Literature Index

The importance of facilitating study and practice materials that are consistent with graded assessments and instructional objectives is well known, if not commonly used , in educaitonal practice. Reciprocal Peer Tutoring (RPT) is a collaborative approach that embeds assessment in a formalized learning process to facilitate student involvement with course content and improve achievement. Students engaging in RPT activity, each student of a dyad is independently responsible for synthesizing course content and constructing practice multiple-choice test questions, complete with answers, based on the course curriculum. Each dyad then administers practice tests to each other prior to formal class examinations. Upon completion of the practice exams, partners score each other's work and alternate roles as tutors, and tutees to assess each other's performance, give feedback on missed items, and discuss individual questions and course content. In this dual role as tutor and tutee, students benefit through the preparation and instruction in which tutors engage, as well as from the instruction that tutees receive. This study examines the impact of reciprocal peer tutoring (RPT) on student achievement over six sections of an introductory statistics course. A comparison of RPT treatment relative to a control accounting for instructor, showed an effect of RPT treatment at the time of the last examination of the semester. This finding is tempered by additional analyses into the effectiveness fo the RPT treatment. Student achievement relative to increasing levels of cognitive complexity of exam items showed mixed results. Furthermore, a comprehensive analysis of the student work within RPT treatment revelaed students having difficulties implementing the intervention.

Although most interesting problems are multivariate (MV) and students and citizens need to be able to reason using MV data, appropriate challenges are rarely encountered in class. In this paper we argue that the curriculum (and ideas about statistical literacy) should encompass reasoning with MV data. Statistics education can occur in a range of disciplines and in informal setting - notably on the web. Strategically, there is a need for dialogue with educators in other disciplines. We also argue for greater collaboration with data providers, who are engaging increasingly in 'People Net' (PN) activities-in short, a reconceptualisation of the education community. The SMART Centre has developed generic software shells that facilitate the import of MV data into interactive displays. We also describe their successful use in Citizenship classrooms where students interpret large-scale survey data on topics such as sexually transmitted infections and drug use.

In this chapter, we use preparation for future learning assessments to work backwards to identify the types of prior knowledge that prepare students to learn. We highlight how to develop a specific form of prior knowledge that many current models of learning and instruction do not address very well.

Constructivist theory has been prominent in recent research on mathematics learning and has provided a basis for recent mathematics education reform efforts. Although constructivism has the potential to inform changes in mathematics teaching, it offers no particular vision of how mathematics should be taught; models of teaching based on constructivism are needed. Data are presented from a whole-class, constructivist teaching experiement in which problems of teaching practice require the teacher/researcher to explore the pedagogical implications of his theoretical (constructivist) perspectives. The analysis of the data led to the development of a model of teacher decision making with respect to mathematical tasks. Central to this model is the creative tension between the teacher's goals with regard to student learning and his responsibility to be sensitive and responsive to the mathematical thinking of the students.