Motivating Students to Learn English: Intrinsic and Extrinsic Strategies to Meet the Needs of First Time Learners

Motivation is the key to learning. The present study is about the relationship between intrinsic and extrinsic motivation as they affect learning with regard to students who are learning EFL for the first time. Cape Verdean seventh grade students learning English for the first time are generally very enthusiastic about the language before they start learning it in the high school. However, that enthusiasm seems not to be maintained throughout the school year and oftentimes teachers hear them complain about the difficulties of mastering aspects of the language. It seems that for some reason their motivation is undermined. Why does that happen? Is it the students’ fault or the teacher’s? If it the teacher’s fault, which motivation strategies work best to cope with this problem: intrinsic or extrinsic? With this in mind I asked the question: What is the relationship between students’ needs, interests, goals and expectations to learn English as a foreign language and teachers’ roles as facilitators and motivators? There are many studies that have been carried out in the field of motivation, and up to now, there seems to be no consensus of which is the best. For the purposes of this paper, three main theories will be discussed that have prevailed in the field of motivational psychology: the behavioural, the cognitive and the humanistic theories. Within these theories sub-theories are discussed and their relationship is explained with intrinsic and extrinsic motivation regarding Cape Verdean students learning English for the first time.

A polynomial algorithm for special case of the one-machine scheduling problem with time-lags

The standard one-machine scheduling problem consists in schedulinga set of jobs in one machine which can handle only one job at atime, minimizing the maximum lateness. Each job is available forprocessing at its release date, requires a known processing timeand after finishing the processing, it is delivery after a certaintime. There also can exists precedence constraints between pairsof jobs, requiring that the first jobs must be completed beforethe second job can start. An extension of this problem consistsin assigning a time interval between the processing of the jobsassociated with the precedence constrains, known by finish-starttime-lags. In presence of this constraints, the problem is NP-hardeven if preemption is allowed. In this work, we consider a specialcase of the one-machine preemption scheduling problem with time-lags, where the time-lags have a chain form, and propose apolynomial algorithm to solve it. The algorithm consist in apolynomial number of calls of the preemption version of the LongestTail Heuristic. One of the applicability of the method is to obtainlower bounds for NP-hard one-machine and job-shop schedulingproblems. We present some computational results of thisapplication, followed by some conclusions.

Strategies for sequential prediction of stationary time series

We present simple procedures for the prediction of a real valued sequence. The algorithms are based on a combinationof several simple predictors. We show that if the sequence is a realization of a bounded stationary and ergodic random process then the average of squared errors converges, almost surely, to that of the optimum, given by the Bayes predictor. We offer an analog result for the prediction of stationary gaussian processes.

Retinal thickening in HLA-B27 associated acute anterior uveitis: evolution with time and association with severity of inflammatory activity.

Purpose: To describe the evolution of retinal thickness in eyes affected with acute anterior uveitis (AAU) in the course of follow-up and to assess its correlation with severity of inflammatory activity in the anterior chamber. Methods: Design: Prospective, cohort study Setting: Institutional study Patient population: 72 eyes (affected and fellow eyes) of 36 patients Observation procedure: Patients were followed daily until beginning of resolution of inflammatory activity and weekly thereafter. Optical coherence tomography and laser flare photometry were performed at each visit. Treatment consisted of topical corticosteroids Main outcome measures: Retinal thickness of affected eyes, difference in retinal thickness between affected and fellow eyes and their evolution in time, association between maximal retinal thickness and initial laser flare photometry. Results: Difference in retinal thickness between affected and fellow eyes became significant on average seven days from baseline and remained so through-out follow-up (p<0.001). There was a steep increase in retinal thickness of affected eyes followed by a progressive decrease after reaching a peak value. Maximal difference in retinal thickness between affected and fellow eyes was observed between 17 and 25 days from baseline and exhibited a strong, positive correlation with initial laser flare photometry values (p=0.015). Conclusions: Retinal thickness in eyes affected with AAU presents a steep increase over 3 to 4 weeks and then gradually decreases. Severity of inflammation at baseline predicts the amount of retinal thickening in affected eyes. A characteristic pattern of temporal response of retinal anatomy to inflammatory stimuli seems to arise.

Improved nonparametric confidence intervals in time series regressions

Condence intervals in econometric time series regressions suffer fromnotorious coverage problems. This is especially true when the dependencein the data is noticeable and sample sizes are small to moderate, as isoften the case in empirical studies. This paper suggests using thestudentized block bootstrap and discusses practical issues, such as thechoice of the block size. A particular data-dependent method is proposedto automate the method. As a side note, it is pointed out that symmetricconfidence intervals are preferred over equal-tailed ones, since theyexhibit improved coverage accuracy. The improvements in small sampleperformance are supported by a simulation study.

Estimating overidentified, nonrecursive, time-varying coefficients structural VARs

This paper provides a method to estimate time varying coefficients structuralVARs which are non-recursive and potentially overidentified. The procedureallows for linear and non-linear restrictions on the parameters, maintainsthe multi-move structure of standard algorithms and can be used toestimate structural models with different identification restrictions. We studythe transmission of monetary policy shocks and compare the results with thoseobtained with traditional methods.

On the closed-form approximation of short-time random strike options

In this paper we propose a general technique to develop first and second order closed-form approximation formulas for short-time options withrandom strikes. Our method is based on Malliavin calculus techniques andallows us to obtain simple closed-form approximation formulas dependingon the derivative operator. The numerical analysis shows that these formulas are extremely accurate and improve some previous approaches ontwo-assets and three-assets spread options as Kirk's formula or the decomposition mehod presented in Alòs, Eydeland and Laurence (2011).