Coping with a changing world: the UK Open University approach to teaching ICT

The rapid pace of change in the ICT field has affected all HE providers, but for the UK Open University (UKOU), used to print-based courses lasting eight years or more, it has been a particular challenge. This paper will present some of the ways the UKOU has been coping with this problem by discussing the design of three courses, the first developed almost a decade ago. All three are distance learning courses that are either core or optional in a variety of bachelors' degrees, including the BSc programmes in: Information and Communication Technology; IT and Computing; and Technology; as well as the BEng (Hons) engineering programme. The first course, Information and Communication Technology: people and interactions is a level 2 (second year undergraduate) course first presented in 2002. It is predominately a print-based course with an eight year lifetime. The second course Networked Living: exploring information and communication technologies is a level 1 (first year undergraduate) course first presented some three-and-a-half years later in 2005. It is expected to have a course life of five years, and uses a mix of print-based (60%) and computer-based (40%) material. Both these courses use assignments as key tools for annual updating. The third course, Keeping ahead in ICT is aimed primarily at equipping students with advanced information searching and evaluation skills that will serve them well in professional life, and is presented at level 3 (final year undergraduate). It was first presented in 2007 and has an expected course life of 8 years. It uses much less print than in most OU courses, and has a greater reliance on third-party resources such as newspaper, conference and journal articles, websites, and other electronic resources. Some elements in each block are designed to change from year to year, in order to retain currency. Finally, the paper will look forward to the development of a new level 2 course with an expected first presentation in 2010, drawing out the lessons learned about course updating, and predicting the approach that the course team may tak

Bayesian Conditioning, the Reflection Principle, and Quantum Decoherence

The probabilities a Bayesian agent assigns to a set of events typically change with time, for instance when the agent updates them in the light of new data. In this paper we address the question of how an agent's probabilities at different times are constrained by Dutch-book coherence. We review and attempt to clarify the argument that, although an agent is not forced by coherence to use the usual Bayesian conditioning rule to update his probabilities, coherence does require the agent's probabilities to satisfy van Fraassen's [1984] reflection principle (which entails a related constraint pointed out by Goldstein [1983]). We then exhibit the specialized assumption needed to recover Bayesian conditioning from an analogous reflection-style consideration. Bringing the argument to the context of quantum measurement theory, we show that "quantum decoherence" can be understood in purely personalist terms---quantum decoherence (as supposed in a von Neumann chain) is not a physical process at all, but an application of the reflection principle. From this point of view, the decoherence theory of Zeh, Zurek, and others as a story of quantum measurement has the plot turned exactly backward.Comment: 14 pages, written in memory of Itamar Pitowsk

Subjective probability and quantum certainty

In the Bayesian approach to quantum mechanics, probabilities--and thus quantum states--represent an agent's degrees of belief, rather than corresponding to objective properties of physical systems. In this paper we investigate the concept of certainty in quantum mechanics. Particularly, we show how the probability-1 predictions derived from pure quantum states highlight a fundamental difference between our Bayesian approach, on the one hand, and Copenhagen and similar interpretations on the other. We first review the main arguments for the general claim that probabilities always represent degrees of belief. We then argue that a quantum state prepared by some physical device always depends on an agent's prior beliefs, implying that the probability-1 predictions derived from that state also depend on the agent's prior beliefs. Quantum certainty is therefore always some agent's certainty. Conversely, if facts about an experimental setup could imply agent-independent certainty for a measurement outcome, as in many Copenhagen-like interpretations, that outcome would effectively correspond to a preexisting system property. The idea that measurement outcomes occurring with certainty correspond to preexisting system properties is, however, in conflict with locality. We emphasize this by giving a version of an argument of Stairs [A. Stairs, Phil. Sci. 50, 578 (1983)], which applies the Kochen-Specker theorem to an entangled bipartite system.Comment: 20 pages RevTeX, 1 figure, extensive changes in response to referees' comment

Engaging Assignments Increase Performance

It is well known that students who complete homework assignments and other outside of class activities related to the course lead to improve student outcomes. However, engaging a student and motivating them to complete their assignments is no easy feat. To address this, we developed new assignments for two sections of the Fall 2018 course CS135.https://digitalscholarship.unlv.edu/btp_expo/1054/thumbnail.jp

Consensus in the Presence of Multiple Opinion Leaders: Effect of Bounded Confidence

The problem of analyzing the performance of networked agents exchanging evidence in a dynamic network has recently grown in importance. This problem has relevance in signal and data fusion network applications and in studying opinion and consensus dynamics in social networks. Due to its capability of handling a wider variety of uncertainties and ambiguities associated with evidence, we use the framework of Dempster-Shafer (DS) theory to capture the opinion of an agent. We then examine the consensus among agents in dynamic networks in which an agent can utilize either a cautious or receptive updating strategy. In particular, we examine the case of bounded confidence updating where an agent exchanges its opinion only with neighboring nodes possessing 'similar' evidence. In a fusion network, this captures the case in which nodes only update their state based on evidence consistent with the node's own evidence. In opinion dynamics, this captures the notions of Social Judgment Theory (SJT) in which agents update their opinions only with other agents possessing opinions closer to their own. Focusing on the two special DS theoretic cases where an agent state is modeled as a Dirichlet body of evidence and a probability mass function (p.m.f.), we utilize results from matrix theory, graph theory, and networks to prove the existence of consensus agent states in several time-varying network cases of interest. For example, we show the existence of a consensus in which a subset of network nodes achieves a consensus that is adopted by follower network nodes. Of particular interest is the case of multiple opinion leaders, where we show that the agents do not reach a consensus in general, but rather converge to 'opinion clusters'. Simulation results are provided to illustrate the main results.Comment: IEEE Transactions on Signal and Information Processing Over Networks, to appea