Using meta-reflection to enhance performance

Much evidence supports the use of reflective practice for personal development, yet it is not commonly used as a learning tool in students. More typically, reflective writing is assessed as a stand-alone piece of work. The objective is then simply a grade. The proposed project would actively promote the use reflections to improve performance by means of using technology to record, store and retrieve them. These individual reflections will populate a database so that ultimately, with permission, each individual's reflections can be accessed by others via the database. Thus these reflections will become a learning tool for students. Using technology facilitates classification and retrieval and reduces the problems associated with human memory

How technology can facilitate students’ reflective practice

Reflective practice, engaging with experience, reflecting-in and reflecting-on action (Schön 1983) develops new understanding and leads to persona-l and professional development (e.g. Moon, 1999). Reflective practitioners are able to self-regulate and monitor their progress. Reflecting on what was learned can help students become more aware of their own thought processes (McCrindle and Christensen 1995), but reflecting on how it was learned, metacognition (Flavell 1978) offers far greater benefits. There exists mounting evidence for the benefits of metacognition in relation to enhanced performance and academic success (e.g. Coutinho 2007; Dunning et al. 2003). However, despite the costly time investment incurred by recording reflections in journals, reflections are more often retrieved from memory than from the written word. Thus the retrieved reflection is subject to the fallibility of human memory (e.g. Baddeley 1999, p.275): distortion, embellishment or forgetting. Furthermore, despite evidence demonstrating that when learners know reflections are to be read, graded or assessed by others, the incentive is to demonstrate knowledge and hide ignorance or doubt (Boud and Walker 1998), students’ reflections in HE are typically assessed. Dewey’s original purpose of reflection was to consider and strive to overcome weaknesses. In fact, Boud (1999) highlights the dichotomies between the nature of reflection and the nature of assessment, and questions the value and integrity of assessing reflective practice at all

A Cognitive and Social Psychological Perspective on the Demand for Fashion

The fashion industry is an important global industry. In 2012, in Britain it generated more than £48 billion annually and employs more than 600,000 people. Whether or not we consider ourselves fashionable or interested in fashion, we all clothe ourselves in items we have bought or have chosen to wear. Individuals in developed countries tend to buy more fashion items than they need and many have bought items that remain unworn. The fashion industry depends on demand for new ideas and products which allow individuals to perceive themselves as socially or economically superior or simply different. From a psychological perspective, this is in conflict with the well understood desire to conform. The psychological underpinnings of the demand for fashion are complex and have been neglected in research. This paper considers the cognitive and social psychological roles of decision making in the demand for fashion

Human vs. Algorithm

We consider the roles of algorithm and human and their inter-relationships. As a vehicle for some of our ideas we describe an empirical investigation of software professionals using analogy-based tools and unaided search in order to solve various prediction problems. We conclude that there exist a class of software engineering problems which might be characterised as high value and low frequency where the human-algorithm interaction must be considered carefully if they are to be successfully deployed in industry

An Investigation of Rule Induction Based Prediction Systems

Traditionally, researchers have used either off-the-shelf models such as COCOMO, or developed local models using statistical techniques such as stepwise regression, to predict software effort estimates. More recently, attention has turned to a variety of machine learning methods such as artificial neural networks (ANNs), case-based reasoning (CBR) and rule induction (RI). This position paper outlines some preliminary research into the use of rule induction methods to build software cost models. We briefly describe the use of rule induction methods and then apply the technique to a dataset of 81 software projects derived from a Canadian software house in the late 1980s. We show that RI methods tend to be unstable and generally predict with quite variable accuracy. Pruning the feature set, however, has a significant impact upon accuracy. We also compare our results with a prediction system based upon a standard regression procedure. We suggest that further work is carried out to examine the effects of the relationships among, and between, the features of the attributes on the generated rules in an attempt to improve on current prediction techniques and enhance our understanding of machine learning methods

Making Software Cost Data Available for Meta-Analysis

In this paper we consider the increasing need for meta-analysis within empirical software engineering. However, we also note that a necessary precondition to such forms of analysis is to have both the results in an appropriate format and sufficient contextual information to avoid misleading inferences. We consider the implications in the field of software project effort estimation and show that for a sample of 12 seemingly similar published studies, the results are difficult to compare let alone combine. This is due to different reporting conventions. We argue that a protocol is required and make some suggestions as to what it should contain

