Supporting Middle School Mathematics Specialists’ Work: A Case for Learning and Changing Teachers’ Perspectives

In this paper, we highlight one whole‐class discussion that took place in a middle school mathematics Rational Number and Proportional Reasoning course, one of the six mathematics courses teachers take to complete our state‐wide middle school mathematics specialist program. Statistical measures indicate that teachers made gains in their understanding of concepts and substantial gains in their views of teaching and preparedness. We provide a microanalysis of one of the lessons, to explain, in part, how they might have made this progress. To develop our argument, we coordinate a social analysis with an analysis of the types of specialized mathematical knowledge that teachers might have considered as they engaged in these discussions. As we will illustrate, these types of classroom discussions provided teachers opportunities to consider new visions for mathematics learning and teaching

K-5 Mathematics Specialists\u27 Teaching and Learning about Fractions

This paper describes the fraction-based mathematical activities of two teachers who are part of 3 Mathematics Specialist preparation program. Their work with fractions is traced from two perspectives: 1) their interactions with students as they struggle with fraction concepts; and, 2) their personal journeys to develop deeper understandings of fractions as participants in the Rational Numbers course that is part of their degree program. Through their stories, we gain a better understanding of the complex nature of their work with students and how their participation in the Mathematics Specialist program helps support their work in the school buildings

Motifs from the deep

Because of the increasing recognition of the importance of non-coding RNAs in gene regulation, there is considerable interest in identifying RNA motifs in genomic data. In a recent report in BMC Genomics, Breaker and colleagues describe a new algorithm for identifying functional noncoding RNAs in metagenomic sequences of marine organisms, a strategy that may be particularly effective for discovering new and unique riboswitches

A Logico-Structural, Worldview Analysis of the Interrelationship between Science Interest, Gender, and Concept of Nature

A few years ago I was speaking with a distinguished professor of science explaining to him my concern for the low level of science interest among school level students. I remarked that in my view a major contributor to this lack of interest was the methodology used to teach science. Students forsake science because their own orientation to the world does not allow them to appreciate science as it is typically taught (Cobern, 1989a). The professor immediately added to my sentence and believed by the vast majority of qualified practitioners. He went on to say that this dropping away of students is a blessing because it leaves science with only those who are truly capable of doing science. What this professor advocated was the natural selection of science students via the survival of the fittest - science education, red in tooth and claw

Structuring discretion: the effects of policy on officers perceptions of discretionary authority

Examines the effect of policy and procedure on individual officer's perception of his/her discretio

Mining Patents with Large Language Models Demonstrates Congruence of Functional Labels and Chemical Structures

Predicting chemical function from structure is a major goal of the chemical sciences, from the discovery and repurposing of novel drugs to the creation of new materials. Recently, new machine learning algorithms are opening up the possibility of general predictive models spanning many different chemical functions. Here, we consider the challenge of applying large language models to chemical patents in order to consolidate and leverage the information about chemical functionality captured by these resources. Chemical patents contain vast knowledge on chemical function, but their usefulness as a dataset has historically been neglected due to the impracticality of extracting high-quality functional labels. Using a scalable ChatGPT-assisted patent summarization and word-embedding label cleaning pipeline, we derive a Chemical Function (CheF) dataset, containing 100K molecules and their patent-derived functional labels. The functional labels were validated to be of high quality, allowing us to detect a strong relationship between functional label and chemical structural spaces. Further, we find that the co-occurrence graph of the functional labels contains a robust semantic structure, which allowed us in turn to examine functional relatedness among the compounds. We then trained a model on the CheF dataset, allowing us to assign new functional labels to compounds. Using this model, we were able to retrodict approved Hepatitis C antivirals, uncover an antiviral mechanism undisclosed in the patent, and identify plausible serotonin-related drugs. The CheF dataset and associated model offers a promising new approach to predict chemical functionality.Comment: Under revie

THE IMPULSE TOWARD THE DISADVANTAGED IN THE GOSPEL PREACHED BY PAUL: AN ANALYSIS OF 1 CORINTHIANS 1:10-4:21 AND 8:1-11:1

Abstract This article examines two major sections of 1 Corinthians,[1][2][3][4