The Effect of Cross-age Tutoring on Reading Attitude

One of the greatest challenges facing teachers of reading today is the negative attitude of students toward reading. One suggested means of positively influencing the reading attitude of students is cross-age tutoring. However, a study is needed to establish whether a clear link exists between cross-age tutoring and positive changes in reading attitude. Experimental research was conducted during the course of an academic quarter (nine weeks) to determine whether cross-age tutoring has a positive impact on reading attitude. The subjects of the study were first grade students (n=12). The first graders were identified for the study based on low scores on the Elementary Reading Attitude Survey. The first graders were placed in matched pairs based on their Elementary Reading Attitude Survey raw scores. Matched pairs were then randomly split into a control group (n=6) and an experimental group (n=6). The tutors were second grade students (n=6) identified through teacher interviews as being enthusiastic and skilled readers. During four 30-minute training sessions, the second grade tutors were trained to implement a two part instructional plan during each tutoring session. The instructional plan included sight word practice, word games, paired reading time with retelling, and testing in the Accelerated Reader computer program. Throughout the nine weeks of the study, the second grade tutors conducted two 30 minute sessions each week with students in the experimental group. During the tutoring sessions, first grade students in the control group engaged in typical independent reading activities such as sustained silent reading. All first grade subjects were retested with the Elementary Reading Attitude Survey following the last tutoring session. A Wilcoxon matched-pairs signed-ranks test was used to analyze the posttest data. In addition, qualitative data were obtained through observational rating scales of reading behaviors completed by a certified teacher acting as a teaching assistant in the classroom. Results indicate that students in the experimental group did show greater increases in reading attitude than those in the control group. However, the Wilcoxon test indicated that these differences were not statistically significant

Real-time pathogen surveillance systems using DNA sequencing

Microbiological research has uncovered the basis of fermentation, infectious disease, vaccination and antibiotics. Now, a technological revolution leveraging DNA, the code of life, has allowed us to unravel cellular and evolutionary processes in exquisite detail. Today our need for new innovation is still great. The modern world is a challenging environment: over-population, climate change and highly mobile populations create a high risk of pandemic disease especially from viruses and many bacteria are now resistant to our life saving antibiotic drugs due to overuse. In hospitals, the spread of pathogens can be rapid and life threatening. Whole-genome sequencing has the power to identify the source of infections and determine whether clusters of cases belong to an outbreak. Portable, real-time nanopore sequencing enables sequencing to be performed near the patient, even in resource-limited settings. Integrating with existing datasets allows digital surveillance able to detect outbreaks earlier while they can still be contained. Early demonstrations of the power of whole-genome sequencing for outbreak surveillance have made it an area of intense interest and further development in laboratory methods and infrastructure will make it an important tool that can be deployed in response to future outbreaks

Formative and Summative Analyses of Disciplinary Engagement and Learning in Big Open Online Course

Situative theories of knowing and participatory approaches to learning and assessment were used to design and then analyze learning in a “big open online course” (“BOOC”) on educational assessment. The course was delivered using Google’s Course Builder platform which was customized extensively to support both summative and formative analyses of disciplinary social engagement and individual learning. The course featured personalized “wikifolio” public assignments peer commenting, endorsement, & promotion, formal online examinations, open digital badges, and participatory learning analytics. The course was first completed by 60 students in 2013 and impressive levels of engagement and learning were documented. The course was further refined in 2014 with embedded streaming videos, embedded formative assessments, and streamlined learning analytics. Of the sixty students who registered for the course, 22 completed it. This paper illustrates the more formative learning analytics used to advance the shared discourse in the course as well as the other new features and provides detailed evidence of engagement & learning.Googl

On Machine-Learned Classification of Variable Stars with Sparse and Noisy Time-Series Data