Qualitative Methods for Classifying and Detecting Online Identity Deception

The overall aim of our research is to use qualitative methods to help understand online identity deception. In this position paper, two pilot studies are described. The first was designed to test the feasibility of using content analysis of online discussions to classify the perceptions of the ‘net generation’ regarding different levels of identity deception. Based on the classifications identified, the second follow-up study will use face-to-face focus groups to collect further thoughts on these classifications, and the new data will be presented at this CHI Workshop. It is hoped that the feedback at the Workshop will help to direct further research using qualitative methods to analyse naturally-occurring identity descriptions found on social networking sites. The overall outcome of the research programme is to produce a set of indicators to assist identity deception in online environments

Wellbeing in fashion and the creative industries

Purpose: To disseminate outcomes from a recent panel discussion on mental health in fashion and the creative industries. Background: World Mental Health Day (WMHD) is held annually on 10th October to raise awareness of mental health issues, mobilise efforts to support psychological wellbeing and discuss the potential to make mental health care a reality for people worldwide. One in four people in the UK will experience a mental health problem each year, and for individuals working in creative industries, the incidence is allegedly one in three. Methods: A multidisciplinary panel, drawn together to explore known mental health issues in fashion and creative industries and propose means of addressing them, took place at London College of Fashion (LCF) on WMHD16. The event was sponsored by BPS London & Home Counties branch (LHC). The audience of 250 comprised students, academics, practitioners from psychology, fashion, art and related disciplines and public. The panel comprised fashion commentator and activist for diversity, Prof Caryn Franklin MBE; fashion model and health advocate, Rosie Nelson; Clinical Psychologist, and ex-ballerina, Dr Annmarie Rankin; and Consultant Psychiatrist, Chair of the Adamson Collection Trust and Director of the Bethlem Gallery, Dr David O'Flynn. The panel was Chaired by Subject Director Psychology LCF, Dr Carolyn Mair, CPsychol, FBPsS, who is also Chair of LHC branch. Conclusions: MH in fashion and the creative industries is poor. In an attempt to alleviate the situation, a working party has formed to develop an accessible, consistent and effective service to improve wellbeing in these industries

An Analysis of Data Sets Used to Train and Validate Cost Prediction Systems

OBJECTIVE - the aim of this investigation is to build up a picture of the nature and type of data sets being used to develop and evaluate different software project effort prediction systems. We believe this to be important since there is a growing body of published work that seeks to assess different prediction approaches. Unfortunately, results – to date – are rather inconsistent so we are interested in the extent to which this might be explained by different data sets. METHOD - we performed an exhaustive search from 1980 onwards from three software engineering journals for research papers that used project data sets to compare cost prediction systems. RESULTS - this identified a total of 50 papers that used, one or more times, a total of 74 unique project data sets. We observed that some of the better known and publicly accessible data sets were used repeatedly making them potentially disproportionately influential. Such data sets also tend to be amongst the oldest with potential problems of obsolescence. We also note that only about 70% of all data sets are in the public domain and this can be particularly problematic when the data set description is incomplete or limited. Finally, extracting relevant information from research papers has been time consuming due to different styles of presentation and levels of contextural information. CONCLUSIONS - we believe there are two lessons to learn. First, the community needs to consider the quality and appropriateness of the data set being utilised; not all data sets are equal. Second, we need to assess the way results are presented in order to facilitate meta-analysis and whether a standard protocol would be appropriate

Applying psychology to enhance well-being in the fashion industries

Background: Humans are involved in every aspect of fashion including design, manufacture, retail, consumption and disposal. Fashion affects us as individuals, in relationships, groups, societies and communities at home, work and leisure. What we wear influences our own and others’ perceptions, our emotions, self-esteem, body-image and confidence. Fashion is powerful and its addictive appeal can lead to economic and environmental problems. However, the potential for harnessing its power to enhance well-being, through applying psychological principles and theories, has not been attempted. Aim: To consider how psychology can be applied in the fashion industries to enhance well-being. Expected outcomes for participants: Participants will discuss the application of psychology to fashion, discuss existing problems, contribute to an action plan and be invited to join a network to work towards promoting well-being through fashion. Key points: Fashion matters! The fashion industry employs almost one million people in the UK and contributes more than £25billion to the British economy annually. It influences and is influenced by psychological factors of individuals, groups and communities, yet traditionally, psychology has been ignored in fashion studies. Existing problems related to fashion include, but are not limited to, social and beauty ideals lacking diversity, unregulated cosmetic treatment and surgery, unethical fashion production, consumption and disposal leading to environmental problems, issues of self-esteem, dysmorphia, eating disorders, and so on. Conclusions: The workshop will identify and discuss existing problems, develop action plans and establish a network of psychologists who wish to apply psychological theory to enhance well-being in fashion