Workshop on Teaching Introductory Statistics Session 2b: Planning the Use of Activities Roger Woodard, North Carolina State University Ginger Holmes Rowell, Middle Tennessee State University Medical College of Wisconsin in Milwaukee July 10 th, 2006

2 Planning the Use  What things should we consider?  Recall from session 1: What do we want them to actually learn? Be sure students will see these things.  What other things?

3 What do we want them to learn?  Learning Objectives Spell out what you want students to learn. Should be action based, not general.

4 Examples:  Explain the meaning of confidence and confidence level.  Calculate confidence intervals for mean from a simple random sample using the formula:

5 Learning Objectives  List of learning objectives for introductory statistics. CAUSEweb: Search for Learning Objectives.  Writing your own Try using Blooms taxonomy.  Levels of thought Be action-oriented. Avoid words like know or understand.

6 Context  How does it fit with other things students know? What other things should students know? Do they need reminders?  Example: Perhaps start a confidence interval activity with a review of using the normal distribution.

7 Mechanics  What will they do to learn this? Will they work in groups or alone? Will they collect data? Do they need equipment or materials? How will you speed up the slow students?  What specific things MUST they do to get the point?

8 Variety  How many levels of thinking will be included? Simple application of techniques. Making conclusions. Evaluating based on evidence.  Try to begin with some basics as a warm-up Students don’t feel overwhelmed.

9 Summary  How will the learning be made concrete? Students put together what they should know. What should they put in their notes?

10 Summary  This step helps students fit the new information in with previous knowledge. Consider asking students to summarize their knowledge in writing. For in-class demos, be sure to include a summary for their notes.

11 Follow-up  How will you come back to this and make the learning important? What they learn should be brought back when possible. Tie topics together.

12 Follow-up  Students value what they are tested over. Students should be exposed to assessment.  Consider providing a practice problem as part of the activity. If several levels of learning are used include several problems

13 Follow-up  In planning a course, consider giving the students a complete list of the objectives with ties to specific problems and activities.

14 Coin Date Example  Learning objectives: What do you want the students to learn? Define a “Sampling Distribution.” Explain why the distribution of the sample averages is less varied than the distribution of the individuals from which they are calculated. Explain that even if the population is very skewed the average from a large random sample will be normally distributed.

15 Coin Date Example  Context: How does this fit with other things students know? Students have calculated the mean. Students have seen distributions of many shapes.

16 Coin Date Example  Mechanics: What will they do to learn this? Students should bring 10 coins to class; some extra coins should be brought. Students will work in groups of 3 on a worksheet. Worksheets should be pre-numbered to facilitate calling on the groups. Students will need a calculator. As the students are calculating their averages the instructor should prepare a histogram on the board or a transparency. Alternatively, you can use Post-It notes to make a Post-It note histogram. After a discussion of the histograms, the instructor will use the online demo to simulate many sampling distributions.

17 Coin Date Example  Variety: How many levels of thinking will be included? Students will need to think abstractly about the shape of the distributions of the date of coins. Students will do some very basic calculations.

18 Coin Date Example  Summary: How will the learning be made concrete?  A summary slide will be used at the end of the activity where students are asked as a group to fill in the following  A sample mean from a sample of N= ____ is less varied than the Parent Population but more varied than sample mean from a sample of N = ___.  Even if a parent population’s distribution is _________ the distribution of the sample mean is _______ and becomes more so as the sample size _________.

19 Coin Date Example  Follow-up: How will you come back to this and make the learning important? The next lecture will bring this back when we talk about calculations with the central limit theorem. Students will be asked a question on the online quiz about this topic. The applet will be used again when beginning the discussion of the ideas of confidence intervals and hypothesis testing.

20 Where do I get the time?

21 Where do I get the time?  Better understanding of a few topics replaces pure bulk of material. Move less vital examples to homework or other independent study.  Reduce time required for note taking. Use guided note outlines.

22 Your turn  Take some time to plan how you will use the resources you have found.  Fill out the planning worksheet.  We will discuss the results when you have finished.