Literature Index

Reasoning about uncertainty is a key and challenging element in informal statistical inferential reasoning. We designed and implemented an “Integrated Pedagogic Approach” to help students understand the relationship between sample and population in making informal statistical inferences. In this case study we analyze two sixth grade students’ reasoning about uncertainty during their first encounters with making informal statistical inferences based on random samples taken from a hidden TinkerPlots2 Sampler. We identified four main stages in the students’ reasoning about uncertainty: Account for, examine, control, and quantify uncertainty. In addition, two types of uncertainties – contextual and a statistical –shaped the students’ reasoning about uncertainty and played a major role in their transitions from stage to stage. Implications for research and practice are also discussed. 

The present study addresses the efficacy of using service-learning methods to meet the GAISE guidelines (http://www.amstat.org/education/gaise/GAISECollege.htm) in a second business statistics course and further explores potential advantages of assigning a service-learning (SL) project as compared to the traditional statistics project assignment. Second semester business students were given the choice of participating in a SL project or doing a traditional project assignment.<br><br>When the projects were completed, students reflected on their experiences via survey. Both groups responded equally (agree or strongly agree) to the Likert scale questions: 96.15% reinforced learning objectives, 98.08% applied to real world, 84.62% positive experience. Responses to the open ended questions revealed that more students in the SL group (p = 0.019) wrote about the benefits of dealing with real world data, more SL students felt their work benefited others (65% felt their statistical expertise was valuable) and more (p=0.005) SL students felt that the experience will help them in future classes. These results suggest that while both groups were able to effectively support the GAISE guidelines, participation in the SL option offered an enhanced learning experience that included elements of social responsibility and personal growth. The experience was perceived more enjoyable and relevant to the real world adding elements of student empowerment while assisting a local agency in need of statistical expertise suggesting one can reap positive learning benefits by introducing service-learning pedagogy into a non-majors statistics course.

The paper describes how the transformative and conjecture-driven research design, a research model that utilizes both theory and common core classroom conditions, was employed in a study examining introductory statistics students' understanding of the concept of variation. It describes how the approach was linked to classroom practice and was employed in terms of research design, data collection, and data analysis. The rich insights into the evolution of students' thinking about variation that have originated from this research are then discussed. Implications for research and instruction follow.

This study seeks to describe the subject matter knowledge needed for teaching<br><br>statistical association at the secondary level. Taking a practice-based qualitative<br><br>approach, three experienced teachers were observed as they taught statistical<br><br>association and interviewed immediately following each observation. Records of<br><br>practice were assembled to create a compilation document to recreate each of the<br><br>fifty observed class sessions along with related materials including textbook pages<br><br>and student work. Analysis of the compilation documents focused on the demands<br><br>upon teachers' subject matter knowledge involved in the practice of teaching.<br><br>Findings regarding the knowledge required for teaching correlation coefficient are<br><br>highlighted, including its computation, interpretation, sensitivity, estimation, and<br><br>related terminology.