Call for papers
The Mathematical Thinking and Learning (MTL) special issue on The Role of Context in Developing Students' Reasoning about Informal Statistical Inference will be published in January of 2011.
Mathematical Thinking and Learning, a fully refereed journal, is directed at researchers interested in mathematics education from the perspective of psychology, sociology, philosophy, anthropology, mathematics and information technology, with a particular focus on mathematical thinking, reasoning and learning.
We are very excited about this fortunate opportunity to reach out to the wider community, particularly the mathematics education community, bridging between our on-going decade-long work and similar efforts in other fields. We plan to include in the special issue 5-8 full scale empirical or theoretical papers, several short research reports, introduction paper by the guest editors, as well as discussion section (2-3 respondents). We have received a permission to publish a double issue, dependant on the number of accepted papers according to the MTL high standards.
This special issue is aimed at presenting the state of the art of our understating of Informal Inferential Reasoning (IIR) and Context and innovative ways to address them in different age levels. We hope that the special issue will help readers to consider statistics seriously as part of their work in mathematics education. We have to keep in mind that in writing to a more general audience some elaboration will be needed from us to acquaint readers with background materials, literature, statistical concepts and terminology in statistics education. We will encourage the group of authors to read each other’s paper and try to connect between the papers. We are confident that you will all join us in this exciting and challenging effort to bring out our word in the best way possible.
In the following we shall briefly outline the theme of the MTL special issue and provide some familiar background. We then present the timeline. Please note that it is a rather tight schedule and we hope that you will make all efforts to meet the various deadlines that are necessary facilitate the quality of the papers and the coherence of the whole special issue. We then present the MTL authors’ instructions, describe the review process and general information about MTL scope and purposes.
We hope that you will find this information useful and you will join in making this special issue an attractive and engaging publication. Please do not hesitate to send us your comments and questions.
Katie and Dani, The MTL special Issue guest co-editors
Statistics education research is emerging as important area of inquiry with multiple implications in school and tertiary curriculum design, instructional activities, technological tools that aid teaching and learning statistics, and teachers’ professional development. Over the past decade there has been an increasingly strong call for statistics education to focus more on statistical literacy, reasoning, and thinking. One of the main arguments presented is that traditional approaches to teaching statistics focus mainly on skills, procedures, and computations, which do not lead students to reason or think statistically. The International Collaboration for Research on Statistical Reasoning, Thinking, and Literacy (SRTL) focus is on current research studies that examine the nature and development of statistical literacy, reasoning, and thinking.
The International Collaboration for Research on Statistical Reasoning, Thinking, and Literacy (SRTL)
The International Collaboration for Research on Statistical Reasoning, Thinking, and Literacy (SRTL) organizes a series of research forums. The First Forum (SRTL-1) was held in Israel in July of 1999. It has been followed by Forums in 2001 (SRTL-2, Australia), 2003 (SRTL-3, USA), 2005 (SRTL-4, New Zealand), and 2007 (SRTL-5, UK), 2009 (SRTL-6, Australia). The Forums are co-chaired by Joan Garfield (University of Minnesota, USA) and Dani Ben-Zvi (University of Haifa, Israel), with the help of local coordinators: Chris Reading, John Pegg, Bill Mickelson, Ruth Heaton, Maxine Pfannkuch, Chris Wild, Janet Ainley, Dave Pratt, Katie Makar and Michael Bulmer. Based on strong support from the participants and the statistics education community SRTL is becoming a biannual scientific event, an alternative to large conferences. The gatherings are stimulating and enriching allowing participants become acquainted with key researchers in this area and to view their work in progress. The Forums’ small size allows plenty of time for interaction and discussion. The forums have a clear focus for each meeting, developed from previous activities, with emphasis on qualitative analysis of classroom videos or interviews.
The Role of Context in Developing Students' Informal Inferential Reasoning
Recent research suggests an important role for developing ideas of informal types of statistical inference even at early educational levels. Researchers have developed instructional activities that encourage students to infer beyond samples of data and use technological tools to support these informal inferences. The findings of these studies reveal that the context of the data may be an important factor to study further. The role of context is of particular interest because in drawing (informal) inferences from data, students must learn to walk two fine lines. First, they must maintain a view of data as “numbers with a context” (Moore, 1992). At the same time, they must learn to see the data as separate in many ways from the real-world event they observed (abstraction) (Konold & Higgins, 2003). In learning how to make data-based claims (argumentation), students must consider the evidence used to support the claim, the quality and justification of the evidence, limitations of the evidence and finally, an indication of how convincing the argument is (Ben-Zvi, Gil, & Apel, 2007).
We characterize Informal Inferential Reasoning (IIR) as the cognitive activities involved in drawing conclusions with some degree of uncertainty that go beyond the data and having empirical evidence for them (Ben-Zvi, Gil, & Apel, 2007). Three principles appear to be essential to informal inference (Makar & Rubin, 2009): (1) generalizations (including predictions, parameter estimates, and conclusions) that go beyond describing the given data; (2) the use of data as evidence for those generalizations; and (3) conclusions that express a degree of uncertainty, whether or not quantified, accounting for the variability or uncertainty that is unavoidable when generalizing beyond the immediate data to a population or a process.
The special issue will include research papers that address questions such as the following:
- What is the role of different types of context in arguments students make for even the simplest forms of statistical inference?
- How do different contexts help or hinder the development of students’ reasoning about IIR?
- How do students rely on, explain and use context in making arguments as part of IIR?
- What are useful tasks or sequences of instructional activities to use to reveal the use of context in informal inferential reasoning, and to help learners develop a conceptual understanding of the role of context in IIR?
- How does students’ reasoning about the roles of context develop while informally drawing conclusions from data?
- What roles do technological tools have in scaffolding the understanding of context in learning to reason about statistical inference?