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Transforming STEM Outcomes: Results from a Seven-Year Follow-Up Study of an After-School Robotics Program's Impacts on Freshman Students

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Title: Transforming STEM Outcomes: Results from a Seven-Year Follow-Up Study of an After-School Robotics Program's Impacts on Freshman Students
Language: English
Authors: Meschede, Tatjana (ORCID 0000-0001-8019-7701), Haque, Zora (ORCID 0000-0003-3256-0494), Warfield, Marji Erickson (ORCID 0000-0002-3198-2348), Melchior, Alan, Burack, Cathy, Hoover, Matthew
Source: School Science and Mathematics. Nov 2022 122(7):343-357.
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 15
Publication Date: 2022
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Student Attitudes, Robotics, STEM Education, After School Programs, Program Effectiveness, College Freshmen
DOI: 10.1111/ssm.12552
ISSN: 0036-6803
1949-8594
Abstract: Over the past two decades, educators and policymakers have expressed growing concerns over the low levels of math and science achievement among American students and the gradual decline in the numbers of young people moving into science, technology, engineering, and math (STEM) careers. While interest in expanding the numbers of young people moving into science and technology fields has grown, a relatively small proportion of STEM education research has focused on the role that after-school programs can play to reinforce STEM learning and help engage young people in educational pathways leading to STEM careers. This study examines the impacts of "FIRST," an after-school robotics program, upon students' interests in STEM, as well as the likelihood for participants to pursue STEM in their academic and professional careers. Data were collected in a 7-year follow-up study of intervention group participants and a matched comparison group. We find that "FIRST" college students reported significantly higher rates of STEM interests, attitudes, and college level behaviors than comparison students. These findings have implications for the role of after-school programming in STEM education involving hands-on learning experiences in science- and technology-related fields, when considering young people's decision-making regarding their STEM college and career choices.
Abstractor: As Provided
Entry Date: 2022
Accession Number: EJ1357363
Database: ERIC
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  Value: <anid>AN0160530016;ssm01nov.22;2022Dec05.02:09;v2.2.500</anid> <title id="AN0160530016-1">Transforming STEM outcomes: Results from a seven‐year follow‐up study of an after‐school robotics program's impacts on freshman students </title> <p>Over the past two decades, educators and policymakers have expressed growing concerns over the low levels of math and science achievement among American students and the gradual decline in the numbers of young people moving into science, technology, engineering, and math (STEM) careers. While interest in expanding the numbers of young people moving into science and technology fields has grown, a relatively small proportion of STEM education research has focused on the role that after‐school programs can play to reinforce STEM learning and help engage young people in educational pathways leading to STEM careers. This study examines the impacts of FIRST, an after‐school robotics program, upon students' interests in STEM, as well as the likelihood for participants to pursue STEM in their academic and professional careers. Data were collected in a 7‐year follow‐up study of intervention group participants and a matched comparison group. We find that FIRST college students reported significantly higher rates of STEM interests, attitudes, and college level behaviors than comparison students. These findings have implications for the role of after‐school programming in STEM education involving hands‐on learning experiences in science‐ and technology‐related fields, when considering young people's decision‐making regarding their STEM college and career choices.</p> <p>Keywords: after‐school STEM (science, technology, engineering and math) programs; longitudinal study; program evaluation; robotics; school‐based programming; STEM college majors</p> <p>Though skills in science, technology, engineering, and math (otherwise known as STEM subjects) have become increasingly important and necessary in the modern U.S. economy, the nation has simultaneously seen a growing shortage of workers available to sustain related industries. The projected growth of STEM industries in the coming decades is quite substantial, as the U.S. Bureau of Labor Statistics ([<reflink idref="bib41" id="ref1">41</reflink>]) estimates STEM jobs will grow nearly 9%—a higher rate than non‐STEM jobs—between 2017 and 2029. The same report also envisions careers in engineering will be among those with the highest prevalence. However, the nation as a whole has only produced 10% of science and engineering college graduates on a worldwide scale (American Affairs, [<reflink idref="bib2" id="ref2">2</reflink>]). Despite the 3.5 million STEM jobs predicted for the U.S. by 2025, two million of these positions are anticipated to be left unfilled due to a lack of skilled candidates (Emerson, [<reflink idref="bib15" id="ref3">15</reflink>]). Research has highlighted various potential explanations for the deficit of STEM‐educated individuals. The difficulty of STEM subjects is often cited as a barrier discouraging the pursuit of extensively studying these fields, and later, STEM careers; other reasons for not engaging in STEM subjects include the perception that these topics are not useful for one's future; and a general lack of interest in STEM (Pew Research Center, [<reflink idref="bib34" id="ref4">34</reflink>]).