Hard to reach and hard to teach: Supporting the self-regulation of learning in an alternative provision secondary school

© 2015 Taylor & Francis. Since 2010, new types of state-funded schools have opened in England with a focus on providing alternative education provision. Very little is known about these schools, partly due to their novelty, and how they are attempting to re-engage those students who for various, and often complex, reasons have become disconnected from education. We scrutinised the approach used at one such school to examine what instructional practices were used, how they were adapted to the needs of the students and what factors enabled and obstructed (re)engagement. Data were collected over a month-long fieldwork visit and included semi-structured interviews with staff and students, and semi-structured classroom observations. Instructional approaches were used that supported the learning of students who were not experienced in, or had difficulty with, regulating their learning. These included breaking down tasks, providing lots of on-task prompts, encouragement, using frequent feedback and scaffolding, and offering quick support to students. This approach allowed students to re-engage with their learning and make progress towards important qualifications required for entry to the labour market and post-compulsory education and training

'That blasted Facebook page': supporting trainee-teachers' professional learning through social media

The creation and use of a Facebook group amongst trainee-teachers in post-16 and further education on a PGCE course at a large university in the North of England was studied. The Facebook group was self-initiated and self-managed by the trainee-teachers as a means of socialisation and peer-support amongst themselves. Data was gathered through parallel interviews with a PGCE trainee and a course tutor. Interviews were semi-structured using Tuckman's stages of group development (forming, storming, norming, performing) to explore the functioning of the Facebook group throughout the duration of the PGCE course. The role of teacher-trainers in influencing professional learning within the Facebook group initiated and owned by the trainee-teachers themselves was explored using the didactical triangle as a theoretical framework. It was found that the Facebook group was highly-valued both for supporting socialisation amongst trainee-teachers and as an additional means of mediating the course content of the PGCE. Lessons can be learnt both by trainee-teachers using social media for socialisation and peer-support and by course-tutors in designing teacher-training courses that may better ameliorate the pressures and sense of alienation trainee-teachers experience during initial teacher training

An Overview of the Jupiter Icy Moons Orbiter (JIMO) Mission, Environments, and Materials Challenges

Congress authorized NASA's Prometheus Project in February 2003, with the first Prometheus mission slated to explore the icy moons of Jupiter with the following main objectives: (1) Develop a nuclear reactor that would provide unprecedented levels of power and show that it could be processed safely and operated reliably in space for long-duration. (2) Explore the three icy moons of Jupiter -- Callisto, Ganymede, and Europa -- and return science data that would meet the scientific goals as set forth in the Decadal Survey Report of the National Academy of Sciences

Influence of Natural Environments in Spacecraft Design, Development, and Operation

Spacecraft are growing in complexity and sensitivity to environmental effects. The spacecraft engineer must understand and take these effects into account in building reliable, survivable, and affordable spacecraft. Too much protections, however, means unnecessary expense while too little will potentially lead to early mission loss. The ability to balance cost and risk necessitates an understanding of how the environment impacts the spacecraft and is a critical factor in its design. This presentation is intended to address both the space environment and its effects with the intent of introducing the influence of the environment on spacecraft performance

Static Deadlock Detection in SHIM with an Automata Type Checking System

With the advent of multicores, concurrent programming languages are become more prevelant. Data Races and Deadlocks are two major problems with concurrent programs. SHIM is a concurrent programming language that guarantees absence of data races through its semantics. However, a program written in SHIM can deadlock if not carefully written. In this paper, we present a divide-and-merge technique to statically detect deadlocks in SHIM. SHIM is asynchronous, but we can greatly reduce its state space without loosing precision because of its semantics

