Novel Statistical Analysis in the Context of a Comprehensive Needs Assessment for Secondary STEM Recruitment
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 ST...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-09-01
|
| Series: | Computation |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-3197/9/10/105 |
| _version_ | 1797514944704413696 |
|---|---|
| author | Norou Diawara Sarah Ferguson Melva Grant Kumer Das |
| author_facet | Norou Diawara Sarah Ferguson Melva Grant Kumer Das |
| author_sort | Norou Diawara |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T06:38:43Z |
| format | Article |
| id | doaj.art-9250130f8abd4cd7935630ab16b05f3c |
| institution | Directory Open Access Journal |
| issn | 2079-3197 |
| language | English |
| last_indexed | 2024-03-10T06:38:43Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Computation |
| spelling | doaj.art-9250130f8abd4cd7935630ab16b05f3c2023-11-22T17:52:03ZengMDPI AGComputation2079-31972021-09-0191010510.3390/computation9100105Novel Statistical Analysis in the Context of a Comprehensive Needs Assessment for Secondary STEM RecruitmentNorou Diawara0Sarah Ferguson1Melva Grant2Kumer Das3Department of Mathematics and Statistics, Old Dominion University, Norfolk, VA 23529, USADepartment of Mathematics and Statistics, Old Dominion University, Norfolk, VA 23529, USATeaching & Learning Department, Old Dominion University, Norfolk, VA 23529, USAOffice of Vice President for Research, Innovation, and Economic Development, University of Louisiana at Lafayette, Lafayette, LA 70504, USAThere 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.https://www.mdpi.com/2079-3197/9/10/105teacher recruitmentSTEM teachingneeds assessmentstatistical methodsquantile regression |
| spellingShingle | Norou Diawara Sarah Ferguson Melva Grant Kumer Das Novel Statistical Analysis in the Context of a Comprehensive Needs Assessment for Secondary STEM Recruitment Computation teacher recruitment STEM teaching needs assessment statistical methods quantile regression |
| title | Novel Statistical Analysis in the Context of a Comprehensive Needs Assessment for Secondary STEM Recruitment |
| title_full | Novel Statistical Analysis in the Context of a Comprehensive Needs Assessment for Secondary STEM Recruitment |
| title_fullStr | Novel Statistical Analysis in the Context of a Comprehensive Needs Assessment for Secondary STEM Recruitment |
| title_full_unstemmed | Novel Statistical Analysis in the Context of a Comprehensive Needs Assessment for Secondary STEM Recruitment |
| title_short | Novel Statistical Analysis in the Context of a Comprehensive Needs Assessment for Secondary STEM Recruitment |
| title_sort | novel statistical analysis in the context of a comprehensive needs assessment for secondary stem recruitment |
| topic | teacher recruitment STEM teaching needs assessment statistical methods quantile regression |
| url | https://www.mdpi.com/2079-3197/9/10/105 |
| work_keys_str_mv | AT noroudiawara novelstatisticalanalysisinthecontextofacomprehensiveneedsassessmentforsecondarystemrecruitment AT sarahferguson novelstatisticalanalysisinthecontextofacomprehensiveneedsassessmentforsecondarystemrecruitment AT melvagrant novelstatisticalanalysisinthecontextofacomprehensiveneedsassessmentforsecondarystemrecruitment AT kumerdas novelstatisticalanalysisinthecontextofacomprehensiveneedsassessmentforsecondarystemrecruitment |