Tag Archive : Ielts Learning Tutorial

Use cohesive devices to keep your writing IELTS method

Use cohesive devices to keep your writing IELTS method

The Writing test takes 60 minutes, so make sure you plan your time accordingly. Most test takers spend approximately 20 minutes on Task 1 and 40 minutes on Task 2. But make sure you leave some time at the end to quickly review your answers and make any necessary changes to your responses.

Cohesive devices help you connect your ideas and help keep your writing responses organised. Use these words and phrases to connect your ideas and help your reader follow your writing.  

Indian, African American, and Caucasian teenage women are high school or college students. They are sitting at a desk in a crowded library and studying using a laptop computer. Indian girl is smiling and looking at the camera.

Some cohesive devices you could use, include: 

  • Furthermore 
  • However 
  • Next 
  • First, second, third 
  • Finally 
  • So  
  • Then 
  • In addition 

Take some time before you take your IELTS test to study and practice using these words, as well as other cohesive devices (linking words). 

Take time in your IELTS preparation to review some sample questions and answers online. You can gain a better understanding of the IELTS test format, the kinds of questions you may be asked and read model answers.

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how to Use the correct format in paragraph writing in IELTS coaching

how to Use the correct format in paragraph writing in IELTS coaching

Writing Task 1 in the General Training test is different to that in the Academic test. 

 In General Training, Writing Task 1, you will need to structure your letter and include: 

  • A short greeting to the recipient 
  • An intro telling the recipient why you are writing.  
  • A paragraph for each of the bullet points in the question or task.  
  • A short closing.  
  • The correct letter-writing conventions to start and finish your letter 

In Academic, Writing Task 1, when describing a graph, chart or diagram in the question, make sure you have: 

  • An introduction – rewording of the question
  • Body paragraph(s) – key details, their relevance, comparisons, etc. 
  • An overview or summary of the main ideas.

For the Writing Task 2 essay, you will write using essay format. You should have: 

  • An introductory paragraph where you write the thesis statement – what the essay will be about 
  • Body paragraphs (usually 2 to 3) with clearly defined topics supported with details and examples 
  • conclusion summarising the points in your essay.
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Read the task take notes for IELTS writing

Read the task take notes for IELTS writing

Before you start writing your response, make sure you take a few moments to carefully read the question or task. It will help you better prepare your answers. 

  • Take notes and write down ideas you think might be suitable for your answer 
  • Highlight keywords in the task or question to better understand what you need to address in your response 
  • Do a quick outline to organise your thoughts in response to each  
  • Expand on your ideas with examples, supporting details, etc.

Once you have chosen your ideas, it is time to start writing. To keep your answers well organised, you must write in paragraphs. Each paragraph should contain a clear topic that is developed within the paragraph.  

Make sure you do not write in bullet points or in point form.

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How to Listening Test and Spoken BEC

How to Listening Test and Spoken BEC

A user can scan through a text easily, but it is not the case for spoken content, because they cannot be directly displayed on-screen. As a result, accessing large collections of spoken con-tent is much more difficult and time-consuming than doing so for the text content. It would therefore be helpful to develop machines that understand spoken content. In this paper, we propose two new tasks for machine comprehension of spoken content. The first is a listening comprehension test for BEC, a challenging academic English examination for English learners who are not the native English speakers. How to Listening Test and Spoken BEC

Group of young college students using laptop in a cafe.

We show that the proposed model out performs the naive approaches and other neural network based models by exploiting the hierarchical structures of natural languages and the selective power of attention mechanism. For the second listening comprehension task – spoken squad we find that speech recognition errors severely impair machine comprehension; we propose the use of sub word units to mitigate the impact of these errors.

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How to PTE Scores to Predict in SPEAK Test

How to PTE Scores to Predict in SPEAK Test

The PTE english test , produced by the Educational Testing Service (ETS), has been in use in institutions of higher American education since the 1960s as a means of measuring incoming international students’ English proficiency. But like any test, the PTE is imperfect. For instance, whereas a high PTE score may be sufficient to admit an international student to an American graduate school, many colleges and universities require more rigorous proof of a student’s English proficiency—often in the form of a passing score on a school-specific oral assessment—if he seeks employment as a Graduate Teaching Assistant (GTA). How to PTE Scores to Predict in SPEAK Test

To mitigate this risk, forecasting models which use the PTE sub-scores of Speaking, Listening, Writing, and Reading to forecast SPEAK test outcome are applied. A student’s sub-scores act as predictive inputs to each model, which outputs the posterior probability of his SPEAK test failure. Bayes Theorem provides the structure required to obtain this probability, and the multivariate meta-Gaussian distribution captures the stochastic dependence between the sub-scores. Therefore, these models are classified as Bayesian Meta-Gaussian Forecasters (BMGFs).

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TOEFL English test for the Graduate and School students

TOEFL English test for the Graduate and School students

To correspond to drastic change in international society such as “globalization”, graduate education plays a key role in development of human resources. The new trans-graduate-school education program called “Nitobe School” was launched in 2015 as one of the main education projects of “Top Global University Project” in Hokkaido University. This is a trial case report of the comparison of commercial English test for the Graduate School students. We employed about 50 students from the various graduate schools in Hokkaido University, and they took same commercial English tests (TOEIC and TOEFL), then its result is discussed in here. TOEFL English test for the Graduate and School students

The pre-post English speaking test: Describing the picture , Pre-English Speaking Test was used without teaching. Post-English Speaking Test was used after teaching.

