Novel Statistical Analysis in the Context of a Comprehensive Needs Assessment for Secondary STEM Recruitment
| Autor: | Sarah Ferguson, Norou Diawara, Melva R. Grant, Kumer Das |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
quantile regression
ComputingMilieux_THECOMPUTINGPROFESSION General Computer Science Applied Mathematics media_common.quotation_subject Context (language use) QA75.5-76.95 STEM teaching Theoretical Computer Science Quantile regression Promotion (rank) needs assessment Electronic computers. Computer science Modeling and Simulation Perception teacher recruitment Needs assessment statistical methods Mathematics education Quality (business) Value (mathematics) Valuation (finance) media_common |
| Zdroj: | Computation, Vol 9, Iss 105, p 105 (2021) Computation Volume 9 Issue 10 |
| ISSN: | 2079-3197 |
| DOI: | 10.3390/computation9100105 |
| Popis: | There is a myriad of career opportunities stemming from science, technology, engineering, and mathematics (STEM) disciplines. In addition to careers in corporate settings, teaching is a viable career option for individuals pursuing degrees in STEM disciplines. With national shortages of secondary STEM teachers, efforts to recruit, train, and retain quality STEM teachers is greatly important. Prior to exploring ways to attract potential STEM teacher candidates to pursue teacher training programs, it is important to understand the perceived value that potential recruits place on STEM careers, disciplines, and the teaching profession. The purpose of this study was to explore students’ perceptions of the usefulness of STEM disciplines and their value in supporting students’ careers. A novel statistical method was utilized, combining exploratory-factor analysis, the analysis of variance, generalized estimating equation evaluations under the framework of a generalized linear model, and quantile regression. Using the outputs from each statistical measure, students’ valuation of each STEM discipline and their interest in pursuing teaching as a career option were assessed. Our results indicate a high correlation of liking and perceived usability of the STE disciplines relative to careers. Conversely, our results also display a low correlation of the liking and perceived usability of mathematics relative to future careers. The significance of these diametrically related results suggests the need for promotion of the interrelatedness of mathematics and STE. |
| Databáze: | OpenAIRE |
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