Autobiographical Accounts of Students' Experiences Learning Mathematics: A Review

ABSTRACT

In this article, we review published literature that draws on autobiographical accounts of students' experiences learning mathematics. We summarize the main findings of the target literature and present recommendations for further research that will extend this field. Our review indicates that autobiographical and narrative methodological approaches have the potential to occasion important advances in our knowledge of students' experiences learning mathematics. However, relative to accounts of preservice teacher learning, there is a paucity of published research that documents the mathematics learning experiences of kindergarten to Grade 12 students.     

An assessment of student preferences for PowerPoint presentation structure in undergraduate courses

Studies have demonstrated that students prefer PowerPoint and respond favorably to classes when it is used. Few studies have addressed the physical structure of PowerPoint. In this study, students enrolled in several psychology classes on two campuses completed a 36 item questionnaire regarding their preferences for the use of PowerPoint in the classroom. Students preferred the use of key phrase outlines, pictures and graphs, slides to be built line by line, sounds from popular media or that support the pictures or graphics on the slide, color backgrounds, and to have the lights dimmed. It is recommended that professors pay attention to the physical aspects of PowerPoint slides and handouts to further enhance students’ educational experience.     

Rigor, rigor mortis, and conspiratorial views of depression research.

The authors reassert the need for methodological changes in depression research appearing in the Journal of Personality and Social Psychology and other personality and social psychology journals. In this rejoinder the authors update their earlier literature review (H. Tennen, J. Hall, & G. Affleck; see record 1995-31710-001) and respond to the commentaries by P C. Kendall and E. C. Flannery-Schroeder (see record 1995-31700-001) and G. Weary, J. A. Edwards, and J. A. Jacobson (see record 1995-31713-001). The authors notice that G. Weary et al.'s own findings demonstrate the need to change how depression is measured and participants are assigned to experimental groups. The authors also challenge G. Weary et al.'s contention that structured interviews are limited because they require interviewer judgments, and they urge personality and social psychologists to learn more about these interviews. Finally, G. Weary et al.'s suspicion that depression research guidelines reflect professional parochialism is disputed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Partial permutation decoding for MacDonald codes

We show how to find s-PD-sets of the minimal size \(s+1\) for the \(\left[ \frac{q^n-q^u}{q-1},n,q^{n-1}-q^{u-1}\right] _q \) MacDonald q-ary codes \(C_{n,u}(q)\) where \(n \ge 3\) and \(1 \le u \le n-1\). The construction of [6] can be used and gives s-PD-sets for s up to the bound \(\lfloor \frac{q^{n-u}-1}{(n-u)(q-1)} \rfloor -1\), of effective use for u small; for \(u \ge \lfloor \frac{n}{2} \rfloor \) an alternative construction is given that applies up to a bound that depends on the maximum size of a set of vectors in \(V_u(\mathbb {F}_q)\) with each pair of vectors distance at least 3 apart.     

Report from the Wellcome Trust/EBA “Perspectives in Clinical Proteomics” retreat--a strategy to implement next-generation proteomic analyses to the clinic for patient benefit: pathway to translation

Proteomics has long been thought to hold the promise of producing results of clinical utility which will influence patient treatment and outcomes. A recent Wellcome Trust/EBI meeting and retreat--“Perspectives in Clinical Proteomics”--brought together experts from a broad range of stakeholder groups with an interest in ensuring proteomics achieves this aim. This viewpoint presents views derived from these forums, proposing a pathway for the development of next-generation proteomic analyses in the clinical setting from selection of candidates through to their validation and ultimate demonstration of utility through health technology assessments. Although not meant to be all encompassing, important elements for proteomics researchers to consider are presented.     

A graph-based approach for assessing storm-induced coastal changes

Hurricanes and tropical storms are severe threats to coastal properties, settlements, and infrastructure. Airborne light detection and ranging (lidar) surveys conducted before and after storm events allow detailed analysis of coastal geomorphologic and sediment volumetric changes and have been proved very useful in the study of coastal changes. Traditionally, most studies use the pixel-based differencing method to quantify the spatial extent and magnitude of coastal changes based on sequential lidar surveys. This research presents a graph theory-based approach and associated software tools for representing and quantifying storm-induced damages to buildings, beaches and sand dunes, coastal vegetation canopy, and infrastructure. Generation of elevation difference grids, construction of local contour trees, and derivation of semantic properties are key components of the new algorithm for change object detection and extraction. An ontology and taxonomy are proposed to classify change objects into different types of coastal damages in terms of their semantic properties. This method has been successfully applied to assess damages of Hurricane Ike to the Bolivar Peninsula on the Texas Gulf Coast based on pre- and post-storm airborne lidar data and colour infrared aerial photographs.     

New statistical methods for investigating submarine pockmarks

We investigate the applicability of some novel spatial analysis techniques, developed for studies of astrophysical datasets, to the analysis of spatial point data in sedimentary basins. The techniques are evaluated and compared with standard methods using two test areas that contain large numbers of submarine pockmarks developed in distributed arrays. The familiar Ripley K and Voronoi tesselation techniques are used, and the results are then compared with those obtained using more novel techniques, the correlation length and minimal spanning tree. The correlation length technique is found to identify the precise distances at which clustering occurs more accurately, making a physical interpretation more clear than is possible using the Ripley K. The minimal spanning tree is found to be powerful at identifying the space-filling nature of the pockmark distribution, and has the advantage of being immune to edge effects. The use of these two novel techniques permits more information to be extracted from the datasets, and demonstrates clear statistically significant differences between them, which are not detectable using standard techniques.     

Bayesian analysis of robust Poisson geometric process model using heavy-tailed distributions

We propose a robust Poisson geometric process model with heavy-tailed distributions to cope with the problem of outliers as it may lead to an overestimation of mean and variance resulting in inaccurate interpretations of the situations. Two heavy-tailed distributions namely Student’s t and exponential power distributions with different tailednesses and kurtoses are used and they are represented in scale mixture of normal and scale mixture of uniform respectively. The proposed model is capable of describing the trend and meanwhile the mixing parameters in the scale mixture representations can detect the outlying observations. Simulations and real data analysis are performed to investigate the properties of the models.     

Cerebral: visualizing multiple experimental conditions on a graph with biological context

Systems biologists use interaction graphs to model the behavior of biological systems at the molecular level. In an iterative process, such biologists obser ve the reactions of living cells under various experimental conditions, view the results in the context of the interaction graph, and then propose changes to the graph model. These graphs ser ve as a form of dynamic knowledge representation of the biological system being studied and evolve as new insight is gained from the experimental data. While numerous graph layout and drawing packages are available, these tools did not fully meet the needs of our immunologist collaborators. In this paper, we describe the data information display needs of these immunologists and translate them into design decisions. These decisions led us to create Cerebral, a system that uses a biologically guided graph layout and incor porates experimental data directly into the graph display. Small multiple views of different experimental conditions and a data-driven parallel coordinates view enable correlations between experimental conditions to be analyzed at the same time that the data is viewed in the graph context. This combination of coordinated views allows the biologist to view the data from many different perspectives simultaneously. To illustrate the typical analysis tasks performed, we analyze two datasets using Cerebral. Based on feedback from our collaboratorsweconcludethat Cerebral is a valuable tool for analyzing experimental data in the context of an interaction graph model.