Roles of metacognition and achievement goals in mathematical modeling competency: A structural equation modeling analysis.
Ontology highlight
ABSTRACT:
SUBMITTER: Hidayat R
PROVIDER: S-EPMC6219774 | biostudies-literature | 2018
REPOSITORIES: biostudies-literature
Publications
Roles of metacognition and achievement goals in mathematical modeling competency: A structural equation modeling analysis.
Hidayat Riyan R Zulnaidi Hutkemri H Syed Zamri Sharifah Norul Akmar SNA
PloS one 20181106 11
This study investigates the relationship between metacognition and achievement goals which may influence mathematical modeling competency in students of mathematics education programs. The current study employs 538 students of mathematics education program; 483 (89.8%) of whom are male and 55 (10.2%) are aged from 18 years old to 22 years old. The study follows a correlational research design to investigate and measure the degree of relationship amongst mathematical modeling competencies, achiev ...[more]
Similar Datasets
Project description:OBJECTIVES:The purpose of this manuscript was to provide a substantive-methodological synergy of potential importance to future research in the psychology of sport and exercise. DESIGN:The substantive focus was the emerging role for, and particularly the measurement of, athletes' evaluations of their coach's competency within conceptual models of effective coaching. The methodological focus was exploratory structural equation modeling (ESEM), a methodology that integrates the advantages of exploratory factor analysis and confirmatory factor analysis (CFA) within the general structural equation model. METHOD:The synergy was a demonstration of when a new and flexible methodological framework, ESEM, may be preferred as compared to a more familiar and restrictive methodological framework, CFA, by reanalyzing existing data. RESULTS:ESEM analysis on extant datasets suggested that for responses to the Athletes' Perceptions of Coaching Competency Scale II - High School Teams (APCCS II-HST), a CFA model based on the relevant literature plus one post hoc modification, offered a viable alternative to a more complex ESEM model. For responses to the Coaching Competency Scale (CCS), a CFA model based on the relevant literature did not offer a viable alternative to a more complex ESEM model. CONCLUSIONS:The ESEM framework should be strongly considered in subsequent studies validity studies - for new and/or existing instruments in the psychology of sport and exercise. A key consideration for deciding between ESEM and the accompanying rotation criterion and CFA in future validity studies should be level of a priori measurement theory.
| S-EPMC3686321 | biostudies-literature
Project description:ObjectivesWhen examining the relationship between smoking intensity and toxicant exposure biomarkers in an effort to understand the potential risk for smoking-related disease, individual biomarkers may not be strongly associated with smoking intensity because of the inherent variability in biomarkers. Structural equation modeling (SEM) offers a powerful solution by modeling the relationship between smoking intensity and multiple biomarkers through a latent variable.MethodsBaseline data from a randomized trial (N = 1250) were used to estimate the relationship between smoking intensity and a latent toxicant exposure variable summarizing five volatile organic compound biomarkers. Two variables of smoking intensity were analyzed: the self-report cigarettes smoked per day and total nicotine equivalents in urine. SEM was compared with linear regression with each biomarker analyzed individually or with the sum score of the five biomarkers.ResultsSEM models showed strong relationships between smoking intensity and the latent toxicant exposure variable, and the relationship was stronger than its counterparts in linear regression with each biomarker analyzed separately or with the sum score.ConclusionsSEM is a powerful multivariate statistical method for studying multiple biomarkers assessing the same class of harmful constituents. This method could be used to evaluate exposure from different combusted tobacco products.
| S-EPMC9075702 | biostudies-literature
Project description:IntroductionMathematical modeling has become a crucial competence in mathematics education in many countries and regions due to the increasingly complex real-world problems that students face in the 21st century. Previous research has shown that mathematical modeling contributes to the development of students' creativity, particularly with respect to stimulating and protecting the curiosity of children. However, previous studies have not explored or examined the relationships among middle school students' mathematical modeling competency, curiosity, and creativity based on data drawn from large-scale assessments and have not investigated the influence of teachers' teaching methods in this context.MethodsThis study used convenience sampling to select 4,531 seventh-grade students from eastern and western, urban and rural areas in China. Online tests and questionnaires were used to measure their mathematical modeling competency, curiosity, creativity and guided inquiry teaching, and a moderated mediation model was used to analyze the effect of mathematical modeling competency on creativity.ResultsThe results showed the following. (1) There are statistically significant differences between boys and girls in terms of their mathematical modeling competency, curiosity, and creativity. Specifically, boys score significantly higher than girls on these variables. (2) Creativity exhibits a statistically significant positive correlation with mathematical modeling competency, curiosity, and guided inquiry teaching. (3) Curiosity mediates the relationship between mathematical modeling competency and creativity, and guided inquiry teaching moderates the influence of curiosity. In high-level guided inquiry teaching classes, curiosity has a stronger influence on creativity, and it mediates the relationship between mathematical modeling competency and creativity more strongly.DiscussionThis study empirically verified the influence of mathematical modeling competency on creativity and provided a possible way to cultivate children's creativity. Future research should use longitudinal analysis to verify the causal relationship between mathematical modeling competency and creativity and to systematically explore the possible path by which mathematical modeling competency affects creativity.
