Trends in qualitative research in language teaching since 2000

This paper reviews developments in qualitative research in language teaching since the year 2000, focusing on its contributions to the field and identifying issues that emerge. Its aims are to identify those areas in language teaching where qualitative research has the greatest potential and indicate what needs to be done to further improve the quality of its contribution. The paper begins by highlighting current trends and debates in the general area of qualitative research and offering a working definition of the term. At its core is an overview of developments in the new millennium based on the analysis of papers published in 15 journals related to the field of language teaching and a more detailed description, drawn from a range of sources, of exemplary contributions during that period. Issues of quality are also considered, using illustrative cases to point to aspects of published research that deserve closer attention in future work, and key publications on qualitative research practice are reviewed

Guess who? Multilingual approach for the automated generation of author-stylized poetry

This paper addresses the problem of stylized text generation in a multilingual setup. A version of a language model based on a long short-term memory (LSTM) artificial neural network with extended phonetic and semantic embeddings is used for stylized poetry generation. The quality of the resulting poems generated by the network is estimated through bilingual evaluation understudy (BLEU), a survey and a new cross-entropy based metric that is suggested for the problems of such type. The experiments show that the proposed model consistently outperforms random sample and vanilla-LSTM baselines, humans also tend to associate machine generated texts with the target author

Randomization does not help much, comparability does

Following Fisher, it is widely believed that randomization "relieves the experimenter from the anxiety of considering innumerable causes by which the data may be disturbed." In particular, it is said to control for known and unknown nuisance factors that may considerably challenge the validity of a result. Looking for quantitative advice, we study a number of straightforward, mathematically simple models. However, they all demonstrate that the optimism with respect to randomization is wishful thinking rather than based on fact. In small to medium-sized samples, random allocation of units to treatments typically yields a considerable imbalance between the groups, i.e., confounding due to randomization is the rule rather than the exception. In the second part of this contribution, we extend the reasoning to a number of traditional arguments for and against randomization. This discussion is rather non-technical, and at times even "foundational" (Frequentist vs. Bayesian). However, its result turns out to be quite similar. While randomization's contribution remains questionable, comparability contributes much to a compelling conclusion. Summing up, classical experimentation based on sound background theory and the systematic construction of exchangeable groups seems to be advisable

The ghosts I called I can\u27t get rid of now : The Keynes-Tinbergen-Friedman-Phillips Critique of Keynesian Macroeconometrics

This chapter offers a fresh perspective on the much publicised dispute between those followers of Keynes who presented econometric evidence in favour of a Phillips curve trade-off, and those monetarists who presented counter econometric evidence. Contrary to common perceptions, the collapse of the Keynesian Phillips curve was a vindication of a common critique of macroeconometric practices, which was jointly authored by John Maynard Keynes, Jan Tinbergen, Milton Friedman and A.W.H. \u27Bill\u27 Phillips. This analysis is informed by the usual sources, plus two sources which had been thought to be no longer in existence (Phillips\u27 private papers and the London School of Economics (LSE) Methodology, Measurement and Testing (M2T) Staff Seminar records), plus two essays by Keynes (1938a, 1938b) which have been overlooked in this context. ISBN: 033373045

The metric tide: report of the independent review of the role of metrics in research assessment and management

This report presents the findings and recommendations of the Independent Review of the Role of Metrics in Research Assessment and Management. The review was chaired by Professor James Wilsdon, supported by an independent and multidisciplinary group of experts in scientometrics, research funding, research policy, publishing, university management and administration. This review has gone beyond earlier studies to take a deeper look at potential uses and limitations of research metrics and indicators. It has explored the use of metrics across different disciplines, and assessed their potential contribution to the development of research excellence and impact. It has analysed their role in processes of research assessment, including the next cycle of the Research Excellence Framework (REF). It has considered the changing ways in which universities are using quantitative indicators in their management systems, and the growing power of league tables and rankings. And it has considered the negative or unintended effects of metrics on various aspects of research culture. The report starts by tracing the history of metrics in research management and assessment, in the UK and internationally. It looks at the applicability of metrics within different research cultures, compares the peer review system with metric-based alternatives, and considers what balance might be struck between the two. It charts the development of research management systems within institutions, and examines the effects of the growing use of quantitative indicators on different aspects of research culture, including performance management, equality, diversity, interdisciplinarity, and the ‘gaming’ of assessment systems. The review looks at how different funders are using quantitative indicators, and considers their potential role in research and innovation policy. Finally, it examines the role that metrics played in REF2014, and outlines scenarios for their contribution to future exercises