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Moodle is an online tool that allows educators to interact with students outside the classroom and manage a course from anywhere. In Moodle Essential Training for Teachers, Chris Mattia shows how this program works for teachers on three levels: disseminating information, creating a forum where ideas are exchanged, and assessing the progress of students. Chris shows how to build course materials with Moodle's HTML editor, post assignments, and save time by using Moodle's grade book to evaluate tests automatically and organize scores. Exercise files accompany the course.
Now that we've looked all the grades that have been calculated for us by Moodle and we have gone in and graded the essay questions. Let's go ahead and look at some of the data analysis that's built in to Moodle. The first place to look at some data analysis is to go ahead and scroll down to the bottom of the Overview page for your quiz grades. When you do, you get a bar graph indicating the number of students with the specific grades that each student got. Here you can start looking for patterns about the grade ranges that your student achieved during their quiz. Let's go ahead and scroll back up to the top of the page and now click on the link for Item analysis.
The Item analysis page gives you an enormous amount of data about your quiz that can help you in refining future exams and looking into specific questions about each question in your exam that you gave. You can sort all of the data that's provided in this table by simply clicking on the column heading for each data type. If we click on the Q#, we can sort all of questions by the question number that's assigned to them in our question pool. We then have a listing of all of the text for each question. The answers for each question and then you get a listing for partial credit. Partial credit shows how much credit was given for each question by the instructor.
R Counts gives you a value for the number of students that entered that answer divided by the number of attempts for that total question. So if we look at question 16, we can see that four out five students selected the correct answer of True, while only one out of five students selected the wrong answer. Next, you see a value for R%, this is a percentage based on the previous column. The next column % Correct Facility is in overall index that measures how difficult each question was for the quiz takers.
The next column SD column is the Standard Deviation for each question, which measures the spread of answers in response to the overall number of students that answered the question. If all users answered the same way, the Standard Deviation would be zero. The next two columns, Discrimination Index, and Discrimination Coefficient provide a measure of the effectiveness of each question and it compares the difficulty of the question as it's answered by students that are considered to be stronger students or weaker students based on their overall performance throughout the rest of the quiz.
If you are interested in the details of the statistics that are run to generate each of these different values, you can click on the question mark next to the heading Item Analysis Table. Here, you can get detailed information about the math that goes into each of these calculations. Let's click on the link for See all course grades at the top to return back to our main Grade Book.
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