</p> <p>Schools also appear not to effectively equip their students to meet the evolving, growing landscape of STEM professions, as only one of every five high school graduates is ready for college‐level STEM courses (American Affairs, [<reflink idref="bib2" id="ref5">2</reflink>]). The deficit of STEM‐educated individuals has been considered to originate from insufficient, lackluster, and inaccessible school curriculum and extracurricular activities for K‐12 students (Arrison, [<reflink idref="bib3" id="ref6">3</reflink>]; National Survey of Science and Mathematics Education, [<reflink idref="bib32" id="ref7">32</reflink>]). Instead, after‐school STEM activities have been found to play a role in increasing children's interest in and engagement with these subjects (Baran et al., [<reflink idref="bib4" id="ref8">4</reflink>]; National Research Council, [<reflink idref="bib29" id="ref9">29</reflink>]). A growing body of research suggests that such extracurricular activities may provide a venue for enhancing the attractiveness and accessibility of STEM education, thus filling a void traditional education may currently be struggling to fill.</p> <p>This study, spanning 7 years, tests the impacts of after‐school STEM activity engagement on participants' STEM‐related interests, attitudes, and academic and career trajectories during their first year in college. Key findings include positive and significant higher scores on STEM‐related attitudes and interests and on college courses and majors for participants in <emph>FIRST</emph>, a national after‐school robotics program engaging students in designing, building, and competing complex robots with the goal of inspiring long‐term interest in STEM. Findings also include particularly strong outcomes for female <emph>FIRST</emph> alumni signaling a potential shift in the gendered discrepancies that have long existed in the field (Cheryan et al., [<reflink idref="bib9" id="ref10">9</reflink>]; Lauermann et al., [<reflink idref="bib21" id="ref11">21</reflink>]; Saw et al., [<reflink idref="bib37" id="ref12">37</reflink>]).</p> <hd id="AN0160530016-2">BACKGROUND</hd> <p>Educators and policymakers have expressed growing concerns over the low levels of math and science achievement among American students and the gradual decline in the numbers of young people moving into STEM careers (Committee on Prospering in the Global Economy of the 21st Century, [<reflink idref="bib11" id="ref13">11</reflink>]; National Science Board, [<reflink idref="bib30" id="ref14">30</reflink>]). These concerns have led to the development of new standards for science and technology education (International Technology Education Association, [<reflink idref="bib20" id="ref15">20</reflink>]; National Committee on Science Education Standards and Assessment, [<reflink idref="bib27" id="ref16">27</reflink>]; National Research Council, [<reflink idref="bib28" id="ref17">28</reflink>]); new policy initiatives aimed at promoting science and technology education (America Competes Act, [<reflink idref="bib1" id="ref18">1</reflink>]; U.S. Department of Education, [<reflink idref="bib43" id="ref19">43</reflink>]; White House Office of Science and Technology Policy, [<reflink idref="bib44" id="ref20">44</reflink>]); and a growing body of research on math and science learning and the pathways leading to STEM‐related careers (Cannady et al., [<reflink idref="bib8" id="ref21">8</reflink>]). While some have challenged the likelihood of looming shortages of scientists and engineers due to recent studies indicating students are taking more science and advanced science courses in high school (Dalton et al., [<reflink idref="bib13" id="ref22">13</reflink>]; Lowell & Salzman, [<reflink idref="bib22" id="ref23">22</reflink>]; National Science Board, [<reflink idref="bib31" id="ref24">31</reflink>]), many insist that an increasingly knowledge‐driven global economy requires the United States to expand the pipeline into STEM‐related careers (American Affairs, [<reflink idref="bib2" id="ref25">2</reflink>]; U.S. Congress Joint Economic Committee, [<reflink idref="bib42" id="ref26">42</reflink>]; Emerson, [<reflink idref="bib15" id="ref27">15</reflink>]).</p> <p>While interest in expanding the numbers of young people moving into science and technology fields has grown, a relatively small proportion of STEM education research has observed the role of after‐school programs in reinforcing STEM learning. Though the literature evaluating individual after‐school programs and summer science enrichment efforts has begun to grow in the past decade (Baran et al., [<reflink idref="bib4" id="ref28">4</reflink>]; Chittum et al., [<reflink idref="bib10" id="ref29">10</reflink>]; Conrad et al., [<reflink idref="bib12" id="ref30">12</reflink>]), most of the existing studies focus on shorter‐term outcomes and/or are based on self‐reported impacts, and few incorporate a control or comparison group design (National Research Council, [<reflink idref="bib29" id="ref31">29</reflink>]). Given the growing emphasis on after‐school programming in education and promoting more hands‐on learning experiences in science and technology‐related fields, it is becoming increasingly important to better understand the role that after‐school science and technology programs can play in moving young people toward STEM‐related careers.</p> <hd id="AN0160530016-3">Historically underrepresented groups in STEM</hd> <p>When considering the ways in which K‐12 student STEM engagement may influence one's interest and future academic and career choices, it is important to take note of the trajectories of traditionally underrepresented groups—including females and Black and Latinx children. Gender disparities in STEM‐intensive educational experiences and outcomes have been persistent in the literature, and find females demonstrating lower levels of interest and involvement in STEM careers (Lauermann et al., [<reflink idref="bib21" id="ref32">21</reflink>]; Saw et al., [<reflink idref="bib37" id="ref33">37</reflink>]). There is evidence of female students having both lower levels of enjoyment and lower confidence in STEM classes when in high school (Huang, [<reflink idref="bib19" id="ref34">19</reflink>]; Ma & Johnson, [<reflink idref="bib24" id="ref35">24</reflink>]; Nagy et al., [<reflink idref="bib26" id="ref36">26</reflink>]). Females also demonstrate lower levels of career interest in STEM at both the start and end of their high school experience (Saw et al., [<reflink idref="bib37" id="ref37">37</reflink>]). Importantly, gender differences have been found to be most significant in engineering and computer science (Cheryan et al., [<reflink idref="bib9" id="ref38">9</reflink>]). The gendered nature of secondary schooling appears to play a role here; young girls are found to experience higher degrees of anxiety in