complete issue

©2015 - Journal of Career and Technical Education, Vol. 30, No.1 –

Journal of Career

and

Technical Education

Volume 30, Number 1

2015

Published by Omicron Tau Theta

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C

T

E


JOURNAL OF CAREER AND TECHNICAL EDUCATION

VOLUME 30 NUMBER 1 2015

Chapters of Omicron Tau Theta.................................................................................................................. 3

Editorial Board Members............................................................................................................................. 4

Notes from the Co-Editors.…..…………………………….…………………............................................ 5

Guidelines for Authors.................................................................................................................................. 7

High School Predictors of a Career in Medicine…………………………………………………………. 9 Travis T. Fuchs Philip M. Sadler Gerhard Sonnert Racial/Ethnic and Gender Equity Patterns in Illinois High School Career and Technical Education Coursework ....................................................................................................................................................29 Asia Fuller Hamilton Joel Malin Donald Hackmann Occupational Safety and Health: A View of Current Practices in Agricultural Education ............................................................................................................................................ ..............................53 Mark C. Threeton John C. Ewing Danielle C. Evanoski

CO-EDITOR Edward C. Fletcher Jr., Ph.D.

Assistant Professor Department of Leadership, Counseling, Adult, Career and Higher Education

Career and Workforce Education College of Education

4202 E. Fowler Ave, EDU 105 Tampa, FL 33620

(813) 974-0029 · FAX (813) 974-3366 E-mail: [email protected]

CO-EDITOR

Victor M. Hernandez-Gantes, Ph.D. Associate Professor

Department of Leadership, Counseling, Adult, Career and Higher Education Career and Workforce Education

College of Education 4202 E. Fowler Ave, EDU 105

Tampa, FL 33620 (813) 974-1277 · FAX (813) 974-3366

Email: [email protected]

PUBLISHED 2014 ISSN: 1531-4952

Printed at the University of Georgia


CHAPTERS OF OMICRON TAU THETA

ALPHA—University of Tennessee ALPHA BETA – New Mexico State University

ALPHA DELTA – University of Arizona ALPHA GAMMA – University of South Florida

BETA—Colorado State University CHI—University of Strathclyde, Glasgow, Scotland

GAMMA—Temple University DELTA—Rutgers University

EPSILON—State University of New York ETA— Ohio State University

IOTA—Virginia Polytechnic Institute and State University KAPPA—University of Wisconsin-Madison

LAMBDA—Southern Illinois University MU— University of Georgia

NU—California State University XI—North Carolina State University

OMICRON—Pennsylvania State University PHI—Oklahoma State University

PI—University of Houston RHO—University of Minnesota

SIGMA—University of Nebraska TAU—Kent State University

UPSILON—University of Jyvaskyla, Finland PHI—Oklahoma State University

CHI—University of Strathclyde, Glasgow, Scotland PSI—University of Idaho

OMEGA—University of Missouri ALPHA ALPHA—Chaing Mei University, Thailand


EDITORIAL BOARD MEMBERS

The quality of any research journal is dependent on the services of a strong Editorial Board and that is certainly true for the Journal of Career and Technical Education. The Board has provided guidance to the manuscript review process and the publication of JCTE and the Editors rely on them to provide quality reviews of several manuscripts each year. We express our appreciation to each Editorial Board member for their contributions to JCTE. Dr. Barbara Hagler, Chair Southern Illinois University Carbondale Dr. J. Elaine Adams University of Georgia Dr. Stephen J. McCaskey Indiana State University Dr. Sally Arnett Northern Illinois University Dr. Kristin Stair Louisiana State University Dr. John Cannon University of Idaho Dr. Sally Arnett Northern Illinois University Dr. Johanna Lasonen University of South Florida Dr. David MacQuarrie Michigan Department of Education Dr. Petri Nokelainen University of Tampere Dr. Jeno Rivera Michigan State University Dr. Adam Manley Western Michigan University Dr. Marianne Teräs University of Helsinki Dr. Karen Jones University of Georgia


NOTES FROM THE CO-EDITORS

In 2015, a total of 15 manuscripts were submitted for publication consideration in the Journal of Career and Technical Education (JCTE). At the end of November, the review process was fully completed for 12 manuscripts, with three articles remaining under review. Based on the review results of the fully reviewed manuscripts, three articles met the standards for publication and were accepted to produce Volume 30, Issue 1 of the journal, representing an acceptance rate of 25%. The articles featured in the current issue, represent two methodological approaches (correlational and descriptive), and address important issues related to career development, equity, and program practice.

In the first article, High School Predictors of a Career in Medicine, Fuchs, Sadler, and Sonnert reported the results of a study of high school students interested in medicine as a career. The authors noted the need to boost participation and equity in the medical career pathway and were particularly interested in determining whether interest at the end of high school is mediated by race/ethnicity. Using multiple logistic regression models, the authors determined there is a relationship between early and at the end of high school. The authors found no racial/ethnic differences in related interest although Asian students tended to show higher interest, while Black and Hispanic students showed high intrinsic motivation but lower science performance limiting the pursuit of related career pathways.

In the second article, Fuller Hamilton, Malin, and Hackman reported the results of a study entitled, Racial/Ethnic and Gender Equity Patterns in Illinois High School Career and Technical Education Course-work. In their study, the authors sought to analyze Career and Technical Education (CTE) student enrollments in Illinois by career cluster and pathway in terms of gender and racial/ethnic participation. The authors were particularly interested in determining participation trends in Science, Technology, Engineering, and Math (STEM) CTE pathways. This was an ex post facto descriptive study using state data to determine participation trends and the authors found gender and ethnicity-based inequities in certain areas, while more equitable patterns were apparent in others. For example, the authors described higher enrollment of male students within STEM pathways, but in other CTE pathways the trend was reversed. In general, based on the results of this study, White student participation was found to be more prevalent in CTE programs in the Illinois when compared to other students.

In turn, the third article features the results of the study, Occupational Safety and Health: A View of Current Practices in Agricultural Education, conducted by Threeton, Ewing, and Evanoski. In this study, the authors used descriptive research relying on a survey to document safety practices in the context of instruction in secondary agricultural education. Based on the results, the authors concluded that although the majority of agricultural education programs in the study included a safety program, about of a fourth of programs did not. Further, the authors found that most of the students receive safety training, while a small fraction of teachers do not provide related instruction. Lack of adequate funding and classroom facilities combined with high student enrollment appeared to hinder the implementation of safety programs.


The results of the first two studies confirm relevant literature in STEM related pathways, especially in the areas of engineering and computer science, noting the need for boosting the participation of underrepresented students in the education pipeline. In addition, the third article contributes to our understanding related to the creation of a safety environment for student participation that should be at the core of CTE programs.

Overall, we appreciate the work of researchers in the field and the opportunity to share their work with others in the CTE community through our journal. In this regard, the review process is rigorous as demonstrated by a 25% rate of acceptance, which continues to solidify the trend in the consistency of the journal quality and review process. To this end, the journal relies on the support of reviewers to make the selection of articles featured in this Winter Issue possible. As such, journal reviewers are critical to the review process and their support is greatly appreciated.

We also want to recognize the support of Chase Dooley at Virginia Tech, who is serving as our de facto Managing Editor. Mr. Dooley is a Digital Publishing Specialist at the Virginia Tech University Libraries and his continued support to JCTE has been greatly appreciated. Thanks to his support, as part of the public service offered by the Virginia Tech University Libraries, the journal should be able to transition to an automated workflow site in 2016 to manage submission, review process, and publication.

Edward C. Fletcher Jr. & Victor M. Hernandez-Gantes Co-Editors, University of South Florida

The Journal of Career and Technical Education can be obtained in

electronic form. Previous printed journals are indexed in the Education Resources Information Clearinghouse (ERIC). The electronic journal is available worldwide on the Internet

and can be accessed at the following case sensitive URL:

http://scholar.lib.vt.edu/ejournals/JCTE/

Prior to Volume 16, Number 2, the Journal of Career and Technical Education was published as the Journal of Vocational and Technical Education. These issues can be

found at the following case sensitive URL:

http://scholar.lib.vt.edu/ejournals/JVTE/

Edward C. Fletcher Jr. & Victor M. Hernandez-Gantes, University of South Florida Co-Editors


GUIDELINES FOR AUTHORS

The Journal of Career and Technical Education (JCTE) is a non-profit, refereed, national publication of Omicron Tau Theta, the national, graduate honorary society of career and technical education. Manuscripts submitted for consideration by JCTE should focus on career and technical education philosophy, theory, or practice. Comprehensive reviews of literature and reports of research and methodology will be considered. All articles should relate to current issues and have direct implications for career and technical educators. It is intended that JCTE serve as a forum for discussion of philosophy, theory, practice, and issues in career and technical education. Manuscripts submitted for review should not have been published or be under current consideration for publication by other journals. Publication Style The Publication Manual of the American Psychological Association (APA), 6th Edition (2010), is the standard of style for JCTE. Place figures and tables in the appropriate place in the manuscript. Underlining should not be used anywhere in the manuscript. Statistics and titles in the reference list should be italicized according to APA 6th Edition Style. Manuscripts not adhering to the style manual will be returned to the authors without review. Figures and Tables Tables and figures should provide only information essential to understanding the article. Authors should avoid reporting the same information in both text and tables. In the preparation of tables and figures, authors should use APA guidelines for format and include the tables and figures in text where they should appear. Tables and figures are to be prepared as a part of the Microsoft Word file. Tables must be developed in columns using the table-formatting feature in the word processor so that they will translate to HTML. Each item in a table should be placed in an individual cell. Do not use tabs to format tables because they will not translate properly. Tables and figures will not be published on oversized or foldout sheets. Submitting Manuscripts Manuscripts accepted for publication normally may not exceed 30 pages of printed, double spaced text, including title page, abstract page, tables, figures, and references. Margins should be 1" all around and use Times New Roman 12-point for all text, tables, and figures. Use the line numbering feature of the word processor to number each line of the manuscript. Electronic submissions are preferred, although mailed copies will be accepted. Submit the following:

1. A separate title page with the manuscript title, author(s), institution(s), complete address(es), telephone number(s), and the author(s)’ e-mail address(es); and 2. one double-spaced copy of the manuscript with the abstract placed immediately after the manuscript title and the lines numbered; author(s) must ensure that all references to the author(s) and their institutions are removed from the manuscript according to APA guidelines to facilitate the double-blind peer review process; the abstract should succinctly describe the manuscript’s contents and cannot exceed 960 characters and spaces (150 words).

The manuscript and title page can be submitted via e-mail to [email protected] and [email protected].


Review and Publication JCTE is published twice a year, spring and fall. All accepted articles will be published in the electronic journal, which is currently available at the following case sensitive URL:

http://scholar.lib.vt.edu/ejournals/JCTE/

The review process for the Journal of Career and Technical Education normally requires six weeks to three months. The Editor will notify you as each stage in the review process is completed. The decision of the reviewers will be one of the following:

1. Accept (publish as submitted, very minor editorial revisions may be needed - this is very rare for initial submissions); 2. Accept Conditionally, with minor revisions (revisions are reviewed by editor, not resubmitted to review panel); 3. Reject but Invite Major Revision and Resubmission (fundamental changes are needed, and the revised manuscript will go back to the same reviewers for reconsideration-this is a very common decision on the initial review and should not be considered as a final rejection); or 4. Reject the manuscript for JCTE (the manuscript will not be considered again).

The manuscript review process for JCTE is a "double-blind" peer review in that the reviewers are not informed of the identity of the author(s) and the author(s) are not informed of the identities of the reviewers. The reviewers of the manuscript are recognized scholars with appropriate professional and educational preparation and are selected for their specific expertise relative to the topic of the manuscript being reviewed. At least one of the reviewers on each manuscript must be a member of the JCTE Editorial Board. The final acceptance rate for JCTE is usually 10%. Authors who persevere through requested revisions are generally the authors whose manuscripts are eventually published in selective, refereed journals such as JCTE. Book Reviews/Thematic Issues Book reviews will also be considered for publication in the JCTE. Persons interested in publication of a book review should contact the Editor-Elect (see inside front cover, page 1). A thematic issue of the JCTE may be published at least once every two years. Themes for upcoming issues will be announced in both the hard copy and electronic journal.


