The author talks about her own experience taking A-level Pure Mathematics and Statistics (Oxford board) and how the content and emphasis of the course has changed over the years.
The author talks about her own experience taking A-level Pure Mathematics and Statistics (Oxford board) and how the content and emphasis of the course has changed over the years.
In this paper we present the results from a theoretical and experimental study concerning university students' conceptions (Artigue, 1990) about the logic of statistical testing.
We asked active psychological researchers to answer a survey regarding the following data-analytic issues: (a) the effect of reliability on Type I and Type II errors, (b) the interpretation of interaction, (c) contrast analysis, and (d) the role of power and effect size in successful replications. Our 551 participants (a 60% response rate) answered 59% of the questions correctly; 46% accuracy would be expected according to participants' response preferences alone. Accuracy was higher for respondents with higher academic ranks and for questions with "no" as the right answer. It is suggested that although experienced researchers are able to answer difficult but basic data-analytic questions at better than chance levels, there is also a high degree of misunderstanding of some fundamental issues of data analysis.
Analogical transfer is transfer of a basic structure acquired through one or more instances to another instance. A basic structure like this is sometimes called a paradigm. Paradigmatic teaching, i.e. teaching for analogical transfer, requires the teaching of a basic structure by appropriate exemplars as well as the teaching of its application in various fields and contexts. This is demonstrated using research on teaching for problem-solving, inductive thinking, and learning-to-learn.
Four experiments tested how well students in a college algebra class could use the solution of a distance, mixture, or work problem to solve other problems in the same category. The solution could either be applied directly to solve equivalent problems or had to be slightly modified to solve similar problems. Students in Experiment 1 could not use the solution to produce more correct solutions on either equivalent or similar problems. Experiments 2 and 3 demonstrated that either allowing students to consult the solution as they worked on the test problems or providing more elaborate solutions improved transfer to equivalent problems but did not improve transfer to similar problems. In Experiment 4 there was some transfer to similar problems that differed in complexity, but students relied too much on a syntactic approach in which they filled in the "slots" of an equation.
This paper examines the need for continuous quality improvement in higher education; the role of academic statisticians in changes in higher education; some of the strategies and techniques colleges and universities are employing related to TQM at college and departmental levels; what individual instructors can do in terms of making improvements in higher education; and the role and importance of a personal quality vision in such an overall effort for organizational change. In addition, it is the authors' intent that the paper be a source for ideas about improving teaching and ways to think about issues related to TQM on campus.
Continuous Quality Improvement (CQI) better known in industry as Total Quality Management (TQM), is a management philosophy which has transformed many businesses and corporations internally and is now beginning to make strong inroads into universities, predominantly on the administrative side. This paper raises the question of whether the conceptual framework provided by CQI/TQM is a fertile one for addressing the problems involved in university teaching. It translates basic tenets of CQI/TQM into the univeristy teaching context and outlines how these ideas have been implemented in a large, multisection, introductory statistics course. Particular attention is given to the problems of fostering steady year-to-year improvements in a course that can survive changes of personnel, and in making improvements by stimulating group creativity and then capturing the results for the future.
In this article, I attempt to explicate the ethical prinicples of data analysis, to suggest some characteristics of research and researchers that give rise to ethical difficulties, and to provide recommendations for improved practice.
An analysis of the process of analogical thinking predicts that analogies will be noticed on the basis of semantic retrieval cues and that the induction of a general schema from concrete analogs will facilitate analogical transfer. These predictions were tested in experiments in which subjects first read one or more stories illustrating problems and their solutions and then attempted to solve a disparate but analagous transfer problem. The studies in Part I attempted to foster the abstraction of a problem schema from a single story analog by means of summarization instructions, a verbal statement of the underlying principle, or a diagrammatic representation of it. None of these devices achieved a notable degree of success. In contrast, the experiments in Part II demonstrated that if two prior analogs were given, subjects often derived a problem schema as an incidental product of describing the similarities of the analogs. The quality of the induced schema was highly predictive of subsequent transfer performance. Furthermore, the verbal statements and diagrams that had failed to facilitate transfer from one analog proved highly beneficial when paired with two. The function of examples in learning was discussed in light of the present study.
Judging statistical claims in social contexts is fundamental to statistical literacy. This article uses a particularly contentious newspaper report that makes a cause-and-effect claim as the basis for discussing this important aspect of statistical understanding. The issue's relevance across the school curriculum is shown by extracts from curriculum documents. Teachers need to structure experiences to build ability to question claims made without proper justification. This article suggests a hierarchy to help teachers plan for and assess student learning in this area, and it closes with a plea for teachers to cooperate across subjects to achieve results.