The major objective of this study was to determine the relationship between academic performance in a statistics course and the students' attitude toward statistics, math self-concept, and attitudes toward tests. A secondary objective was to determine what relationships exist between students' attitudes toward statistics, math self-concept, and attitudes toward tests. A third objective was to investigate the relationship between students' mathematics background and attitude toward statistics, math self-concept, and attitude toward tests.
This report describes four kinds of understanding that students rely on in statistics--logical/deductive, computational/algorithmic, graphical/dynamic, and verbal/interpretive. These kinds of understanding will be illustrated, as will four unifying themes (production, exploration, repetition, and inference) that instructors can use to give students a better sense of the subject of statistics as a structured whole. Structured concept maps will also be illustrated, as will four topics (transforming, adjusting, blocking, and crossing/interaction) that are often missing in introductory statistics courses.
This study is aimed at the investigation of the non-cognitive factors related to students' beliefs and attitude before and after taking an introductory statistics course using an interview methodology. Of particular interest is to compare students' beliefs and attitude between students from a technology-rich class and from a traditional class. The purposes are (a) to investigate if students' attitude has changed after taking a technology-rich statistics class and their experience about technology, and (b) to compare if there is a dramatic difference between the technology-rich class and a traditional class before and after taking the course.
This paper presents five principles of learning, derived from cognitive theory and supported by empirical results in cognitive psychology. To bridge the gap between theory and practice, each of these principles is transformed into a practical guideline and exemplified in a real teaching context. It is argued that this approach of putting cognitive theory into practice can offer several benefits to statistics education: a means for explaining and understanding why reform efforts work, a set of guidelines that can help instructors make well-informed design decisions when implementing these reforms, and a framework for generating new and effective instructional innovations.
This paper compares the learning experiences of students from a technology based introductory statistics course with that of a group of students with non-technology based instruction.
This brief guide provides some practical guidelines for the assessment of students' statistical knowledge and reasoning about data. It is intended for teachers who are just beginning to teach statistics (usually as part of the mathematics curriculum) and who have relatively little experience in this area.
One objective of this chapter is to introduce a diagnostic approach to assess how well students answer questions about a research report. A second objective is to show how the proposed assessment tools can be used to identify teaching strategies for overcoming students' errors in interpreting reports. A third objective is to suggest how the interpretation-of-research assessment questions can be used to help students identify what information needed for interpretation is missing in journal or media reports.
In the experimental study reported here we intended to examine possible differences in secondary students' conceptions about randomness before and after instruction in probability, which occurs for the Spanish students between the ages of 14 and 17. To achieve this aim, we gave 277 secondary students a written questionnaire with some items taken from Green (1989, 1991). with our results we extend Green's previous research to 17-year-old students and complement his results with the analysis of students' arguments to support randomness in bidimensional distributions. Our results also indicate that students' subjective understanding of randomness is close to some interpretations of randomness throughout history.
This article discusses the method of resampling and how it can be of benefit to teachers and to the teaching process. Currently, the method has been little taught in conventional texts and classes.