math classes, have lower perceptions of their abilities in math, and express lower interest in math, all contributing to female students finding the subject to be less beneficial in comparison to their male counterparts (Gaspard et al., [<reflink idref="bib17" id="ref39">17</reflink>]). However, recent studies have questioned earlier findings in this realm, indicating a possibility that a shifting cultural mindset has begun to slowly narrow the gap. For example, Sax et al. ([<reflink idref="bib38" id="ref40">38</reflink>]) determined one's self‐concept in mathematics has in fact become a weaker predictor for female students choosing STEM jobs, suggesting confidence in math skills no longer correlates as strongly as it once did for explaining female underrepresentation in STEM fields. In addition, a meta‐analysis examining 78 studies of children's stereotypes regarding gender and science revealed the once firmly held belief that only men work in STEM careers has weakened over time, suggesting that the incremental growth in female representation in these fields has perhaps begun to decrease the prevalence of this mindset (Master et al., [<reflink idref="bib23" id="ref41">23</reflink>]; Miller et al., [<reflink idref="bib25" id="ref42">25</reflink>]). Thus, the current literature appears to be reflecting potential progress regarding female representation in STEM college majors and careers, though the field has not yet provided substantial evidence, particularly when considering female students' likelihood of persisting in STEM over time.</p> <p>Research also finds Black, Hispanic and Latinx students expressing lower levels of interest in STEM careers throughout their high school experience, which exposes enduring diversity and equity issues in STEM fields (Brown et al., [<reflink idref="bib7" id="ref43">7</reflink>]; Saw et al., [<reflink idref="bib37" id="ref44">37</reflink>]). K‐12 educators inadvertently practice racialized gatekeeping in their determination of how to "track" students into advanced coursework, often resulting in reduced access to quality math and science education for Black, Latinx, and Indigenous children (Ridgeway & McGee, [<reflink idref="bib36" id="ref45">36</reflink>]). Black people, while representing about 12% of the US population, comprise only 9% of workers in STEM; further, there has been no change in the proportionality of Blacks in STEM industries since 2016 (Pew Research Center, [<reflink idref="bib35" id="ref46">35</reflink>]). Insufficient representation of Blacks' educational and professional successes may harm Black students' perceptions of their own potential to successfully pursue STEM, diminishing their desire to pursue such fields (Brown et al., [<reflink idref="bib7" id="ref47">7</reflink>]). This is particularly true in the case of Black males (Brown et al., [<reflink idref="bib7" id="ref48">7</reflink>]). Further, Black children's internalization of racialized stereotypes has also been found to lessen their interest in STEM, often resulting from a perceived incongruence between their identities and those of individuals considered capable of succeeding in STEM fields—namely, white children (Gholson & Wilkes, [<reflink idref="bib18" id="ref49">18</reflink>]). The same holds true for Hispanic and Latinx students, though the current body of literature is substantially smaller in the case of studies evaluating their perceptions of their STEM identities (Fleshman, [<reflink idref="bib16" id="ref50">16</reflink>]).</p> <p>This study focuses on the role of an after‐school STEM program on STEM interest, attitudes, and behavior during college. The central hypothesis for this study is that involvement in organized after‐school STEM programs positively influences participants' education and STEM‐related attitudes, leading to increased involvement in STEM‐related courses and activities in college. In this article, we analyze data from round seven of a longitudinal study following participants and a matched comparison group, as a more robust college sample of students allows us to now address the following research questions:</p> <p></p> <ulist> <item> To what extent are there differences in STEM outcomes, such as interest in STEM and STEM careers; understanding of STEM and its pathways; science, math, and technology identities; and science and technology activities?</item> <p></p> <item> To what extent are there differences in STEM outcomes among key subpopulations? In particular, are there differences in impacts by race, gender, family income, or among those from urban, rural, and suburban communities?</item> <p></p> <item> What are the differences in STEM‐related behaviors between the intervention and comparison group? Specifically, what are the differences between college course‐taking and college majors?</item> </ulist> <hd id="AN0160530016-4">METHODS</hd> <p>The <emph>FIRST</emph> longitudinal study began in 2012, surveying middle and high school students participating in an after‐school intervention program and a matched comparison group, and has been collecting annual follow‐up data of both groups for 7 years. The <emph>FIRST</emph> intervention provides hands‐on STEM learning challenges for students in grades K‐12 aimed at strengthening their interest in science and technology while building teamwork, project management, communications, and other life skills. While differing in their specific designs and target age groups, the activities are based on a common model: teams of school‐aged youth work together under the guidance of two or more adults (an adult team leader plus technical mentors and other volunteers) to design and build robots that compete with other teams in completing a set of prescribed tasks. The overarching goal of the <emph>FIRST</emph> longitudinal study is to document the longer‐term correlations of the intervention on participating youth through quasi‐experimental evaluation research.