 Welcome to this video on supporting students with their vocabulary in an EMI course. The video demonstration is by Dr. Amoon Cho, Ohio University visiting professor, who taught EMI courses in mathematics and statistics. Please watch this demonstration of an EMI course and critique it using the following questions. 1. Identify at least three strategies Dr. Cho uses to help students with unknown vocabulary. Give an example of each. Some strategy options include defining the word, using a synonym or paraphrase, explaining the term, repeating the term, using an illustration or a picture of the term, or checking students' understanding. 2. Discuss how you think you can use or recommend some of these strategies in EMI courses at your university. Okay, here is Dr. Cho. Hello everyone, today I'm going to be lecturing on chai square analysis. We use chai square analysis when you have to deal with categorical variables. As we all know by now, categorical variables fall into different categories or groups. It's like you're classifying data points according to their underlying characteristics. For example, we could have a category of eye color. Under that category, we could have categorical variables like brown, blue, black, green, and so on. Another example can be college admission results. In this case, the two categorical variables would be accepted, hee hee, or rejected. An applicant either accepted or rejected, not both at the same time. So applicants belong to one of the two categories. It is really important with the categorical variables that they be separate. A data point cannot belong to both at the same time. When we analyze these kinds of categorical variables, we use a different approach from analyzing continuous variables. Now, before we get into the details of chai square analysis, we need to understand some fundamental or important mathematical concepts behind a contingency table. A contingency table, which is a matrix or a rectangular array of frequencies in rows and columns, as it's showing right now, is a table showing frequency counts under different conditions. The word contingent is very similar to dependent or conditional. So the numbers of counts in each cell in a contingency table represents, for example, the number 13 represents the condition under sound sleep, yes, and taking vitamin, yes. So in this example, the first column here represents a participant took vitamin and they had a really good sound sleep. Thank you, Dr. Cho, for this demonstration. Now it's your turn. Please go to the discussion board and write your answers to these two questions. One, identify at least three strategies that Dr. Cho uses to help students with unknown vocabulary and give an example of each. Two, discuss how you think you can use or recommend some of these strategies in EMI courses at your university. Also, remember to read what some of your peers write and post a response to at least one peer's posting. Thanks.