High School Predictors of a Career in Medicine

Travis T. Fuchs Harvard University

Philip M. Sadler

Harvard University and Smithsonian Institution

Gerhard Sonnert Harvard University

ABSTRACT

While there is no dearth of high school students who are interested in becoming physicians, racial/ethnic disparities still exist in the medical profession. This retrospective cohort study examined the influences on students’ desire, at the end of high school, for a medical career, and, in particular, how these influences differed by race/ethnicity. Multiple logistic regression models were used to predict students’ medical career intentions at the end of high school. Interest in a medical career at the beginning of high school strongly predicted interest in a medical career at the end of high school. Authors found almost no racial/ethnic differences in interest in medicine, after controlling for other predictors. The exception was elevated medical career interest amongst Asians. Furthermore, Black and Hispanic students who wanted to become physicians tended to have high intrinsic motivations, but low science performance. Limited proficiency in science may impede Black and Hispanic students’ further progress through the medical pipeline. Introduction Medicine is an attractive career for many students (Mcharg, Mattick, & Knight, 2007). Whereas there is no general shortage of students vying for admission to medical school, disparities still exist in how race/ethnicity is represented in the medical profession (Komaromy et al., 1996). This has been a concern internationally as well in the United States, where relatively low numbers of underrepresented minority (URM) students apply to, enter, and graduate from medical school (Dames, 2014; Griffin & Hu, 2015). For example, while U.S. census data from 2010 show 17% and 12% of the American population identifying as Hispanic and Non-Hispanic Black (henceforth referred to as Black), respectively (United States Census Bureau, 2010), medical school graduates in 2014 are reported as 6% Hispanic and 6% Black (Association of American Medical Colleges, 2014). At a relatively late stage in the medical career pipeline, our estimates show that the numbers of Black (15,000) and Hispanic (22,500) freshmen interested in a career in

medicine are still large enough to potentially bring the ethnic/racial composition of the medical profession more in line with that of the general population. (These estimates were made by taking the racial/ethnic percentages of students interested in a career in medicine by the end of high school in our representative sample and multiplying them by the total


number of freshmen in the U.S in 2014 (Eagan et al., 2014). However, the URM numbers drop substantially by medical school application and enrollment (Association of American Medical Colleges, 2010). To deal with this disparity, many programs have been developed to assist students at these later stages of the medical pipeline. These include selecting for both academic and non-cognitive factors in medical admissions (Powis, Hamilton, & McManus, 2007), providing admissions materials and support before application (Keith & Hollar, 2012), and, controversially, lowering academic requirements (O'Neill, Vonsild, Wallstedt, & Dornan, 2013). However, as Ferguson, James, Yates, and Lawrence (2012) stated, such interventions that occur late along the pipeline to choosing a medical career take place only “after ethnic, sex and socio-economic biases may already be established (p. 382).” Our study expanded on Ferguson et al. (2012) by looking at predictors of student interest in medicine earlier along the medical career pipeline: at the end of high school. It was intended to inform policy initiatives that are planned to support URM students. Academic factors predicting interest in medicine Most studies agree that academic competence in high school, especially in science, is vital for students’ continuation through the medical pipeline (Aschbacher, Li, & Roth, 2010; El Mouzan, 1992; Oscos-Sanchez, Oscos-Flores, & Burge, 2008; Terrell, 2006). Thurmond and Cregler (1999) have suggested that early intervention directed at basic science courses is important to maintaining students’ interest in, and progression through, the medical pipeline. Moreover, URM students can have negative experiences with science education due to issues with scientific identity (Carlone, Haun-Frank, & Webb, 2011; Hazari, Sadler, & Sonnert, 2013) and with their relationships with primary and secondary science teachers (Kitts, 2009; Mcharg, Mattick, & Knight, 2007). However, the majority of the studies examining the relationship between academic performance and the pursuit of a medical career have focused on the implementation of a specific program and its immediate effects; not on its longer-term impact (Terrell, 2006). In general, there is a dearth of empirical knowledge about how academic experiences and performance at the high school level influence students’ medical career choices (Dames, 2014). As such, academic variables typically reported upon in science, technology, engineering, and mathematics (STEM) pipeline studies were selected for analysis (Sadler, Sonnert, Hazari, & Tai, 2014). These variables matched the aforementioned focus on scientific competency in high school. In addition, a strong performance in STEM courses and majoring in a STEM field in college are often cited as predictors of doing well in medical school (Lambe & Bristow, 2011; Montague & Odds, 1990). However, non-science majors can also succeed in the medical profession where verbal reasoning/analytical writing skills are also highly valued (Ellaway et al., 2014; Herman & Veloski, 1981). Hence, in addition to high school STEM variables, students’ final English grade in high school was included in our variable list.


Career motivation predicting interest in medicine An extensive body of psychological and educational studies has explored human motivation; and, within this field of research, the distinction between intrinsic and extrinsic motivations has been fundamental (Ryan & Deci, 2000). The distinction has been widely used also in the study of work preferences (Amabile, Hill, Hennessey, & Tighe, 1994). In the present study of medical career interest, these two concepts of intrinsic and extrinsic motivation serve as a conceptual foundation. Doctors’ intrinsic and extrinsic motivations are important for the quality of the relationship between physician and patient (Barr, 2010; Powis, 1994). In addition, these motivation variables play a role in students’ medical career aspirations (Mcharg, Mattick, & Knight, 2007) especially in Black and Hispanic students (Boekeloo, Randolph, Timmons-Brown, & Wang, 2014; Boekeloo, Jones, Bhagat, Siddiqui, & Wang, 2015). Given that some high school students do not have a grasp of the nuanced differences between various medical careers (e.g., scientific researcher, clinical physician, family doctor, etc.) they may make decisions about their career choice based on previous experiences (Todaro, Washington, Boekeloo, Gilchrist, & Wang, 2013), interactions with adults (Zebrak, Le, Boekeloo, & Wang, 2013), or on general cues (Boekeloo, Jones, Bhagat, Siddiqui, & Wang, 2015). Of these influences some may relate to intrinsic motivation by highlighting aspects of the job like helping others and working with people, or to extrinsic motivation by underscoring potential fame and making money. Suggesting the importance of influences outside academics, a study following 239 premedical undergraduates through the first and second years of their program found that students’ favorite high school or college subject, as well as academic major, was unrelated to their decision to apply to medical school (Staley & Hood, 1977). In a study of 33 ethnically and economically diverse high school students, Aschbacher, Li, & Roth (2010)

found that, despite doing less well in science courses, many students’ medical career aspirations persisted due to family support and intrinsic motivations. Similarly, a study of 90 students participating in a “Mini-Med School” launched by the Royal College of Surgeons in Ireland found that high school students’ interest in medicine was primarily due to the perceived ability to help others and not to any other surveyed motivations (Shaikh, Babar, & Cross, 2013). These motivational findings are echoed by Dames’s (2014) case study in which eight URM subjects entering the medical pipeline did so “in spite of their science disengagement (p. 150).” Alternatively, it is often assumed, with varying degrees of alarm, that students with an interest in medicine are driven by extrinsic motivations (e.g., prestige, money, power) (Green, 1989). McFarland (1987) was troubled by the existence of a so-called ‘pre-med syndrome,’ in which students become, “narrow grade-conscious overachievers, who are less sociable and more interested in money and prestige (p. B1).” This fear has not abated since 1987 and lingers in medical dissertations and journals, where the quality and motivation of students admitted to medical schools and the culture in which they will be immersed have been critically examined (Leblanc, 2007; Neilson, 2003).


Study Aim Because academic success alone does not fully predict who wishes to pursue medicine as a career (Greenhalgh, Seyan, & Boynton, 2004), we also included the subject of career motivations in our study. Through examining students’ background, academic, and motivation variables our study aimed to add to the evidence base about students’ career interests in medicine at the end of high school. Its main research questions were:

1. What are the main predictors of students’ medical career interest at the end of high school?

2. Do these predictors differ by race/ethnicity?

Methods

We employed a retrospective cohort method, which is a standard method used especially in epidemiological, public health, and medical research (MacMahon, 1965; Mantel & Haenszel, 1959). In a retrospective cohort study, members of cohorts who currently fall into different categories recall their earlier experiences. Through statistical methods, such studies are then able to simultaneously test the strength of a multitude of existing hypotheses. In this study, we compared past experiences of two different groups of college students – those who planned to pursue a medical career and those who did not – in a nationally representative sample of college entrants in the U.S. Although randomized control trials are generally considered the “gold standard” in establishing causal effects, they require much longer time periods than retrospective studies and are often fraught with practical and ethical difficulties. Alternatively, longitudinal education studies are commonly prospective in that they follow a group of similar individuals forward in time to find how certain differences in exposure result in different outcomes. Such prospective studies again typically take much longer (and are more expensive) than retrospective studies and, hence, cannot include variables generated from recent research in the field. Instead, we asked students early in their college experience to report retrospectively about their earlier experiences. They reported their career interests at several educational junctures as well as on a variety of experiences and background variables. The Persistence Research in Science and Engineering (PRiSE) project was a large-scale study of students from 34 two- and four-year colleges and universities selected from a stratified random sample that accounted for institution size and type.

Sample

The PRiSE project sought to recruit students at the beginning of their studies and enrolled in a mandatory introductory English class at their institution. The rationale for this particular class versus a STEM course required for premedical students was that it included the full complement of students for analysis – those who, at some time did, and those who never did, contemplate a medical career. Recruitment of institutions began with a 2005 National Center for Education Statistics (NCES) list of degree-granting postsecondary institutions in the United States (containing Fall 2004 enrolment numbers), generated from the Integrated Postsecondary Education Data System (IPEDS) database. The table


comprised 4,454 institutions. Of these, 3,799 post-secondary institutions were deemed eligible for our study due to their enrolment being greater than 100 undergraduates (1,672, 44.0%, were two-year institutions and 2,127, 56.0%, were four-year institutions). In these groups, institutions were divided into bins based on their size. The sample selected contained 1,732 small four-year colleges, 297 medium four-year colleges, 134 large four-yeas colleges, 1,277 small two-year colleges, 298 medium two-year colleges, and 91 large two-year colleges.

Within these six bins, the institutions were randomized, and any schools without

science majors were excluded. We then went down each list, recruiting institutions that agreed to participate until a sufficient number of students in each category could be reached. To prevent the possibility of students being overrepresented by one institution a cap of 500 students per institution was instated, which was triggered a few times. In all, 160 institutions were contacted. Of these, only 43 institutions initially agreed to participate. Usable student questionnaires were received from 34 institutions.

To understand if the participating institutions systematically differed from the

institutions that declined the invitation to participate, we compared the participating and non-participating institutions on variables that were available in the IPEDS data set. We found no statistically significant differences in terms of Carnegie classification. This was true when we compared those who initially agreed to participate with those who initially declined as well as when we compared those who actually returned completed surveys with those who initially declined or initially agreed but did not follow through.

The full dataset of returned surveys included 6,598 students of which 56.4% (3,721)

attended four-year, and 43.6% (2,877) attended two-year institutions. In all, fourteen two-year schools (six small, three medium, five large) and twenty four-year schools participated (twelve small, three medium, five large). The proportion of participants from four- and two-year institutions was very similar to the corresponding proportion in the population, as described above (56.0% vs. 44.0%). Regarding our second stratification criterion, we had aimed at a sample that contained, among the four- and two-year students, a third of students who attend large, medium, and small institutions. Among the four-year students in our sample, 1,556 (41.8%) attended large, 967 (26.0%) attended medium, and 1,198 (32.2%) attended small institutions; among the two-year students in our sample, 1,139 (39.6%) attended large, 708 (24.6%) attended medium, and 1,030 (35.8%) attended small institutions. Whereas the target percentages of 33.3% for each group were not attained, the actual percentages were deemed close enough to be an adequate representation of the population.

Instrument

The 7-page, 50-item survey instrument was constructed to gather information on the full range of student experiences in high school that might impact a student’s choice to pursue a STEM or STEM-related career. Many items used were drawn from another survey study of students enrolled in introductory college science courses (Factors Influencing


College Science Success [FICSS]) that underwent rigorous validity and reliability checks (Sadler & Tai, 2007a; Sadler & Tai, 2007b). These items included: high school science and math course-taking history, standardized test performance, and background characteristics, such as gender, and parental education. A pilot survey was taken by 49 undergraduate students to adjust scales for ceiling and floor effects. These students also served as a focus group to help clarify wording. In addition, a focus group on the PRiSE survey was held with about ten experts in science education, including a psychometrician, former high school science teachers, and university-level science instructors. The discussion in this group indicated that the survey questions could be considered valid for the purpose of identifying students’ career aspirations and experiences during high school. Further, content validity was established through open-ended online surveys with 412 science teachers and professors to incorporate the breadth of views and hypotheses posed by the community. We also conducted a test-retest reliability study of 96 students who took the PRiSE survey and then completed it again after a two-week interval. Combining tests of both dichotomous and continuous variables (correlation coefficient and Cohen’s Kappa), the reliability of the survey was 0.70. Coupled with the large sample size, the likelihood of a reversal in the direction of effect of a variable is less than 0.04% (Thorndike, 1997). In the case of identification of career interest, test-retest agreement was high, 87.2% between the two administrations.

We were greatly influenced by the methodological practices of epidemiology in

which great care is employed when substituting recall for longitudinal data collection. We closely followed recommendations that improve accuracy and reliability in large-scale studies that depend on self-reported data (Bradburn, 2000; Niemi & Smith, 2003; Pace, Barahona, & Kaplan, 1985). Self-reports from college students of course-taking, grades earned, and standardized test scores tend to be highly accurate (Anaya, 1999; Baird, 1976). Kuncel, Credé, and Thomas (2005) found that self-report may be characterized as reasonably accurate in samples where the surveys address issues relevant to the respondents. In surveying college students, most in their first semester of college, reflection on their prior preparation and career aspirations would be commonplace. In addition, the students’ own professors (who were individually recruited by the project) administered the surveys in class at the start of the term, raising student compliance and perceived importance of the survey.

Variables

Subjects were asked to choose from multiple categories to characterize their career aspirations at several times prior to college. Among these were middle school (MS), beginning of high school (BHS), and end of high school (EHS). Interest in a medical profession was exhibited by 1,201 (18.2%) of our sample of 6,598 students when they were in MS. The interest level decreased to 957 (14.5%) at BHS and to 726 (11.0%) at EHS. The dummy variable EHS interest in medicine was used as the dependent variable in our logistic models, while interest at the earlier stages served as control.


In addition to gender (female=0, male=1), demographic information was collected on the level of each parents’ education (i.e., less than high school=1, high school=2, some college=3, four-year degree=4, graduate degree=5), the parent having a science-related career (yes=1, no=0), and race/ethnicity. The race/ethnicity variables were collected using the U.S. Census Bureau’s classification system (United States Census Bureau, 2010). Individuals were asked if they were of Hispanic origin and with which race they identified. In our study, participants who identified as being of Hispanic origin were labeled as Hispanic, and participants who did not identify as having Hispanic origins were grouped into the following (Non-Hispanic) categories: White, Black, Asian, and Other (including Native American Indian, Pacific Islander, and Other).

Of the students interested in medicine in middle school, 788 (65.6%) identified as

White, 162 (13.5%) identified as Hispanic, 100 (8.3%) as Black, 70 (5.8%) as Asian, and 81 (6.8%) as Other. These numbers changed to 608 (63.5%) White, 125 (13.1%) Hispanic, 86 (9.0%) Black, 64 (6.7%) Asian, and 74 (7.7%) Other by BHS and to 458 (63.1%) White, 99 (13.6%) Hispanic, 66 (9.1%) Black, 50 (6.9%) Asian, and 53 (7.3%) Other by EHS.

Because academic variables within each discipline of mathematics, English, and

science were found to correlate, composite variables were constructed. The math and English composites each contained the students’ grade in the most advanced math or English course taken in high school, their SAT/ACT math or English score, and, for the math composite, information on whether they took calculus in high school (Table 1). The variables were standardized, added, and standardized again for ease of interpretation. The science composite contained the count of the total number of science courses taken in high school and the average grade for each of those science courses. Like before, these variables were standardized, added, and standardized again (Table 1).

