Wellbeing: How we make sense of it and what this means for teachers

In this paper, the authors discuss their grounded research carried out with teachers about the wellbeing of teachers. They explore the importance of making the concept of wellbeing more intimate and consider hedonic and eudaimonic ways of looking at wellbeing. They present a model of layered reflection which illuminates key factors that have an impact on the wellbeing of teachers.     

Effects of Manipulative Instruction on Solving Area and Perimeter Problems by Students with Learning Disabilities

Abstract. A multiple baseline design was employed to test the effect of manipulative instruction on the perimeter and area problem‐solving performance of middle and high school students who had been diagnosed with LD in the area of mathematics. Modeling, prompting/guided practice, and independent practice in conjunction with manipulative training were employed to teach both perimeter and area problem‐solving skills. Analysis of data revealed that the students rapidly acquired the problem‐solving‐skills, maintained these skills over a two‐month period, and transferred these skills to a paper and pencil problem‐solving format. This research extends previous findings by revealing that use of concrete manipulatives promotes the long‐term maintenance of skills.     

The value of structured abstracts in information retrieval from MEDLINE

Objective: To determine whether information retrieval might be enhanced by making each component of a structured abstract a separately searchable field. Design: Parallel searches on records arranged so that each abstract could either be searched in its entirety or as a collection of structured fields. Subjects: Records about cardiovascular disease downloaded from MEDLINE and tested against clinical questions derived from a concurrent survey of CD-ROM use in three health science libraries. Intervention: The investigators identified terms used to structure abstracts on MEDLINE and imported the abstracts into an Idealist database prior to searching using keywords from clinical questions. Measurements and main results: recall and precision rates are given for each question in the ‘structured’ and the ‘unstructured’ set of records. Conclusions: Use of structured, rather than unstructured, abstracts improves precision at the ex-pense of recall and places heavier demands upon the searcher’s skill in choosing the correct fields within the abstract to search. Further investigation requires more accurate simulation of MEDLINE software that utilizes features such as MeSH terms, explode, facilities and delimiters.     

Advances in the phylogenesis of Agaricales and its higher ranks and strategies for establishing phylogenetic hypotheses

We present an overview of previous research results on the molecular phylogenetic analyses in Agaricales and its higher ranks (Agaricomycetes/Agaricomycotina/Basidiomycota) along with the most recent treatments of taxonomic systems in these taxa. Establishing phylogenetic hypotheses using DNA sequences, from which an understanding of the natural evolutionary relationships amongst clades may be derived, requires a robust dataset. It has been recognized that single-gene phylogenies may not truly represent organismal phylogenies, but the concordant phylogenetic genealogies from multiple-gene datasets can resolve this problem. The genes commonly used in mushroom phylogenetic research are summarized.     

Analysis of Academic Libraries' Facebook Posts: Text and Data Analytics

This research analyzed a dataset of academic libraries' posts on Facebook. It applied a text and data analytics approach to a dataset collected from the Facebook posts of academic libraries at the top 100 English-speaking universities, as listed by the 2014 Shanghai World University Rankings. The dataset is from a two-year posting history of 18,333 unique posts, 113,621 likes, and 3401 comments. Less than a quarter of the libraries had more than 2000 post-related likes, and only seven received more than 100 comments on their postings. Content analysis identified the most prevalent single word (unigrams), bigrams (two-word sequences), and trigrams (three-word sequences) in high and low engagement content. Semantic analysis identified the semantic categories for posts with high and low engagement. The findings can assist academic libraries in their social media strategies for engagement, marketing, and visibility.