The English speaking ability evaluation form. The evaluation criteria were as follows: Grammar and vocabulary ,Structures: Process of speaking , Fluency and pronunciation , Self confidence,Persuasiveness .

The collected data was analyzed using computer program. The t-test was employed to compare the subjects’ English speaking ability before and after using English speaking based on communicative approach. The mean and standard deviations of scores from English speaking evaluation form, the satisfaction questionnaire were used to measure at the end of the class.

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How to Test of Spoken English Competence Advanced Learners

How to Test of Spoken English Competence Advanced Learners

It is evident that English has become an essential part of everyone’s life. In higher education, especially graduate studies, English inevitably plays a crucial role in determining the success or failure of the students. In order to screen applicants for graduate studies, it is important to devise a standardized test which is reliable, valid, and practical. Conventionally, most English proficiency tests in Thailand will have three subtests in common. These sub tests include: Error identification, Multiple-choice cloze, and Reading comprehension. How to Test of Spoken English Competence Advanced Learners

Teaching speaking English has a crucial role in English instruction as a foreign language. That’s because teaching English based on communicative approach theory is worldwide. Therefore, Institute of Technology emphasizes communicative approach teaching. Thus the students need to have competence in listening and speaking. [9] stated that the principle of communicative training involves the use of complex communicative situations, aimed at developing the pupil’s speech that promotes “overcoming a sharp transition from education to the natural conditions of communication due to the formation of students’ strong associative links”. The teacher becomes free to choose a variety of instructional techniques and incentives that can maintain motivation and mental activity of students during the entire study period.

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Information System for Game TOEFL like App

Information System for Game TOEFL like App

Educative games are trending among students. Games can be used to support student learning.Difficulties in completing a TOEFL (Test of English as a Foreign Language) can be helped by doing game exercises that are similar to the actual test conditions. The TOEFL learning method while playing the game becomes an interesting project, to see how students can use the game experience to master the skills needed for doing a TOEFL. Information System for Game TOEFL like App

One of the criteria of an English student‟s mastery in the language is to show how proficient that student is in doing a TOEFL. For this reason, a TOEFL-Like App game has been created by the researchers, who are a team made up from the English Department and Information Systems Department that specifically deals with Game Technology. The researchers see that managing the results of a TOEFL test that goes on for almost an hour, needs to be assisted with some kind of system to ease the burden of the English teachers. Henceforth, the TOEFL-Like Game App is built with an information system to help teachers access the final results online.

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Relationship between Perception and Production of English Vowels by Chinese English Learners

Relationship between Perception and Production of English Vowels by Chinese English Learners

In previous studies, no consensus has been reached on the existence of significant correlation between perception and production. A large number of empirical studies have been done upon first and second languages from different language families. However, few studies were carried out on the perception-production relation of Chinese English learners. Therefore, in the current study, under the theoretical framework of PAM-L2, 40 subjects with even numbers in two genders, who differ in language proficiency, are invited to participate in the perception experiment and the production experiment, in which discrimination, identification and pronunciation of /ɪ/-/ε/, /ε/-/æ/, /ʊ/-/ʌ/, and /ʌ/-/ɒ/ contrasts are observed. Results reveal that vowel perception of Chinese English learners is neither statistically correlated nor spectrally related to vowel production. Relationship between Perception and Production of English Vowels by Chinese English Learners

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As foreign language teaching develops worldwide, scholars in second language (L2) learning and acquisition unanimously found a vague link between “listening” and “speaking”. Spoken proficiency of L2 learners was improved even though they didn’t receive training in pronunciation but increased exposure to native production [1]. Scholars began to consider whether there was a close bond between perception and production. If there was, in L2 education, teachers could not only concentrate their training on production, but also add some training to the perception of L1 sounds. Training of perception could also be applied as a supplementary method in phoniatric training for those who failed to adjust their pronunciation merely by articulation training such as imitation.

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TWO-LAYER APPROACH FOR SPOKEN LANGUAGE TRANSLATION

TWO-LAYER APPROACH FOR SPOKEN LANGUAGE TRANSLATION

This study proposes a new two-layer approach for spoken language translation. First, we develop translated examples and transform them into speech signals. Second, to properly retrieve a translated example by analyzing speech signals, we expand the translated example into two layers: an intention layer and an object layer. The intention layer is used to examine intention similarity between the speech input and the translated example. The object layer is used to identify the objective components of the examined intention. Experiments were conducted with the languages of Chinese and English. The results revealed that our proposed approach achieves about 86% and 76% understandable translation rate for Chinese-to English and English-to-Chinese translations, respectively. TWO-LAYER APPROACH FOR SPOKEN LANGUAGE TRANSLATION

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With the growing of globalization, people now often meet and do business with those who speak different languages, on-demand spoken language translation (SLT) has become increasingly important (See JANUS 111 [I], Verbmobil [2], EUTRANS [3], and ATR-MATRIX [4]). Recently, an integrated architecture based on stochastic finite-state transducer (SFST) has been presented for SLT [3,5]. The SFST approach integrated three models in a single network where the search process takes place. The three models are Hidden Markov Models for the acoustic part, language models for the source language and finite state transducers for the transfer between the source and target language. The output of this search process is the target word sequence associated to the optimal path. Fig. 1 shows an example of the SFST approach. The source sentence ‘‘una habitacidn doble” can he translated to either “a double room” or “a room with two beds”. The most probable translation is the first one with probability of 0.09.

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