Table 1 Variables contained in academic composites before standardization (n=6,598) (A+=4.33, A=4.0, A-=3.67, B+=3.33, B=3.0, B-=2.67 etc.) Academic Composite

Variables Included in Composite Mean Standard Deviation

Math Composite

Grade in most Advanced Math Course 3.1 0.90 SAT/ACT Math 529 126 Took Calculus in High School 11.4%

English Composite

Grade in most Advanced English Course 3.5 0.72 SAT/ACT Verbal 532 103

Science Composite

Total Number of Courses (of possible 7) 3.0 1.50 Average Grade 3.3 0.67

Note: A+=4.33, A=4.0, A-=3.67, B+=3.33, B=3.0, B-=2.67 etc. A range of motivation variables were collected through the survey question that

asked subjects to “Rate the following factors in terms of their importance for your future career satisfaction” on a scale from 0 (not at all important) to 5 (very important). These values were standardized. A factor analysis was performed with varimax rotation to reduce


the overall number of variables yielding two distinct factors, which were named Intrinsic Motivation and Extrinsic Motivation. Extrinsic Motivation included the variables: importance of fame, leading, money, inventing, and an easy job. Intrinsic Motivation included the variables: importance of helping others, working with people, time for family, use of talent, career development, job security, personal time, job excitement, job opportunities, and making own career decisions. For each group, the standardized individual motivations were summed and standardized again to produce the composites Intrinsic and Extrinsic Motivation. Analytical Plan To address our first research question, the most appropriate means for analyzing the issue of medical career interest at EHS (a binary variable) was to construct logistic regression models that simultaneously tested multiple independent variables for significance. To address our second research question we compared significant variables from the most parsimonious logistic regression model by race/ethnicity for students in the medically interested and non-medically interested groups and then between students interested in medicine at EHS and students not interested in medicine by EHS within race/ethnicity.

Results

Predicting medical interest through logistic regression

Table 2 presents a series of logistic regression models. Model 0 contained only students’ race/ethnicity. Model 1 contained students’ background and prior interest. In Model 2, the academic composite variables were added (and parental education was removed, owing to its non-significance). Model 3 further added the motivation variables. In Model 4, all non-significant values from Model 3 were removed (with exception of race/ethnicity). Finally, we tested all possible interactions, and presented the significant ones in Model 5.

We selected the most parsimonious model (Model 4) to interpret. The odds of

reporting a medical career interest (rather than a career interest outside of medicine) at EHS were about eleven times higher for students who reported an interest in medicine at BHS than for students who did not report such an interest at BHS (Table 2). Additional positive effects were found for students who had medical career aspirations already in MS, who had a parent in a science-related field, and who identified as Asian. Furthermore, controlling for the other predictors, the odds of being interested in a medical career at EHS were 1.3 times greater for females than for males.

The odds of a student reporting a medical career interest at EHS increased by 1.3

times for each standard deviation increase in the Science Composite and 1.3 times for each standard deviation increase in Intrinsic Motivation. Conversely, the odds of not reporting a


medical career interest at EHS increased 1.2 times for each standard deviation increase in Extrinsic Motivation.

Whereas we found that the Math Composite and English Composite variables were

significant by themselves (p≤0.05, not shown), only the Science Composite was a significant predictor when all three composites were present in the model of wanting a medical career at EHS, owing to collinearities.

All interactions between the independent variables were tested for significance.

Two were found significant (Model 5) and graphed in Figure 1. Intrinsic motivation mattered slightly less in predicting EHS interest in medicine for Hispanic students and students who identified as Other than for White students (Figure 1 top). We also found for students with an interest at BHS in medicine, there was very little gender difference in their odds of persisting in that interest to EHS. Among students who were not interested in medicine at BHS, however, females became more attracted than males by the end (Figure 1 bottom).


Table 2 Logistic models predicting end of high school interest in medicine with odds-ratios and statistical significance of variable indicated

Note: Interactions indicated by asterisk between variables. The McFadden Pseudo R2 varies with each model. Differences in the amount of variance associated by Models 3, 4, and 5 are not significant, however the most parsimonious model is Model 4. Statistical significance noted: p=* < 0.05, **< 0.01, ***<0.001

Variable Model 0 Model 1 Model 2 Model 3 Model 4 Model 5

Interest BHS 11.6(0.11)*** 11.1(0.10)*** 10.9(0.10)*** 10.9(0.10)*** 9.20(0.12)***

Interest MS 1.54(0.11)*** 1.55(0.11)*** 1.52(0.11)*** 1.53(0.11)*** 1.54(0.11)*** Gender (male= 1) 0.71(0.09)*** 0.70(0.09)*** 0.76(0.10)** 0.75(0.10)** 0.58 (0.13)*** Parent Sci-Related Career 1.43(0.09)*** 1.40(0.09)*** 1.37(0.10)*** 1.35(0.09)*** 1.34(0.09)*** Total Parent Ed 1.01(0.02) Other 1.17(0.15) 1.30(0.18) 1.25(0.18) 1.29(0.18) 1.29(0.18) 1.04(0.29) Hispanic 0.88(0.15) 1.20(0.18) 1.18(0.14) 1.18(0.14) 1.17(0.14) 1.14(0.19) Black 1.24(0.15) 1.10(0.21) 1.20(0.17) 1.27(0.17) 1.24(0.17) 1.29(0.23) Asian 1.64(0.16)* 1.50(0.21)* 1.35(0.19) 1.48(0.19)* 1.48(0.19)* 1.48(0.28) Math Composite 1.01(0.05) 1.01(0.05) English Composite 1.07(0.05) 1.07(0.05) Science Composite 1.24(0.05)*** 1.24(0.05)*** 1.28(0.05)*** 1.27(0.05)*** Intrinsic Motivation 1.31(0.06)*** 1.33(0.06)*** 1.47(0.06)*** Extrinsic Motivation 0.84 (0.05)*** 0.83(0.05)** 0.84(0.05)*** Interest BHS * Gender 1.71(0.19)** Intrinsic Motivation * Hispanic 0.70(0.16)* Intrinsic Motivation * Other 0.69(0.17)* N 6598 6598 6598 6598 6598 6598 McFadden Pseudo R2 0.003 0.216 0.226 0.231 0.231 0.237


Figure 1. Interactions of logistic regression variables. Top: Odds predicting EHS interest in medicine vs. intrinsic motivation for White, Hispanic and Other race/ethnicities. Bottom: Interaction between BHS interest in medicine and gender when predicting EHS interest in medicine. Error bars indicate ±1 standard error (SE)

White


Describing detailed variable patterns

Addressing our second research question, we investigated to what extent the variables that were found to influence career interest in medicine at EHS showed differences by racial/ethnic groups. (Speaking more technically, we explored the collinearities of relevant independent variables.) Of the significant variables from Model 4 (Table 2), we examined the science composite, intrinsic motivation, and extrinsic motivation by race/ethnicity of the medically interested (Table 3 left) and non-medically interested (Table 3 right) groups. Looking specifically at the medically interested students by EHS we found that Black and Hispanic students had a lower science composite than White and Asian students, of which Asian students had the highest (Table 3). Our data also indicated complex differences in career motivations. Intrinsic motivation was highest among Black, Hispanic, and White students and lowest among Asian students. Black, Hispanic, and Asian students had the highest extrinsic motivation, not differing within ±1 standard error (SE). Extrinsic motivation was lowest among White students. Looking specifically at the non-medically interested students by EHS we found that Asian students had the highest science composite followed by White, Hispanic, and Black students, not differing by ±1 SE. Intrinsic motivation was highest among Black and Hispanic students and lowest among White and Asian students. Extrinsic motivation was highest among Black and Asian students, with Asian and Hispanic students not differing by ±1 SE. Hispanic students did differ from Black students by ±1 SE. Extrinsic motivation was lowest among White students.

Finally, we examined the differences between students interested in medicine at EHS and students not interested in medicine by EHS within race/ethnicity. Our data indicated that high school students with medical career aspirations tended to have a stronger science background (except among Black students) than did their peers (±1 SE) (Table 3). White and Black students interested in medicine had higher intrinsic and lower extrinsic career motivations than their non-medically interested counterparts. Asian students interested in medicine had lower extrinsic career motivations than Asian students not interested in medicine. The values from Table 3 were plotted in Figure 2 for ease of comparison.

Limitations

It is practically impossible to account for all variables associated with medical career interest by EHS. Clearly there were other variables, both positive and negative, at play that we did not measure. These may include scientific experiences students have within their high school courses, interactions with parents, teachers, or members of the medical community, as well as varying forms of media. Moreover, our study was correlational and could not prove causal connections between variables and outcomes. Nonetheless, the relationships identified by this kind of study are worthy of controlled, intervention studies (to the extent possible) that may establish, with increasing certainty, the suggested causal connections.


Table 3 Standardized Science Composite, Intrinsic Motivation, and Extrinsic Motivation variables by race/ethnicity of students with a medical interest at the end of high school (n=726) and students with non-medical interest at the end of high school (n=5,872)

Medical Interest EHS (n=726) Non-medical Interest EHS (n=5,872) Variables White Hispanic Black Asian Other All White Hispanic Black Asian Other All

Science Composite (±1 SE) SD

0.331 (0.286, 0.376) 0.963

0.157 (0.045, 0.269) 1.116

-0.080 (-0.206, 0.047) 1.029

0.608 (0.497, 0.719) 0.785

0.520 (0.388, 0.652) 0.960

0.306 (0.269, 0.342) 0.999

-0.018 (-0.033, -0.003) 0.964

-0.074 (-0.108, -0.041) 0.978

-0.227 (-0.275, -0.178)

1.06

0.257 (0.198, 0.317) 1.02

-0.034 (-0.090, 0.022) 1.04

-0.036 (-0.048, -0.023) 0.995

Intrinsic Motivation (±1 SE) SD

0.219 (0.181, 0.256) 0.803

0.304 (0.229, 0.379) 0.748

0.354 (0.232, 0.476) 0.992

-0.043 (-0.151, 0.066) 0.770

-0.050 (-0.187, 0.087) 0.996

0.204 (0.173, 0.234) 0.829

-0.054 (-0.068, -0.040) 0.917

0.205 (0.172, 0.237) 0.939

0.177 (0.126, 0.227) 1.104

-0.060 (-0.118, -0.002) 1.010

-0.096 (-0.161, -0.032) 1.192

-0.023 (-0.037, -0.010) 1.015

Extrinsic Motivation (±1 SE) SD

-0.170 (-0.211, -0.129) 0.868

0.203 (0.106, 0.300) 0.965

0.211 (0.094, 0.329) 0.953

0.043 (-0.074, 0.161) 0.831

-0.090 (-0.220, 0.040) 0.946

-0.077 (-0.110, -0.044) 0.899

-0.093 (-0.107, -0.079) 0.906

0.272 (0.237, 0.307) 1.015

0.464 (0.412, 0.515) 1.131

0.349 (0.288, 0.410) 1.055

-0.023 (-0.083, 0.037) 1.111

0.009 (-0.004, 0.023) 1.010

Note: Brackets indicate ±1 SE; SD indicates standard deviation

©2015 - Journal of Career and Technical Education, Vol. 30, No.1, 2015 –

Discussion and Conclusion

Our models showed that pre-high school factors predicted EHS interest in medicine more than any other tested variable. This result agreed with recent studies from the UK (Ferguson et al., 2012; Mcharg, Mattick, & Knight, 2007) and potentially highlight how early medical career intentions take shape and, thus, how important early strategies may be if one wants to foster students’ interest in medicine. When considering our second research question we found almost no racial/ethnic differences in interest in medicine, when controlling for relevant factors (Model 4), with the exception that Asians showed an elevated interest in medicine. We also found complex racial/ethnic differences in career motivations related to interest in medicine (Figure 2). For example, intrinsic motivation was highest among Black, Hispanic, and White students and lowest among Asian students. Yet, Black, Hispanic, and Asian students had the highest extrinsic motivation, not differing within ±1 SE. (Note that the intrinsic and extrinsic motivation variables were independent: a racial/ethnic group could have high means or low means on both.) These findings highlighted the comparatively high overall motivational variables of Black and Hispanic students at the start of college and could perhaps be related to socioeconomic status (Greenhalgh, Seyan, & Boynton, 2004) or broad cultural trends (Twenge, Campbell, Hoffman, & Lance,

2010). Finally, our data showed that a lower average level of scientific achievement set apart the Black and Hispanic students from the other students interested in a medical profession (Figure 2).

Figure 2. Standardized Intrinsic and Extrinsic Motivation means plotted against Science Composite means for five races/ethnicities by interest in medical and non-medical careers (n=6,598). Races/ethnicities include Black, Hispanic, White, Asian, and Other (Native American, Pacific Islander, Other). Area of circles and squares are proportional to N for each race/ethnicity. Errors bars indicate ±1 SE


Although sufficient numbers of Black and Hispanic students are interested in a career in

medicine at the end of high school to contribute to the needed improvement in the racial/ethnic physician patient match, not enough students apply to, enroll in, or graduate from medical school (Association of American Medical Colleges, 2010; Association of American Medical Colleges, 2014). Limited proficiency in science may impede further progress through the medical pipeline. To reach medical school enrollment students must first advance through various educational merit barriers (Southgate, Kelly, & Symonds, 2015) and, in the U.S., obtain premedical undergraduate education (Cooper, 2003). In U.S. premedical education, it is not the motivations of the students that earn them competitive grades and program completion, but their scholastic and, particularly, scientific achievement. Any negative academic experiences these students have in college may dissuade them from applying to medical school (Barr & Matsui, 2008). If students thus leave the premedical path early, interventions that recommend reforming the medical school admissions procedure (e.g., less emphasis on quantitative measures of success) may not reach them (Girotti, Park, & Tekian, 2015; Keith & Hollar, 2012).

For those wishing to develop intervention strategies that support URM students on the path toward medicine, strengthening the scientific achievement of high school (or pre-high school) students who already have an interest in medicine is recommended. If such programs start early and capitalize on high student motivations, they could potentially aid the development of scientific aptitude that helps students progress through various educational barriers. Ideas could be appropriated from the four-day Mini-Med School (Shaikh, Babar, & Cross, 2013) where students were exposed to the structure and vernacular of medical education, the epistemology of physician diagnosis, and the sub-fields of medicine. Special attention should be paid to the science curriculum of the area to ensure that programs build scientific competency. Such programs could elicit the dual benefit of not only bolstering pre-college interest in medicine, but also addressing the major barriers post-secondary science education provides. Both a sustained career interest and persistent high academic performance are needed for ultimate positive outcomes. While various critics of the standards of medical school admissions may advocate reforms, such as less emphasis on STEM skills and more emphasis on other factors, the current cohort of aspiring medical students needs support in navigating the system as it exists (before any reform takes hold).

