Making sense of ‘pure’ phenomenography in information and communication technology in education

Research in information and communication technology in education places an increasing emphasis on the use of qualitative analysis (QA). A considerable number of approaches to QA can be adopted, but it is not always clear that researchers recognize either the differences between these approaches or the principles that underlie them. Phenomenography is often identified by researchers as the approach they have used, but little evidence is presented to allow anyone else to assess the objectivity of the results produced. This paper attempts to redress the balance. A small‐scale evaluation was designed and conducted according to ‘pure’ phenomenographic principles and guidelines. This study was then critiqued within the wider context of QA in general. The conclusion is that pure phenomenography has some procedural weaknesses, as well as some methodological limitations regarding the scope of the outcomes. The procedural weaknesses can be resolved by taking account of good practice in QA. The methodological issues are more serious and reduce the value of this approach for research in collaborative learning environments

Grounded Theory as an approach to studying students’ uses of learning management systems

This paper presents the first phase of a qualitative study of students’ use of a Learning Management System (LMS). A group of students at Kingston University with experience of two different systems were afforded the opportunity to study the relationship between the interface to an LMS and the usability of the system

Are randomised controlled trials positivist? Reviewing the social science and philosophy literature to assess positivist tendencies of trials of social interventions in public health and health services

Background: We have previously proposed that trials of social interventions can be done within a ‘realist’ research paradigm. Critics have countered that such trials are irredeemably positivist and asked us to explain our philosophical position. Methods: We set out to explore what is meant by positivism and whether trials adhere to its tenets (of necessity or in practice) via a narrative literature review of social science and philosophical discussions of positivism, and of the trials literature and three case studies of trials. Results: The philosophical literature described positivism as asserting: 1) the epistemic primacy of sensory information; 2) the requirement that theoretical terms equate with empirical terms; 3) the aim of developing universal laws; and 4) the unity of method between natural and social sciences. Regarding 1), it seems that rather than embodying the epistemic primacy of sensory data, RCTs of social interventions in health embrace an anti-positivist approach aiming to test hypotheses derived deductively from prior theory. Considering 2), while some RCTs of social interventions appear to limit theorization to concepts with empirical analogues, others examine interventions underpinned by theories engaging with mechanisms and contextual contingencies not all of which can be measured. Regarding 3), while some trialists and reviewers in the health field do limit their role to estimating statistical trends as a mechanistic form of generalization, this is not an inevitable feature of RCT-based research. Trials of social interventions can instead aim to generalize at the level of theory which specifies how mechanisms are contingent on context. In terms of 4), while RCTs are used to examine biomedical as well as social interventions in health, RCTs of social interventions are often distinctive in using qualitative analyses of data on participant accounts to examine questions of meaning and agency not pursued in the natural sciences. Conclusion: We conclude that the most appropriate paradigm for RCTs of social interventions is realism not positivism

On reification: A reinterpretation of designed and emergent practice

This paper is a response to the article: ‘Examining the five‐stage e‐moderating model: designed and emergent practice in the learning technology profession, published in ALT‐J 11 (1). Whilst we agree with the concerns of the authors on the problems of commodification and the increasing control of learning technology from a financial or predominantly management perspective, we wish to offer a reinterpretation of the research by taking a stricter analysis of the events described by the authors

The Environmental Dependence of the Incidence of Galactic Tidal Features

In a sample of 54 galaxy clusters (0.04<z<0.15) containing 3551 early-type galaxies suitable for study, we identify those with tidal features both interactively and automatically. We find that ~3% have tidal features that can be detected with data that reaches a 3-sigma sensitivity limit of 26.5 mag arcsec^-2. Regardless of the method used to classify tidal features, or the fidelity imposed on such classifications, we find a deficit of tidally disturbed galaxies with decreasing clustercentric radius that is most pronounced inside of ~0.5R_200. We cannot distinguish whether the trend arises from an increasing likelihood of recent mergers with increasing clustercentric radius or a decrease in the lifetime of tidal features with decreasing clustercentric radius. We find no evidence for a relationship between local density and the incidence of tidal features, but our local density measure has large uncertainties. We find interesting behavior in the rate of tidal features among cluster early-types as a function of clustercentric radius and expect such results to provide constraints on the effect of the cluster environment on the structure of galaxy halos, the build-up of the red sequence of galaxies, and the origin of the intracluster stellar population.Comment: 12 pages, 12 figures. Accepted for publication in AJ. For a brief video explaining the key results of this paper, see http://www.youtube.com/user/OSUAstronom

The association of metacognitive beliefs with emotional distress after diagnosis of cancer.

Objective: Emotional distress after a diagnosis of cancer is normal and, for most people, will diminish over time. However, a significant minority of patients with cancer experience persistent or recurrent symptoms of emotional distress for which they need help. A model developed in mental health, the self-regulatory executive function model (S-REF), specifies that maladaptive metacognitive beliefs and processes, including persistent worry, are key to understanding why such emotional problems persist. This cross-sectional study explored, for the first, time whether metacognitive beliefs were associated with emotional distress in a cancer population, and whether this relationship was mediated by worry, as predicted by the S-REF model. Method: Two hundred twenty-nine participants within 3 months of diagnosis of, and before treatment for, primary breast or prostate cancer completed self-report questionnaires measuring anxiety, depression, posttraumatic stress disorder (PTSD) symptoms, metacognitive beliefs, worry, and illness perceptions. Results: Regression analysis showed that metacognitive beliefs were associated with symptoms of anxiety, depression, and PTSD, and explained additional variance in these outcomes after controlling for age, gender, and illness perceptions. Structural equation modeling was consistent with cross-sectional hypotheses derived from the theory that metacognitive beliefs cause and maintain distress both directly and indirectly by driving worry. Conclusions: The findings provide promising first evidence that the S-REF model may be usefully applied in cancer. Further study is required to establish the predictive and clinical utility of these findings

A Continuous Relaxation of Beam Search for End-to-end Training of Neural Sequence Models

Beam search is a desirable choice of test-time decoding algorithm for neural sequence models because it potentially avoids search errors made by simpler greedy methods. However, typical cross entropy training procedures for these models do not directly consider the behaviour of the final decoding method. As a result, for cross-entropy trained models, beam decoding can sometimes yield reduced test performance when compared with greedy decoding. In order to train models that can more effectively make use of beam search, we propose a new training procedure that focuses on the final loss metric (e.g. Hamming loss) evaluated on the output of beam search. While well-defined, this "direct loss" objective is itself discontinuous and thus difficult to optimize. Hence, in our approach, we form a sub-differentiable surrogate objective by introducing a novel continuous approximation of the beam search decoding procedure. In experiments, we show that optimizing this new training objective yields substantially better results on two sequence tasks (Named Entity Recognition and CCG Supertagging) when compared with both cross entropy trained greedy decoding and cross entropy trained beam decoding baselines.Comment: Updated for clarity and notational consistenc