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Physical Sciences and Mathematics Commons

Open Access. Powered by Scholars. Published by Universities.®

Computer Sciences

University of Texas at El Paso

2012

Uncertainty

Articles 1 - 2 of 2

Full-Text Articles in Physical Sciences and Mathematics

How To Divide Students Into Groups So As To Optimize Learning: Towards A Solution To A Pedagogy-Related Optimization Problem, Olga Kosheleva, Vladik Kreinovich Jul 2012

How To Divide Students Into Groups So As To Optimize Learning: Towards A Solution To A Pedagogy-Related Optimization Problem, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

To enhance learning, it is desirable to also let students learn from each other, e.g., by working in groups. It is known that such groupwork can improve learning, but the effect strongly depends on how we divide students into groups. In this paper, based on a first approximation model of student interaction, we describe how to optimally divide students into groups so as to optimize the resulting learning. We hope that, by taking into account other aspects of student interaction, it will be possible to transform our solution into truly optimal practical recommendations.


Partial Orders For Representing Uncertainty, Causality And Decision Making: General Properties, Operations, And Algorithms, Francisco Adolfo Zapata Jan 2012

Partial Orders For Representing Uncertainty, Causality And Decision Making: General Properties, Operations, And Algorithms, Francisco Adolfo Zapata

Open Access Theses & Dissertations

One of the main objectives of science and engineering is to help people select the most beneficial decisions. To make these decisions, we must know people's preferences, we must have the information about different possible consequences of different decisions. Since information is never absolutely accurate and precise, we must also have information about the degree of certainty of different parts on information. All these types of information naturally lead to partial orders:

- For preferences, a <= b means that b is preferable to a. This relation is used in decision theory.

- For events, a <= b means that a can influence b. This causality relation is one of the fundamental notions of physics, especially of physics of space-time.

* For uncertain statements, a <= b means that a is less certain than b. This relation is used in logics describing uncertainty, such as fuzzy logic.

In each of these areas, there is abundant research about studying the corresponding partial orders. …