scholarly journals Understanding the Conceptions of Engineering in Early Elementary Students

2022 ◽  
Vol 12 (1) ◽  
pp. 43
Author(s):  
Sandra A. Lampley ◽  
Sarah Roller Dyess ◽  
Michael P. J. Benfield ◽  
Andrew M. Davis ◽  
Sampson E. Gholston ◽  
...  

There is a demand for more STEM professionals. Early elementary students’ conceptions about engineering can influence whether or not they explore STEM career paths and ultimately select an engineering career. This study examined the conceptions elementary students have regarding the work that engineers perform. The research questions were the following: (1) what images do early elementary students associate with engineering and engineers, (2) do these associations vary from grade to grade, (3) are there gendered differences in these associations, and (4) how do the associations from this sample compare with the associations from the broader (grades one–five) Cunningham, Lachapelle, and Lindgren-Steider (2005) sample? Survey data from 1811 students in grades one–three were analyzed by comparison analysis and cluster analysis and then compared to the initial Cunningham et al. (2005) study. The results indicate two ways elementary students envision engineering: (a) creating designs or collecting and analyzing data, and (b) utilizing equipment to build and improve things. Comparison with the Cunningham et al. (2005) study suggests that there may be shifts in the way elementary students perceive engineering. Since these shifts could be attributed to a variety of factors, future work that determines what learning experiences might be contributing to students’ conceptions about engineering is recommended.

2013 ◽  
Vol 04 (02) ◽  
pp. 1350007 ◽  
Author(s):  
K. S. KAVI KUMAR ◽  
BRINDA VISWANATHAN

While a wide range of factors influence rural–rural and rural–urban migration in developing countries, there is significant interest in analyzing the role of agricultural distress and growing inter-regional differences in fueling such movement. This strand of research acquires importance in the context of climate change adaptation. In the Indian context, this analysis gets further complicated due to the significant presence of temporary migration. This paper analyzes how weather and its variability affects both temporary and permanent migration in India using National Sample Survey data for the year 2007–2008. The paper finds that almost all of the rural–urban migrants are permanent. Only temperature plays a role in permanent migration. In contrast, many temporary migrants are rural–rural and both temperature and rainfall explain temporary migration.


2021 ◽  
pp. 097370302110296
Author(s):  
Soumyajit Chakraborty ◽  
Alok K. Bohara

Being from backward castes, classes and Muslims in India has an economic cost associated with the nature of institutional discrimination. Using the 2011–2012 National Sample Survey data, this study identifies that caste and religion still rule the modern Indian labour market. We find that discrimination is evident in the socio-religious earnings gaps. While the parametric decompositions suggest that most of these gaps are due to differential human capital endowment, the nonparametric method almost evenly attributes inequality to discrimination and endowment. The results presented in this study suggest that discrimination against Scheduled Castes and Scheduled Tribes, Muslims and Other Backward Classes should be included in policy designs to promote equity in the Indian labour market.


2004 ◽  
Vol 41 (A) ◽  
pp. 119-130
Author(s):  
Y.-X. Lin ◽  
D. Steel ◽  
R. L Chambers

This paper applies the theory of the quasi-likelihood method to model-based inference for sample surveys. Currently, much of the theory related to sample surveys is based on the theory of maximum likelihood. The maximum likelihood approach is available only when the full probability structure of the survey data is known. However, this knowledge is rarely available in practice. Based on central limit theory, statisticians are often willing to accept the assumption that data have, say, a normal probability structure. However, such an assumption may not be reasonable in many situations in which sample surveys are used. We establish a framework for sample surveys which is less dependent on the exact underlying probability structure using the quasi-likelihood method.


2020 ◽  
Author(s):  
Santiago Papini ◽  
Mikael Rubin ◽  
Michael J Telch ◽  
Jasper A. J. Smits

Background. The application of psychopathological symptom networks requires reconciliation of the observed cross-sample heterogeneity. We leveraged the largest sample to be used in a PTSD network analysis (N = 28,594) to examine the impact of criteria-based and data-driven sampling approaches on the heterogeneity and interpretability of networks.Methods. Severity and diagnostic criteria identified four overlapping subsamples and cluster analysis identified three distinct data-derived profiles. Networks estimated on each subsample were compared to a respective benchmark network at the symptom-relation level by calculating sensitivity, specificity, correlation, and density of the edges. Negative edges were assessed for Berkson’s bias, a source of error that can be induced by threshold samples on severity.Results. Criteria-based networks showed reduced sensitivity, specificity, and density but edges remained highly correlated and a meaningfully higher proportion of negative edges was not observed relative to the benchmark network of all cases. Among the data-derived profile networks, the Low Severity network had the highest proportion of negative edges not present in the benchmark network of symptomatic cases. The High Severity profile also showed a higher proportion of negative edges, whereas the Medium Severity profile did not. Conclusion. Although networks showed differences, Berkson’s bias did not appear to be a meaningful source of systematic error. These results can guide expectations about the generalizability of symptom networks across samples that vary in their ranges of severity. Future work should continue to explore whether network heterogeneity is reflective of meaningful and interpretable differences in the symptom relations from which they are composed.


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