</p> <hd id="AN0160530016-5">Outcome measures</hd> <p>The major focus of the <emph>FIRST</emph> longitudinal study is to compare students who have participated in the program during middle and high school with matched comparison students on STEM‐related interests, attitudes, and college level behaviors. Outcome measures include a combination of interest and scale measures and behavioral measures such as STEM‐related course‐taking in college. For the purposes of the current study, we have focused on the STEM interest and measures, and interest and course taking during the first year in college. Interest and outcomes are assessed by a set of scales as detailed below:</p> <p></p> <ulist> <item> STEM Interest: A four‐question scale assessing students' level of interest in science, technology, engineering, and mathematics, Alpha = 0.67, created by authors</item> <p></p> <item> Involvement in Science and Technology Activities: A six‐question scale assessing students' involvement in non‐school STEM activities, Alpha = 0.76, adapted from the US Department of Education, High School Longitudinal Study, 2009</item> <p></p> <item> STEM Careers: A seven‐question scale measuring interest in STEM‐related careers, such as a scientist, engineer, computer specialist, Alpha = 0.81, adapted from the BS Barker (2006) Nebraska 4‐H Study</item> <p></p> <item> Science, Math, and Technology Identity: A 12‐question scale measuring the extent to which one sees themselves as a science, math or technology person, Alpha = 0.70, adapted from the US Department of Education, High School Longitudinal Study, 2009</item> <p></p> <item> STEM Understanding and Pathways: An 11‐question scale that assesses one's awareness of STEM application in the real world and interest in learning more about STEM, Alpha = 0.94, created and tested by authors in prior studies (see Appendix for detailed scale questions)</item> </ulist> <p>Behavioral outcome measures at the end of participants' first year in college included questions on interest in college majors, college course taking, and extracurricular STEM activities. Control variables for the analyses included demographic information such as age, gender, and race/ethnicity, as well as information on program participation and academic background (including one's honors courses at baseline). Parent/caregiver surveys provided information on family income and parental support for their children's involvement in STEM. As discussed below, these baseline characteristics were used in the analysis to control for differences between intervention and comparison group member characteristics.</p> <hd id="AN0160530016-6">Sample</hd> <p>To address these questions, the study has been tracking at baseline 1273 students (822 intervention participants and 451 comparison students) over 7 years beginning with entry of participants into the intervention program. <emph>FIRST</emph> participants were recruited through a national sample of the program's teams across 10 states. This sample was gathered by using a stratified random sampling process, in order to match the distribution of intervention program's teams when considering community (urban, rural, suburban); community income (percent above/below poverty level); and proximity to other <emph>FIRST</emph> teams, in order to track participants across teams. Based on the random sample of <emph>FIRST</emph> teams, schools were approached by the study researchers who sent 15,000 packets of recruitment materials to team leaders who then distributed the information to math and science classes. All participants were thus gathered through convenience sampling with both <emph>FIRST</emph> and comparison group students opting into the study, described to them as an exploration of the ways in which young people are involved in science and technology, and how their interests, activities, educational goals, and career plans change over time.</p> <p>Recruitment occurred in two waves: the initial group of students in Fall 2012, in addition to recruiting additional participants in Fall 2013 to increase the study sample size. Once recruited, intervention and comparison students were surveyed at baseline and post‐program in their first year, with annual follow‐up surveys each spring thereafter. The initial baseline surveys were administered in Fall 2012 (Wave One) and Fall 2013 (Wave Two). A baseline survey of parents provided additional background information on the family context for team members and comparison students.</p> <p>As of the Spring 2020 surveys, data have been collected through 84 months of follow‐up (baseline, post‐program, and six annual follow‐up surveys). Overall, 74% of study participants have remained in the study throughout the 84 months of data collection, including 67% of program participants and 86% of comparison group students. For this article, we focus on 806 study participants with at least 1 year of college, including 491 in the intervention group and 315 in the comparison group.</p> <hd id="AN0160530016-7">Freshman intervention and comparison group characteristics</hd> <p>We first test differences between the intervention and comparison groups (Table A1) contrasting baseline characteristics. Among <emph>FIRST</emph> participants, 66% were male and 34% female. Approximately 66% of <emph>FIRST</emph> participants were white, 21% Asian, and 7% Black/African‐American; in a separate item, 14% reported that they were Hispanic. Program participants included a mix of students from urban (22%), suburban (56%), and rural (22%) communities; additionally, 23% were from families that might be classified as low income.</p> <p>College‐going participants and comparison students closely resembled each other at baseline when observing demographic characteristics and academic background. Comparison group members were more likely to be female. Participants and comparison students included comparable proportions of African‐American and Hispanic students, though a much higher percentage of program participants were Asian. The two groups had no significant differences in terms of community type and family income. There were, however, significant differences at baseline in initial interest and involvement in STEM. Program participants scored significantly higher on baseline measures of STEM‐related attitudes. Specifically, the comparison group showed low rates of interest in STEM careers with especially low levels of interest in engineering jobs. However, comparison group members engaged in STEM‐related activities—including math clubs, science camps, and summer programs—at slightly higher rates than <emph>FIRST</emph> participants. As discussed below, these and other baseline differences were controlled for in the analysis.