Criteria and Scale for Argumentation

This paper presents an updated and practical criteria and scale for teaching, learning, and evaluating argumentation. The ability criteria and scale is generated from existing knowledge of argumentation as expected by CEFR, TOEFL and IELTS, as well as recent interest in argumentation. Examination of the academic literature suggests that the new criteria and scale should consider relevancy, reasoning, language use, organization and writer’s voice. Relevancy has not yet been seriously highlighted in the existing criteria. Reasoning, language use and organization are common criteria in argumentation. Writer’s voice is not emphasized in the existing criteria but often discussed in recent publications on argumentation. It is added to the updated framework in this paper to keep up with advancements in the field. This new framework could be a powerful option for teaching, learning and evaluating argumentation particularly in EFL or ESL contexts

A pragmatic approach to semantic repositories benchmarking

The aim of this paper is to benchmark various semantic repositories in order to evaluate their deployment in a commercial image retrieval and browsing application. We adopt a two-phase approach for evaluating the target semantic repositories: analytical parameters such as query language and reasoning support are used to select the pool of the target repositories, and practical parameters such as load and query response times are used to select the best match to application requirements. In addition to utilising a widely accepted benchmark for OWL repositories (UOBM), we also use a real-life dataset from the target application, which provides us with the opportunity of consolidating our findings. A distinctive advantage of this benchmarking study is that the essential requirements for the target system such as the semantic expressivity and data scalability are clearly defined, which allows us to claim contribution to the benchmarking methodology for this class of applications

Real-time value-driven diagnosis

Diagnosis is often thought of as an isolated task in theoretical reasoning (reasoning with the goal of updating our beliefs about the world). We present a decision-theoretic interpretation of diagnosis as a task in practical reasoning (reasoning with the goal of acting in the world), and sketch components of our approach to this task. These components include an abstract problem description, a decision-theoretic model of the basic task, a set of inference methods suitable for evaluating the decision representation in real-time, and a control architecture to provide the needed continuing coordination between the agent and its environment. A principal contribution of this work is the representation and inference methods we have developed, which extend previously available probabilistic inference methods and narrow, somewhat, the gap between probabilistic and logical models of diagnosis

Operational Risk Management using a Fuzzy Logic Inference System

Operational Risk (OR) results from endogenous and exogenous risk factors, as diverse and complex to assess as human resources and technology, which may not be properly measured using traditional quantitative approaches. Engineering has faced the same challenges when designing practical solutions to complex multifactor and non-linear systems where human reasoning, expert knowledge or imprecise information are valuable inputs. One of the solutions provided by engineering is a Fuzzy Logic Inference System (FLIS). Despite the goal of the FLIS model for OR is its assessment, it is not an end in itself. The choice of a FLIS results in a convenient and sound use of qualitative and quantitative inputs, capable of effectively articulating risk management's identification, assessment, monitoring and mitigation stages. Different from traditional approaches, the proposed model allows evaluating mitigation efforts ex-ante, thus avoiding concealed OR sources from system complexity build-up and optimizing risk management resources. Furthermore, because the model contrasts effective with expected OR data, it is able to constantly validate its outcome, recognize environment shifts and issue warning signals.Operational Risk, Fuzzy Logic, Risk Management Classification JEL:G32, C63, D80

