abstract the study aimed at investigating the efficacy of written corrective feedback (cf) in improving iranian efl learners’ grammatical accuracy. it compared the effects of focused and unfocused written cf on the learners’ grammatical accuracy. 75 efl students formed a one control and two experimental groups. the focused feedback group was provided with error correction in tenses. the unfocus...

The setting is that of an agent who needs to find out in which sense a predicate may have been used in a set of sentences received from a source. The agent should take into account both the logical constraints of the set of sentences and relevant semantic information concerning the predicate stored in his semantic memory. I present several adaptive fuzzy hedge logics. Each of these logics check...

Recent advances in machine learning make it possible to design efficient prediction algorithms for data sets with huge numbers of parameters. This paper describes a new technique for “hedging” the predictions output by many such algorithms, including support vector machines, kernel ridge regression, kernel nearest neighbours, and by many other state-of-the-art methods. The hedged predictions fo...

This study investigates the effect of four types of oral corrective feedback, namely, explicit elicitation, implicit elicitation, explicit recast and implicit recast on the most commonly mispronounced phonological features among Iranian EFL learners through immediate uptake and retention. Five classes were randomly categorized into four experimental groups and one control group, each with 18 in...

Load serving entities providing electricity to regulated customers have an obligation to serve load that is subject to systematic and random fluctuations at fixed prices. In some jurisdictions like New Jersey, such obligations are auctioned off annually to third parties that commit to serve a fixed percentage of the fluctuating load at a fixed energy price. In either case the entity holding the...

Recent advances in machine learning make it possible to design efficient prediction algorithms for data sets with huge numbers of parameters. This article describes a new technique for ‘hedging’ the predictions output by many such algorithms, including support vector machines, kernel ridge regression, kernel nearest neighbours, and by many other state-of-the-art methods. The hedged predictions ...

A new Bayesian multi-chain Markov Switching GARCHmodel for dynamic hedging in energy futures markets is developed: a system of simultaneous equations for return dynamics on the hedged portfolio and futures is introduced. More specifically, both the mean and variance of the hedged portfolio are assumed to be governed by two unobserved discrete state processes, while the futures dynamics is drive...

Facilitating the provision of detailed, deep and useful feedback is an important design feature of any educational programme. Here we evaluate feedback provided to medical students completing short transferable skills projects. Feedback quantity and depth were evaluated before and after a simple intervention to change the structure of the feedback-provision form from a blank free-text feedback ...