With the coming data deluge from synoptic surveys, there is a growing need for frameworks that can quickly and automatically produce calibrated classification probabilities for newly-observed variables based on a small number of time-series measurements. In this paper, we introduce a methodology for variable-star classification, drawing from modern machine-learning techniques. We describe how to homogenize the information gleaned from light curves by selection and computation of real-numbered metrics ("feature"), detail methods to robustly estimate periodic light-curve features, introduce tree-ensemble methods for accurate variable star classification, and show how to rigorously evaluate the classification results using cross validation. On a 25-class data set of 1542 well-studied variable stars, we achieve a 22.8% overall classification error using the random forest classifier; this represents a 24% improvement over the best previous classifier on these data. This methodology is effective for identifying samples of specific science classes: for pulsational variables used in Milky Way tomography we obtain a discovery efficiency of 98.2% and for eclipsing systems we find an efficiency of 99.1%, both at 95% purity. We show that the random forest (RF) classifier is superior to other machine-learned methods in terms of accuracy, speed, and relative immunity to features with no useful class information; the RF classifier can also be used to estimate the importance of each feature in classification. Additionally, we present the first astronomical use of hierarchical classification methods to incorporate a known class taxonomy in the classifier, which further reduces the catastrophic error rate to 7.8%. Excluding low-amplitude sources, our overall error rate improves to 14%, with a catastrophic error rate of 3.5%.Comment: 23 pages, 9 figure

Complete Closed Genome Sequence of Nontoxigenic Invasive Corynebacterium diphtheriae bv. mitis Strain ISS 3319

The genome sequence of the human pathogen Corynebacterium diphtheriae bv. mitis strain ISS 3319 was determined and closed in this study. The genome is estimated to have 2,404,936 bp encoding 2,257 proteins. This strain also possesses a plasmid of 1,960 bp

Subtle interactions for distress regulation: efficiency of a haptic wearable according to personality

The incorporation of empathic systems in everyday life draws a lot of attention from society. Specifically, the use of wearables to perform stress regulation is a growing field of research. Among techniques explored, the haptic emulation of lowered physiological signals has been suggested to be promising. However, some discrepancies remain in empirical research focusing on such biofeedback (BF) regarding their efficacy, and the mechanisms underlying the effects of these wearables remains unclear. Moreover, the influence of individual traits on the efficiency of BF has been marginally studied, while it has been shown that personality could impact both stress and its regulation. The aim of this study is to investigate the outcome of interactions with these technologies from a psycho-physiological standpoint, but also to explore whether personality may influence its efficiency when other interaction devices are present. Participants had to play a challenging game while a lowered haptic BF of their heart rate was induced on their wrist. Results showed variable efficiency of the wearable among the participants: a subjective relaxation was evident for the participants exhibiting the highest neurotic and extraverted traits score. Our results highlight the plurality of the modes of action of these techniques, depending on the individual and on the level of stress to regulate. This study also suggests that tailoring these regulation methods to individual characteristics, such as personality traits, is important to consider, and proposes perspectives regarding the investigation of stress and regulation systems embedded in wearables

A reference bacterial genome dataset generated on the MinION™ portable single-molecule nanopore sequencer

BACKGROUND: The MinION™ is a new, portable single-molecule sequencer developed by Oxford Nanopore Technologies. It measures four inches in length and is powered from the USB 3.0 port of a laptop computer. The MinION™ measures the change in current resulting from DNA strands interacting with a charged protein nanopore. These measurements can then be used to deduce the underlying nucleotide sequence. FINDINGS: We present a read dataset from whole-genome shotgun sequencing of the model organism Escherichia coli K-12 substr. MG1655 generated on a MinION™ device during the early-access MinION™ Access Program (MAP). Sequencing runs of the MinION™ are presented, one generated using R7 chemistry (released in July 2014) and one using R7.3 (released in September 2014). CONCLUSIONS: Base-called sequence data are provided to demonstrate the nature of data produced by the MinION™ platform and to encourage the development of customised methods for alignment, consensus and variant calling, de novo assembly and scaffolding. FAST5 files containing event data within the HDF5 container format are provided to assist with the development of improved base-calling methods