Future research should investigate how the studied academic and motivation variables

play out in post-secondary education, and how they differ between races/ethnicities. Long-term effects of any interventions implemented should be studied.

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AUTHORS’ NOTE

T.T. Fuchs was a research assistant at the Science Education Department, Harvard-Smithsonian Center for Astrophysics, and student, Harvard Graduate School of Education, Cambridge, Massachusetts, United States, at the time this research was conducted. [email protected] P.M. Sadler is the F.W. Wright Senior Lecturer in the Department of Astronomy and Director of the Science Education Department, Harvard-Smithsonian Center for Astrophysics, Cambridge, Massachusetts, United States. [email protected] G. Sonnert is a research associate at the Science Education Department, Harvard-Smithsonian Center for Astrophysics, Cambridge, Massachusetts, United States. [email protected] Funding/Support: This project was carried out under grant #0624444 from the National Science Foundation. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Acknowledgments: The authors would like to thank the PRiSE team for their dedicated work and all the participating English professors and their students for making this study possible.


Racial/Ethnic and Gender Equity Patterns in Illinois High School Career and Technical Education Coursework

Asia Fuller Hamilton

University of Illinois

Joel Malin Miami University

Donald Hackmann University of Illinois

ABSTRACT

This study analyzed high school Career and Technical Education (CTE) enrollments in Illinois, with comparisons to national data when possible, by career cluster and pathway and with respect to gender and racial/ethnic makeup of students. Enrollment patterns in Science, Technology, Engineering, and Math (STEM) CTE programming were emphasized. Gender and ethnicity-based inequities were found in certain areas and more equitable patterns were apparent in others. Of concern, student enrollment in courses fitting within STEM pathways included substantially greater male than female participation (64.1% male vs. 35.9% female), whereas other pathways showed the reverse enrollment pattern (45.0% male and 55.0% female). With respect to ethnicity, all subgroups except White students were underrepresented in CTE programming in general. The underrepresentation was exacerbated for all but Asian students when concerning STEM CTE programming. Considering implications, we recommend heightened focus, support, and goal setting concerning equity of CTE programming.

Introduction

Attaining equitable career pathways for high school students requires educators to engage in honest, reflective discourse concerning data, construct an understanding of the term “equity,” and determine how underlying assumptions may influence a school’s progress toward providing a rigorous curriculum that prepares every student for college and careers (Welton & LaLonde, 2013). Racial/ethnic and gender inequities existing within Career and Technical Education (CTE) course enrollments restrict students’ access to Science, Technology, Engineering, and Mathematics (STEM) fields, not only as they attempt to transition to postsecondary educational experiences but also as they matriculate into STEM occupations (Fletcher, 2012).

As the knowledge-based economy has grown in the U.S., jobs in high-technology fields

are expanding but postsecondary institutions are producing insufficient numbers of graduates in these fields (Fletcher, 2012). To maintain our nation’s global competitiveness, a focus on equity is critical as all high school graduates strive to gain access to postsecondary career and educational opportunities. Amid reports that women, non-Hispanic Blacks, and Hispanics have been consistently underrepresented in STEM occupations (Beede, Julian, Khan et al., 2011; Beede, Julian, Langdon et al., 2011), racial and gender compositions within high school CTE


STEM programs of study, in particular, require closer examination. Racial and ethnic inequities existing within CTE course enrollments restrict students’ access to STEM fields, not only as they attempt to transition to postsecondary educational experiences but also as they matriculate into STEM occupations (Fletcher, 2012). Therefore, the purpose of this study was to examine participation patterns of historically underrepresented students within high school CTE courses in STEM fields. This article begins with an overview of research on participation in career fields by gender and race/ethnicity, with a focus on STEM, and then presents findings from an analysis of public high school CTE enrollments in the state of Illinois. In the discussion and implications section, we integrate our findings with existing literature. We conclude with recommendations for educational leaders and policymakers.

Review of Literature

Career and technical education has evolved in the past two decades from its initial

mission to integrate manual vocational training into the secondary curriculum to meet the industrial needs of the nation (Fletcher, 2012). As our knowledge-based economy has shifted, so too have expectations for students’ academic preparation. High school practices historically steered students into either academic tracks for college-bound students or vocational tracks for students who were perceived as being more inclined to enter the workforce after high school (Hess, 2010). Vocational coursework has been perceived as being less rigorous and associated with low prestige and low-wage occupations (Fletcher, 2012). Hess (2010) claimed that “vocational education has reinforced social divisions along racial lines, as black students have been far more likely to be enrolled in vocational education than are white students” (p. 119).

One consequence of lowered academic expectations for students is the skills gap in the

U.S. workforce, with many young adults lacking essential knowledge and skills to be productive workers in our knowledge-based economy (Symonds, Schwartz, & Ferguson, 2011). This gap is particularly challenging in the state of Illinois, where 80% of jobs within the state require some form of postsecondary training but only 41% of adults have attained industry credentials or earned postsecondary degrees (Advance Illinois, 2012). In recent years, policymakers and educators across the U.S. have acknowledged this gap in expectations. Thirty-five states have joined the American Diploma Project (2004), with a goal of improving secondary preparation so that students are ready for college and work (Achieve, 2014), and college and career readiness standards have been formulated as a result of this project. According to Achieve (2014),

college and career readiness means that a high school graduate has the knowledge and skills necessary to qualify for and succeed in entry-level, credit-bearing postsecondary coursework without the need for remediation—or to qualify for and succeed in the postsecondary job training and/or education necessary for his or her chosen career. (p. 6)

Achieve further notes: “To be college and career ready, high school graduates must have studied a rigorous and broad curriculum that is grounded in the core academic disciplines but also consists of other subjects that are part of a well-rounded education” (p. 6).

The Carl D. Perkins Career and Technical Education Act of 2006 (Perkins IV) provides funds to each state for CTE programming and has been influential in expanding definitions of CTE beyond traditional concepts of vocational education. Perkins IV requires programs of study to include rigorous academic and career/technical content, with courses sequenced in a


coordinated, non-duplicative manner and containing both secondary and postsecondary elements. In addition, programs should lead to an industry-recognized credential, postsecondary certificate, and/or degree and include opportunities for students to earn dual credit or dual enrollment. CTE coursework has the potential not only to prepare students for college and careers but also to disrupt race and gender inequity patterns within STEM professions (U.S. Department of Education, 2014). In recent years, and promoted through Perkins IV, high school educators have made strides in making CTE courses more academically challenging and have focused on preparing students for additional training beyond high school (Fletcher, 2012).

The National Career Clusters Framework (National Association of State Directors of

Career Technical Education Consortium, n.d.) has developed 16 career cluster areas: Agriculture, Food and Natural Resources; Architecture and Construction; Arts, Audio/Video, Technology and Communications; Business Management and Administration; Education and Training; Finance; Government and Public Administration; Health Sciences; Hospitality and Tourism; Human Services; Information Technology; Law, Public Safety, Corrections and Security; Manufacturing; Marketing; Science, Technology, Engineering and Mathematics; and Transportation, Distribution and Logistics. The state of Illinois has adopted these 16 career clusters within its state model (Nicholson-Tosh & Bragg, 2013), and Perkins IV funding at the

secondary level is provided for CTE coursework in all cluster areas, with the exception of

Government and Public Administration. In its federal Race to the Top (RttT) application, the State of Illinois (2011) identified eight career clusters as STEM fields, with a goal to expand CTE programs of study within these clusters in Illinois school districts participating in RttT activities. The Illinois STEM clusters include Agriculture, Food and Natural Resources; Architecture and Construction; Finance; Health Sciences; Information Technology; Manufacturing; Science, Technology, Engineering and Mathematics; and Transportation, Distribution and Logistics. The Illinois RttT application also included a performance measure to increase the enrollments of underrepresented high school students participating in STEM programs of study. Within the state of Illinois, Perkins IV funding is provided to school districts when they obtain approval for specified CTE programs of study within the career cluster areas. CTE educators are required to engage in curriculum development activities, offering courses that meet minimum program of study requirements. Through Illinois RttT activities, funding has been provided for the creation of centers—known as Learning Exchanges—whose function is to develop curriculum materials within the Illinois-defined STEM career cluster areas. In the following sections, we address participation in CTE fields by gender and race/ethnicity; we also address student enrollments in the Illinois-defined STEM fields, when relevant.

Gender Participation

The U.S. Department of Education (2014) defines nontraditional fields as “those in which individuals from one gender comprise less than 25 percent of the individuals employed in the occupation or field of work” (p. 36). It is important to note that this definition encompasses both sexes, although females typically are more likely to experience the negative effects of gender inequities. For example, the U.S. Bureau of Labor Statistics (2013) reported that females earn only 81% of the median wages earned by full-time male workers. Domenico and Jones (2006) also noted that women traditionally have worked within only 20 of 400 job categories, which tend to be lower paying occupations. Females comprise nearly half of the U.S. workforce, yet


only about one in five workers in scientific and technological fields are women (Committee on Science, Engineering, and Public Policy, 2007). In addition, females are underrepresented in STEM CTE coursework (National Coalition for Women and Girls in Education [NCWGE], 2012; National Women’s Law Center [NWLC], 2007; Toglia, 2013).

Reviewing data from the 1997 National Longitudinal Survey of Youth, Fletcher (2012)

found that gender was significantly related to high school students’ career choices. Females were nearly twice as likely to select occupations in Health Sciences and Human Services than were males, while males were 20 times more likely to select occupations in Agriculture, Food and Natural Resources and nearly 17 times more likely to select occupations within Transportation. In fiscal year 2012, 47% of students enrolled in high school CTE courses in the U.S. were females (National Alliance for Partnerships in Equity [NAPE], 2014). Examining national CTE enrollment patterns, Lufkin et al. (2007) found that no states reported having more than 25% of females enrolled in nontraditional coursework, leading them to conclude that “girls are preparing for traditionally female occupations at a disproportionately high rate” (p. 428). Reviewing STEM high school course enrollment trends between 1990 and 2005, Laird, Alt, and Wu (2009) reported that both males and females had experienced increases in STEM credits, with females earning slightly more credits in advanced mathematics and science and engineering coursework, and males earning slightly more credits in physics, computer science, engineering, and engineering/science technologies. However, gender differences were not significant.

Although the majority of research tends to focus on the negative effects of gender

inequities for women, this issue is also a concern for men in fields in which they are underrepresented. For example, only 6% of registered nurses in the U.S. are males (Lucci, 2007). Both females and males may be confronted with gender stereotypes when they attempt to access coursework within their chosen occupations (Lufkin et al., 2007).

Several factors may contribute to female under-participation within STEM-related career

fields, including lack of self-confidence and loss of interest in science and math during middle school (National Science Foundation (2003). Lufkin et al. (2007) cited eight potential reasons for inequities within CTE that may affect both genders: (a) insufficient exposure to nontraditional occupations and role models, (b) students’ attitudes regarding certain occupations, (c) gender-biased career guidance practices and published materials (d) insufficient encouragement to enroll in STEM coursework, (e) use of gender-stereotyped curricula and instructional approaches, (f) school and classroom climates that isolate students who choose to enroll in nontraditional CTE courses, (g) lack of student self-efficacy, and (h) limited individual support services for students.

Race/Ethnicity Participation Students’ racial or ethnic backgrounds may influence their enrollment in rigorous high school programs of study. According to Rojewski and Xing (2013), race/ethnicity potentially affects students’ perceptions of career opportunities and barriers, as well as their decisions to enroll in CTE coursework. Of concern, just one fourth of CTE research specifically reports the racial/ethnic composition of the research samples.


Historical influences regarding race/ethnicity play a role in enrollments in high school CTE programs. Compared to those who intend to enroll in postsecondary education, youth who plan to enter the workforce immediately after high school are disproportionately male, from minority backgrounds, and/or exhibiting lower academic performance than their peers (Rojewski & Kim, 2003). Racial discrimination, systemic exposure to less academically rigorous curricula, and unfavorable societal perceptions of persons on the basis of their racial or ethnic backgrounds are factors that contribute to stratification of educational and occupational attainment (Fletcher 2012; Rojewski & Kim, 2003). There has been national support to close the equity gap that exists for minorities in high school CTE programs, and recent research indicates some progress on this front. Analysis of CTE student enrollments across the U.S. by race in fiscal year 2012 disclosed that 52% were White, 23% Hispanic, 16% Black, 4% Asian, 2% two or more races, 1% American Indian or Alaska Native, and 1% Native Hawaiian or Other Pacific Islander (NAPE, 2014); these proportions were in close alignment with overall secondary enrollment data.

Race/ethnicity still remains a critical factor in STEM occupational fields and course

enrollments. Data from the 1997 National Longitudinal Survey of Youth determined that Whites were 2.4 times more likely than were African Americans and 4.5 times more likely than Hispanics to be employed in STEM occupations (Fletcher, 2012). Reviewing STEM high school course enrollments between 1990 and 2005, Laird et al. (2009) found that all racial/ethnic groups had experienced increases in STEM credits, but White and Asian/Pacific Islander students earned more credits than Black and Hispanic students. Many children begin reaching decisions about career fields at an early age, which may serve to restrict access into STEM fields for students of color. Riegle-Crumb, Moore, and Ramos-Wada (2010) reported that racial/ethnic disparities exist in math and science career aspirations well before students enter into high school, with students of color less likely to identify these fields. Dynamics such as one’s attitude toward certain occupations may contribute to reduced participation of non-White females in math and science fields and can influence occupational choices later in life.

Tracking enrollment patterns into postsecondary settings also can provide insights into

STEM participation, and research confirms that women and minorities exhibit higher rates of leaving STEM fields of study than do their peers (Shaw & Barbuti, 2010). Following a cohort of undergraduate students majoring in STEM fields between 2003-2006, Chen (2013) observed that approximately 28% of entering students pursuing bachelor’s degrees and 20% pursuing associate’s degrees were enrolled in STEM fields, which Chen identified as mathematics, physical sciences, biological/life sciences, computer and information sciences, engineering and engineering technologies, and science technologies. However, 48% of those enrolled in bachelor’s degree programs and 69% enrolled in associate’s degree program had left these STEM fields by spring 2009. Attrition rates for Black and Hispanic students were higher than those for other racial/ethnic groups, and females were more likely to transfer than were males (Chen). Focusing on female and minority students at the high school level may affect the likelihood that they will remain within STEM fields of study throughout college and into the workforce.


