Self-Locating Belief and Updating on Learning

Self-locating beliefs cause a problem for conditionalization. Miriam Schoenfield offers a solution: that on learning E, agents should update on the fact that they learned E. However, Schoenfield is not explicit about whether the fact that they learned E is self-locating. I will argue that if the fact that they learned E is self-locating then the original problem has not been addressed, and if the fact that they learned E is not self-locating then the theory generates implausible verdicts which Schoenfield explicitly rejects

Multiple Universes and Observation Selection Effects

The fine-tuning argument can be used to support the Many Universe hypothesis. The Inverse Gambler’s Fallacy objection seeks to undercut the support for the Many Universe hypothesis. The objection is that although the evidence that there is life somewhere confirms Many Universes, the specific evidence that there is life in this universe does not. I will argue that the Inverse Gambler’s Fallacy is not committed by the fine-tuning argument. The key issue is the procedure by which the universe with life is selected for observation. Once we take account of the procedure, we find that the support for the Many Universe hypothesis remains

Confirmation in a Branching World: The Everett Interpretation and Sleeping Beauty

Sometimes we learn what the world is like, and sometimes we learn where in the world we are. Are there any interesting differences between the two kinds of cases? The main aim of this article is to argue that learning where we are in the world brings into view the same kind of observation selection effects that operate when sampling from a population. I will first explain what observation selection effects are ( Section 1 ) and how they are relevant to learning where we are in the world ( Section 2 ). I will show how measurements in the Many Worlds Interpretation of quantum mechanics can be understood as learning where you are in the world via some observation selection effect ( Section 3 ). I will apply a similar argument to the Sleeping Beauty Problem ( Section 4 ) and explain what I take the significance of the analogy to be ( Section 5 ). Finally, I will defend the Restricted Principle of Indifference on which some of my arguments depend ( Section 6

Ought-contextualism and reasoning

What does logic tells us how about we ought to reason? If P entails Q, and I believe P, should I believe Q? I will argue that we should embed the issue in an independently motivated contextualist semantics for ‘ought’, with parameters for a standard and set of propositions. With the contextualist machinery in hand, we can defend a strong principle expressing how agents ought to reason while accommodating conflicting intuitions. I then show how our judgments about blame and guidance can be handled by this machinery

Toward a user-oriented analytical approach to learning design

The London Pedagogy Planner (LPP) is a prototype for a collaborative online planning and design tool that supports lecturers in developing, analysing and sharing learning designs. The tool is based on a developing model of the components involved in learning design, and the critical relationships between them. As a decision tool, it makes the pedagogical design explicit as an output from the process, capturing it for testing, redesign, reuse and adaptation by the originator, or by others. The aim is to test the extent to which we can engage lecturers in reflecting on learning design, and make them part of the educational community that discovers how best to use Technology Enhanced Learning (TEL). This paper describes the development of LPP, presents pedagogical benefits of visual representations of learning designs, and proposes an analytical approach to learning design based on these visual representations. The analytical approach is illustrated based on an initial evaluation with the lecturers