An investigation of statistical thinking in two different contexts: Detecting a signal in a noisy process and determining a typical value

The study describes students’ patterns of thinking for statistical problems set in two different contexts. Fifteen students representing a wide range of experiences with high school mathematics participated in problem-solving clinical interview sessions. At one point during the interviews, each solved a problem that involved determining the typical value within a set of incomes. At another point, they solved a problem set in a signal-versus-noise context [Konold, C., & Pollatsek, A. (2002). Data analysis as the search for signals in noisy processes. Journal for Research in Mathematics Education, 33, 259-289]. Several patterns of thinking emerged in the responses to each task. In responding to the two tasks, some students attempted to incorporate formal measures, while others used informal estimating strategies. The different types of thinking employed in using formal measures and informal estimates are described. The types of thinking exhibited in the signal-versus-noise context are then compared against those in the typical value context. Students displayed varying amounts of attention to both data and context in formulating responses to both problems. Suggestions for teachers in regard to helping students attend to both data and context when analyzing statistical data are given.     

Computational Estimation Performance on Whole‐Number Multiplication by Third‐ and Fifth‐Grade Chinese Students

Four hundred and three 3rd‐ and 5th‐grade Chinese students took the Multiplication Estimation Test or participated in the interview on it, designed to assess their computational estimation performance on whole‐number multiplication. Students perform better when tasks are presented visually than orally. Third graders tend to use rounding based while fifth graders tend to use written algorithm based strategies, but boys' and girls ‘performances do not differ. It is concluded that students often will not estimate simply at the request to estimate if an exact answer is within their mental computation capability, and a two‐step process is suggested for helping students decide what route to take when given arithmetic problems.     

Iranian students’ measurement estimation performance involving linear and area attributes of real-world objects

This article reports on an exploratory investigation of the measurement estimation performance of ten Iranian high school students on a set of real-world length and area measurement tasks. The results of a qualitative analysis of the data indicate that the students employed a variety of either mental or physically present Individual Frames of Reference as the non-tool units of measure in various estimation tasks. The analysis also found that a range of types of frames of reference was used across students in response to particular tasks and to the physical environments in which the tasks were situated. These results suggest that there is a complex interaction among a student’s individual preference for a particular type of Individual Frame of Reference, the nature of the estimation activity, and the physical context in which the activity takes place. These findings, which contribute to an understanding of the nature of the measurement unit that is employed during an estimation process, provide a different perspective from other studies that focus on categorizing estimation strategies, or processes.     

Relationships between students’ learning and their participation during enactment of middle school algebra tasks

This study examines a sequence of four middle school algebra tasks through their enactment in three teachers’ classrooms. The analysis centers on the cognitive demand—the kinds of thinking processes entailed in solving the task—and the participatory demand—the kinds of verbal contributions expected of students—of the task as written in the instructional materials, as set up by the three teachers, and as discussed by the teachers and their students. Relationships between the nature of the task enactments and students’ performance on a pre- and post-test are explored. Findings include the fact that the enacted tasks differed from the written tasks with regard to both the cognitive demand and the participatory demand, which related to students’ lack of success on the post-test. Specifically, cognitive demand declined in the enacted curriculum at different points for different classes, and the participatory demand during enactment tended to involve isolated mathematical terms rather than students verbally expressing mathematical relations.     

Examining and developing fourth grade children’s area estimation performance

This study explored children’s area estimation performance. Two groups of fourth grade children completed area estimation tasks with rectangles ranging from 5 to 200 square units. A randomly assigned treatment group completed instructional sessions that involved a conceptual area measurement strategy along with numerical feedback. Children tended to underestimate areas of rectangles. Furthermore, rectangle size was related to performance such that estimation error and variability increased as rectangle size increased. The treatment group exhibited significantly improved area estimation performance in terms of accuracy, as well as reduced variability and instances of extreme responses. Area measurement estimation findings are related to a Hypothetical Learning Trajectory for area measurement.     