Sputum neutrophils as a biomarker in COPD: findings from the ECLIPSE study

<p>Abstract</p> <p>Introduction</p> <p>The percentage of neutrophils in sputum are increased in COPD patients, and may therefore be a biomarker of airway inflammation. We studied the relationships between sputum neutrophils and FEV₁, health status, exacerbation rates, systemic inflammation and emphysema, and long term variability at 1 year.</p> <p>Methods</p> <p>Sputum samples were obtained from 488 COPD patients within the ECLIPSE cohort. 359 samples were obtained at baseline, and 297 after 1 year. 168 subjects provided samples at both visits. Serum interleukin-6 (IL-6), IL-8, surfactant protein D and C-reactive protein levels were measured by immunoassays. Low-dose CT scans evaluated emphysema.</p> <p>Results</p> <p>Sputum neutrophil % increased with GOLD stage. There was a weak association between % sputum neutrophils and FEV₁% predicted (univariate r²= 0.025 and 0.094 at baseline and year 1 respectively, p < 0.05 after multivariate regression). Similar weak but significant associations were observed between neutrophil % and health status measured using the St Georges Respiratory Questionairre. There were no associations between neutrophils and exacerbation rates or emphysema. Associations between sputum neutrophils and systemic biomarkers were non-significant or similarly weak. The mean change over 1 year in neutrophil % was an increase of 3.5%.</p> <p>Conclusions</p> <p>Sputum neutrophil measurements in COPD are associated weakly with FEV₁% predicted and health status. Sputum neutrophil measurements were dissociated from exacerbation rates, emphysema and systemic inflammation.</p

PERCLOS: An Alertness Measure of the Past

The growing number of fatigue related accidents in recent years has become a serious concern. Accidents caused by fatigue, or more precisely impaired alertness, in transportation and in mining operations involving heavy equipment can lead to substantial damage and loss of life. Preventing such fatigue related accidents is universally desirable, but requires techniques for continuously estimating and predicting the operator’s alertness state. PERCLOS (percentage of eye closure) was introduced as an alertness measure. Some years later, it was claimed to be superior in fatigue detection to any other measure, including the general Eye-Tracking Signal (ETS) and even EEG recordings. This study will show that this is not the case. To put things into the prospective a fair and objective comparison between PERCLOS, the general ETS and EEG/EOG has to be established. To achieve this purpose, a protocol was established to investigate the fatigue detection capabilities of PERCLOS, ETS, and EEG/EOG in a simple two class discrimination analysis using an ensemble of Learning Vector Quantization (LVQ) networks as a classification tool. Karolinska Sleepiness Scale (KSS) and Variation of Lane Deviation (VLD) were used in order to obtain independent class labels, whereas KSS provided subjective alertness labels while VLD provided objective alertness labels. The general ETS and the fused EEG/EOG measures contain substantially greater amounts of fatigue information than the PERCLOS measures alone. These conclusions were found to be valid for all three commercially available infrared video camera systems that were utilized in the study. The data utilized in the discrimination analysis were obtained from 16 young volunteers who participated in overnight experiments in the real car driving simulation lab at the University of Schmalkalden

Microsleep Episodes and Related Crashes During Overnight Driving Simulations

Microsleep (MS) episodes and related crashes were studied in an overnight driving simulation study. A new definition of MS proposed recently was applied and the mean number as well as the mean length of MS was calculated. MS occurred much more frequently than crashes. Within all pre-crash intervals (length 1 minute) the percentage of MS was calculated. Results showed that there are numerous MS episodes before every crash. The mean length of MS was between 5 and 9 seconds and did not change significantly during the night. The mean MS percentage was high within pre-crash intervals (60-80%) and is a predictor for crashes

Estimating Fatigue from Predetermined Speech Samples Transmitted by Operator Communication Systems

We present an estimation of fatigue level within individual operators using voice analysis. One advantage of voice analysis is its utilization of already existing operator communications hardware (2-way radio). From the driver viewpoint it’s an unobtrusive, non-interfering, secondary task. The expected fatigue induced speech changes refer to the voice categories of intensity, rhythm, pause patterns, intonation, speech rate, articulation, and speech quality. Due to inter-individual differences in speech pattern we recorded speaker dependent baselines under alert conditions. Furthermore, sophisticated classification tools (e.g. Support Vector Machine, Multi-Layer Perceptron) were applied to distinguish these different fatigue clusters. To validate the voice analysis predetermined speech samples gained from a driving simulator based sleep deprivation study (N=12; 01.00-08.00 a.m.) are used. Using standard acoustic feature computation procedures we selected 1748 features and fed them into 8 machine learning methods. After each combining the output of each single classifier we yielded a recognition rate of 83.8% in classifying slight from strong fatigue