| S-EPMC9880854 | biostudies-literature
Project description:Schizophrenia (SCZ) is a psychiatric disorder of unknown etiology. There is evidence suggesting that aberrations in neurodevelopment are a significant attribute of schizophrenia pathogenesis and progression. To identify biologically relevant molecular abnormalities affecting neurodevelopment in SCZ we used cultured neural progenitor cells derived from olfactory neuroepithelium (CNON cells). Here, we tested the hypothesis that variance in gene expression differs between individuals from SCZ and control groups. In CNON cells, variance in gene expression was significantly higher in SCZ samples in comparison with control samples. Variance in gene expression was enriched in five molecular pathways: serine biosynthesis, PI3K-Akt, MAPK, neurotrophin and focal adhesion. More than 14% of variance in disease status was explained within the logistic regression model (C-value = 0.70) by predictors accounting for gene expression in 69 genes from these five pathways. Structural equation modeling (SEM) was applied to explore how the structure of these five pathways was altered between SCZ patients and controls. Four out of five pathways showed differences in the estimated relationships among genes: between KRAS and NF1, and KRAS and SOS1 in the MAPK pathway; between PSPH and SHMT2 in serine biosynthesis; between AKT3 and TSC2 in the PI3K-Akt signaling pathway; and between CRK and RAPGEF1 in the focal adhesion pathway. Our analysis provides evidence that variance in gene expression is an important characteristic of SCZ, and SEM is a promising method for uncovering altered relationships between specific genes thus suggesting affected gene regulation associated with the disease. We identified altered gene-gene interactions in pathways enriched for genes with increased variance in expression in SCZ. These pathways and loci were previously implicated in SCZ, providing further support for the hypothesis that gene expression variance plays important role in the etiology of SCZ.
| S-EPMC6004421 | biostudies-literature
Project description:The metaSEM package provides functions to conduct univariate, multivariate, and three-level meta-analyses using a structural equation modeling (SEM) approach via the OpenMx package in the R statistical platform. It also implements the two-stage SEM approach to conducting fixed- and random-effects meta-analytic SEM on correlation or covariance matrices. This paper briefly outlines the theories and their implementations. It provides a summary on how meta-analyses can be formulated as structural equation models. The paper closes with a conclusion on several relevant topics to this SEM-based meta-analysis. Several examples are used to illustrate the procedures in the supplementary material.
| S-EPMC4283449 | biostudies-literature
Project description:Gene expression is controlled by multiple regulators and their interactions. Data from genome-wide gene expression assays can be used to estimate molecular activities of regulators within a model organism and extrapolate them to biological processes in humans. This approach is valuable in studies to better understand complex human biological systems which may be involved in diseases and hence, have potential clinical relevance. In order to achieve this, it is necessary to infer gene interactions that are not directly observed (i.e. latent or hidden) by way of structural equation modeling (SEM) on the expression levels or activities of the downstream targets of regulator genes. Here we developed an R Shiny application, termed "Structural Equation Modeling of In silico Perturbations (SEMIPs)" to compute a two-sided t-statistic (T-score) from analysis of gene expression data, as a surrogate to gene activity in a given human specimen. SEMIPs can be used in either correlational studies between outcome variables of interest or subsequent model fitting on multiple variables. This application implements a 3-node SEM model that consists of two upstream regulators as input variables and one downstream reporter as an outcome variable to examine the significance of interactions among these variables. SEMIPs enables scientists to investigate gene interactions among three variables through computational and mathematical modeling (i.e. in silico). In a case study using SEMIPs, we have shown that putative direct downstream genes of the GATA Binding Protein 2 (GATA2) transcription factor are sufficient to infer its activities in silico for the conserved progesterone receptor (PGR)-GATA2-SRY-box transcription factor 17 (SOX17) genetic network in the human uterine endometrium.
| S-EPMC8652139 | biostudies-literature
Project description:Trypanosome RNA polymerase II transcription is polycistronic, individual mRNAs being excised by trans splicing and polyadenylation. In this study, we refined the previously published mathematical model for bloodstream form parasites and extended it to the procyclic form. We used the model, together with known mRNA half-lives, to predict the abundances of individual mRNAs, assuming rapid, unregulated mRNA processing; then we compared the results with measured mRNA abundances. Remarkably, the abundances of most mRNAs in procyclic forms are predicted quite well by the model, being largely explained by variations in mRNA decay rates and length. In bloodstream forms substantially more mRNAs are less abundant than predicted. We list mRNAs that are likely to show particularly slow or inefficient processing, either in both forms or with developmental regulation. We also measured ribosome occupancies of all mRNAs in trypanosomes grown in the same conditions as were used to measure mRNA turnover. In procyclic forms there was a weak positive correlation between ribosome density and mRNA half-life, suggesting cross-talk between translation and mRNA decay; ribosome density was related to the proportion of the mRNA on polysomes, indicating control of translation initiation. Ribosomal protein mRNAs in procyclics appeared to be exceptionally rapidly processed but poorly translated. Through this study, we conclude that lLevels of mRNAs in procyclic form trypanosomes are determined mainly by length and mRNA decay, with some control of precursor processing. In bloodstream forms variations in nuclear events play a larger role in transcriptome regulation, suggesting acquisition of new control mechanisms during adaptation to mammalian parasitism. Ribosome profiling and mRNA libraries were constructed in triplicate from in vitro PCF and in duplicate from in vitro T. brucei Lister427, to understand global differntial gene transcription.