Conceptual Framework

This study was motivated and framed by cultural reproduction theory (Bourdieu & Wacquant, 1992). Cultural reproduction has been defined as “the complex ideological and cultural processes that reproduce social forms such as racism, gender bias, authority structures, attitudes, values, and norms” (Zacharakis & Flora, 2005, p. 293). These processes help to explain how and why group-based inequalities, once established, tend to be highly resistant to change. In large part, this tendency toward reproduction is supported by dominant groups’ efforts to preserve their advantages (Bourdieu & Wacquant; Giroux, 1983), for instance by securing access to better funded or higher quality schools. Although the education system is positioned as a central mechanism for cultural reproduction (Sullivan, 2002), arguably, it is the responsibility of educators to establish practices within their schools to counter it (e.g., to promote social mobility by opening up new opportunities to members of historically oppressed groups; Marshall & Oliva, 2006). Nevertheless, even in the midst of significant reform efforts, such as those previously described and intended to increase non-traditional students’ participation in CTE programs of study, large-scale improvements may not come about easily. Powerful psychological and institutional counterforces may serve to buttress the status quo. Given the focus of this study, most pertinent are cultural reproduction processes related to gender and race/ethnicity with respect to CTE enrollments. A large body of literature supports the historical and continued salience in the U.S. of individuals’ race/ethnicity and gender; these features affect students’ daily experiences and may influence their real or perceived access to, or suitability for, a variety of socially-valued opportunities (Darling-Hammond, 2010; Lufkin et al., 2007; Rojewski & Kim, 2015). In terms of education, and specifically regarding the provision of CTE, there are several structural and psychological reasons why inequities of access or participation might arise and persist. Structurally, the decentralized schooling system in the U.S. invariably fosters wide differences in terms of available resources (and, therefore, the types and qualities of school counseling services and programmatic offerings) by school district (Ladson-Billings, 2014; Malin, 2015). The state of Illinois is no exception, as its funding inequities across school districts are persistent and sizeable (Baker, Sciarra, & Farrie, 2014; Malin & Noppe, 2015). Too, in the face of resource limitations, schools and districts have been shown to ration their “high-quality curriculum through tracking and interschool disparities” (Darling-Hammond, 2010, p. 30). Closely related are individuals’ (e.g., students, parents, teachers, or counselors) beliefs and attitudes, which too often incorporate deficit thinking and serve to reinforce the status quo (Valencia, 2012). For instance, a teacher or counselor who perceives nursing as a field that is better suited for women may be more likely to encourage female students to enroll in CTE courses in the health sciences field (Lufkin et al., 2007). Likewise, a student might internalize that certain career fields or courses of study are not for them based upon negative messages, both implicit and explicit, that they have received from their peers, educators, and parents. Altogether, these factors would help to explain an underrepresentation of females (NCWGE, 2012; NWLC, 2005; Toglia, 2013) and minorities (Rojewski & Kim, 2013) in STEM CTE coursework. Therefore, guided by our understanding of cultural reproduction theory as it applies to U.S. public schooling systems, we were motivated to examine Illinois students' participation, by gender and race/ethnicity, in different types of CTE programming.


Our research center has been involved throughout the past three years in supporting the implementation of STEM CTE programs of study in Illinois school districts that are participating in the federal Race to the Top initiative. As part of our district supports and to discern any state-related issues involving students’ access to CTE programming, we were interested in examining differences in Illinois CTE enrollments for both STEM and non-STEM programming. Guided by our understanding of cultural reproduction theory as it applies to United States public schooling systems, our study addressed the following research questions:

1. What are Illinois students’ CTE enrollment patterns, by gender, in both STEM and non-STEM career cluster areas?

2. What are Illinois students’ CTE enrollment patterns, by race/ethnicity, in both STEM and non-STEM career cluster areas?

Research Methods

We requested and obtained a dataset from the Illinois State Board of Education containing duplicated high school enrollments in CTE programs of study for the 2012-13 school year for every Illinois public high school and career center. First, we performed exploratory data analysis techniques (Tukey, 1977) to the dataset, looking especially for unusual data patterns (e.g., unusually high enrollments given the size of a particular high school, etc.) that might suggest data corruption. Uncovering no such issues, we proceeded to modify the dataset in a manner that would permit us to analyze our research questions. Namely, we added data elements, associating each program of study with the career pathway and the career cluster to which it belonged, and tagging each with a “0” to represent a non-STEM area or a “1” to represent a STEM area, based upon state of Illinois definitions of STEM career cluster areas in the Race to the Top application (State of Illinois, 2011).1 Fifteen of the 16 Illinois Career Cluster areas were represented, as were 40 career pathways. Eight of these 15 career clusters and 20 of 40 career pathways are considered to represent STEM cluster areas. As part of our research center activities, we were interested in noting participation of Illinois high school students in both STEM and non-STEM fields, to determine if differences existed by gender and race/ethnicity.

In analyzing data for this study, we aggregated program of study enrollments by gender and race/ethnicity to the career cluster and pathways (limited to STEM cluster areas) levels. We also analyzed national high school CTE enrollments from the 2011-12 school year (U.S. Department of Education, n.d.), which was the most recent CTE dataset available, so comparisons could be made between the state of Illinois and national enrollment patterns. This national dataset represented a compilation of states’ 2011-12 annual reports to the U.S. Department of Education (per Perkins IV requirements); although we could not confirm the accuracy of the data, we chose to employ it given the source and our desire to make a nation-wide comparison to contextualize the Illinois gender data.

1 The STEM career clusters, with rankings showing popularity (Illinois duplicated student enrollments) in parentheses, are as follows: Finance (1); Health Science (2); Agriculture, Food, and Natural Resources (5); Architecture and Construction (7); Transportation, Distribution, and Logistics (8); Manufacturing (9); Information Technology (10); and Science, Technology, Engineering, and Mathematics (11).


Because we were able to access secondary CTE enrollment data from all school districts in Illinois, we considered our data set as representing population-level data. We were not working with sample data, so it was unnecessary to conduct inferential statistical analyses. Our findings, based upon descriptive data analyses, represent the full context of Illinois high school CTE enrollments in 2012-13. To address our research questions, we cross-tabulated information and calculated enrollment percentages in different CTE programs and clusters by gender and race/ethnicity, respectively. We then aspired to assess the proportionality or disproportionality of enrollments and employed the following reasoning to aid our interpretations. With respect to gender, we assumed that parity, reflected by equally proportioned (50% male, 50% female) participation in CTE programming, is ideal. Because this ideal of exact equality in gender participation in each cluster area is mathematically improbable, we employed a 20% range (40-60% female participation) as our working definition of gender parity for the purposes of this study. Therefore, we considered that gender parity had been approached when participation fit this pattern. With respect to race/ethnicity, to assess the extent of parity, we compared CTE participation rates by race/ethnicity to the racial/ethnic distribution of the total Illinois public high school student population.

Findings

Illinois CTE Participation Rates, by Gender Gender and career cluster. Substantial gender-based inequities were found in certain career cluster areas. Illinois public high school CTE student enrollments in courses fitting within the Illinois-defined STEM career clusters included substantially greater male (64.1%) than female (35.9%) participation, whereas non-STEM clusters showed the reverse participation pattern. In total, 364,388 enrollments (233,664 male and 94,837 female) were recorded in STEM clusters, and 210,976 enrollments (116,139 female and 94,837 male) were recorded in other career clusters. Table 1 shows the full set of Illinois CTE enrollments by career cluster and gender in Illinois. Applying the U.S. Department of Education (2014) definition (25% or less participation) of a nontraditional occupation to CTE enrollments across genders, females were substantially underrepresented in four career cluster areas, which are defined within the state of Illinois as STEM fields: Architecture and Construction; Transportation, Distribution, and Logistics; Manufacturing; and Science, Technology, Engineering, and Mathematics. Males were substantially underrepresented in two career cluster areas, which are not Illinois-identified STEM fields: Human Services, and Education and Training.

If gender parity is the goal, then relatively similar proportions of males and females

should be enrolled in CTE coursework within each career cluster area. Examining CTE enrollment patterns across the United States, several cluster areas approached gender parity (Table 2). Using our working definition of 40-60% female participation as gender parity, we noted parity had been approached in U.S. CTE enrollments for two STEM clusters: Finance, and Agriculture, Food and Natural Resources. Comparing state of Illinois high school student CTE enrollments to national enrollments in the STEM fields, Illinois enrollments showed greater gender-based disproportionality in all Illinois-defined STEM career cluster areas except Health


Science. Applying the 40-60% participation range for females in the Illinois STEM clusters, Illinois approaches parity only in Finance.

Table 1. Illinois and U.S. High School CTE Enrollment Percentages by Career Cluster and Gender

Career Cluster IL CTE Ran

k

Total Enrollmen

t

Percent of Total

Enrollment

Male Enrollmen

t (N)

Female Enrollmen

t (N)

Male (%)

Female (%)

Finance 1 98,619 17.1 55,565 43,054 56.3 43.7 Health Science 2 80,526 14.0 31,619 48,907 39.3 60.7 Human Services 3 66,950 11.6 15,343 51,607 22.9 77.1 Arts, A/V Technology and Communications

4 61,592 10.7 40,113 21,479 65.1 34.9

Agriculture, Food and Natural Resources

5 48,826 8.5 30,963 17,863 63.4 36.6

Business, Management and Administration

6 43,679 7.6 24,806 18,873 56.8 43.2

Architecture and Construction

7 36,488 6.3 32,471 4,017 89.0 11.0

Transportation, Distribution and Logistics

8 30,847 5.4 28,608 22,39 92.7 7.3

Manufacturing 9 27,798 4.8 23,047 4,751 82.9 17.1 Information Technology

10 22,820 4.0 15,775 7,045 69.1 30.9

Science, Technology, Engineering and Mathematics

11 18,464 3.2 15,616 2,848 84.6 15.4

Hospitality and Tourism

12 16,221 2.8 6,378 9,843 39.3 60.7

Marketing 13 14,089 2.4 4,971 9,118 35.3 64.7 Education and Training

14 4,351 0.8 366 3,985 8.4 91.6

Law, Public Safety, Corrections and Security

15 4,094 0.7 2,860 1,234 69.9 30.1


Table 2. Illinois and United States High School CTE Enrollment Percentages, By Career Cluster and Gender

Career Cluster Illinois Female (%)

United States Female (%)

Finance 43.7 48.7 Health Science 60.7 66.2 Human Services 77.1 71.7 Arts, A/V Technology and Communications 34.9 41.5 Agriculture, Food and Natural Resources 36.6 41.6 Business, Management and Administration 43.2 47.6 Architecture and Construction 11.0 18.5 Transportation, Distribution and Logistics 7.3 13.5 Manufacturing 17.1 18.7 Information Technology 30.9 38.9 Science, Technology, Engineering and Mathematics 15.4 30.8 Hospitality and Tourism 60.7 53.8 Marketing 64.7 50.2 Education and Training 91.6 69.4 Law, Public Safety, Corrections and Security 30.1 42.0 Source: U.S. Department of Education, Office of Career, Technical, and Adult Education. (n.d.) Gender and career pathway. We also analyzed participation in Illinois high school CTE courses by gender and career pathway, limiting our focus to career pathways that fall within STEM clusters. As expected, we found gender participation patterns by pathway within Illinois-defined STEM clusters to be quite variable, and prima facie these patterns appeared to mirror occupational data that we have reviewed. For instance, male participation within the Health Science career cluster ranged from 13.0% and 16.3% in the health informatics and therapeutic pathways, respectively, to 46.5% in the diagnostic services pathway (Table 3).


Table 3. Illinois High School CTE Enrollments by STEM Career Pathway and Gender, 2012-13

Cluster Pathway Male (N)

Female (N)

Male (%)

Female (%)


Plant Systems 11,648 9,476 55.1 44.9 Power Structure and

Technical Systems 11,168 3,693 75.1 24.9

Natural Resources Systems 8,147 4,694 63.4 36.6 Architecture and

Construction

Construction 18,172 1,678 91.5 8.5 Design/Pre-Construction 13,869 2,220 86.2 13.8 Maintenance/Operations 430 119 78.3 21.7

Finance Financial and Investment Planning

55,565 43,054 56.3 43.7

Health Science Support Services 28,181 33,360 45.8 54.2 Therapeutic Services 2,839 14,566 16.3 83.7 Diagnostic Services 410 472 46.5 53.5 Biotechnology 186 489 27.6 72.4 Health Informatics 3 20 13.0 87.0 Information Technology

Network Systems 10,886 5,674 65.7 34.3 Programming and Software

Development 4,889 1,371 78.1 21.9

Manufacturing

Production 17,054 1,391 92.5 7.5 Maintenance, Installation and

Repair 5,813 1,743 76.9 23.1

Manufacturing Production Process Development

180 1,617 10.0 90.0

Science, Technology, Engineering, and Mathematics

Engineering and Technology 15,616 2,848 84.6 15.4


Facility and Mobile Equipment Maintenance

24,495 1,768 93.3 6.7

Transportation Operations 4,113 471 89.7 10.3 Illinois CTE Participation Rates, by Race/Ethnicity Race/ethnicity and career cluster. Conspicuous racial/ethnic participation differences in Illinois CTE enrollments were found in several career cluster areas (Table 4). For instance, Asian students’ participation in the Science, Technology, Engineering, and Math career cluster, representing 9.7% of enrollments while comprising 4.3% of the overall population, was striking. Black students’ participation in all but one career cluster area (Hospitality and Tourism; 22.7%) was lower than what would have been expected based upon their 18.0% makeup of the total Illinois public high school population. Likewise, Hispanic students, who comprise 21.5% of the Illinois public high school population, were underrepresented in all areas except Transportation, Distribution, and Logistics (23.6%). White students were overrepresented in every career cluster


area. Because nationwide CTE data disaggregated by race/ethnicity were not reported, we were unable to compare the state of Illinois to national CTE enrollments on this factor. Table 4. Illinois High School CTE Enrollments by Career Cluster and Race/Ethnicity, 2012-13

Career Cluster Asian (%)

Black (%)

Hispanic (%)

White (%)

Other (%)

State Enrollment Data, FY 2013 4.3 18.0 21.5 53.4 2.9 Finance 3.4 15.7 15.5 62.7 2.7 Health Science 3.5 16.6 17.7 59.5 2.8 Human Services 2.0 11.2 15.1 68.8 3.0 Arts, A/V Technology and Communications 2.4 15.2 18.7 60.9 2.7 Agriculture, Food and Natural Resources 0.4 4.0 3.8 90.2 1.6 Business, Management and Administration 3.6 14.6 13.6 65.3 2.9 Architecture and Construction 2.0 9.3 14.7 71.4 2.6 Transportation, Distribution and Logistics 2.1 11.6 23.6 60.2 2.4 Manufacturing 1.6 9.4 13.5 72.9 2.5 Information Technology 4.7 10.1 14.8 67.7 2.9 Science, Technology, Engineering and Mathematics 9.7 7.2 14.2 65.9 3.1 Hospitality and Tourism 1.7 22.7 18.9 53.9 2.8 Marketing 3.3 14.3 15.8 63.7 2.9 Education and Training 5.4 7.8 17.6 65.8 3.4 Law, Public Safety, Corrections and Security 0.8 8.4 19.2 68.8 2.8

Interesting patterns also were evident when data were analyzed in terms of participation

rates in Illinois CTE courses by race/ethnicity for Illinois-defined STEM clusters and other career clusters (Figure 1). White (67.6% STEM, 64.2% other) and Asian (3.0% STEM, 2.6% other) students’ proportional participation rates were greater in STEM than other career clusters, whereas the reverse pattern was found for Black (12.1% STEM, 14.1% other), Hispanic (14.8% STEM, 16.3% other), and “other” racial/ethnic groups (2.6% STEM, 2.9% other).