</p> <hd id="AN0160530016-8">ANALYSIS AND RESULTS</hd> <p>The primary analysis applied repeated measures linear mixed models analysis to test differences in STEM attitudes in the intervention and comparison groups. This approach estimated average outcome scores on STEM‐related attitude and interest scales for the two groups accounting for differences between the groups at baseline and data from all eight points in time (baseline, post‐program, and six annual follow‐up surveys). Such mixed analyses are advantageous to assessing longitudinal studies, as they make full use of cases with missing data, rather than excluding them from the dataset (O'Connell & McCoach, [<reflink idref="bib33" id="ref51">33</reflink>]; Singer, [<reflink idref="bib39" id="ref52">39</reflink>]). The study also conducted logistic regression analyses to examine group differences for binary outcomes. To do so, we created a binary variable measuring increase versus no increase on the STEM attitude scales, and also tested differences in interest and actual STEM course‐taking during the first semester in college.</p> <p>All analyses controlled for differences between the intervention and comparison groups at baseline, including covariates for gender, race/ethnicity, family income, participation in STEM honors courses at baseline (as a proxy for baseline STEM interest), and baseline parental/caregiver support for STEM. The mixed models analysis of scale scores includes baseline scores for the scale being analyzed as a data point in the analysis (hence controlling for baseline differences); the logit analyses on changes in STEM attitude scores include baseline scale scores as covariates for each scale being measured.</p> <p>The guiding questions for this article include whether previously detected positive impacts of the intervention continued to persist as students continue through school and into college and whether there is further evidence of longer‐term impacts from program participation in the form of increased interest in STEM‐related majors, STEM course‐taking, and involvement in other STEM‐related activities in college. Students who completed a post‐survey at the end of their first year of college were included in the sample of the current analysis.</p> <hd id="AN0160530016-9">Impacts on STEM‐related attitudes and interests</hd> <p>As Table A2 shows, the 84‐month survey data indicated a positive impact for <emph>FIRST</emph> participants on all five of the STEM‐related interest and attitude measures at the end of their first year in college. Based on the mixed methods analysis, <emph>FIRST</emph> participants showed significantly higher scale scores at 84 months than comparison group students on all five measures after adjusting for differences at baseline. In each case, the differences were significant at <emph>p</emph> ≤ 0.05. The effect sizes for each impact were either "large" (the impact on STEM interest) or "medium," indicating that program impacts were not only statistically significant, but also large enough to represent a meaningful difference in attitudes and interests.</p> <p>Extending this analysis, we applied logistic regression analysis to examine whether <emph>FIRST</emph> participants were more likely to show increased scores between baseline and 84 months than comparison students. As Table A3 shows, after adjusting for differences in baseline characteristics and baseline scale scores, <emph>FIRST</emph> participants were more likely to show increased scores on all five measures. All differences were significant at <emph>p</emph> ≤ 0.05.</p> <p>Additional analyses for subpopulations not shown here also showed significant differences on the STEM scales. Male and female program participants, white and students of color, higher and lower income <emph>FIRST</emph> students, and those from urban, rural, and suburban communities, all showed significantly higher scale scores than those of comparable students in the comparison group. In most cases, effect sizes were "medium" or "large."</p> <p>While both male and female <emph>FIRST</emph> students showed significantly higher scores than their comparison group counterparts, scale scores for female <emph>FIRST</emph> participants were significantly greater than those for program participants as a whole. That is, female <emph>FIRST</emph> students showed additional, statistically higher scores beyond those for all <emph>FIRST</emph> participants, on all STEM‐related measures. All differences were statistically significant at <emph>p</emph> ≤ 0.05.</p> <hd id="AN0160530016-10">College‐related impacts</hd> <p> <emph>FIRST</emph> students reported higher levels of interest in STEM majors at the end of their first year in college, though with a clear distinction between engineering and technology‐related majors and other STEM fields. Table A4 shows the percent of all first‐year college students who were "very interested" in majoring in the specified field (i.e., reporting a 6, 7, or "already declared" on a 7‐point scale measuring interest in specific college majors). The calculations of statistical significance and the odds ratios are based on a logistic regression analysis that calculates the relative likelihood of being "very interested" in majoring in each field after adjusting for baseline difference. In this instance, an odds ratio of 1 indicates an equal likelihood of being highly interested in majoring in a field between the program participants and comparison students; a ratio above 1 indicates that <emph>FIRST</emph> students were <emph>more</emph> likely to be highly interested; a ratio below 1 indicated that <emph>FIRST</emph> participants are <emph>less</emph> likely to be highly interested.</p> <p>At the end of their first year in college, <emph>FIRST</emph> students reported statistically significant higher interest in majoring in computer science, engineering, and robotics in their first year in college than comparison students. <emph>FIRST</emph> participants were over two times as likely (2.17 times) to be highly interested in majoring in computer science, 3 times more likely to be interested in engineering, and 2.8 times more likely to be interested in robotics than comparison students. Overall, 53% of <emph>FIRST</emph> students reported being "highly interested" in majoring in engineering; 41% reported high interest in computer science and 37% were interested in majoring in robotics during their first year of college.