A literature review of expert problem solving using analogy

We consider software project cost estimation from a problem solving perspective. Taking a cognitive psychological approach, we argue that the algorithmic basis for CBR tools is not representative of human problem solving and this mismatch could account for inconsistent results. We describe the fundamentals of problem solving, focusing on experts solving ill-defined problems. This is supplemented by a systematic literature review of empirical studies of expert problem solving of non-trivial problems. We identified twelve studies. These studies suggest that analogical reasoning plays an important role in problem solving, but that CBR tools do not model this in a biologically plausible way. For example, the ability to induce structure and therefore find deeper analogies is widely seen as the hallmark of an expert. However, CBR tools fail to provide support for this type of reasoning for prediction. We conclude this mismatch between experts’ cognitive processes and software tools contributes to the erratic performance of analogy-based prediction

Understanding object feature binding through experimentation as a precursor to modelling

In order to explore underlying brain mechanisms and to further understand how and where object feature binding occurs, psychophysical data are analysed and will be modelled using an attractor network. This paper describes psychophysical work and an outline of the proposed model. A rapid serial visual processing paradigm with a post-cue response task was used in three experimental conditions: spatial, temporal and spatio-temporal. Using a ‘staircase’ procedure, stimulus onset asynchrony for each observer for each condition was set in practice trails to achieve ~50% error rates. Results indicate that spatial location information helps bind objects features and temporal location information hinders it. Our expectation is that the proposed neural model will demonstrate a binding mechanism by exhibiting regions of enhanced activity in the location of the target when presented with a partial post-cue. In future work, the model could be lesioned so that neuropsychological phenomena might be exhibited. In such a way, the mechanisms underlying object feature binding might be clarified

Software Defect Association Mining and Defect Correction Effort Prediction

Much current software defect prediction work concentrates on the number of defects remaining in software system. In this paper, we present association rule mining based methods to predict defect associations and defect-correction effort. This is to help developers detect software defects and assist project managers in allocating testing resources more effectively. We applied the proposed methods to the SEL defect data consisting of more than 200 projects over more than 15 years. The results show that for the defect association prediction, the accuracy is very high and the false negative rate is very low. Likewise for the defect-correction effort prediction, the accuracy for both defect isolation effort prediction and defect correction effort prediction are also high. We compared the defect-correction effort prediction method with other types of methods: PART, C4.5, and Na¨ıve Bayes and show that accuracy has been improved by at least 23%. We also evaluated the impact of support and confidence levels on prediction accuracy, false negative rate, false positive rate, and the number of rules. We found that higher support and confidence levels may not result in higher prediction accuracy, and a sufficient number of rules is a precondition for high prediction accuracy

Data quality: Some comments on the NASA software defect datasets

Background-Self-evidently empirical analyses rely upon the quality of their data. Likewise, replications rely upon accurate reporting and using the same rather than similar versions of datasets. In recent years, there has been much interest in using machine learners to classify software modules into defect-prone and not defect-prone categories. The publicly available NASA datasets have been extensively used as part of this research. Objective-This short note investigates the extent to which published analyses based on the NASA defect datasets are meaningful and comparable. Method-We analyze the five studies published in the IEEE Transactions on Software Engineering since 2007 that have utilized these datasets and compare the two versions of the datasets currently in use. Results-We find important differences between the two versions of the datasets, implausible values in one dataset and generally insufficient detail documented on dataset preprocessing. Conclusions-It is recommended that researchers 1) indicate the provenance of the datasets they use, 2) report any preprocessing in sufficient detail to enable meaningful replication, and 3) invest effort in understanding the data prior to applying machine learners

Possible geopotential improvement from satellite altimetry

Possible geopotential improvement from satellite altimetr

Social Studies of Social Science: A Working Bibliography

The social sciences are currently going through a reflexive phase, one marked by the appearance of a wave of studies which approach their disciplines’ own methods and research practices as their empirical subject matter. Driven partly by a growing interest in knowledge production and partly by a desire to make the social sciences ‘fit-for-purpose’ in the digital era, these studies seek to reinvigorate debates around methods by treating them as embedded social and cultural phenomena with their own distinctive biographical trajectories – or “social lives”. Empirical studies of social scientific work and the role of methods within it, however, remain relatively scarce. There are several reasons for this but, for one thing, it can be difficult to find examples of how such studies might be undertaken. This contribution draws together a literature scattered across various social science disciplines and their sub-fields in which social science methods have been studied empirically. We hope this working bibliography will provide a useful resource for those who wish to undertake such studies in the future. We also hope to show that the more recent literature can be connected to, and stands to be informed by, a much broader literature. We do not pretend that our bibliography is complete and comprehensive but we do think it represents a starting point for those who wish to pursue these issues for themselves

A Guide to Psychological Literacy and Psychologically Literate Global Citizenship.

This guide provides a basic introduction to the related concepts of psychological literacy and psychologically literate citizenship. Psychological literacy encapsulates the idea that an understanding of basic principles of human behaviour and development gained through study of Psychology will help us to better understand ourselves and others, and will help individuals and organisations to function better. Psychologically literate citizenship extends this idea, to incorporate the benefits that an understanding of Psychology can bring to the individuals who study it, and their local and global communities. The guide will argue that Psychology offers potential solutions to many of the world’s most pressing problems. Its publication is particularly timely following the report of Trapp, Banister, Ellis, Latto, Miell and Upton (2011) and the subsequent inclusion of psychological literacy within the criteria for accreditation of undergraduate Psychology degrees by the British Psychological Society (BPS 2012). The guide commences by introducing the theoretical contexts of psychological literacy and psychologically literate citizenship. It links these concepts to issues around graduate attributes, including employability and global citizenship, suggesting that psychologically literate graduates are also highly employable global citizens. It then goes on to outline some possible areas of the typical undergraduate Psychology curriculum that lend themselves to developing psychological literacy in students. These suggestions are not intended to be exhaustive, but rather to stimulate creative thinking in the reader, and encourage psychologists everywhere to think about the real-life value of their particular areas of expertise in Psychology. We hope that you will find it useful, share it with your colleagu es, and use it to spark enthusiasm for Psychology in your students