The Impact of Professional Noticing on Teachers' Adaptations of Challenging Tasks

This study investigates how teacher attention to student thinking informs adaptations of challenging tasks. Five teachers who had implemented challenging mathematics curriculum materials for three or more years were videotaped enacting instructional sequences and were subsequently interviewed about those enactments. The results indicate that the two teachers who attended closely to student thinking developed conjectures about how that thinking developed across instructional sequences and used those conjectures to inform their adaptations. These teachers connected their conjectures to the details of student strategies, leading to adaptations that enhanced task complexity and students' opportunity to engage with mathematical concepts. By contrast, the three teachers who evaluated students' thinking primarily as right or wrong regularly adapted tasks in ways that were poorly informed by their observations and that reduced the complexity of the tasks. The results suggest that forming communities of inquiry around the use of challenging curriculum materials is important for providing opportunities for students to learn with understanding.     

The Effect of Nature of Science Metacognitive Prompts on Science Students’ Content and Nature of Science Knowledge,Metacognition, and Self‐Regulatory Efficacy

The purpose of the present explanatory mixed‐method design is to examine the effectiveness of a developmental intervention, Embedded Metacognitive Prompts based on Nature of Science (EMPNOS) to teach the nature of science using metacognitive prompts embedded in an inquiry unit. Eighty‐three (N = 83) eighth‐grade students from four classrooms were randomly assigned to an experimental and a comparison group. All participants were asked to respond to a number of tests (content and nature of science knowledge) and surveys (metacognition and self‐regulatory efficacy). Participants were also interviewed. It was hypothesized that the experimental group would outperform the comparison group in all measures. Partial support for the hypotheses was found. Specifically, results showed significant gains in content knowledge and nature of science knowledge of the experimental group over the comparison group. Qualitative findings revealed that students in the comparison group reported scientific thinking in similar terms as the scientific method, while the experimental group reported that scientists were creative and had to explain events using evidence, which is more closely aligned to the aspects of the nature of science. EMPNOS may have implications as a useful classroom tool in guiding students to check their thinking for alignment to the nature of science.     

Sequence limits in calculus: using design research and building on intuition to support instruction

This article is based on research completed within an ongoing project to develop a calculus course which serves as the foundation for the mathematical education of undergraduate students who are training to become elementary teachers. Several research-based activities have been developed, tested, and refined. In this paper we discuss how the design research approach was used to create and implement an instructional task that introduces the concept of limit of a sequence using popular characters from a children’s television show. We present the intuition that students brought to the instructional sequence, the development of the tasks based on the instructional design theory of Realistic Mathematics Education, and the evolution of the intuition that students displayed after instruction. Results include the instructional task developed and student work which reveals that students use context, informal notions of limit, and the notion of “arbitrarily close” to write about their limit understandings.     

Rate of Change: AP Calculus Students' Understandings and Misconceptions After Completing Different Curricular Paths

This study examined Advanced Placement Calculus students' mathematical understanding of rate of change, after studying four years of college preparatory (integrated or single‐subject) mathematics. Students completed the Precalculus Concept Assessment (PCA) and two open‐ended tasks with questions about rates of change. After adjusting for prior achievement with the Iowa Algebra Aptitude Test, students from these two paths performed comparably (F = 3.54, p = .063) on the PCA. Student errors on the three instruments revealed a lack of understanding of the interpretation or meaning of rate of change regardless of the curricular path. Students successfully calculated the rate of change of linear functions; however, when the function was not linear, students struggled to calculate it, model it on a graph, or interpret it in a real‐world context.     

Book Reviews

The making of pictures and the use of mathematics are often considered as activities carried out by two different classes of people.

It may be true that the artist can get on without mathematics, but the converse is far less true.

The operation which an artist terms ‘drawing’, might be described by a mathematician as ‘the mapping of a three‐dimensional network into a two‐dimensional one’.

