مطالب

This study explores the relationship and interconnections between EFL teachers’ beliefs and their motivational practices in the classroom. The present study combined qualitative and quantitative methods of research. First, the motivational practices of 30 teachers in two private language schools in Tehran were explored with a classroom observation instrument, the Motivation Orientation of Language Teaching (MOLT) which was used to estimate the time that teachers spent for each motivational strategy. Then, teachers’ beliefs were examined through the Beliefs about Language Learning Inventory (BALLI) and an open-ended questionnaire aimed to assess beliefs about motivational strategies. The quantitative results indicated that the higher the teachers’ scores on the BALLI, the less frequently their use of motivational strategies in the classroom. The findings based on qualitative data, drawing largely on data from observations and the open-ended questionnaire, showed that although teachers were observed to generally follow their beliefs, there existed several points of difference between their beliefs and practices. Also, there was evidence that what teachers practice in the classrooms does not always impact their beliefs.

Optimal Portfolio Selection is one of the most important issues in the field of financial research. In the present study, we try to compare four various different models, which optimize three-objective portfolios using “Postmodern Portfolio Optimization Methods”, and then to solve them. These modeling approaches take into account both multidimensional nature of the portfolio selection problem and requirements imposed by investors. Concretely different models optimize the expected return, the down side risk, skewness and kurtosis given portfolio, taking into account budget, bounds and cardinality constrains. The quantification of uncertainty of the future returns on a given portfolio is approximated by means of LR-fuzzy numbers, while the moments of its returns are evaluated using possibility theory. In order to analyze the efficient portfolio, which optimize three criteria simultaneously, we build a new NSGAII algorithm, and then find the best portfolio with most Sortio ratio from the gained Pareto frontier. Thus, in this paper we choose 153 different shares from different industries and find their daily return for ten years from April of 2006 till March of 2017 and then we calculate their monthly return, downside risk, skewness, kurtosis and all of their fuzzy moments. After designing the four models and specific algorithm, we solve all of the four models for ten times and after collection of a table of the answers, compare all of them with Treyner ratio. At last, we find that using fuzzy and possibistic theory make higher return and better utilized portfolios.