Here are the resources for Open Forum 2. Download and print the worksheet for the chapter you would like more practice with. Then download the listening. Open Forum online. Click on a book for extra listening selections and worksheets . Open Forum 1 Open Forum 2 Open Forum 3. Open Forum 1 | Open Forum 2. Start by marking “Open Forum 2 Student Book: Academic Listening and Speaking” as Want to Read: Including listening texts, this work provides opportunities for conversation practice and student interaction. It also includes a student website that provides downloads MP3 for.
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Volume 11, Number 1 1. Open Forum: Academic Listening and Speaking, Book 2. Author: Angela Blackwell and Therese Naber (). available on the Open Forum Web site (medical-site.info) for extended practice. Open Forum. Level 1. Level 2. Level 3. Available at each level . Open Forum 2: Answer Key and Test Booklet, , available at Book Depository with free delivery worldwide.
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Then listen to the interview again and write T for true or F for false for each question.. Chapters 79Name: Read questions 1 and 2. Then listen to the conversation and choose the correct answer for each question.. Read questions 11 and Then listen to two extracts from the conversation.
After listening to each extract, write T for true or F for false for each question.. T show.
Then listen to the conversation again and write T for true or F for false for each question.. T technology.
T not. T the. T money. T because. T writer. T tools. Assessment Tests5Test 4: Chapters Name: Then listen to the news report and choose the correct answer for each question.. Then listen to the news report again and choose the correct answer for each question..
Then listen to three extracts from the news report.
Open Forum: Lynette HanA:. States looked.
C Listening for More Detailexercise 2 p. D Focus on the Listening Skillexercise 2 p. H wild?. C units. C learn?.
D Working Out Unknown Vocabulary p. W this. Extract 2.
Tom I. Speaker 2: Tracy I. They focus on two types of threads: problem solving and discussion, both in nested threads. Central aspects of their method are the detection of the thread structure responses, quotes and mentions , the prominence of messages, and the prominence of authors in the thread. They cluster the comments and rank them by their estimated relevance within their cluster. The top comments from each cluster are used to give an overview of that cluster. The authors find that for the task of summarizing newspaper comments topic model clustering gave the best results when compared to a human reference summary.
They implement a feature-based method using linear regression for optimally combining the features.
Their results demonstrate how automatically labeled comment clusters can be used to generate an abstractive summary of a discussion thread. They evaluate their method on two forums: ubuntuforums. Our experimental contribution is that we first conduct an extensive user study to create reference summaries, analyze the collected data, and then build a summarization model based on the combined reference summaries by multiple human raters.
A reference summary in extractive summarization is defined by the concatenation of the most important bits of information in the text, and hiding or removing the less important fragments in between Hahn and Mani In order to create these summaries, we presented human raters with a discussion thread and asked them to select the most important posts.
In contrast with the other reference data sets, we deliberately did not specify the length of the desired summary and left it to the raters to decide. Each thread was shown to 10 different raters. We analyzed their responses to address our research questions. We trained an automatic extractive summarizer and compared its performance to the reference summaries.
In the next sections we discuss each step in detail. The discussions on the forum are mostly directed at experience and opinion sharing. Registered users can start new threads and comment on threads. The Viva forum has 19 Million page views per month 1. We obtained a sample of 10, forum threads from the forum owner, Sanoma Media.
The average number of posts in a thread is For our experiment we created a sample of randomly selected threads that have at least 20 posts. Of threads with more than 50 responses, we only used the first 50 for manual labelling.
The median number of posts shown to a rater per thread is The users provided some basic information in the login screen, such as how often they have visited the Viva forum in the past month. They were then presented with one example thread to get used to the interface.
After that, they were presented with a randomly selected thread from our sample. The raters decided themselves how many threads they wanted to summarize. They were paid a gift certificate. The left column of the screen shows the complete thread; the right column shows an empty table.