taxonomy of actions. Paper presented at CogSci 2008.


Hansjörg Neth, Thomas Müller

Thinking by doing and doing by thinking: A taxonomy of actions

Abstract:  Taking a lead from existing typologies of actions in the philosophical and cognitive science literatures, we present a novel taxonomy of actions. 

Paper: Arithmetic with Arabic vs. Roman numerals


… how information is represented can greatly affect how easy it is
to do different things with it. (…) it is easy to add, to subtract,
and even to multiply if the Arabic or binary representations are used,
but it is not at all easy to do these things — especially multiplication —
with Roman numerals.  This is a key reason why the Roman culture failed
to develop mathematics in the way the earlier Arabic cultures had.
D Marr (1982): Vision, p. 21

[Copyright neth.de, 2008]:

Dirk Schlimm and Hans Neth (2008).

Modeling ancient and modern arithmetic practices: Addition and multiplication with Arabic and Roman numerals. Paper presented at CogSci 2008.


Dirk Schlimm, Hansjörg Neth

Modeling ancient and modern arithmetic practices: Addition and multiplication with Arabic and Roman numerals

Abstract:  To analyze the task of mental arithmetic with external representations in different number systems we model algorithms for addition and multiplication with Arabic and Roman numerals.  This demonstrates that Roman numerals are not only informationally equivalent to Arabic ones but also computationally similar — a claim that is widely disputed.  An analysis of our models’ elementary processing steps reveals intricate trade-offs between problem representation, algorithm, and interactive resources.  Our simulations allow for a more nuanced view of the received wisdom on Roman numerals.  While symbolic computation with Roman numerals requires fewer internal resources than with Arabic ones, the large number of needed symbols inflates the number of external processing steps.