Figure 1. Illinois CTE Enrollments by Race/Ethnicity, for STEM and Other Career Clusters, 2012-13

Race/ethnicity and career pathway. We also analyzed participation in Illinois CTE

courses by race/ethnicity and career pathway, limiting our focus to career pathways within Illinois-defined STEM clusters. We found racial/ethnic participation patterns by STEM pathways to be quite variable. For instance, within Information Technology, Black student participation ranged from 7.8% in the Network Systems Pathway to 16.0% in the Programming and Software Development Pathway. Hispanic students’ participation in Information Technology showed a reverse pattern: Hispanic students comprised 13.8% of the enrollments in Network Systems and 17.2% of the enrollment in Programming and Software Development. The pattern of findings underscores the importance of viewing the data at this level of detail, in addition to the career cluster and individual course levels.


Table 5. Illinois High School CTE Enrollments by STEM Career Pathway and Race/Ethnicity, 2012-13

Career Cluster Pathway Title Asian (%)

Black (%)

Hispanic (%)

White (%)

Other (%)


Plant Systems 0.5 5.5 4.7 87.6 1.7 Power Structure and

Technical Systems 0.3 3.2 3.2 91.8 1.5

Natural Resources Systems

0.3 2.5 3.0 92.7 1.6

Architecture and Construction

Construction 1.2 10.8 14.3 70.8 2.8 Design/Pre-Construction 3.1 7.4 14.4 72.7 2.4 Maintenance/Operations 1.5 11.3 32.8 53.0 1.5

Finance Financial and Investment Planning

3.4 15.7 15.5 62.7 2.7

Health Science Support Services 2.6 15.3 16.7 62.6 2.8 Therapeutic Services 6.8 20.4 21.6 48.6 2.6 Diagnostic Services 2.0 5.0 12.4 78.0 2.6 Biotechnology 4.1 48.9 10.2 35.0 1.8 Health Informatics 8.7 26.1 17.4 47.8 0.0 Information

Technology

Network Systems 3.6 7.8 13.8 72.0 2.8 Programming and

Software Development 7.6 16.0 17.2 56.2 3.0

Manufacturing Production 0.7 6.1 11.0 79.5 2.7 Maintenance, Installation

and Repair 3.3 16.1 19.3 59.3 2.0

Manufacturing Production Process Development

4.2 14.8 15.0 62.6 3.4

Science, Technology, Engineering, and Mathematics

Engineering and Technology

9.7 7.2 14.2 65.9 3.1


Facility and Mobile Equipment Maintenance

Transportation Operations

2.2

2.0

11.8

10.6

23.3

25.5

60.3

59.8

2.5

2.2

Discussion and Implications

We analyzed the distribution of Illinois high school CTE enrollments by career pathway and career cluster, paying special attention to STEM programming due to its current policy emphasis in the U.S. and nationally. There were pronounced gender and ethnicity-based inequities in certain pathways and clusters. Enrollments in courses fitting within Illinois-defined STEM pathways included substantially greater male than female participation (64.1% male, 35.9% female), whereas non-STEM pathways showed the reverse (45.0% male, 55.0% female). With respect to race/ethnicity, all subgroups except White students were underrepresented in CTE programming in general. Moreover, when we limited our focus to STEM CTE


programming, underrepresentation was exacerbated for all but Asian students. Comparing Illinois CTE enrollments to nationwide enrollment statistics, there were greater gender disparities in Illinois in nearly all career cluster areas, which is particularly troubling and reinforces the urgency of Illinois policymakers’ RttT focus on STEM programming within the state’s high schools. The findings from our study provide support for cultural reproduction theory, as these inequalities by gender and race/ethnicity appear to be persistent in the state of Illinois and highly resistant to change.

Our findings also are consistent with national data indicating underrepresentation of females in STEM CTE coursework (NCWGE, 2012; NWLC, 2007; Toglia, 2013). Under-enrollments appear to be commonplace in the state of Illinois, despite Perkins IV goals to achieve more equitable outcomes in CTE coursework. These results are concerning, because students’ identification of career pathways and course selections during their high school years can serve to restrict their future career and earning prospects. Female students, for example, are more likely to enroll in career cluster areas that have lower mean salaries (U.S. Department of Labor, n.d.), which likely perpetuates ongoing issues regarding wage inequities for females in the U.S. workforce. In this discussion section, we address our findings as they relate to gender and race/ethnicity equity within CTE programming.

Gender Illinois CTE enrollment data reflected a large discrepancy in male and female participation within many career cluster areas that have been defined as STEM-related within the state of Illinois. These disparities are particularly pronounced for females in the career cluster areas of Transportation, Distribution and Logistics (7.3% female enrollments); Architecture and Construction (11.0% female); Science, Technology, Engineering and Mathematics (15.4% female); and Manufacturing (17.1% female). Greater male enrollments in STEM clusters and greater female participation in non-STEM clusters within Illinois are consistent with the disproportionality in national workforce trends citing the lack of female employment in STEM fields (Committee on Science, Engineering, and Public Policy, 2007). Both males and females were underrepresented in Illinois CTE enrollments in numerous cluster areas. Males were substantially underrepresented in two cluster areas; females were substantially underrepresented in four cluster areas that are identified within the state of Illinois as STEM fields. With respect to gender parity, applying our working definition of 40-60% female participation range, Illinois approached parity only in one of the eight Illinois-defined STEM cluster areas (Finance). Illinois enrollments demonstrated greater gender-based disproportionality in all STEM career cluster areas except Health Sciences. While we conducted relatively limited analysis career pathways, we did find that pathways within STEM clusters had varied participation patterns by gender, but these generally mirrored occupational data (U.S. Department of Labor, n.d.). It was especially concerning, when comparing enrollments by gender, to note that Illinois fell below national CTE enrollment patterns in nearly every cluster area. Some differences were particularly striking. For example, in Illinois only 7.3% of students enrolled in Transportation, Distribution and Logistics were female, compared to 13.5% nationally; in Science, Technology,


Engineering and Mathematics, 15.4% of enrolled students were female compared to 30.8% nationally. Only 8.4% of those enrolled in Education and Training are male, compared to 30.6% nationally (U.S. Department of Education, n.d.). These data underscore the urgency of the state’s goal within the Race to the Top initiative to increase female students’ participation in STEM CTE coursework. These data also reflect the potential existence of gender bias within Illinois CTE programming—again reinforced by cultural reproduction theory—which subsequently may contribute to the overall national workforce data that shows limited female representation in scientific and technological fields (Committee on Science, Engineering and Public Policy, 2007). Equally important are the reduced enrollments by gender in cluster areas that may be considered as nontraditional fields for both male and female high school students. Race/Ethnicity

Racial/ethnic participation differences in Illinois CTE enrollments were found in several career clusters and career pathways. Disparities existed in the overall population representation versus the enrollment representation for Asians, Black, and Hispanic students in particular. White students were overrepresented in every career cluster area. Participation rates in Illinois CTE courses by race/ethnicity for STEM and other career clusters showed greater STEM participation by White and Asian students, but the reverse pattern emerged for African-American, Hispanic and other racial/ethnic groups.

These findings run counter to claims that Black students are overrepresented in CTE

coursework (Hess, 2010)—at least, within in the state of Illinois. Black students were underrepresented in every career cluster area, except for Hospitality and Tourism. Under-enrollments for Black students were particularly noticeable in Agriculture, Food and Natural Resources; Science, Technology, Engineering and Mathematics; Law, Public Safety, Corrections and Security; Education and Training; and Architecture and Construction. Hispanic students also were under-enrolled in every cluster area, with the exception of Transportation, Distribution and Logistics. These STEM enrollment patterns are consistent with research indicating that Blacks and Hispanics are less likely to be employed in STEM fields, (Fletcher, 2012).

Asian students were highly overrepresented in CTE coursework in the Science,

Technology and Engineering career cluster and also slightly overrepresented in the Illinois CTE fields. This finding aligns with research (Laird et al. 2009) indicating that Asian students are more likely to earn STEM credits in high school.

Our study did not include an analysis of CTE course offerings based upon high school

demographic settings (urban, rural, and suburban), as that was beyond the scope of our research. Yet, it was not unexpected that Asian, Black, and Hispanic students were underrepresented in Agriculture, Food and Natural Resources. In the state of Illinois agriculture education courses typically are offered in rural school districts and are infrequently provided in urban and suburban high schools. Clearly, students can only gain access to CTE coursework if it is made available to them, either within their local school or at a regional career center. Thus, it is possible that racial/ethnic participation within some career cluster areas may speak more to their school demographics than to students’ interests in selected career fields. For example, nearly one fourth of students enrolled in Transportation, Distribution and Logistics CTE courses were Hispanic;


additional research is needed to determine whether courses in this cluster area are more frequently offered in schools and communities with large Hispanic populations.

Our study also did not investigate whether schools were offering CTE programs of study

based upon labor market analyses within their regions and/or whether students may be selecting CTE coursework based upon perceived labor needs within their local communities; this is an important area for future research. Differences were noted by race/ethnicity and gender in students’ enrollments for cluster areas and career pathways. Additional research is needed to determine whether Illinois school districts are offering CTE coursework and encouraging students to enroll in career areas that are not in high demand or that are offering high wages within the regions.

We also did not examine whether CTE courses—and in particular, STEM CTE courses—

were more prevalent in Illinois school districts with higher per-pupil student expenditures. As noted earlier, Illinois has significant funding disparities across school districts (Baker et al., 2014; Malin & Noppe, 2015). Limits on school district financial resources can hamper educators’ efforts to expand CTE programming for their students, particularly for those students of color who attend schools in communities with fewer resources.

Limitations

Although this study reveals important and useful information concerning participation

rates in high school CTE programs, it does have some limitations. The student enrollment counts for this study were reported for the 2012- 2013 school year, which was the most recent data that we could obtain from the state. The dataset contained information provided by Illinois public school district personnel and is subject to reporting errors that may have occurred when compiling and transmitting this information. In addition, as was noted previously, the study did not review CTE enrollment patterns based upon school district demographics and funding levels.

Recommendations for Policy and Practice

Based upon our research, we provide recommendations to policymakers and school

practitioners to strengthen equity efforts within CTE programs. The federal government has outlined expectations through the No Child Left Behind Act for reducing education gaps, and the Illinois Race to the Top initiative includes a goal to increase underrepresented students’ participation in CTE STEM coursework. State policymakers and school district educators are jointly accountable for ensuring that CTE programming is equitable and accessible to all students regardless of gender and race/ethnicity. By critically reviewing equity-conscious practices in relationship to gender and race/ethnicity, policymakers and educational leaders and may help produce better outcomes for all CTE participants. We offer the following suggestions as initial steps toward creating better educational outcomes for all students within CTE programs. Recommendations for Policymakers One suggestion as policymakers strive to monitor and improve equity is to ensure that statewide data reporting systems include comprehensive information regarding the profiles of


students enrolled in CTE coursework. Information such as socio-economic status, assessment data, race/ethnicity, and gender can assist in better understanding issues of access. Further, collecting data on the postsecondary decisions of CTE students can provide information on how to address and improve equity efforts within high schools. For example, it would be helpful to discern whether students transition into higher education, obtain postsecondary training, or immediately obtain employment in CTE fields, and whether they are adequately prepared for these transitions. It is also essential that statewide data systems are accessible to educators, researchers, and policymakers. If this information is unavailable for policy analysis and/or it is not in user-friendly formats, dialogue and change are unlikely. Policymakers have a responsibility to ensure that school district officials are accountable in ensuring access and equitable outcomes for all CTE students with respect to race/ethnicity and gender. Offering financial incentives for increasing underrepresented student enrollments in STEM CTE programming, as well as selecting schools as exemplars or models, demonstrates to educators that ensuring equity is a priority. Providing incentives and public recognition can encourage school and district officials to concentrate their efforts on the array of CTE programs that can be offered in their schools, to fully address students’ career interests. In addition, featuring CTE students who have obtained desired employment and/or successfully transitioned to postsecondary experiences can provide tangible examples of student success. State legislators could enact legislation requiring all school districts to develop Individualized Learning Plan (ILP) processes, with each student creating an ILP aligned to her/his career interests. ILPs are plans generated by students, in consultation with teachers, counselors, and parents, which align high school coursework with their intended career goals. ILPs help guide students in their academic planning and assist them in their college and career readiness by providing an understanding of relevant coursework to career and college plans, as well as their short- and long-term goals (Fox, 2014). ILPs also should incorporate students’ post-graduation planning, indicating how high school coursework connects with high education courses, military, and/or workforce employment. Currently, over 20 states mandate ILPs for all high school students (Solberg, Phelps, Haakenson, Durham, & Timmons, 2012); within the state of Illinois, school districts that are voluntarily participating in the Race to the Top initiative must implement an ILP process that commences in the seventh grade. However, only 32 of Illinois’ 850+ public school districts are involved in RttT. Thus, only a small portion of the state’s students are engaged with ILPs. Through the ILP process and associated school supports, students can discern which coursework, including CTE courses, align with their career interests and ensure that they are adequately prepared for postsecondary success.

