Changing attitudes? A longitudinal study of pupils' attitudes to science between the primary and secondary phases of education.

The findings are reported of a 4-year (1995-1998) longitudinal study, conducted in three primary schools (Years 5 and 6) and a single comprehensive school (Years 7 and 8) in Oxfordshire, of pupils' (n=71) attitudes towards various aspects of school-based science. The objectives were to investigate whether the pupils', especially the girls', attitudes to school science had changed (particularly in the early secondary years) from those reported in the pre-National Curriculum research literature. Data on various aspects of school science, including attitudes to the individual biological and physical science topics in Years 5 to 7, were collected from the pupils via annual questionnaires and, for 36 pupils, from annual, semi-structured tape-recorded interviews. Year 6 pupils also provided some "mini-essays". The cohort pupils' attitudes varied little from those reported in the pre-national Curriculum literature - science was regarded as a 'favourite' subject by very few pupils. The girls' lack of enthusiasm for the physical sciences, and the boys' disinterest in the biological sciences, were demonstrated. Some tentative links were suggested between the type of "out-of-school" activities, hobbies and interests recorded by the pupils and the pupils' attitudes to school science. Data were also collected on the parental experiences of, and attitudes towards, science as well as the parents' involvement in science-orientated and 'tinkering' activities. There was a positive correlation between the Year 7 pupils' attitudes to the physical sciences and the fathers' attitudes to their secondary science education. Fathers still appeared to be the main 'tinkerers' - they were more likely to be involved with their sons (rather than their daughters) in joint science-orientated activities. Using multiple regression procedures on the "in-school" and "out-of-school" data, the types of "out-of-school" activities enjoyed by the primary pupils, together with the maternal involvement in such activities, were shown to be predictors of the pupils' attitudes to science. The importance of the pupils' perceived performance in science, together with gender (especially with the respect to the physical sciences) were identified as two of the main predictors of pupils' attitudes at the end of the study. Finally, suggestions are made on how pupils' attitudes to school science might be improved by changes in the nature and delivery of the science curriculum

Intent inferencing with a model-based operator's associate

A portion of the Operator Function Model Expert System (OFMspert) research project is described. OFMspert is an architecture for an intelligent operator's associate or assistant that can aid the human operator of a complex, dynamic system. Intelligent aiding requires both understanding and control. The understanding (i.e., intent inferencing) ability of the operator's associate is discussed. Understanding or intent inferencing requires a model of the human operator; the usefulness of an intelligent aid depends directly on the fidelity and completeness of its underlying model. The model chosen for this research is the operator function model (OFM). The OFM represents operator functions, subfunctions, tasks, and actions as a heterarchic-hierarchic network of finite state automata, where the arcs in the network are system triggering events. The OFM provides the structure for intent inferencing in that operator functions and subfunctions correspond to likely operator goals and plans. A blackboard system similar to that of Human Associative Processor (HASP) is proposed as the implementation of intent inferencing function. This system postulates operator intentions based on current system state and attempts to interpret observed operator actions in light of these hypothesized intentions

The effect of an internet option and single-sided printing format to increase the response rate to a population-based study : a randomized controlled trial

Acknowledgements We would like to thank the Institute of Applied Health Sciences (IAHS) at the University of Aberdeen for funding the PhD studentship of EF. Furthermore, we would like to thank everyone who was involved in the study, including Professor Sir Lewis Ritchie (Director of Public Health, NHS Grampian), John Lemon (University of Aberdeen), Dr. Fiona Garton (University of Aberdeen) and the Aberdeen Service User Group. Lastly, we would like to acknowledge all data entry clerks (Maxx Livingstone, Rory Macfarlane, Georgia Mannion-Krase and Hazel Reilly) and participants of the study.Peer reviewedPublisher PD

ALLY: An operator's associate for satellite ground control systems

The key characteristics of an intelligent advisory system is explored. A central feature is that human-machine cooperation should be based on a metaphor of human-to-human cooperation. ALLY, a computer-based operator's associate which is based on a preliminary theory of human-to-human cooperation, is discussed. ALLY assists the operator in carrying out the supervisory control functions for a simulated NASA ground control system. Experimental evaluation of ALLY indicates that operators using ALLY performed at least as well as they did when using a human associate and in some cases even better

Genetic engineering of cyanobacteria as biodiesel feedstock.

Algal biofuels are a renewable energy source with the potential to replace conventional petroleum-based fuels, while simultaneously reducing greenhouse gas emissions. The economic feasibility of commercial algal fuel production, however, is limited by low productivity of the natural algal strains. The project described in this SAND report addresses this low algal productivity by genetically engineering cyanobacteria (i.e. blue-green algae) to produce free fatty acids as fuel precursors. The engineered strains were characterized using Sandia's unique imaging capabilities along with cutting-edge RNA-seq technology. These tools are applied to identify additional genetic targets for improving fuel production in cyanobacteria. This proof-of-concept study demonstrates successful fuel production from engineered cyanobacteria, identifies potential limitations, and investigates several strategies to overcome these limitations. This project was funded from FY10-FY13 through the President Harry S. Truman Fellowship in National Security Science and Engineering, a program sponsored by the LDRD office at Sandia National Laboratories

Managing Patient Health Across Diverse Spaces: Using Activity Theory to Model Pervasive Decision Support

Clinical decision support (CDS) systems can offer health care providers and patient data that is intelligently filtered and presented in ways to enhance diagnosis and long-term health care management, both within and outside clinical spaces. Challenges to this information management include diagnostic error and inefficiencies from conflicting, incomplete, or suboptimal clinical systems [3] as well as extending care outside the traditional clinical environment. We propose a Clinical Activity Model (CAM) to understand pervasive CDS system design and use across multiple health care spaces as patients move between critical care, recovery, and long-term home care. We discuss CAM in the context of research findings comparing a novel CDS system with traditional modes of data delivery and by describing use of that system as a mobile diagnostic tool to bridge clinical care and home care