</p> <p> <emph>FIRST</emph> students were less likely to major in other STEM fields, such as the biological sciences. While <emph>FIRST</emph> participants were more interested in engineering and technology‐related fields, comparison group members showed greater interest in the biological sciences and health‐related majors. Participants from <emph>FIRST</emph> were roughly half as likely as comparison students to be interested in majoring in biology (odds ratio of 0.535) and health professions (odds ratio of 0.514). These differences were also statistically significant.</p> <p> <emph>FIRST</emph> participants were statistically significantly more likely to take engineering courses in their first year at college than comparison students, and less likely to take courses in the non‐engineering‐related STEM field of biology, or in social science‐related fields. As Table A5 shows, intervention program participants were 2.3 times more likely to take engineering courses in their freshman year than comparison students, with 32% of program participants reporting that they took an engineering course compared to 13% of the comparison students. At the same time, <emph>FIRST</emph> participants were roughly half as likely as comparison students to take courses in the arts and humanities, biology, social sciences, and pre‐professional courses in law or medicine.</p> <p>The positive impacts on interest in engineering and technology majors and course‐taking were also evident when the results are broken down by gender. In particular, female intervention participants were more than 3.5 times more likely to be interested in majoring in engineering, 2.2 times more likely to be interested in majoring in computer science, and 2.3 times more likely to be interested in majoring in robotics than female comparison students. Female intervention participants were also 4.2 times more likely to take an engineering course in their first year of college than female comparison students. All of those results were statistically significant at <emph>p</emph> ≤ 0.05.</p> <p>Finally, the study also asked college students about the kinds of co‐curricular activities and opportunities they were engaged in during their first year at college. As Table A6 shows, <emph>FIRST</emph> participants were more likely than comparison students to engage in a variety of engineering and technology‐related activities in their first year of college; all differences were statistically significant. <emph>FIRST</emph> participants were also more likely to have a STEM‐related internship during their freshman year; to belong to a computer, engineering, or math club; to participate in computer or engineering competitions; and, to receive an engineering‐related grant or scholarship. <emph>FIRST</emph> participants were less likely than comparison students to have a summer job, but those with jobs were more likely to have one in a STEM‐related field. Other types of activities (not shown in the table) such as participation in apprenticeship programs, science clubs or math and science competitions, and participation in environmental clubs and programs showed no significant differences between program participants and comparison students.</p> <hd id="AN0160530016-11">DISCUSSION</hd> <p>The data presented here suggest that intensive, hands‐on after school STEM experiences not only positively impact the STEM‐related attitudes and interests of middle and high school aged youth, but that these impacts persist beyond secondary school and into college. Our findings underscore the ability of programs such as <emph>FIRST</emph> to produce such outcomes, resulting from innovative interventions including using a mentor‐based and hands‐on approach, fostering curiosity and innovation in STEM subjects, and encouraging stronger senses of leadership, confidence, agency, and communication among program participants. The data from first‐year college students demonstrate that positive impacts persist beyond high school and into college. At this point in time in the longitudinal study, college student data must be seen as preliminary as not all participants had entered college by the time of the 84‐month survey is limited. However, the first‐year college data reported here suggest that not only do the impacts on STEM‐related attitudes persist into college, but that they are reflected in the choices that <emph>FIRST</emph> participants make about college majors, first‐year courses, and engagement in STEM‐related co‐curricular activities. We find these findings to have significant implications on both societal and individual levels, including those pertaining to the national and global impacts of a transforming U.S. STEM workforce, as well as those that appear to promise greater opportunity for historically underrepresented and underserved populations.</p> <hd id="AN0160530016-12">Differences among program impacts on STEM outcomes</hd> <p>A key question for this study is whether after‐school robotics programs can effectively promote and support interests and attitudes likely to lead to sustained STEM involvement. Scholarship suggests that increased interest in STEM, a sense of STEM identity, an understanding of the relevance and utility of STEM in the real world, and the kinds of career opportunities available all promote increased involvement in STEM‐related education and careers (Blotnicky et al., [<reflink idref="bib6" id="ref53">6</reflink>]; Dou et al., [<reflink idref="bib14" id="ref54">14</reflink>]). The interventions incorporated into the program model appear to encourage stronger senses of each of these measures, as indicated by the study findings. Both mixed models and logistic regression analyses reveal <emph>FIRST</emph> participants as having significantly higher scale scores on all five STEM measures than comparison group students, and the impacts on STEM‐related interests and attitudes are also shown to persist among <emph>FIRST</emph> participants in their first year of college (Table A7).