Policymakers also can encourage school districts to develop robust CTE programs of study that permit students to attain industry-recognized credentials or certificates. Such credentials certify to potential employers that the applicant has attained the necessary skills to meet entry-level standards of employment (Castellano, Stone & Stringfield, 2005). Students also can obtain additional credentials as they enroll in postsecondary educational opportunities. Credentials can facilitate advancement of students within a particular pathway and provide for more versatility in the skills they acquire.


Recommendations for Practitioners School leaders can influence race/ethnicity and gender patterns within CTE programs by performing equity audits, examining access and availability of opportunities within CTE programs, and encouraging all educators to actively adopt and advance an equity agenda. By employing the following recommendations, practitioners can begin to systemically address processes that have reinforced inequitable practices in their schools, rather than a means of simple adherence to state, local, or federal policies.

Through data examination, practitioners can begin to uncover patterns that exist within their CTE programs, possibly revealing gender and/or race/ethnicity inequities. School leaders and teachers also can learn about cultural reproduction theory (Bourdieu & Wacquant, 1992), to assist in understanding how they may be maintaining school cultures that tend to reinforce the status quo. Additionally, through the use of equity audits (Skrla, McKenzie, & Scheurich, 2009), educators can analyze CTE assignments to gain insight on how students choose to enroll in and participate in CTE courses. They then can lead their faculties in discourse centered on the enrollment patterns and begin to identify factors that may contribute to any inequities found. The most critical aspect of engaging in equity audits is responding to the data and insights in a way that contributes to changing or reforming practices. In other words, it is not enough to merely identify the issues contributing to inequities within CTE programming: Educators also must take actionable steps toward remedying any identified problems. Possible areas for exploration may include district practices related to students’ exposure to career exploration materials and activities, efforts to encourage students to consider fields that may be nontraditional for them, examination of curriculum materials for potential race or gender bias, and the continuing refinement of teaching and learning practices.

Data examination also may expose inequities within CTE programs. Not only is it critical

to understand who is participating in CTE programming but it also is important to understand any circumstances surrounding the lack of participation by gender and race/ethnicity. Sharing and promoting positive aspects of CTE programs to all students may promote interest from a wider, more diverse audience. School officials also may wish to examine potential barriers that may restrict students’ access to program participation. For example, some students may be unable to obtain transportation to business/industry sites or may not be able to afford professional attire for work-based learning opportunities that are available in their career fields.

School leaders also can work with their faculty to implement Individualized Learning Plan processes for their students, irrespective of whether they are mandated by state policy. School leaders will need to provide professional development, ensuring that school counselors and teachers are trained in supporting students’ ILP activities and can assist students with career exploration and the development of course plans that extend through high school and into postsecondary settings. School officials also can review course selections contained in their students’ projected programs of study, as a mechanism to identify changing career interests of the student body and plan for future course needs.

Lastly, we encourage educational leaders to adopt and advance an equity agenda within their schools and districts. The adoption of such an agenda requires school leaders to critically


inspect practices and policies to ensure that they encompass all students fairly and justly. Focusing on equity requires educators to continually examine their beliefs and perceptions about students and/or student groups. Education leaders have the capacity to create the vision toward reaching the equity goal and set goals to achieve this vision.

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AUTHORS’ NOTE

Asia N. Fuller Hamilton is a graduate research assistant and Doctor of Philosophy student in Education Policy, Organization and Leadership with a concentration in Educational Administration and Leadership, at the University of Illinois at Urbana-Champaign. Her email contact is [email protected]. Joel R. Malin is an Assistant Professor in the Department of Educational Leadership at Miami University-Oxford, Ohio. He is also a faculty affiliate of the Office of Community College Research and Leadership and a faculty fellow for the Forum on the Future of Public Education at the University of Illinois at Urbana-Champaign. He can be reached at [email protected]. Donald G. Hackmann is a Professor of Educational Leadership in the Department of Education Policy, Organization and Leadership at the University of Illinois at Urbana-Champaign. He can be reached at [email protected].


Occupational Safety and Health: A View of Current Practices in Agricultural Education

Mark D. Threeton The Pennsylvania State University

John C. Ewing

The Pennsylvania State University

Danielle C. Evanoski The Pennsylvania State University

ABSTRACT

Providing safe and secure teaching and learning environments within schools is an ongoing process which requires a significant amount of attention. Therefore, this study sought to: 1) explore safety and health practices within secondary Agricultural Mechanics Education; and 2) identify the perceived obstacles which appear to hinder implementation of safety and health programs. While it might appear logical to assume that Agricultural Mechanics Education consistently reflect acceptable safety standards to promote enhanced learning and skill development, the results suggested there is room for improvement within schools. Findings may be useful to agricultural educators; school administration, teacher educators and safety compliance personnel interested in promoting enhanced occupational safety and health practices.

Introduction

Since the beginning of agricultural education in schools, educators have been concerned

about the health and safety of their students. A great deal of attention has been focused on providing a safe educational environment to promote enhanced learning and skill development (Storm, 1993; Threeton & Walter, 2013). However, recent events of the day have revealed that there is good reason for concern related to safety and health practices within Agricultural Education. For example, in 2010, an 11th grade student from a New England state was injured while completing an assigned task within the laboratory setting. The student was instructed to cut what was believed to be a de-energized wire and replace it. Unfortunately, the wire was located in a junction box, which was still energized. As a result, the student was energized by 277 volts of electricity and subsequently hospitalized for burns suffered from the initial shock. Nine-months later the same injury occurred in a similar program in the state. On both occasions, the instructors were not present during the event (MDPH, 2011).

Incidents such as this highlight the ever growing need to examine occupational safety and

health practices within Agricultural Education. While all individuals are susceptible to accidents, occupationally related safety literature has revealed that teens are injured at a higher rate than adult workers (NIOSH, 2007a). Every year, 70 teens die from work injuries in the U.S., while another 84,000 are injured severely enough as to require a visit to an emergency room (UC Berkeley Labor Occupational Health Program, 1997; NIOSH, 2007b). As a training ground for the world-of-work, Agricultural Education professionals must provide a safe teaching and


learning environment while simultaneously preparing students to work safely and successfully in the school as well as transfer those assets on-the-job. Therefore, the purpose of this research was to examine current occupational safety and health practices within Agricultural Education programs to determine if further research and development is needed within the field.

Occupational Safety and Health: Deficiencies in Agricultural Education

Conducting classroom and laboratory instruction in a manner that promotes learning, but also ensures the safety and health of the student is a major point of obligation (Gray & Herr, 1998). In response to this obligation, the National Institute for Occupational Safety and Health (NIOSH) developed a Safety Checklist Model (CDC, 2012) for establishing effective occupational safety and health programs within Career and Technical Education (CTE), which includes Agricultural Education. An occupational safety and health program within Agricultural Education is a set of policies, procedures and practices specifically designed to promote a safe teaching and learning environment. NIOSH’s Checklist Model contains five essential classifications of guidelines including: 1) Assuring management commitment; 2) Assuring employee and student involvement; 3) Identifying and prioritizing potential hazards; 4) Eliminating hazards; and 5) Training personnel. While many states require the use of NIOSH’s Safety Checklist Model as the minimum, little to no research has been conducted to determine whether or not instructors are implementing and enforcing occupational safety and health programs as an element of their curriculum and instruction (CDC, 2012; OSHA, 2013). This question tends to go ignored until an incident occurs, causing the educational institution, state, or NIOSH to investigate.

As an example, NIOSH recently conducted an investigation into an accident in which an

11th grade student within a New England state was injured while turning a piece of stock on wood working equipment. Despite successfully passing an OSHA 10-hour safety course, the student’s ring finger came in contact with the rotating cutting head of a jointer (MDPH, 2009). Following the accident, the student was transported to the hospital, where the finger was amputated at the middle knuckle. The student’s instructor was present but did not witness the incident. One of the prescribed recommendations from the National Institute for Occupational Safety and Health was that the NIOSH Safety Checklist Model be utilized, as it was designed to aid in complying with OSHA regulations (MDPH, 2009).

With clear guidelines established by NIOSH as well as corresponding state and federal

legislation, why are accidents in Agricultural Education occurring? Are instructors utilizing the guidelines? Is safety legislation being enforced? Do students, instructors, and administration understand it? Are the guidelines supported and encouraged by administration? Questions such as these need to be explored in order to gauge what obstacles Agricultural Education instructors face in implementing occupational safety and health practices within their designated programs. Yet little scholarly literature exists which examines if the elements of NIOSH’s guidelines are being implemented at the classroom/laboratory level (CDC, 2012; OSHA, 2013).

Occupational safety and health regulations are in place, not only to protect students and

school personnel from preventable injuries, but also to protect instructors from unnecessary negligence claims. Despite great efforts, accidents still occur and in some instances can be rather


serious (Gray & Herr, 1998). Instructors may not always consider the liability risks within their classrooms and labs (Storm, 1993). Gray and Herr noted that instructors must anticipate unsafe situations which could reasonably be foreseen and design curriculum and instructional practices to minimize the possibilities of such risks. In today’s “sue-happy society” instructors must create a safe environment not only to protect students, but also to avoid possible legal ramifications (Zirkle, 2013). Therefore, preparing the laboratory, educating students, acting as a safety role model, and most importantly implementing and enforcing applicable legislation as well as the NIOSH guidelines can aid efforts to avoid liability issues (Meanor & Walter, 2010). Threeton and Walter (2013) emphasized that only continuous monitoring for potential hazards, supervision of students, adherence to safety guidelines, and routinely enforcing safety standards will improve an instructor’s chances in avoiding unnecessary negligence claims. Since accidents can happen in the safest of lab settings, Threeton and Walter advised to accurately record any and all incidents in a detailed manner, regardless of how superfluous it may seem, as some legal proceedings may not transpire until well after the accident has past. This is particularly important, as it is the instructor’s responsibility to keep themselves, their program, and students safe.

As the standard bearers within the institution, Agricultural Education instructors and

administration have a major responsibility to consistently evaluate the occupational safety and health practices to promote security. Balamuralikrishna and Dugger (1995) noted that staff and administrators play a key role in shaping the future of their institutions. In order to be initiators of the solution, Balamuralikrishna and Dugger recommended completing a SWOT (strengths, weaknesses, opportunities, and threats) analysis of the vocational programs to evaluate both internal and external factors that could contribute to the occupational safety and health within an institution. When educators complete a SWOT analysis, it causes them to reflect on systematic approaches, which could promote the advancement of the safety practices within the institution.

Similarly, Schulte, Carol, Okun, Palassis, and Biddle, (2005) concluded that little

quantitative information exists on safety practices provided within career and technical programs, therefore efforts to evaluate occupational safety and health in workforce preparation programs will require studies that evaluate programs in a systematic manner. As Balamuralikrishna and Dugger (1995) indicated, gathering both positives and negatives relating to a program can shed light on potential improvements needed. With the theme of reflecting on areas in need of improvement, this research study sought to explore the safety and health practices within one of the most hazardous educational programs within the U.S., Agricultural Mechanics.

The Problem

Agricultural mechanics laboratories and classrooms are often filled with dangerous tools, equipment, processes, materials and supplies, within a wide range of environmental conditions, which are difficult to control. Agricultural educators, unlike their academic counterparts, are expected to manage the learning environment as well as promote safe practice to control for these potential hazards. As scholars have highlighted, the margin for error within some agricultural programs is so small that improper program safety and health practices can be the difference between life and death (Threeton & Walter, 2013; Meanor & Walter, 2010; Storm,


1993). Yet, little research has been conducted on this topic to determine the level to which safe and healthful practices are being provided (CDC, 2012; OSHA, 2013). Therefore, this phenomenon creates a problem that requires attention, as the results could safeguard life and limb.

Purpose and Research Questions

This research was conducted to examine current occupational safety and health practices within Agricultural Education to determine if further research and development is needed within the field. While a multitude of studies have examined safety and health practices within the workforce (NIOSH, 2004), few have investigated this topic within Agricultural Mechanics Education. Therefore, this study sought to answer the following questions:

1. What is the distribution of practicing agricultural mechanics instructors with a structured

occupational safety and health program as an integral component of their curriculum and instruction?

2. What is the distribution of students, which are required to complete safety training prior to participation within the agricultural mechanics laboratory?

3. What is the distribution of students, which are required to complete safety tests prior to participation within the agricultural mechanics laboratory?

4. What is the distribution of students, which are required to complete a safety test with a perfect score prior to participation within the agricultural mechanics laboratory?

5. What, if any, obstacles do agricultural mechanics instructors perceive to hinder their ability to implement an occupational safety and health program in their classroom/laboratory?

Conceptual Framework

In 2010, the U.S. Department of Labor reported approximately 3.1 million nonfatal occupational injuries and illnesses. Given that Agricultural Education is a gateway to the world-of-work, and that over 90 percent of high school graduates have taken at least one related course (U.S. Department of Education, 2012), agricultural educators have a major responsibility to establish and maintain safe and healthful teaching and learning environments to promote future career success. While there are a multitude of important educational initiatives today, Zirkle (2013) emphasized, that providing a safe teaching and learning environment should be the first priority of every instructor. According H.W. Heinrich (1931) preventable accidents result from a chain of sequential events, which are metaphorically similar to a line of falling dominoes. Therefore, as one domino falls it triggers the next and so on. By removing factors such as unsafe conditions and acts from the learning environment, Agricultural Educators can prevent this harmful chain reaction.