This article attempts to show how the mathematically minded student can use his mathematics to manipulate pictures. In doing so it introduces him to the tasks which a computer must perform in picture manipulation.

The article is in two parts:

Part A, discusses the use of three‐dimensional sketching and the role it plays in the preparation of ‘orthographic’ working drawings.

It describes how a designer transfers his thoughts about spacial objects to paper, thus assisting himself to refine them and enabling others to perceive them.

A case is made for encouraging perspective sketching in the teaching of engineering drawing.

Part B describes a technique for plotting perspective sketches by numerical methods, which may be useful in motivating numerically inclined students towards involvement with perspective sketching.     

Probing for reasons: Presentations, questions, phases

This paper reports on a research study based on data from experimental teaching. Undergraduate dance majors were invited, through real-world problem tasks that raised central conceptual issues, to invent major ideas of calculus. This study focuses on work and thinking by these students, as they sought to build key ideas, representations and compelling lines of reasoning. Speiser and Walter's psychological and logical perspectives (see Speiser, Walter, & Sullivan, 2007) provide opportunities to focus not just on the students’ thinking, but perhaps most especially, through detailed examination of important choices, on their exercise of agency as learners. Close analysis of student data through these lenses triggered the development of two new analytic categories—logic of agency and logic of proof. The analysis presented here treats students as active shapers of their own experience and understanding, whose choices open opportunities for continued growth and learning, not just for themselves but also for each other.     

The Authority of the Calculator in the Minds of College Students

A group of 25 undergraduate students was given seven estimation tasks that involved computation of whole or decimal numbers. The subjects (10 elementary education majors, 7 mathematics majors, and 8 undecided or premajors) were selected because of high achievement in their current college mathematics class. They were asked to estimate an answer to a computational task and then use a calculator provided by the researchers to determine the exact answer. The calculator had been programmed to give incorrect answers that were increasingly higher than the actual answer (beginning with a 10% error and ending with a 50% error). While the majority of subjects produced reasonable estimates, only 7 of the 25 students questioned the accuracy of the answers produced on the calculator. The study points out the subjects’ lack of confidence in estimation skills, as well as a reluctance to question calculator produced results.     

Exploring US textbooks’ treatment of the estimation of linear measurements

Learning to estimate a linear measurement is critical in becoming a successful measurer. Research indicates that the teaching of the estimation of linear measurement is quite open and that instruction does not make explicit to students how to carry out estimation work. Because written curriculum has been identified as one of the main sources affecting teachers’ instruction and students’ learning, this study examined how estimation of linear measurement tasks were presented to students in three US elementary mathematics curricula to see how much and in what ways these tasks were presented in an open manner. The principal result was that the length estimation tasks were frequently not explicit about which attribute of the object to measure and the requested level of precision of the estimate. Length estimation tasks were also left more open than other measurement tasks like measuring length with rulers.     

Drawing inferences from learners’ examples and questions to inform task design and develop learners’ spatial knowledge

Examples that learners generate, and questions they ask while generating examples, are both sources for inferring about learners’ thinking. We investigated how inferences derived from each of these sources relate, and how these inferences can inform task design aimed at advancing students’ knowledge of scale factor enlargement (i.e. scaling). The study involved students in two secondary schools in England who were individually tasked to generate examples of scale factor enlargements in relation to specifically designed prompts. Students were encouraged to raise questions while generating their examples. We drew inferences about students’ thinking from their examples and, where available, from their questions. These inferences informed our design and implementation of a set of follow-up tasks for all students, and an additional personalised task for each student who raised any questions. Students showed increased knowledge of, and confidence with, scale factor enlargement independently of whether they asked questions during the exemplification task.     