</p> <p>Our findings indicate impacts of the intervention persist into <emph>FIRST</emph> participants' college experience to be of particular significance. <emph>FIRST</emph> participants exhibited the greatest difference in interest in engineering majors when contrasted against comparison students, and are shown to be three times more likely to express a high interest in the field. Such findings align with our results regarding actual course‐taking as well—program participants were nearly three times more likely than comparison students to take engineering courses in their first year of college. It appears, therefore, that were the program's set of interventions to be applied more widely, there may be an impact on the engineering pipeline from college to career, which is significant due to recent trends showing only one of every 10 college graduates worldwide studied engineering in the U.S. (American Affairs, [<reflink idref="bib2" id="ref55">2</reflink>]). Given careers in engineering are projected to grow the most among STEM jobs within the next several years (U.S. Bureau of Labor Statistics, [<reflink idref="bib41" id="ref56">41</reflink>]), increased participation in STEM fields such as engineering will be critical in order to ensure the United States is equipped to keep up with a knowledge‐driven global economy that significantly depends upon STEM careers.</p> <p>Program participants are also nearly three times more likely to have high interest in robotics majors, which we find notable given the nature and content of <emph>FIRST's</emph> components. Further, as robotics combines mechanical, electronic, and computer engineering, those pursuing the field may be even better equipped to contribute to areas of daily life that increasingly depend upon STEM knowledge and skills. This includes rapidly growing industries like artificial intelligence, driverless automobiles, surgical robots, e‐commerce robots, and safety and security robots (World Economic Forum, [<reflink idref="bib45" id="ref57">45</reflink>]). As our study findings emphasize significant differences favoring <emph>FIRST</emph> participants in their pursuit of STEM fields in college, it appears highly likely that these students will seek to continue to engage in these subjects in their later college years as well as their career paths, which will benefit not only themselves as individuals who will both gain important skills and knowledge as well as secure futures in high‐yield careers, but also the larger American society in its national <emph>and</emph> global footprint.</p> <hd id="AN0160530016-13">Differences among key subpopulations</hd> <p>The seven‐year longitudinal survey data show positive, statistically significant impacts on a core set of STEM‐related attitudes for <emph>FIRST</emph> participants as a whole and for students from communities that are historically underrepresented in STEM fields. Our study sample includes several such subgroups, including female participants, students of color, low‐income participants, and students from urban and rural communities. In most cases, not only were the differences in STEM‐related attitudes and interests statistically significant, but the effect size measures indicate that the differences were large enough to represent meaningful differences.</p> <p>The study findings are noteworthy, as they suggest that programs such as <emph>FIRST</emph> have the capacity to close gaps in STEM participation between men and women (Cheryan et al., [<reflink idref="bib9" id="ref58">9</reflink>]; Saw et al., [<reflink idref="bib37" id="ref59">37</reflink>]), and whites and Blacks (Brown et al., [<reflink idref="bib7" id="ref60">7</reflink>]; Pew Research Center, [<reflink idref="bib35" id="ref61">35</reflink>]). As girls and Black children have been systematically excluded from participating, let alone excelling in STEM studies, putting STEM within arm's reach is critical in ensuring the possibility of closing not only opportunity gaps but pay gaps as well (State of the Gender Pay Gap Report, [<reflink idref="bib40" id="ref62">40</reflink>]). Further, the inclusion of minoritized groups within STEM careers has been shown to improve their economic security, and ensure a diverse STEM workforce, which is integral for meeting STEM workforce demands (Benish, [<reflink idref="bib5" id="ref63">5</reflink>]). Greater access to STEM fields can only be further enriched with the involvement of currently underrepresented groups, and such access begins with STEM education and programming.</p> <hd id="AN0160530016-14">LIMITATIONS</hd> <p>There are some important limitations to the study. As random assignment to the intervention and control group was not feasible, this study uses a comparison group design. As shown in Table A1, there are notable differences in baseline STEM attitudes between <emph>FIRST</emph> participants and comparison students. While the statistical analysis takes those differences into account, it is possible that there are unmeasured differences that are not reflected in the analysis. The study also focuses on one particular group of intervention programs, though it does encompass several STEM areas of interest (engineering, computer science, and robotics). Other robotics programs and other types of after‐school STEM activities may have different outcomes. Ideally, other researchers can begin examining the broader array of after‐school STEM programming. Finally, the 84‐month data presented here represent interim findings for the study. Current plans call for data collection through 10 years of follow‐up. With additional data, we should be able to continue to examine even longer‐term impacts on STEM‐related attitudes as well as those upon educational and career decisions.</p> <hd id="AN0160530016-15">CONCLUSION</hd> <p>Within such limitations, our analyses still strongly suggest that after‐school STEM programs that utilize hands‐on, unique interventions such as the one at hand can have a positive, long‐term impact upon participant attitudes about STEM and their college experience. <emph>FIRST</emph> participants showed a significantly stronger interest in STEM and STEM careers, and continued to think of themselves as "STEM people" to a greater degree than comparison group members in the study. Such differences in attitudes were reflected in the differences in the respective levels of interest in technology‐related majors (engineering, computer science, and robotics) and initial course‐taking, and appear to lead to heightened engagement in non‐classroom‐based STEM activities, including clubs, competitions, internships, and summer jobs. In that regard, the evidence presented here suggests that the <emph>FIRST</emph> program is meeting its primary goal of generating and helping to sustain interest in STEM and encouraging young people to pursue these fields in college. Arguably even more significant, however, is the promise <emph>FIRST</emph> has in generating positive growth in the U.S. STEM workforce, through its introduction and encouragement of STEM fields to youth during a pivotal stage in their lives.