نتایج جستجو برای: learning objectives

تعداد نتایج: 815039  

Journal: :Proceeding of the Electrical Engineering Computer Science and Informatics 2018

Journal: :Frontiers: The Interdisciplinary Journal of Study Abroad 2019

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه فردوسی مشهد - دانشکده ادبیات و علوم انسانی 1393

this exploratory study aimed to investigate a possible relationship between learners’ beliefs about language learning and one of their personality traits; that is,locus of control (loc). both variables, beliefs and locus of control, are assumed to influence the language learning process. the internal control index (ici) and the beliefs about language learning inventory (balli) were administered...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه سیستان و بلوچستان - دانشکده ادبیات و علوم انسانی 1392

the construct of self-efficacy has received increasing attention in research over the past two decades. many studies have been carried out 1.3 significance of the study this study has pedagogical implications since improving students’ self- efficacy and autonomy is important for promoting actual performance on classroom academic tasks. in academic settings, it has been shown that self-effi...

پایان نامه :دانشگاه تربیت معلم - تهران - دانشکده ادبیات و علوم انسانی 1394

learning english is very popular all over the world nowadays and it is considered a high prestigious language among citizens of different societies. one of the most important materials for learning a new language are textbooks. the debate that whether learning a new language is natural and neutral or ideological and influential on people’s worldviews, has always been of great importance.

2015
Ingyu Lim Kira L. Barton

Iterative learning control (ILC) is a 2-degree-of-freedom technique that seeks to improve system performance along the time and iteration domains. Traditionally, ILC has been implemented to minimize trajectory-tracking errors across an entire cycle period. However, there are applications in which the necessity for improved tracking performance can be limited to a few specific locations. For suc...

2011
Siwei Lyu

When used to learn high dimensional parametric probabilistic models, the classical maximum likelihood (ML) learning often suffers from computational intractability, which motivates the active developments of non-ML learning methods. Yet, because of their divergent motivations and forms, the objective functions of many non-ML learning methods are seemingly unrelated, and there lacks a unified fr...

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