Solving professional problems together

Future professionals should be prepared for scientific reasoning, i.e., to construct and apply scientific knowledge, in order to analyze and solve problems in their professional practice. Yet, future practitioners’ scientific reasoning skills often seem to be deficient when solving practical problems. This dissertation explores to what extent collaboration may foster the engagement of future practitioners in scientific reasoning: i.e., in epistemic processes (e.g., hypothesizing, evaluating evidence) and in referring to scientific content knowledge (e.g., scientific theories and evidence). Therefore, two studies were conducted to compare collaborative and individual problem solving of pre-service teachers regarding their scientific reasoning. Study 1 investigates the effect of group heterogeneity with respect to problem solving scripts on scientific reasoning. Study 2 explores to what extent Epistemic Network Analysis can serve as a methodological approach for measuring scientific reasoning. As part of Study 1, pre-service teachers solved an educational problem either as individuals (N=16) or as pairs (N=30 pairs). Collaboration showed a mixed effect on scientific reasoning processes: pairs engaged more in explaining and reasoning about the problem and drew more conclusions, while individuals engaged more in generating solutions. Additional analyses showed that the more heterogeneous pairs were regarding their members’ problem solving scripts the more they engaged in hypothesizing and evaluating evidence and the less they engaged in generating solutions. Finally, pairs less often referred to scientific content than individuals did during problem solving. Study 2 further analyzed the data by applying Epistemic Network Analysis. This method has the advantage of analyzing patterns of connections between epistemic processes, i.e., epistemic networks of scientific reasoning. The central epistemic process for pairs was evidence evaluation, which they frequently used in combination with hypothesizing and communicating and scrutinizing. On the other hand, the most characteristic process in individuals’ scientific reasoning was solution generation, which very often co-occurred with hypothesizing and evidence evaluation. The overall results indicate that if the aim is to develop a more reflective understanding of the problem, future practitioners should collaborate with each other, especially in heterogeneous settings. However, they should be supported (1) to share knowledge regarding scientific theories and evidence as well as (2) to reach a mutual understanding (e.g., by coordinating explanations) on the problem after a certain time so as to be able to have the capacity of generating solutions. Moreover, the different effects of collaboration on the process and content aspects of scientific reasoning imply that scientific reasoning might not be a unidimensional construct, and its process and content levels should be differentiated in future research. A further important methodological implication is that the process aspect of scientific reasoning can be analyzed as a network of interconnected skills and such analysis might bring more explanatory value than the mere reliance on frequencies of occurrences of isolated activities

Introduction

This chapter begins by explaining two widespread attitudes towards the methods of moral philosophy. The first common attitude is that the appropriate method for doing ethics was described by John Rawls when he formulated the reflective equilibrium method. Another common attitude is that moral philosophy has no method – anything goes in ethical theorising as long as the results are significant enough. The chapter then motivates the volume by arguing that these attitudes are not helpful. The reflective equilibrium method has its limits and yet not all ways of proceeding in ethics are equally good. For this reason, I argue that we need to be more aware of the argumentative strategies we employ in ethics. This requires being methodologically reflective and transparent and taking part in the debates about the merits and problems of different methodologies exactly in the way done in the chapters of this volume. The second half of the chapter then provides an outline of the other chapters. Here I focus on clarifying exactly how these chapters contribute to the new discussions about the methods of ethics

Helping education undergraduates to use appropriate criteria for evaluating accounts of motivation

The aim of the study was to compare students in a control group with those in a treatment group with respect to evaluative comments on psychological accounts of motivation. The treatment group systematically scrutinized the nature and interpretation of evidence that supported different accounts, and the assumptions, logic, coherence and clarity of accounts. Content analysis of 74 scripts (using three categories) showed that the control group students made more assertions than either evidential or evaluative points, whereas the treatment group used evaluative statements as often as they used assertion. The findings provide support for privileging activities that develop understanding of how knowledge might be contested, and suggest a need for further research on pedagogies to serve this end. The idea is considered that such understanding has a pivotal role in the development of critical thinking

Building an Expert System for Evaluation of Commercial Cloud Services

Commercial Cloud services have been increasingly supplied to customers in industry. To facilitate customers' decision makings like cost-benefit analysis or Cloud provider selection, evaluation of those Cloud services are becoming more and more crucial. However, compared with evaluation of traditional computing systems, more challenges will inevitably appear when evaluating rapidly-changing and user-uncontrollable commercial Cloud services. This paper proposes an expert system for Cloud evaluation that addresses emerging evaluation challenges in the context of Cloud Computing. Based on the knowledge and data accumulated by exploring the existing evaluation work, this expert system has been conceptually validated to be able to give suggestions and guidelines for implementing new evaluation experiments. As such, users can conveniently obtain evaluation experiences by using this expert system, which is essentially able to make existing efforts in Cloud services evaluation reusable and sustainable.Comment: 8 page, Proceedings of the 2012 International Conference on Cloud and Service Computing (CSC 2012), pp. 168-175, Shanghai, China, November 22-24, 201