Anxiety is not enough to drive me away: A latent profile analysis on math anxiety and math motivation

Mathematics anxiety (MA) and mathematics motivation (MM) are important multi-dimensional non-cognitive factors in mathematics learning. While the negative relation between global MA and MM is well replicated, the relations between specific dimensions of MA and MM are largely unexplored. The present study utilized latent profile analysis to explore profiles of various aspects of MA (including learning MA and exam MA) and MM (including importance, self-perceived ability, and interest), to provide a more holistic understanding of the math-specific emotion and motivation experiences. In a sample of 927 high school students (13–21 years old), we found 8 distinct profiles characterized by various combinations of dimensions of MA and MM, revealing the complexity in the math-specific emotion-motivation relation beyond a single negative correlation. Further, these profiles differed on mathematics learning behaviors and mathematics achievement. For example, the highest achieving students reported modest exam MA and high MM, whereas the most engaged students were characterized by a combination of high exam MA and high MM. These results call for the need to move beyond linear relations among global constructs to address the complexity in the emotion-motivation-cognition interplay in mathematics learning, and highlight the importance of customized intervention for these heterogeneous groups

Analysis of question text properties for equality monitoring.

INTRODUCTION: Ongoing monitoring of cohort demographic variation is an essential part of quality assurance in medical education assessments, yet the methods employed to explore possible underlying causes of demographic variation in performance are limited. Focussing on properties of the vignette text in single-best-answer multiple-choice questions (MCQs), we explore here the viability of conducting analyses of text properties and their relationship to candidate performance. We suggest that such analyses could become routine parts of assessment evaluation and provide an additional, equality-based measure of an assessment's quality and fairness. METHODS: We describe how a corpus of vignettes can be compiled, followed by examples of using Microsoft Word's native readability statistics calculator and the koRpus text analysis package for the R statistical analysis environment for estimating the following properties of the question text: Flesch Reading Ease (FRE), Flesch-Kincaid Grade Level (Grade), word count, sentence count, and average words per sentence (WpS). We then provide examples of how these properties can be combined with equality and diversity variables, and the process automated to provide ongoing monitoring. CONCLUSIONS: Given the monitoring of demographic differences in assessment for assurance of equality, the ability to easily include textual analysis of question vignettes provides a useful tool for exploring possible causes of demographic variations in performance where they occur. It also provides another means of evaluating assessment quality and fairness with respect to demographic characteristics. Microsoft Word provides data comparable to the specialized koRpus package, suggesting routine use of word processing software for writing items and assessing their properties is viable with minimal burden, but that automation for ongoing monitoring also provides an additional means of standardizing MCQ assessment items, and eliminating or controlling textual variables as a possible contributor to differential attainment between subgroups

Operons

Operons (clusters of co-regulated genes with related functions) are common features of bacterial genomes. More recently, functional gene clustering has been reported in eukaryotes, from yeasts to filamentous fungi, plants, and animals. Gene clusters can consist of paralogous genes that have most likely arisen by gene duplication. However, there are now many examples of eukaryotic gene clusters that contain functionally related but non-homologous genes and that represent functional gene organizations with operon-like features (physical clustering and co-regulation). These include gene clusters for use of different carbon and nitrogen sources in yeasts, for production of antibiotics, toxins, and virulence determinants in filamentous fungi, for production of defense compounds in plants, and for innate and adaptive immunity in animals (the major histocompatibility locus). The aim of this article is to review features of functional gene clusters in prokaryotes and eukaryotes and the significance of clustering for effective function