Literature Index

Mnemonics (memory aids) are often viewed as useful in helping students recall information, and thereby possibly reducing stress and freeing up more cognitive resources for higher-order thinking. However, there has been little research on statistics mnemonics, especially for large classes. This article reports on the results of a study conducted during two consecutive fall semesters at a large U.S. university. In 2014, a large sample (n = 1487) of college students were asked about the usefulness of a set of 19 published statistics mnemonics presented in class, and in 2015, the students (n = 1468) were presented 12 mnemonics related to inference and then asked whether or not they used mnemonics on that exam. This article discusses how students assess the usefulness of mnemonics and evaluates the relationship between using mnemonics and reducing anxiety. Additionally, the relationship between mnemonic usage and learning outcomes achievement will be discussed, along with this study's limitations and implications for teaching.  

This study developed a graphicacy assessment instrument which can (a) assess and measure pupils' progress in graphical understanding for the National Curriculum, (b) identify significant errors and misconceptions in graphing held by Year 10 Mathematics pupils and so (c) help raise teachers' awareness of their pupils' mathematical thinking.<br>A carefully constructed set of graphical problems related to the research literature and located in the National Curriculum was administered to a pilot group of pupils. The problems were deliberately posed in such a way as to encourage relevant isconceptions to come to the surface. The test was 'scaled' using Rasch methodology and a graphicacy measure results, with the main misconceptions plotted with the items on the same scale. The pupils producing the most common errors in the test were selected to take part in some group interviews to get an insight into their way of thinking and to collect evidence for discussion with teachers. Data from teachers' interviews and questionnaires were also collected to ascertain the curriculum validity of the ssessment and to probe their knowledge of their pupils' understanding.

In this report, the method of free recall is put forward as a tool to evaluate a prototypical statistical learning environment. A number of students from the faculty of Health Sciences, Maastricht University, the Netherlands, were required to write down whatever they could remember of a statistics course in which they had participated. By means of examining the free recall protocols of the participants, insight can be obtained into the mental representations they had formed with respect to three statistical concepts. Quantitative as well as qualitative analyses of the free recall protocols showed that the effect of the constructive learning environment was not in line with the expectations. Despite small-group discussions on the statistical concepts, students appeared to have disappointingly low levels of conceptual understanding.

PhD students and others from all kinds of disciplines have the need for statistical learning and<br>understanding in common. For that reason, research courses in research method and biostatistics are<br>open for all kinds of participants, which mean that a large variety of applied topics are represented in<br>each course. The participants are commonly involved in the research process on different stages, some<br>of them having only a research topic, others have collected all data. Furthermore there is also a<br>variation in opinion about statistics, not regarding the need for statistics but the concerns about the<br>demand for mathematical skills etc. The heterogeneity of the participants' research fields and<br>experience in research is a real challenge in teaching but also in assessment of learning. However, a<br>common issue is that all participants are highly motivated as they need knowledge and understanding<br>in statistical thinking and literacy. The aim of this paper is to present the experiences of an<br>examination approach in which the participants get the opportunity to formulating their own<br>examination tasks based on own research problems and to solve them. This approach not only<br>improved the participants' learning and understanding, but good statistical practice was also<br>implemented the research group as a whole.