Renormalization schemes for SFT solutions

In this paper, we examine the space of renormalization schemes compatible with the Kiermaier and Okawa [arXiv:0707.4472] framework for constructing Open String Field Theory solutions based on marginal operators with singular self-OPEs. We show that, due to freedom in defining the renormalization scheme which tames these singular OPEs, the solutions obtained from the KO framework are not necessarily unique. We identify a multidimensional space of SFT solutions corresponding to a single given marginal operator.Comment: 41 pages, 1 figur

Editorial

This is the second special issue to be developed from the international conference ‘At the Crossroads: New Directions in Teacher Education’, held at Canterbury Christ Church University in July 2012, which brought together over 200 scholars from 16 countries. As well as a range of methodological approaches to research in teacher education, represented in the studies published in the previous special issue (Vol. 6 issue 1, March 2014), many of the conference papers focussed on the development of innovative practice in initial teacher education. The five papers presented here, which have been updated for this special issue, illustrate some of these exciting initiatives

Editorial

Editorial special issue 1, Methodological approaches to researching teacher education: The idea for this special issue of TEAN developed from the international conference ‘At the Crossroads: New Directions in Teacher Education’, held at Canterbury Christ Church University in July 2012, which brought together over 200 scholars from 16 countries. It was striking that a sizeable number of papers focussed on specific methodologies used in researching teacher education, representing a growing interest in this area. The six articles published here, originally presented at the conference, represent just some of the different and innovative methodological approaches being used in current studies

The Voice Transcription Technique: Use of Voice Recognition Software to Transcribe Digital Interview Data in Qualitative Research

Transcribing interview data is a time-consuming task that most qualitative researchers dislike. Transcribing is even more difficult for people with physical limitations because traditional transcribing requires manual dexterity and the ability to sit at a computer for long stretches of time. Researchers have begun to explore using an automated transcription process using digital recordings and voice recognition software (VRS). While VRS has improved in recent years, it is not yet available to the general public in a format that can recognize more than one recorded voice. This article outlines a strategy used to circumvent this problem and improve the speed and ease of transcription. The equipment and the Voice Transcription Technique used are outlined, as well as suggestions for future technological advances in transcription

Student Perceptions of Learning Disability Labels at the Junior High and High School Level

This qualitative research study provides student perceptions of their own Learning Disability labels at the Junior High and High School level. All thirty-five students who were involved answered questions during in-depth interviews. The students represented a sample population of small, rural, and public junior high and high school students. Interview questions focused on the benefits and limitations of being labeled with a learning disability. Data analysis results showed that students preferred being in special education or being labeled as learning disabled because they are able to gain help in order to be successful in school. Limitations and negative aspects were also noted and taken into account in this study. This information within this study can be used for educators to gain more insight into the personal opinions and perceptions of his or her LD students