
| Pengarang | : | Jennifer Ruef |
| Nama Majalah/Jurnal | : | Journal for Research in Mathematics Education |
| Volume / Edisi | : | 52 (No. 2) |
| Halaman | : | 152-188 |
| Abstrak | : | What does it mean to be “good-at-math,” and how is it determined? Cobb et al. (2009) defined the normative identity of mathematics classrooms as the obligations that students must meet to be considered good-at-math. Obligations are negotiated between teachers and students through series of bids. Normative identities reveal distributions of agency and authority within classrooms, which affect learning opportunities for students. Traditionally, mathematics teachers held the predominance of agency and authority in classrooms. Research supports shifting toward more equitable teaching and learning (e.g., National Council of Teachers of Mathematics, 2018). Clear examples of enacting and supporting changes are helpful. This article shares how sixth-grade students and their teacher co-constructed good-at-math to invite and obligate students to become active agents in mathematical argumentation. |
| Pengarang | : | Luis A. Leyva |
| Nama Majalah/Jurnal | : | Journal for Research in Mathematics Education |
| Volume / Edisi | : | 52 (No. 2) |
| Halaman | : | 117-151 |
| Abstrak | : | This article proposes and employs a framework that characterizes mathematics education as a white, patriarchal space to analyze undergraduate Black women’s narratives of experience in navigating P–16 mathematics education. The framework guided a counter-storytelling analysis that captured variation in Black women’s experiences of within-group tensions—a function of internalized racial-gendered ideologies and normalized structural inequities in mathematics education. Findings revealed variation in Black women’s resilience through coping strategies for managing such within-group tensions. This analysis advances equity-oriented efforts beyond increasing Black women’s representation and retention by challenging the racialized-gendered culture of mathematics. Implications for educational practice and research include ways to disrupt P–16 mathematics education as a white, patriarchal space and broaden within-group solidarity, including Sisterhood among Black women. |
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Analisis Kebudayaan |
| Volume / Edisi | : | III-3, - (No. 3) |
| Halaman | : | 87-93 |
| Abstrak | : | - |
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Analisis Kebudayaan |
| Volume / Edisi | : | III-3, - (No. 3) |
| Halaman | : | 80-86 |
| Abstrak | : | - |
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | The American Statistician |
| Volume / Edisi | : | 72 (No. 2) |
| Halaman | : | 199-205 |
| Abstrak | : | The score statistic continues to be a fundamental tool for statistical inference. In the analysis of data from high-throughput genomic assays, inference on the basis of the score usually enjoys greater stability, considerably higher computational efficiency, and lends itself more readily to the use of resampling methods than the asymptotically equivalent Wald or likelihood ratio tests. The score function often depends on a set of unknown nuisance parameters which have to be replaced by estimators, but can be improved by calculating the efficient score, which accounts for the variability induced by estimating these parameters. Manual derivation of the efficient score is tedious and error-prone, so we illustrate using computer algebra to facilitate this derivation. We demonstrate this process within the context of a standard example from genetic association analyses, though the techniques shown here could be applied to any derivation, and have a place in the toolbox of any modern statistician. We further show how the resulting symbolic expressions can be readily ported to compiled languages, to develop fast numerical algorithms for high-throughput genomic analysis. We conclude by considering extensions of this approach. The code featured in this report is available online as part of the supplementary material. |
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Analisis Kebudayaan |
| Volume / Edisi | : | III-3, - (No. 3) |
| Halaman | : | 72-79 |
| Abstrak | : | - |
| Pengarang | : | Kathryn Schaefer Ziemer |
| Nama Majalah/Jurnal | : | The American Statistician |
| Volume / Edisi | : | 72 (No. 2) |
| Halaman | : | 191-198 |
| Abstrak | : | The combination of log-linear models and correspondence analysis have long been used to decompose contingency tables and aid in their interpretation. Until now, this approach has not been applied to the education Statewide Longitudinal Data System (SLDS), which contains administrative school data at the student level. While some research has been conducted using the SLDS, its primary use is for state education administrative reporting. This article uses the combination of log-linear models and correspondence analysis to gain insight into high school dropouts in two discrete regions in Kentucky, Appalachia and non-Appalachia, defined by the American Community Survey. The individual student records from the SLDS were categorized into one of the two regions and a log-linear model was used to identify the interactions between the demographic characteristics and the dropout categories, push-out and pull-out. Correspondence analysis was then used to visualize the interactions with the expanded push-out categories, boredom, course selection, expulsion, failing grade, teacher conflict, and pull-out categories, employment, family problems, illness, marriage, and pregnancy to provide insights into the regional differences. In this article, we demonstrate that correspondence analysis can extend the insights gained from SDLS data and provide new perspectives on dropouts. Supplementary materials for this article are available online. |
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Analisis Kebudayaan |
| Volume / Edisi | : | III-3, - (No. 3) |
| Halaman | : | 65-71 |
| Abstrak | : | - |
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | The American Statistician |
| Volume / Edisi | : | 72 (No. 2) |
| Halaman | : | 184-190 |
| Abstrak | : | A simulation study was conducted to assess how well the necessary sample size to achieve a stipulated margin of error can be estimated prior to sampling. Our concern was particularly focused on performance when sampling from a very skewed distribution, which is a common feature of many biological, economic, and other populations. We examined two approaches for estimating sample size—one being the commonly used strategy aimed at regulating the average magnitude of the stipulated margin of error and the second being a previously proposed strategy to control the tolerance probability with which the stipulated margin of error is exceeded. Results of the simulation revealed that (1) skewness does not much affect the average estimated sample size but can greatly extend the range of estimated sample sizes; and (2) skewness does reduce the effectiveness of Kupper and Hafner's sample size estimator, yet its effectiveness is negatively impacted less by skewness directly, and to a much greater degree by the common practice of estimating the population variance via a pilot sampling from the skewed population. Nonetheless, the simulations suggest that estimating sample size to control the probability with which the desired margin of error is achieved is a worthwhile alternative to the usual sample size formula that controls the average width of the confidence interval only. |
| Pengarang | : | Harris M. Nasution |
| Nama Majalah/Jurnal | : | Analisis Kebudayaan |
| Volume / Edisi | : | III-3, - (No. 3) |
| Halaman | : | 60-64 |
| Abstrak | : | - |