Incremental net effects in multiple regression

A regular problem in regression analysis is estimating the comparative importance of the predictors in the model. This work considers the ‘net effects’, or shares of the predictors in the coefficient of the multiple determination, which is a widely used characteristic of the quality of a regression model. Estimation of ;the net effects can be a difficult task because multicollinearity among the regressors can produce negative inputs to multiple determination. This paper suggests estimating the incremental net effects as subsequent marginal inputs to the coefficient of multiple determination, and it is shown that the results coincide with estimation by cooperative game theory. This approach guarantees positive and interpretable net effects, which offers a better interpretation of the regression results.     

How Much Do Mathematics Skills Improve With Age? Evidence From LTT NAEP

The Long‐Term Trend (LTT) mathematics assessment of the National Assessment of Educational Progress (NAEP) used the same set of items from 1982 through 2004, including 20 items that were administered to 9‐ and 13‐year‐olds, 29 items that were administered to 13‐ and 17‐year‐olds, and 4 items that were administered at all three ages. This study used these items to identify areas of mathematics that had substantial gain from one age level to the next and to identify patterns of gain by age and how those patterns changed over time. Findings included the facts that older students usually did better on items than younger students, although item context and wording was often as important as mathematical knowledge in explaining differences in performance by age. LTT NAEP included a unique set of estimation items and analysis of performance on those items showed that students at all levels could identify an appropriate estimate only when numbers were small and the context for the estimate was familiar. The LTT data also indicated that addition and subtraction skills of 9‐year‐olds increased and the estimation skills of 13‐ and 17‐year olds improved in some contexts from 1982 through 2004.     

Toward a model for students’ combinatorial thinking

Combinatorics has many applications in different disciplines, however, only a few studies have explored students’ combinatorial thinking at the upper secondary and tertiary levels concurrently. The present research is a grounded theory study of eight Year 12 and five undergraduate students, who have participated in semi-structured interviews and responded to eight combinatorial tasks. Three types of combinatorial tasks were designed: combinatorial reasoning, evaluating, and problem-posing tasks. In the open coding phase of data analysis, seventy-one codes were identified which categorized into seven main categories at the axial coding phase. At the selective coding phase, five relationships between categories were identified that led to designing a model of students’ combinatorial thinking. The model consists of three movements: Horizontal, vertical downward, and vertical upward movement. It is asserted that this model could be used to improve the quality of teaching combinatorics, and also as a lens to explore students’ combinatorial thinking.     

Game show mathematics: Specializing,conjecturing, generalizing,and convincing

This article describes the authors’ use of three game shows – Survivor, The Biggest Loser, and Deal or No Deal? – to determine to what degree students engaged in mathematical thinking: specializing, conjecturing, generalizing, and convincing ( Burton, 1984). Student responses to the task of creating winning strategies to these shows were collected and analyzed. The data showed that students generally did not engage in the process of mathematical thinking unless directed to do so and the effects this had on the students’ responses is discussed.     

Variational Approximations for Generalized Linear Latent Variable Models

Generalized linear latent variable models (GLLVMs) are a powerful class of models for understanding the relationships among multiple, correlated responses. Estimation, however, presents a major challenge, as the marginal likelihood does not possess a closed form for nonnormal responses. We propose a variational approximation (VA) method for estimating GLLVMs. For the common cases of binary, ordinal, and overdispersed count data, we derive fully closed-form approximations to the marginal log-likelihood function in each case. Compared to other methods such as the expectation-maximization algorithm, estimation using VA is fast and straightforward to implement. Predictions of the latent variables and associated uncertainty estimates are also obtained as part of the estimation process. Simulations show that VA estimation performs similar to or better than some currently available methods, both at predicting the latent variables and estimating their corresponding coefficients. They also show that VA estimation offers dramatic reductions in computation time particularly if the number of correlated responses is large relative to the number of observational units. We apply the variational approach to two datasets, estimating GLLVMs to understanding the patterns of variation in youth gratitude and for constructing ordination plots in bird abundance data. R code for performing VA estimation of GLLVMs is available online. Supplementary materials for this article are available online.