A critical look at the Communicative Approach (1) Michael Swan This (the first of two articles) examines some of the more theoretical ideas underlying the ‘Communicative Approach‘. These include the belief that we should teach ‘use’ as well as ‘meaning; and some attitudes regarding the teaching of ‘skills’ and ‘strategies’. A second article will deal with more pedagogical aspects of the approach‚ especially the idea of a ‘semantic syllabus’ and the question of ‘authenticity’ in materials and methodology
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Organic vs Conventional Essay Organic food‚ which was once only found in health food stores‚ is now a regular feature at most grocery stores‚ and has created a bit of a dilemma in the produce aisle. On one hand‚ you have an organically grown apple. On the other hand‚ you have an apple that was grown conventionally. Both of these apples are shiny‚ red‚ and firm. Both provide us with vitamins and fiber‚ and both are free from sodium‚ fat‚ and cholesterol. Which should you choose? For many reasons
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Collecting Data Shauntia Dismukes BSHS/405 June 1‚ 2015 Tim Duncan Collecting Data Data collection is the process of gathering and measuring information on variables of interest‚ in an established systematic fashion that enables one to answer stated research questions‚ test hypotheses‚ and evaluate outcomes. In this paper I will define the importance of data collecting in the helping field. While working in the helping field‚ there are many important things that must happen
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Lecture Notes 1 Data Modeling ADBMS Lecture Notes 1: Prepared by Engr. Cherryl D. Cordova‚ MSIT 1 • Database: A collection of related data. • Data: Known facts that can be recorded and have an implicit meaning. – An integrated collection of more-or-less permanent data. • Mini-world: Some part of the real world about which data is stored in a database. For example‚ student grades and transcripts at a university. • Database Management System (DBMS): A software package/ system to facilitate
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Test Anxiety is defined by Kondo (1996) as a double situation specific personality trait‚ consisting of two psychological components; emotional arousal and worry. Several studies have focused on test anxiety‚ as it is associated with lower test results and a higher amount of stress‚ so has attracted attention from researchers and teachers (Hembree 1998; Sarason and Sarason 1990) as cited in Kondo (1996). Most of the focus has been to reduce test anxiety by investigating the cognitive‚ affective
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best alternative in the following: Q.1 In the relational modes‚ cardinality is termed as: (A) Number of tuples. (B) Number of attributes. (C) Number of tables. (D) Number of constraints. Ans: A Q.2 Relational calculus is a (A) Procedural language. (C) Data definition language. Ans: B Q.3 The view of total database content is (A) Conceptual view. (C) External view. Ans: A Q.4 Cartesian product in relational algebra is (A) a Unary operator. (B) a Binary operator. (C) a Ternary operator. (D) not defined
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Personality tests are used to better understand how one is perceived by others in day to day interactions. Although the questions asked seem very random at times‚ they cover a wide range of topics to better evaluate the individual. Along with evaluating someone’s personality‚ the tests are also used to give suggestions of possible career fields that would best suit the individual. After taking a few of these tests myself‚ I hope to have a better idea of my personality and apply the results to my
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Introduction to Data Mining Assignment 1 Ex1.1 what is data mining? (a) Is it another hype? Data mining is Knowledge extraction from data this need for data mining has arisen due to the wide availability of huge amounts of data and the imminent need for turning such data into useful information and knowledge. So‚ data mining definitely is not another hype it can be viewed as the result of the natural evolution of information technology. (b) Is it a simple transformation of technology developed
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Components of DSS (Decision Support System) Data Store – The DSS Database Data Extraction and Filtering End-User Query Tool End User Presentation Tools Operational Stored in Normalized Relational Database Support transactions that represent daily operations (Not Query Friendly) Differences with DSS 3 Main Differences Time Span Granularity Dimensionality Operational DSS Time span Real time Historic Current transaction Short time frame Long time frame Specific Data facts Patterns Granularity Specific
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environmentally friendly than our typical paper and cardboard book‚ even a paperback. There are certain tactile to real book‚ just feeling the paper‚ turning the pages. But on the surfaces‚ the e-reader would seem to be much greener. E-reader vs. conventional book is a provocative question.
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