Picture this: the value of multiple visual representations for student learning of quantum concepts in general chemistry

Mental models for scientific learning are often defined as, "cognitive tools situated between experiments and theories" (Duschl & Grandy, 2012). In learning, these cognitive tools are used to not only take in new information, but to help problem solve in new contexts. Nancy Nersessian (2008) describes a mental model as being [loosely] characterized as a representation of a system with interactive parts with representations of those interactions. Models can be qualitative, quantitative, and/or simulative (mental, physical, computational)" (p. 63). If conceptual parts used by the students in science education are inaccurate, then the resulting model will not be useful. Students in college general chemistry courses are presented with multiple abstract topics and often struggle to fit these parts into complete models. This is especially true for topics that are founded on quantum concepts, such as atomic structure and molecular bonding taught in college general chemistry. The objectives of this study were focused on how students use visual tools introduced during instruction to reason with atomic and molecular structure, what misconceptions may be associated with these visual tools, and how visual modeling skills may be taught to support students' use of visual tools for reasoning. The research questions for this study follow from Gilbert's (2008) theory that experts use multiple representations when reasoning and modeling a system, and Kozma and Russell's (2005) theory of representational competence levels. This study finds that as students developed greater command of their understanding of abstract quantum concepts, they spontaneously provided additional representations to describe their more sophisticated models of atomic and molecular structure during interviews. This suggests that when visual modeling with multiple representations is taught, along with the limitations of the representations, it can assist students in the development of models for reasoning about abstract topics such as atomic and molecular structure. There is further gain if students’ difficulties with these representations are targeted through the use additional instruction such as a workbook that requires the students to exercise their visual modeling skills

Constraint-Based Qualitative Simulation

We consider qualitative simulation involving a finite set of qualitative relations in presence of complete knowledge about their interrelationship. We show how it can be naturally captured by means of constraints expressed in temporal logic and constraint satisfaction problems. The constraints relate at each stage the 'past' of a simulation with its 'future'. The benefit of this approach is that it readily leads to an implementation based on constraint technology that can be used to generate simulations and to answer queries about them.Comment: 10 pages, to appear at the conference TIME 200

Rational physical agent reasoning beyond logic

The paper addresses the problem of defining a theoretical physical agent framework that satisfies practical requirements of programmability by non-programmer engineers and at the same time permitting fast realtime operation of agents on digital computer networks. The objective of the new framework is to enable the satisfaction of performance requirements on autonomous vehicles and robots in space exploration, deep underwater exploration, defense reconnaissance, automated manufacturing and household automation