Monitoring the Pipeline: STEM Education in Rural U.S.

Author:Marksbury, Nancy
Position:Science, technology, engineering and mathematics - Report
 
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Introduction

Post-secondary first- and second- year students in STEM most often struggle due to:

* Gaps in prerequisite knowledge and skills necessary to succeed in STEM gateway courses.

* Insufficient time beyond scheduled class hours where students can pre-learn and re-learn required course content.

* Lack of support to improve student success and persistence in the form of people and systems.

* Lack of support for faculty to lead pedagogical reform.

To understand the systemic mechanisms that affect students' interest in persisting through difficult course content, we must look in both directions of the educational pipeline--from students in higher education to those currently in primary and secondary education--so that we can identify the barriers to STEM engagement and persistence and marshal resources available to improve our educational persistence and attainment.

Looking Downstream: Barriers to STEM Engagement and Persistence In College

Addressing interest and persistence in STEM majors requires a multifaceted approach that considers the academic, emotional, cultural, and resource needs (NAS 2011; Goonewardene et al. 2016) of the individual student. Pyzdrowski et al. (2013) identified three broad areas that define student indicators of success in difficult topics, like math and science: Prior experience, instruction, and attitude and effort. These factors are exacerbated by socio-economic status--students from the wealthiest families outscore those from the poorest by almost 400 points on SAT scores (Zumbrun 2014). College enrollments across the nation rose during the recession, but nearly all growth was among low-income students (College Board 2017). A demographic shift in undergraduate enrollments and Pell status has resulted, highlighting the need for student academic support structures described below.

Underrepresented Minorities

Johnson (2011) found the average percentage of African-Americans enrolled is 2.4% in total. When compared to the average of STEM majors of 7.8%, we can deduce that African-American STEM major enrollment is very low. With fewer numbers of minority students enrolling in STEM majors, it is heartening that community colleges are seen as educational pipelines for Hispanic and Native American students into STEM majors.

The important role played by community colleges as an educational pipeline for URM is gaining recognition. Approximately 40% of students graduating with a bachelor's degree in STEM attended a community college (Chen & Weko, 2009). Furthermore, a large portion of community college students are not college ready, represent historically underserved populations, and are first-generation college goers (Juszkiewicz, 2014). We also know that there is a high attrition rate in STEM disciplines for these students and a relatively low degree completion record for community colleges overall (approximately 35% of community college students graduate with a two-year degree within six years, Juszkiewicz, 2015). It is both prudent and advantageous to include community colleges in our examination of learning and teaching strategies to support an increased number of students successful in STEM disciplines.

Characteristics of at-risk students entering a STEM major

In 2015, only 28% of high school graduates nationwide met or surpassed ACT benchmarks for college readiness across 4 subject areas, and only 16% of Hispanic and 13% of African- American students met or surpassed those benchmarks (ACT 2015). Scholars operationalize the concept of college readiness by placement scores, SAT benchmarks, or most difficult high school math course completed (Castleman, Long, and Mabel 2014). Advocates of using multiple measures for gauging readiness suggest using a combination of metrics, specifically those that are an aggregation of high school math courses passed, a measure of their difficulty, and combined with scores for those courses. These have greater predictive validity for African-American and Hispanic students' success in aspiring to STEM majors (Ngo and Kwon 2015). Another measure of college readiness uses mean math placement scores, ranging from college-prepared (87.14) to college-unprepared (52.88), and students' mean math SAT scores (568 and 538 respectively) for courses completed (Hesser and Gregory 2016). Conversely, prepared students qualifying for NSF-based grants (STEM-S) were reported to start college with a mean high school GPA of 3.65 and combined SAT scores of 1,175 (Kalevitch et al. 2015). It appears that in general, high school curricula do not necessarily prepare entering college freshmen for more rigorous coursework, and greater deficiencies appear in mathematics.

