Literature Index

The introductory applied statistics course taken by many thousands of undergraduate students has undergone a transformation over the past 25 years. Changes in what we teach, how we teach, and how we assess have impacted introductory statistics courses at institutions worldwide. In this article we shift focus from what we teach and how we teach to when we teach. We propose changes to the sequence in which core statistical concepts are presented in an introductory applied statistics course. The proposed ordering of topics repeats the sequence of descriptive summaries - probability theory - statistical inference several times throughout the course in various contexts.

I am inclined to believe that despite the different settings in which statisticians work, it is nevertheless important for them to be aware of good teaching and learning techniques, so that they may continue in their own lifelong learning, dealing with the continual increase of new information to be learned, and also so that they may teach others, whether in an academic stetting with students or in another type of setting in government or industry. To this end, I think that course work and experience in teaching should be required of all graduate students in statistics, as well as for students in other disciplines.<br><br>However, I have some concerns about teacher training programs that focus exclusively on lesson plans, syllabi, handouts, and lectures. In deeping with the suffestions for good teaching I have described, I would like to see teacher training programs help graduate students learn about the teaching and learning process, learn now to develop adn facilitate cooperative learning actrivities, become experienced with the role of assessment (and alternative forms of assessment), and learn about current ways of improce teaching in their discipline (that is, the use of software as a teaching tool, the use of pojects, and so on). The development of programs such as these could lead to a new generation of improved statistics teachers and statisticians who are able to work more effectively in any type of setting. I look forward to seeing this happen.

Previous research suggests that a randomization-based introductory statistics course may improve student learning compared to the consensus curriculum. However, it is unclear whether these gains are retained by students post-course. We compared the conceptual understanding of a cohort of students who took a randomization-based curriculum (n = 76) to a cohort of students who used the consensus curriculum (n = 79). Overall, students taking the randomization-based curriculum showed higher conceptual retention in areas emphasized in the curriculum, with no significant decrease in conceptual retention in other areas. This study provides additional support for the use of randomization-methods in teaching introductory statistics courses.

Some questions that teachers who are ready to venture online for the first time or who are trying to rethink how they are currently using online resources in the classroom should ask are provided. These questions ask what the educational purpose of the activity is, where the activity fits into the curriculum, how using the Internet will enhance the activity, how students will use the online resources, what experience students have with data analysis and thoughtful discussion, and what will happen if the intended resources are not available.