Learning to like or dislike : revealing similarities and differences between evaluative learning effects

Researchers study phenomena such as the mere-exposure effect, evaluative conditioning, and persuasion to learn more about the ways in which likes and dislikes can be formed and changed. Often, these phenomena are studied in isolation. Here, we review and integrate conceptual analyses that highlight ways to relate these different phenomena and that reveal new avenues for research on evaluative learning. At the core of these analyses lies the idea that evaluative learning can be defined as changes in liking that are due to regularities in the environment. We discuss how this definition allows one to distinguish different types of evaluative learning on the basis of the nature of regularities (e.g., in the presence of one stimulus vs. in the presence of two stimuli) and the function of regularities (i.e., symbolic vs. nonsymbolic)

Issues Affecting Security Design Pattern Engineering

Security Design Patterns present the tried and tested design decisions made by security engineers within a well documented format. Patterns allow for complex security concepts, and mechanisms, to be expressed such that non domain experts can make use of them. Our research is concerned with the development of pattern languages for advanced crypto-systems. From our experience developing pattern languages we have encountered several recurring issues within security design pattern engineering. These issues, if not addressed, will affect the adoption of security design patterns. This paper describes these issues and discusses how they could be addressed

Evaluative conditioning as a symbolic phenomenon: on the relation between evaluative conditioning, evaluative conditioning via instructions, and persuasion

Evaluative conditioning (EC) is sometimes portrayed as a primitive way of changing attitudes that is fundamentally different from persuasion via arguments. We provide a new perspective on the nature of EC and its relation to persuasion by exploring the idea that stimulus pairings can function as a symbol that conveys the nature of the relation between stimuli. We put forward the concept of symbolic EC to refer to changes in liking that occur because stimulus pairings function as symbols. The idea of symbolic EC is consistent with at least some current theories of persuasion. It clarifies what EC research can add to the understanding of the origins of our preferences and has implications for how (symbolic and non-symbolic) EC can be established, the boundaries of EC research, and cognitive and functional models of EC

On the stability of bubble functions and a stabilized mixed finite element formulation for the Stokes problem

In this paper we investigate the relationship between stabilized and enriched finite element formulations for the Stokes problem. We also present a new stabilized mixed formulation for which the stability parameter is derived purely by the method of weighted residuals. This new formulation allows equal order interpolation for the velocity and pressure fields. Finally, we show by counterexample that a direct equivalence between subgrid-based stabilized finite element methods and Galerkin methods enriched by bubble functions cannot be constructed for quadrilateral and hexahedral elements using standard bubble functions.Comment: 25 pages, 13 figures (The previous version was compiled by mistake with the wrong style file, the current one uses amsart, and there is no difference in the text or the figures

Expanding the boundaries of evaluative learning research: how intersecting regularities shape our likes and dislikes

Over the last 30 years, researchers have identified several types of procedures through which novel preferences may be formed and existing ones altered. For instance, regularities in the presence of a single stimulus (as in the case of mere exposure) or 2 or more stimuli (as in the case of evaluative conditioning) have been shown to influence liking. We propose that intersections between regularities represent a previously unrecognized class of procedures for changing liking. Across 4 related studies, we found strong support for the hypothesis that when environmental regularities intersect with one another (i.e., share elements or have elements that share relations with other elements), the evaluative properties of the elements of those regularities can change. These changes in liking were observed across a range of stimuli and procedures and were evident when self-report measures, implicit measures, and behavioral choice measures of liking were employed. Functional and mental explanations of this phenomenon are offered followed by a discussion of how this new type of evaluative learning effect can accelerate theoretical, methodological, and empirical development in attitude research

Peaks of Otter Salamander (Plethodon hubrichti) Condition Declines along an Elevational Gradient

Undergraduate Basi

Smart Tea Project

Conference poster. The lab book is a big block to publication@source, if it’s not digital, it’s difficult to share. Most experimental information is recorded in a lab book in a highly personal way. We have created a new analogy to fully understand the use of the lab book and successfully built and evaluated a working electronic replacement

On the assumptions that we make about the world around us : a conceptual framework for feature transformation effects

Various phenomena such as halo effects, spontaneous trait inferences, and evaluative conditioning have in common that assumptions about object features (e.g., whether a person is intelligent or likeable) are influenced by other object features (e.g., whether that person is attractive or co-occurs with other liked persons). Surprisingly, these phenomena have rarely been related to each other, most likely because different phenomena are described using different terms. To overcome this barrier, we put forward a conceptual framework that can be used to describe a wide range of these phenomena. After introducing the four core concepts of the framework, we illustrate how it can be applied to various phenomena. Doing so helps to reveal similarities and differences between those phenomena, thus improving communication and promoting interactions between different areas of research. Finally, we illustrate the generative power of the framework by discussing some of the new research questions that it highlights