We want to emphasize from the outset that there is no one "right" way to teach with this book. We hope that it will prove useful to students and instructors in a wide variety of settings. Naturally, we think that the text will work best in a classroom environment that promotes the features extolled in the preface: active learning, conceptual understanding, genuine data, and use of technology.

The following suggestions are based on our own experiences and on those of many instructors who have taught with the original version of Workshop Statistics:
 

1. Take control of the course.

While this may seem obvious, we feel the "control" needed in the course differs from the traditional lecture setting but is still quite important. Students need to see that the instructor is monitoring and facilitating the progress of the course and that there is a pedagogical purpose behind all of the classroom activities.
 

2. Keep the class roughly together.

Part of the control that needs to be taken is to keep the students roughly together with the material, not letting some groups get too far ahead while others lag far behind.
 

3. Allow students to discover.

We encourage you to resist the temptation to tell students too much. Rather, let them discover the ideas and conduct analyses for themselves, while you point them in the right direction as needed. This principle of self-discovery enables students to construct their own knowledge, ideally leading to a deeper understanding of fundamental ideas and a heightened ability to apply these ideas beyond this course.
 

4. Promote collaborative learning among students.

This course provides a natural occasion for encouraging students to work in groups, allowing them to collaborate and learn from each other as well from you and the book.
 

5. Encourage students' guessing and development of intuition.

We believe that much can be gained by asking students to think and make predictions about issues and data before detailed analysis. We urge you to give students time to think about and respond to "Preliminaries" questions in the hope that these questions lead students to care more about the data they will analyze, as well as to gradually develop their own statistical intuition.
 

6. Lecture when appropriate.

By no means do we propose that you never speak to the class as a whole. In many circumstances interrupting the class for a "mini-lecture" is appropriate and important. As a general rule, though, we advocate lecturing on an idea only after students have begun to grapple with it first themselves.
 

7. Have students do some work by hand.

While we believe strongly in using technology to explore statistical phenomena as well as to analyze genuine data, we think that students have much to gain by first performing small-scale analyses by hand. We feel particularly strongly about this point in the context of simulations, where students can better comprehend the process of simulation through physical examples before proceeding to computer simulations. We also encourage instructors to assign a mixture of problems to be solved by hand and with the computer.

 
8. Use technology as a tool.

The counterbalance to the previous suggestion is that students should come to regard technology as an invaluable tool both for analyzing data and for studying statistics. After you have given students the chance to do some small-scale displays and calculations by hand, we suggest that you then encourage them to use technology to alleviate their computational burdens.

 
9. Be pro-active in approaching students.

As your students work through the activities, we strongly suggest that you not wait for them to approach you with questions. Rather, approach them to check their work and provide quick feedback.

 
10. Give students access to "right" answers.

Some students are fearful of a self-discovery approach because they worry about discovering the "wrong" things. We appreciate this objection, and feel it makes a strong case for giving students regular and consistent feedback, including access to right answers.
 

11. Provide plenty of feedback.

This suggestion closely follows the two previous ones about being pro-active and providing "right" answers. An instructor can supply much more personalized, in-class feedback with this "workshop" approach than in a traditional lecture setting.

 
12. Stress good writing.

We regard writing-to-learn as an important aspect of Workshop Statistics, although it is certainly a feature that students resist. Many activities call for students to write interpretations and explanations of their findings, and we urge you to insist that students relate these to the context at hand.

 
13. Implore students to read well.

Students can do themselves a great service by taking their time and reading carefully. By reading directions and questions well, students can better know what is expected in an activity. Moreover, the book's expository passages interspersed among the activities contain a great deal of information that is essential for students to understand.
 

14. Have fun!

We sincerely hope that you and your students will enjoy a dynamic and productive learning environment as you study with Workshop Statistics.