How do Students Choose and use Technology for Collaborative Learning?

In this case study, 86 physiotherapy undergraduate students studying a third year module, chose a blend for a collaborative task. Data was focused in capturing the students’ experience, and included interviews, questionnaires, and observation of both face-to-face and online activity. The students held strong views on collaborative learning that included inclusivity, valuing difference, democracy and the importance of all group members participating fully in decision making. All groups used a similar range of technology. They highly valued the classroom technologies provided in a specialised collaborative classroom that included computers and data projectors that enabled a group to visualise their output and connect to their online group sites. They used the online environment (the University’s managed learning environment) largely as a repository, ‘offloading’ some of the organisational components of collaboration and for knowledge acquisition that enabled them to use the face-to-face meetings for interaction and co-construction of knowledge. They did not use the asynchronous facilities for discussion, more for basic information giving, in common with other studies on undergraduate students. Students also wanted their education and social sites e.g. Facebook kept separate. The process undertaken in completing the weekly tasks had clear stages which included individual and group components. The students’ experience reflected aspects of both of the two major metaphors of learning ‘acquisition’ and ‘participation’. Students organised their use of technology to enable them to maximise interaction when they met faceto- face. The implications for practice include, creating more dedicated high technology classrooms, introducing technologies in a structured way earlier in the course and tutors modelling their use

Injection accuracy characteristics for lunar missions

Launch vehicle injection accuracy characteristics for lunar mission

Representational momentum in the motor system?

PURPOSE: If presented with a moving object which suddenly disappears observers usually misjudge the object's last seen position as being further forward along the path of motion. This effect, called representational momentum, can also be seen in objects that change size or shape. It has been argued that the effect is due to perceptual anticipation. We tested whether a similar effect is present in the motor system. METHODS: Using stereo computer graphics we presented cubes of different sizes on a CRT monitor. In each trial three cubes were successively presented for 200 msec with increasing or decreasing size (steps of 1 cm width difference). Ten participants either compared the last cube to a comparison cube (perceptual task) or grasped the cube using a virtual haptic setup (motor task). The setup consisted of two robot arms (Phantom TM) attached to index finger and thumb. The robot arms were controlled to create forces equivalent to the forces created by real objects. The CRT monitor was viewed via a mirror such that the visual position of the cubes matched the position of the virtual haptic objects. RESULTS: In the motor task participants opened their fingers by 1.1+/-0.4 mm wider if they grasped a cube that was preceded by smaller cubes than if they grasped a cube that was preceded by larger cubes. This is the well-known representational momentum effect. In the perceptual task the effect was reversed (-2.2+/-0.4 mm). The effects correlated between observers (r=.71, p=.02). CONCLUSIONS: It seems that a representational momentum occurs also in grasping tasks. The correlation between observers suggests that the motor effect is related to the perceptual effect. However, our perceptual task showed a reversed effect. Reasons for this discrepancy will be discussed

The FOMC's balance-of-risks statement and market expectations of policy actions

In January 2000, the Federal Open Market Committee (FOMC) instituted the practice of issuing a “balance of risks” statement along with their policy decision immediately following each FOMC meeting. Robert H. Rasche and Daniel L. Thornton evaluate the use of the balance-of-risks statement and the market’s interpretation of it. They find that the balance-of-risks statement is one of the factors that market participants use to determine the likelihood that the FOMC will adjust its target for the federal funds rate at their next meeting. Moreover, they find that, on some occasions, the FOMC behaved in such a way as to encourage the use of the balance-of-risks statement for this purpose. The clarifying statements that sometimes accompany these balance-of-risks statements, as well as general remarks made by the Chairman and other FOMC members, often provide additional useful information.Federal Open Market Committee ; Federal funds rate ; Monetary policy

Greenspan's unconventional view of the long-run inflation/output trade-off

Greenspan, Alan ; Inflation (Finance)

The monetary/fiscal policy debate: a controlled experiment

Fiscal policy - Japan ; Monetary policy - Japan

Mechanical properties of brittle materials

Brittle materials are difficult to tensile test because of gripping problems. They either crack in conventional grips or they are crushed. Furthermore, they may be difficult to make into tensile specimens having, for example, threated ends or donut shapes. To overcome the problem, simple rectangular shapes can be used in bending (i.e., a simple beam) in order to obtain the modulus of rupture and the elastic modulus. The equipment necessary consists of a fixture for supporting the specimens horizontally at two points, these points contact points being rollers which are free to rotate. The force necessary to bend the specimen is produced by a tup attached to the crosshead of an Instron machine. Here, the experimental procedure is explained

Response to sunitinib (Sutent) in chemotherapy refractory clear cell ovarian cancer

• Case describes a response to sunitinib in clear cell ovarian cancer. • Discussion of unique molecular characteristics of clear cell ovarian cancers; • Practical points regarding dosing and toxicity when using sunitinib discussed

Auto-WEKA: Combined Selection and Hyperparameter Optimization of Classification Algorithms

Many different machine learning algorithms exist; taking into account each algorithm's hyperparameters, there is a staggeringly large number of possible alternatives overall. We consider the problem of simultaneously selecting a learning algorithm and setting its hyperparameters, going beyond previous work that addresses these issues in isolation. We show that this problem can be addressed by a fully automated approach, leveraging recent innovations in Bayesian optimization. Specifically, we consider a wide range of feature selection techniques (combining 3 search and 8 evaluator methods) and all classification approaches implemented in WEKA, spanning 2 ensemble methods, 10 meta-methods, 27 base classifiers, and hyperparameter settings for each classifier. On each of 21 popular datasets from the UCI repository, the KDD Cup 09, variants of the MNIST dataset and CIFAR-10, we show classification performance often much better than using standard selection/hyperparameter optimization methods. We hope that our approach will help non-expert users to more effectively identify machine learning algorithms and hyperparameter settings appropriate to their applications, and hence to achieve improved performance.Comment: 9 pages, 3 figure