While researchers document connections between mathematics and interest in STEM courses, students also identify that math self-efficacy, exposure to math and science in high school, and math achievement in high school are predicators of math readiness in college (Wang 2013). Between 2003-2009, 69% of associate degree-seeking students entering STEM majors dropped out with mathematics as the primary hurdle (NCES 2013), and 93% of Americans report negative feelings when learning math (Pyzdrowski et al. 2013). Math aptitude is an indicator of STEM orientation, can be measured in multiple ways, and its deficiencies mitigated by addressing student confidence and teaching practices. The latter involves social interaction in the math classroom, study skill intervention, and goal setting (Cho and Heron 2015). "Mathematics is central to our technology, society and culture, yet goes unnoticed most of the time" (Bengtsson 2014, 48).

Affectively, underprepared students demonstrate less deliberateness, lowered persistence, and dispositional issues (Melzer and Grant 2016). While measures of adjustment, motivation, and self-perception are strong predictors of college success, particularly for underrepresented minorities (Ngo and Kwon 2015), personal resilience is as important a factor in persistence to graduation as is academic grit. Additionally, URM often face financial barriers to STEM coursework and degree completion (Castleman, Long, and Mabel 2014). Choosing a STEM field of study is significantly and positively influenced by student ethnicity (particularly for Asian and Caucasian students) and socioeconomic status (Wang 2013). Once enrolled, URM are likely to have less frequent interactions with faculty than white students (Hurtado et al. 2011). Female persistence in STEM lags overall, and this situation is exacerbated by coursework rigor that can produce loneliness and social isolation (Kocak 2008). Learning can be negatively impacted by the awareness that others hold expectations that one's gender or ethnicity makes them less capable (Rydell, Rydell, and Boucher 2010).

How institutions mitigate those risk factors

Institutional interventions tend to fall into three broad categories: community building, cognitive development, and developing vocational interests and science identities (Lane 2016). Most appear to combine aspects of the first two: community building and cognitive development. For example, Hunter College increased their graduation rate among STEM majors by 75% with a multi-semester enrichment program, early alerts, and keeping their program structurally nimble (Salmun and Buonaiuto 2016). Multiple component programs that include various bridge and enrichment components, support structures that are both in- and out-of-class, smaller classes, peer mentoring, and financial support effectively increase retention and degree attainment for all STEM majors (Booth et al. 2014; D'Souza et al. 2015; Goonewardene et al. 2016; Lane 2016). Raines (2012) reports a retention rate of 91% for a pre-college summer bridge program addressing math deficiencies for a cohort that was predominantly female. Institutions implementing learning supports, both in-course (Gross et al. 2015; Ni Fhloinn et al. 2014) and out-of-class drop-in centers or informal learning labs (Denson et al. 2015; MacGillivray and Croft 2011; Solomon, Croft, and Lawson 2010), helped students persist, achieve, and grow their confidence, camaraderie with peers, and application of math and science.

The third category of institutional intervention, i.e., developing vocational interests and science identities, is identified as playing a major role in STEM persistence. The University of Florida reported pre-research activities before and throughout students' first semester reduced barriers to involvement in faculty-led activities and increased student confidence (Schneider et al. 2016). Spelman College credits success for assisting African-American females with STEM career attainment by offering undergraduate research opportunities and other components, such as small class size, faculty encouragement and promotion, and academic supports (Perna et al. 2009). STEM majors themselves point to undergraduate research and interaction with faculty as activities that help them develop independence, confidence, and their science identity (Agarwal 2011; Gross et al. 2015; Hurtado et al. 2011; Thiry, Laursen, and Hunter 2011). These opportunities, accompanied with reliable, timely and tailored advising, are supports that STEM scientists point to as influential in their own development as a scientist (Ovink and Veazey 2011; Venville et al. 2013).

Faculty responses to mitigate risk factors for persistence and attainment

Knowledge and application of evidence-based pedagogies can improve achievement by helping students process new information more deeply and transfer new understanding to novel situations (Mulnix, Vandegrift, and Chaudhury 2016; Nadelson 2016). For example, traditional lecturing may disadvantage students with diverse learning preferences (Bernold, Spurlin, and Anson 2007) and activate only superficial student learning (Allendoerfer et al. 2014). Dialogic interaction (Tofel-Grehl and Callahan 2016), higher-order feedback and questioning (Hall and...

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