Levels of inquiry: Hierarchies of pedagogical practices and inquiry processes

Provides pedagogical insight concerning the skill of inquiry The resource being annotated is: http://www.dlese.org/dds/catalog_COSEE-1808.htm

Attributions as Behavior Explanations: Toward a New Theory

Attribution theory has played a major role in social-psychological research. Unfortunately, the term attribution is ambiguous. According to one meaning, forming an attribution is making a dispositional (trait) inference from behavior; according to another meaning, forming an attribution is giving an explanation (especially of behavior). The focus of this paper is on the latter phenomenon of behavior explanations. In particular, I discuss a new theory of explanation that provides an alternative to classic attribution theory as it dominates the textbooks and handbooks—which is typically as a version of Kelley’s (1967) model of attribution as covariation detection. I begin with a brief critique of this theory and, out of this critique, develop a list of requirements that an improved theory has to meet. I then introduce the new theory, report empirical data in its support, and apply it to a number of psychological phenomena. I finally conclude with an assessment of how much progress we have made in understanding behavior explanations and what has yet to be learned

Explainable and Advisable Learning for Self-driving Vehicles

Deep neural perception and control networks are likely to be a key component of self-driving vehicles. These models need to be explainable - they should provide easy-to-interpret rationales for their behavior - so that passengers, insurance companies, law enforcement, developers, etc., can understand what triggered a particular behavior. Explanations may be triggered by the neural controller, namely introspective explanations, or informed by the neural controller's output, namely rationalizations. Our work has focused on the challenge of generating introspective explanations of deep models for self-driving vehicles. In Chapter 3, we begin by exploring the use of visual explanations. These explanations take the form of real-time highlighted regions of an image that causally influence the network's output (steering control). In the first stage, we use a visual attention model to train a convolution network end-to-end from images to steering angle. The attention model highlights image regions that potentially influence the network's output. Some of these are true influences, but some are spurious. We then apply a causal filtering step to determine which input regions actually influence the output. This produces more succinct visual explanations and more accurately exposes the network's behavior. In Chapter 4, we add an attention-based video-to-text model to produce textual explanations of model actions, e.g. "the car slows down because the road is wet". The attention maps of controller and explanation model are aligned so that explanations are grounded in the parts of the scene that mattered to the controller. We explore two approaches to attention alignment, strong- and weak-alignment. These explainable systems represent an externalization of tacit knowledge. The network's opaque reasoning is simplified to a situation-specific dependence on a visible object in the image. This makes them brittle and potentially unsafe in situations that do not match training data. In Chapter 5, we propose to address this issue by augmenting training data with natural language advice from a human. Advice includes guidance about what to do and where to attend. We present the first step toward advice-giving, where we train an end-to-end vehicle controller that accepts advice. The controller adapts the way it attends to the scene (visual attention) and the control (steering and speed). Further, in Chapter 6, we propose a new approach that learns vehicle control with the help of long-term (global) human advice. Specifically, our system learns to summarize its visual observations in natural language, predict an appropriate action response (e.g. "I see a pedestrian crossing, so I stop"), and predict the controls, accordingly

How Do Gestures Influence Thinking and Speaking? The Gesture-for-Conceptualization Hypothesis.

Peer reviewedPostprin

Effects of Compensation Strategy on Job Pay Decisions

Previous research has revealed wide variations in pay for the same job, even within a single locality. To date, however, the sources of such pay differentials are not well understood. The present research investigates how compensation managers from a wide variety of organizations combine infonnation about current job pay rates, market rates, and job evaluation points to arrive at new pay rates for jobs. In addition, it examines the role of two pay strategy variables (pay leadership position and external versus internal orientation) in job pay decisions, controlling for differences in organizational demographic characteristics (e.g., size, industry). Results suggest that pay strategies affect assigned pay levels, with higher pay being assigned by managers from fmns with market-leading strategies and internal pay orientations. In addition, pay strategies appear to influence the relative weights attached to market survey versus job evaluation infonnation in pay-setting for jobs. Specifically, although market survey information consistently explained more variance in assigned pay than did job evaluation, this effect was more pronounced among managers from finns having an external orientation. Organizational demographics also affected assigned pay levels, but to a lesser extent than pay strategies

The Arts of Persuasion in Science and Law: Conflicting Norms in the Courtroom

Epistemology is important in the debate about science and technology in the courtroom. The epistemological issues and the arguments about them in the context of scientific and technical evidence are now well developed. Of equal importance, though, is an understanding of norms of persuasion and how those norms may differ across disciplines and groups. Norms of persuasion in the courtroom and in legal briefs differ from norms at a scientific conference and in scientific journals. Here, Kritzer examines the disconnect between science and the courtroom in terms of the differing norms of persuasion found within the scientific community and within the legal community

Backwards is the way forward: feedback in the cortical hierarchy predicts the expected future

Clark offers a powerful description of the brain as a prediction machine, which offers progress on two distinct levels. First, on an abstract conceptual level, it provides a unifying framework for perception, action, and cognition (including subdivisions such as attention, expectation, and imagination). Second, hierarchical prediction offers progress on a concrete descriptive level for testing and constraining conceptual elements and mechanisms of predictive coding models (estimation of predictions, prediction errors, and internal models)

A Fundamentally Irreversible World as an Opportunity towards a Consistent Understanding of Quantum and Cosmological Contexts

In a preceding publication a fundamentally oriented and irreversible world was shown to be de- rivable from the important principle of least action. A consequence of such a paradigm change is avoidance of paradoxes within a “dynamic” quantum physics. This becomes essentially possible because fundamental irreversibility allows consideration of the “entropy” concept in elementary processes. For this reason, and for a compensation of entropy in the spread out energy of the wave, the duality of particle and wave has to be mediated via an information self-image of matter. In this publication considerations are extended to irreversible thermodynamics, to gravitation and cos- mology with its dependence on quantum interpretations. The information self-image of matter around particles could be identified with gravitation. Because information can also impose an al- ways constant light velocity there is no need any more to attribute such a property to empty space, as done in relativity theory. In addition, the possibility is recognized to consider entropy genera- tion by expanding photon fields in the universe. Via a continuous activation of information on matter photons can generate entropy and release small energy packages without interacting with matter. This facilitates a new interpretation of galactic redshift, emphasizes an information link between quantum- and cosmological phenomena, and evidences an information-triggered origin of the universe. Self-organized processes approach maximum entropy production within their constraints. In a far from equilibrium world also information, with its energy content, can self- organize to a higher hierarchy of computation. It is here identified with consciousness. This ap- pears to explain evolution of spirit and intelligence on a materialistic basis. Also gravitation, here identified as information on matter, could, under special conditions, self-organize to act as a su- per-gravitation, offering an alternative to dark matter. Time is not an illusion, but has to be understood as flux of action, which is the ultimate reality of change. The concept of an irreversible physical world opens a route towards a rational understanding of complex contexts in nature