The foundation of this research began with the premise that accidents should be viewed

as preventable by removing unsafe conditions and acts, while promoting enhanced learning through increased educational safety programming. As Storm (1993) noted, the responsibility for the physical welfare of students rests with the instructor. If Agricultural Educators are responsible for educating future workplace professionals on occupational safety and health practices, it is critical to understand the extent to which they are incorporating safety and health


NIOSH’s Safety Checklist Model for Occupational Safety & Health Programs in CTE

Management Commitment

Identify & Prioritize Hazards

Training Personnel

Employee & Student

Involvement

Eliminating Hazards

The Key to Safe & Healthful Practice Within

CTE Related Programs

Figure 1. Removal of unsafe conditions and acts via NIOSH safety programing

programs into their curriculum and instruction as well as assess what is either helping or hindering them from doing so. Therefore, the conceptual framework in which this research was founded included NIOSH’s Safety Checklist Model (CDC, 2012) for establishing Occupational Safety and Health Programs in CTE, which includes Agricultural Education. According to NIOSH, the key to safe practice within the educational environment while simultaneously promoting enhanced teaching and learning opportunities is to establish a quality occupational safety and health program (CDC, 2012). NIOSH’s Safety Checklist Model contains five elements which serve as a guide to establishing effective safety and health programs including: 1) Assuring management commitment; 2) Assuring employee and student involvement; 3) Identifying and prioritizing potential hazards; 4) Eliminating hazards; and 5) Training personnel. Therefore, this model served as the conceptual framework for this research. This study specifically focused on two elements of the model including: 1) Identifying and prioritizing potential hazards (i.e., identifying and prioritizing items, which are obstacles to implementation of a safety and health program); and 2) Training personnel (i.e., safety training provided and assessed prior to student participation in the program laboratory), as educating students and detecting safety concerns is a priority of Agricultural Education. Figure 1 is provided to illustrate the conceptual framework in context.

Materials and Methods Instrumentation

The researchers utilized survey research in this investigation in an attempt to provide a platform for honest and unambiguous responses. The instrumentation utilized was an investigator-developed survey based on NIOSH’s Safety Checklist Model for establishing effective safety and health programs within CTE related settings such as Agricultural Education. The survey included 27 questions, which corresponded with the identifying and prioritizing potential hazards and training personnel elements of NIOSH’s prescribed safety and health model (CDC, 2012). The specific survey items included status of a safety and health program, safety training and assessments completed by students prior to participation within the laboratory


as well as instructor’s perceived obstacles to implementing an occupational safety and health program. Additional items included a demographics section within the final portion of the survey. The survey was reviewed for face and content validity by a 15 member panel of current technical educators well versed in proper safety practices, teacher education faculty members, and experts in survey development. After the panel completed the analysis, the primary investigator amended the survey to correspond with the prescribed recommendations.

Following human subjects protocol approval, a pilot study was administered to assess the

reliability of the instrumentation as well as determine if there was a need for a formal investigation. Therefore, Agricultural instructors from the same state, which were not a part of the formal study, completed the survey via the web-based assessment platform, “Qualtrics”. Upon analysis of the results, the Cronbach’s alpha coefficient was determined to be .833 for the items related to the perceived obstacles to implementing an occupational safety and health program. Further analysis of the pilot study revealed a need for a formal investigation into occupational safety and health practices within Agricultural Mechanics.

Target Population of the Formal Study

The target population for the formal study included active educators in Pennsylvania currently teaching Agricultural Mechanics at the secondary level. These instructors were specifically targeted, as they represented one of the most hazardous subject area classifications during the spring of 2014. According to the designated State Department of Education records, there were a combined total of 156 educators teaching Agricultural Mechanics in Pennsylvania during the spring of 2014.

Data Collection

The data collection phase of this research was conducted during the spring of 2014. The appropriate clearance was obtained from the Office for Research Protections regarding the inclusion of human subjects in this research. Like the pilot, the formal study was also conducted using the web-based survey assessment platform, Qualtrics. In order to obtain an acceptable response rate, Dillman’s (2000) procedures and timelines for conducting Internet surveys were employed. An email pre-announcement, an initial invitation to participate and three email contacts were sent to non-respondents.

Rate of Return

Sixty-eight out of 156 potential participants responded to the survey, which provided an overall response rate of 44%. Adjusted response rate, due to unexplained nonresponses, was 37%. The statistical technique of comparing early and late respondents (Miller & Smith, 1983) was utilized to control for non-response error. Individuals that responded prior to the third contact were considered to be early respondents, while those who responded after the third contact were considered late. A comparison of early and late responses revealed no statistical difference. This process allowed the researchers to generalize to the non-respondents and provided a methodological basis for assuming that they had responded (Miller & Smith, 1983).


Background of Participants

Demographic data is included in Table 1 to describe the respondents in this study. The majority of participants were male (n= 40, 70%), possessed an instructional II teaching certificate (n=42, 74%), and taught at a rural school (n=46, 81%).

Results

Research Question 1

The first research question sought to identify the distribution of practicing Agricultural Mechanics instructors with a structured occupational safety and health program as an integral component of their curriculum and instruction. This question was answered by calculating the frequencies and percentages of the items related to this query within the survey. The results revealed that 52 (76%) instructors reported having a structured occupational safety and health program as an integral element of the curriculum and instruction while 16 (24%) did not (see Table 2).


Table 2 Participant Response Pertaining to Safety and Health Program Status (n =68)

Research Question 2, 3 and 4

The second, third and fourth questions sought to assess the distribution to which students were required to complete safety training and related assessment protocol prior to participation within the agricultural mechanics laboratory. These questions were answered by calculating the frequencies of the data collected from the survey, which related to the training personnel elements of NIOSH’s prescribed safety and health practices within the model.

The results for the second research question revealed that 55 (95%) instructors indicated

students receive safety training prior to participation in the laboratory, while three did not. Similarly, the results for research question three indicated that 55 (95%) instructors required their students to complete a safety test prior to participation in the laboratory, while three did not. Surprisingly, the findings for the fourth research question revealed that 32 (55%) instructors permitted students to participate in laboratory activities without earning 100% on a safety test (see Table 3).

Research Question 5

The fifth question sought to identify perceived obstacles to implementing an occupational safety and health program via a four point Likert-type scale, as well as a follow-up open-ended text entry item. These questions related to the identifying and prioritizing potential hazards

Table 3 Safety Training, Assessments and Laboratory Participation

Participant Response

Question Yes No

Do students receive safety training prior to participation within the program laboratory? (*n=58) 55 3

Are students required to complete a safety test prior to participation within the program laboratory? (*n = 58) 55 3

Are students permitted to participate in laboratory activities without earning 100% on a safety test (*n = 58) 32 26

Note. The *n represents the number of participants in the sample who responded to the given question, out of n = 68).


elements of NIOSH’s prescribed safety and health practices within the model. All participants were given the opportunity to respond to this question regardless of how they answered question one within the survey, as per a recommendation from the expert panel responsible for reviewing the survey for content and face validity. The intent behind this recommendation was to capture the full extent of perceived obstacles to implementing an occupational safety and health program.

Upon analysis, the item: lack of funding (M=2.79, SD=.89) rated the highest among

perceived obstacle, with 25% strongly agreeing (n=14) and 39% agreeing (n=22). The item: chronic student absences (M= 2.58, SD=.78) was also rated higher among perceived obstacles, with 7.4% strongly agreeing (n=4) and 48% agreeing (n=26). The items rating the lowest in disagreement as perceived obstacles included: serving as a Career and Technical Student Organization (FFA) advisor (M=1.67, SD=.74), which was followed by the demands of state teacher certification requirements (M=1.91, SD=.79) (see Table 4).

Table 4 Perceived Obstacles to Implementing an Occupational Safety and Health Program

Conclusions

Note. Scale used 1 = strongly disagree, 2 = disagree, 3= agree, 4 = strongly agree. In addition to the questions listed on the Likert-type scale, participants were given the opportunity to provide a text response, allowing them to list any other obstacles that they believe hinder their ability to carry out a health and safety program in their CTE program. Other obstacles (differing from Table 4) included: Administrators lack of knowledge and support (mentioned 3 times), lack of time to add/modify safety plans (mentioned 2 times), lack of communication (mentioned 2 times), and “differences in opinion between Ag Educators in the building about how procedures should be done”.


Research Question 1

While it might appear logical to assume that agricultural education programs consistently reflects acceptable safety standards to promote enhanced learning and skill development, the results suggested there is need for concern related to occupational safety and health practices within some agricultural mechanics programs. The results for question one revealed that 52 (76%) instructors reported having a structured occupational safety and health program as an integral element of the curriculum and instruction while 16 (24%) did not. Overall, this finding appears to be very positive with a majority of participants reporting an occupational safety and health program as an integral component of the agricultural mechanics program as is recommended within NIOSH’s Safety Checklist Model. However, there were 16 (24%) instructors, which reported not having an occupational safety and health program. Thus, increased risk may well be associated with programs, which have instructors that do not implement a safety and health program, as it is an effective way to comply with applicable safety and health standards (OSHA, 2013).

Research Questions 2, 3 and 4

The findings related to safety training and evaluation practices in the agricultural mechanics program, corresponded with research questions two, three and four. When asked if students receive safety training prior to participation in the laboratory, 55 (95%) instructors indicated they did, while three reported their students did not. Similarly, 55 (95%) instructors revealed their students were required to complete a safety test prior to participation in the laboratory, whereas three educators did not require an assessment. While these findings represent a relatively small distribution of participants whom did not require safety training and assessments of students prior to participation in the laboratory, the results are troubling, as providing a safe teaching and learning environment for all students should be the first priority of every educator (CDC, 2012; Zirkle, 2013).

Another notable finding, which corresponds with research question four included 32 (55%) instructors reporting that they permitted students to participate in laboratory activities without earning 100% on a safety test. This finding is noteworthy, as the margin for error within some elements of the agricultural mechanics program can be so small that any form of miscommunication or misstep could be life threating. It could be the one or more items missed on the safety evaluation that causes the greatest harm (Threeton & Walter, 2013). Students could find themselves unable to recognize occupational hazards upon transition to the world-of-work.

Research Question 5

The fifth research question sought to identify perceived obstacles to implementing an occupational safety and health program. The questionnaire gauged instructors’ perceptions using a four point Likert-type scale (i.e. 1 = strongly disagree, 2 = disagree, 3 = agree, 4 = strongly agree). At first glance the results for question five are not astounding; the means for each obstacle appear to be somewhat neutral. The instructors’ responses, for the most part, appear to “disagree” with the question, meaning that these items do not hinder their ability to implement an occupational safety and health program, as most of the obstacles’ means tend to be around a 2 =


disagree. However, a few of the perceived obstacles’ means were closer to “agree” than “disagree”, such as lack of funding (M=2.79, SD=.89), chronic student absences (M=2.58, SD=.78), lack of adequate classroom/laboratory space (M=2.57, SD=.92) and high student enrollment per class (M=2.54, SD=.94). Moreover, instructors were provided with the option to offer an open entry text response, in reference to perceived obstacles. Instructors noted: administrators lack of knowledge and support (mentioned 3 times), lack of time to add/modify safety plans (mentioned 2 times), lack of communication (mentioned 2 times) and differences in opinion between Agricultural Educators in the building about how procedures should be done (mentioned once).

Intervention strategies appear to be needed in these particular areas to support

implementation of occupational safety and health programs. Strategies could range from providing alternative pathways of safety programming for absent students, strategies in dealing with high student enrollment per class and limitations in classroom/laboratory space as well as expanded financial revenue in the form of grants and contracts. It is plausible that lack of acknowledged hindrances may be due to the fact that they were not identified in the questionnaire as potential obstacles, and therefore went undisclosed by participants. Conversely, the scarcity of perceived obstacles could also be owed to the diligence that the surveyed instructors have in implementing occupational safety and health programs in their classrooms, and therefore they found no notable hurdles.

Discussion

Scholarly Significance

While a multitude of studies have examined safety and health practices within the workforce (NIOSH, 2004), few have investigated this topic within Agricultural Education. We now know there is need for concern related to occupational safety and health elements within some Agricultural Mechanics programs in Pennsylvania. While 76% of participants within this study reported having a structured occupational safety and health program as an integral element of the curriculum and instruction, the results appear to reveal a subgroup of instructors in need of occupational safety and health remediation.

Instructors identified lack of funding, chronic student absences, lack of adequate

classroom/laboratory space, and high student enrollment per class as the highest of perceived obstacles to implementing safety and health programs. However there appears to be an additional area of concern, as the results of research question four revealed, over half of the participants within this study permitted students to participate in laboratory activities without earning 100% on a safety evaluation. This finding is of great importance, as the margin for error could be so small that any form of miscommunication within certain elements of the program could be the difference between life and death. While it may take multiple attempts for some students to earn a perfect score on safety evaluations, investment in the remediation process can safeguard life and limb.

Therefore, the occupational safety and health concerns highlighted within this study should be viewed as critical elements in need of attention. Based on the conclusions of this study the following recommendations are made.


1.) School administration and instructors from the designated programs should seek technical

assistance from school safety specialists, OSHA, NIOSH and teacher educators to immediately correct the occupational safety and health concerns highlighted in this study. This support should align with NIOSH’s Safety Checklist Model (CDC, 2012).

2.) Professional development opportunities should be provided to the instructors and school administration, which emphasizes interventions to overcome significant obstacles noted within Table 4.

3.) Since there is a dearth of occupational safety and health studies within Agricultural Education this investigation should be replicated on a larger scale within Pennsylvania as well as other parts of the country. As with any body of research, there are limitations of this investigation including: 1) the

results are not generalizable outside of the target population; 2) the instrumentation format was self-reporting in nature and could have been incorrectly reported by participants; and 3) a majority of the survey items were multiple choice, thus some occupational safety and health practices may not have been fully captured. Therefore the results should be viewed as an initial call to action, which promotes further research and professional development to advance proper occupational safety and health practices within Agricultural Education.

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AUTHORS’ NOTE

Mark D. Threeton is an Assistant Professor of Education within the Workforce Education and Development Program at Pennsylvania State University. He can be reached at [email protected].

John C. Ewing is an Associate Professor of Agricultural and Extension Education in the Department of Agricultural Economics, Sociology, and Education at Pennsylvania State University. He can be reached at [email protected].

Danielle C. Evanoski is a doctoral candidate within the Workforce Education and Development Program at Pennsylvania State University and is an organization development practitioner in the private sector. She can be reached at [email protected].

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