2016-03-16 | E-GEOD-79208 | biostudies-arrayexpress
Project description:Culture-independent phylogenetic analysis of 16S ribosomal RNA (rRNA) gene sequences has emerged as an incisive method of profiling bacteria present in a specimen. Currently, multiple techniques are available to enumerate the abundance of bacterial taxa in specimens, including the Sanger sequencing, the 'next generation' pyrosequencing, microarrays, quantitative PCR, and the rapidly emerging, third generation sequencing, and fourth generation sequencing methods. An efficient statistical tool is in urgent need for the followings tasks: (1) to compare the agreement between these measurement platforms, (2) to select the most reliable platform(s), and (3) to combine different platforms of complementary strengths, for a unified analysis.We present the latent variable structural equation modeling (SEM) as a novel statistical application for the comparative analysis of measurement platforms. The latent variable SEM model treats the true (unknown) relative frequency of a given bacterial taxon in a specimen as the latent (unobserved) variable and estimates the reliabilities of, and similarities between, different measurement platforms, and subsequently weighs those measurements optimally for a unified analysis of the microbiome composition. The latent variable SEM contains the repeated measures ANOVA (both the univariate and the multivariate models) as special cases and, as a more general and realistic modeling approach, yields superior goodness-of-fit and more reliable analysis results, as demonstrated by a microbiome study of the human inflammatory bowel diseases.Given the rapid evolution of modern biotechnologies, the measurement platform comparison, selection and combination tasks are here to stay and to grow--and the latent variable SEM method is readily applicable to any other biological settings, aside from the microbiome study presented here.
| S-EPMC3608994 | biostudies-literature
Project description:At least 282 Food Policy Councils (FPCs) are currently working to improve access to healthy foods in their communities by connecting food system sectors, gathering community input, and advising food policy. Empirical research on FPCs is limited. This study empirically evaluates FPCs to better understand the relationships between Organizational Capacity, Social Capital, and Council Effectiveness by testing a FPC Framework adapted from Allen and colleagues (2012). Members of all FPCs in the U.S., Canada, and Native American Tribes and First Nations were invited to complete the Food Policy Council Self-Assessment Tool (FPC-SAT). Structural equation modeling was used to test the FPC Framework. Three hundred and fifty-four FPC members from 95 councils completed the FPC-SAT. After slight modification, a revised FPC Framework was a good fit with the data (?2 = 40.085, df = 24, p-value = .021, comparative fit index = 0.988, Tucker Lewis index = 0.982, root mean squared error of approximation = 0.044, p-close = .650). A moderation analysis revealed that community context influences the relationship between Social Capital and Council Effectiveness within the FPC Framework. The FPC Framework can guide capacity building interventions and FPC evaluations. The empirically tested framework can help FPCs efficiently work toward achieving their missions and improving their local food system.
| S-EPMC7262635 | biostudies-literature
Project description:Collaborative problem-solving (CPS) competency is critical for 21st century students. However, reports from the Programme for International Student Assessment (PISA) 2015 have revealed significant deficiencies in this competency among young students globally, indicating a critical need for the cultivation of CPS skills. Therefore, it is essential for educators and researchers to examine the factors that influence CPS competency and understand the potential role of CPS in secondary education. The present study aims to investigate the relationship between collaboration dispositions and students' CPS competency as well as the relationships of CPS competency and inquiry-based science instruction (IBSI) with science achievement using the PISA 2015 data. A total of 408,148 students from 52 countries and economies (i.e., regions) were included in our analysis. Unlike most previous studies that only investigated one country at a time and neglected the multilevel data structure of PISA, this study provided a global view through adopting multilevel modeling to account for the cluster effect at the school and country levels. Our findings revealed that valuing relationship was positively associated with CPS, whereas valuing teamwork was negatively associated with CPS. Furthermore, CPS competency was found to be a dominant and positive predictor of science achievement among all study variables, underscoring the importance of integrating CPS into teaching practices to promote student success in science. Additionally, different IBSI activities show varying relationships with science achievement, indicating that caution should be taken when recommending any specific practices associated with IBSI to teachers.
| S-EPMC10707649 | biostudies-literature