Statistical Analyses and Reproducible Research

For various reasons, it is important, if not essential, to integrate the computations and code used in data analyses, methodological descriptions, simulations, etc. with the documents that describe and rely on them. This integration allows readers to both verify and adapt the statements in the documents. Authors can easily reproduce them in the future, and they can present the document's contents in a different medium, e.g. with interactive controls. This paper describes a software framework for authoring and distributing these integrated, dynamic documents that contain text, code, data, and any auxiliary content needed to recreate the computations. The documents are dynamic in that the contents, including figures, tables, etc., can be recalculated each time a view of the document is generated. Our model treats a dynamic document as a master or ``source'' document from which one can generate different views in the form of traditional, derived documents for different audiences. We introduce the concept of a compendium as both a container for the different elements that make up the document and its computations (i.e. text, code, data, ...), and as a means for distributing, managing and updating the collection. The step from disseminating analyses via a compendium to reproducible research is a small one. By reproducible research, we mean research papers with accompanying software tools that allow the reader to directly reproduce the results and employ the methods that are presented in the research paper. Some of the issues involved in paradigms for the production, distribution and use of such reproducible research are discussed.

Basic Erosive Wear Examination (BEWE): a new scoring system for scientific and clinical needs

A new scoring system, the Basic Erosive Wear Examination (BEWE), has been designed to provide a simple tool for use in general practice and to allow comparison to other more discriminative indices. The most severely affected surface in each sextant is recorded with a four level score and the cumulative score classified and matched to risk levels which guide the management of the condition. The BEWE allows re-analysis and integration of results from existing studies and, in time, should initiate a consensus within the scientific community and so avoid continued proliferation of indices. Finally, this process should lead to the development of an internationally accepted, standardised and validated index. The BEWE further aims to increase the awareness of tooth erosion amongst clinicians and general dental practitioners and to provide a guide as to its management.

Learning Analytics: Challenges and Future Research Directions

In recent years, learning analytics (LA) has attracted a great deal of attention in technology-enhanced learning (TEL) research as practitioners, institutions, and researchers are increasingly seeing the potential that LA has to shape the future TEL landscape. Generally, LA deals with the development of methods that harness educational data sets to support the learning process. This paper provides a foundation for future research in LA. It provides a systematic overview on this emerging field and its key concepts through a reference model for LA based on four dimensions, namely data, environments, context (what?), stakeholders (who?), objectives (why?), and methods (how?). It further identifies various challenges and research opportunities in the area of LA in relation to each dimension.

The COLOSS BEEBOOK Volume II, Standard methods for Apis mellifera pest and pathogen research: Introduction

The COLOSS BEEBOOK is a practical manual compiling standard methods in all fields of research on the western honey bee, Apis mellifera. The COLOSS network was founded in 2008 as a consequence of the heavy and frequent losses of managed honey bee colonies experienced in many regions of the world (Neumann and Carreck, 2010). As many of the world’s honey bee research teams began to address the problem, it soon became obvious that a lack of standardized research methods was seriously hindering scientists’ ability to harmonize and compare the data on colony losses obtained internationally. In its second year of activity, during a COLOSS meeting held in Bern, Switzerland, the idea of a manual of standardized honey bee research methods emerged. The manual, to be called the COLOSS BEEBOOK, was inspired by publications with similar purposes for fruit fly research (Lindsley and Grell, 1968; Ashburner, 1989; Roberts, 1998; Greenspan, 2004).

Ontology driven integration platform for clinical and translational research

Semantic Web technologies offer a promising framework for integration of disparate biomedical data. In this paper we present the semantic information integration platform under development at the Center for Clinical and Translational Sciences (CCTS) at the University of Texas Health Science Center at Houston (UTHSC-H) as part of our Clinical and Translational Science Award (CTSA) program. We utilize the Semantic Web technologies not only for integrating, repurposing and classification of multi-source clinical data, but also to construct a distributed environment for information sharing, and collaboration online. Service Oriented Architecture (SOA) is used to modularize and distribute reusable services in a dynamic and distributed environment. Components of the semantic solution and its overall architecture are described.

Quantitative and qualitative research approaches to assess student well-being

Although there is dissimiliarity in theoretical research approaches to subjective well-being and to assessments of well-being, there is agreement regarding the value of well-being, especially among student populations. In the highly structured, achievement-oriented, non-optimal context of a classroom, individual well-being is a necessary pre-condition for learning. Among student populations well-being should not be construed as an achievement enhancer; but, rather, recognized and measured as an educational value of its own. However, it is necessary for the positive bias towards learning at least in highly structured, achievement-orientated, non-optional learning contexts like school [cf. Hascher, T. (2004). Wohlbefinden in der Schule. Münster: Waxmann]. How can it be measured? Since different research approaches lead to a variety of instruments, the following paper will focus on two ways of assessing well-being in school: a questionnaire on student well-being (N = 2014) 1 and a semi-structured daily diary about relevant emotional situations in school (N = 58, period 3 × 2 weeks). Both methods are introduced and their methodological quality is discussed in terms of reliability, validity and in terms of their usefulness for improving school practice. Furthermore, the research potential of combining quantitative and qualitative data on students’ well-being is addressed.