</p> <hd id="AN0160530016-16">FUNDING INFORMATION</hd> <p>Financial support for this study has been provided by For Inspiration and Recognition of Science and Technology (FIRST®). Partial funding has been provided by the Overdeck Family Foundation.</p> <hd id="AN0160530016-17">CONFLICT OF INTEREST</hd> <p>The authors have no conflicts of interest to disclose.</p> <hd id="AN0160530016-18">A APPENDIX</hd> <p>Tables A1–A7</p> <p>A1 TABLE FIRST and comparison group characteristics</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left" /><th align="left"><italic>FIRST</italic></th><th align="left">Comparison</th><th align="left">All</th></tr><tr><th align="left">Measure</th><th align="left"><italic>N</italic> = 491</th><th align="left"><italic>N</italic> = 315</th><th align="left"><italic>N</italic> = 806</th></tr></thead><tbody valign="top"><tr><td align="left">Gender</td></tr><tr><td>Male</td><td>66.4%</td><td>41.6%*</td><td>56.7%</td></tr><tr><td align="left">Race</td></tr><tr><td>Asian</td><td>21.4%</td><td>9.4%*</td><td>16.8%</td></tr><tr><td>Black/African‐American</td><td>7.4%</td><td>5.9%</td><td>6.8%</td></tr><tr><td>White</td><td>65.6%</td><td>84.6%</td><td>72.9%</td></tr><tr><td align="left">Ethnicity</td></tr><tr><td>Hispanic</td><td>13.6%</td><td>10.3% (NS)</td><td>12.3%</td></tr><tr><td align="left">Geography at baseline</td></tr><tr><td>Urban</td><td>22.2%</td><td>23.4% (NS)</td><td>22.7%</td></tr><tr><td>Suburban</td><td>56.2%</td><td>50.8%</td><td>54.1%</td></tr><tr><td>Rural</td><td>21.6%</td><td>25.7%</td><td>23.2%</td></tr><tr><td align="left">Family income at baseline</td></tr><tr><td>Low income</td><td>23.3%</td><td>21.7% (NS)</td><td>22.6%</td></tr><tr><td>Higher income</td><td>76.7%</td><td>78.3%</td><td>77.4%</td></tr><tr><td align="left">Survey scales (average baseline scale score)</td></tr><tr><td>STEM Interest (5‐point scale)</td><td>4.1</td><td>3.7*</td><td align="left" /></tr><tr><td>Involvement in Science & Technology Activities (5‐point scale)</td><td>3.4</td><td>3.1*</td><td align="left" /></tr><tr><td>STEM Careers (7‐point scale)</td><td>4.5</td><td>3.7*</td><td align="left" /></tr><tr><td>Science, Math & Technology Identity (4‐point scale)</td><td>3.1</td><td>2.9*</td><td align="left" /></tr><tr><td>STEM Understanding & Pathways (7‐point scale)</td><td>5.6</td><td>4.9*</td><td align="left" /></tr></tbody></table> </ephtml> </p> <p>1 <emph>Note</emph>: An asterisk (*) indicates differences between participants and comparison group members that are statistically significant <emph>p</emph> ≤ 0.05. (NS) stands for not significant.</p> <p>A2 TABLE Mixed models results: Impacts on STEM measures at the end of first year in college</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left" /><th align="left">Estimated outcomes</th><th align="left">Difference</th><th align="left">Effect size</th></tr><tr><th align="left">STEM measures</th><th align="left"><italic>FIRST</italic></th><th align="left">Comparison</th><th align="left">Value</th><th align="left">Sig.</th><th align="left"><italic>ω</italic><sup>2</sup></th><th align="left">Strength</th></tr></thead><tbody valign="top"><tr><td>STEM Interest</td><td>4.00</td><td>3.50</td><td>0.50</td><td><italic>0.000</italic></td><td>0.14</td><td>Large</td></tr><tr><td>Involvement in Science & Technology Activities</td><td>3.37</td><td>2.93</td><td>0.44</td><td><italic>0.000</italic></td><td>0.10</td><td>Medium</td></tr><tr><td>Interest in STEM Careers</td><td>4.21</td><td>3.51</td><td>0.70</td><td><italic>0.000</italic></td><td>0.11</td><td>Medium</td></tr><tr><td>Science, Math & Technology Identity</td><td>3.14</td><td>2.97</td><td>0.17</td><td><italic>0.000</italic></td><td>0.08</td><td>Medium</td></tr><tr><td>STEM Understanding & Pathways</td><td>5.66</td><td>4.95</td><td>0.71</td><td><italic>0.000</italic></td><td>0.12</td><td>Medium</td></tr></tbody></table> </ephtml> </p> <p>2 <emph>Note</emph>: Controlling for Gender, Race, Honors Courses in HS, Family Income and parental support for STEM. Effect size measure is "Omega Squared" (<emph>ω</emph><sups>2</sups>). Effect size categories: Small > 0.01, medium > 0.06, large > 0.14.</p> <p>A3 TABLE Logistic regression (logit) results for STEM scale scores at 84 months, freshman in college</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left" /><th align="left">Pct. with increased scores baseline to follow‐up (unadjusted)</th><th align="left">Relative probability of increase</th><th align="left" /></tr><tr><th align="left">Measure</th><th align="left"><italic>FIRST</italic> % increase</th><th align="left">Comparison % increase</th><th align="left">Odds ratio</th><th align="left">Sig.</th></tr></thead><tbody valign="top"><tr><td>STEM Interest</td><td>36.2%</td><td>29.8%</td><td>1.7</td><td><italic>0.011</italic></td></tr><tr><td>Involvement in Science & Technology Activities</td><td>43.7%</td><td>38.0%</td><td>1.8</td><td><italic>0.001</italic></td></tr><tr><td>Interest in STEM Careers</td><td>36.9%</td><td>32.1%</td><td>1.5</td><td><italic>0.012</italic></td></tr><tr><td>Science, Math & Technology Identity</td><td>52.6%</td><td>48.0%</td><td>2.0</td><td><italic>0.000</italic></td></tr><tr><td>STEM Understanding & Pathways</td><td>52.5%</td><td>48.6%</td><td>1.6</td><td><italic>0.039</italic></td></tr></tbody></table> </ephtml> </p> <p>3 <emph>Note</emph>: Controlling for Gender, Race, Honors Courses in HS, Family Income, parental support for STEM and scale at baseline.</p> <p>A4 TABLE Interest in college majors (percent highly interested) at the end of first year in college</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left" /><th align="left">Percent highly interested (unadjusted)</th><th align="left">Relative likelihood of being interested (logit)</th></tr><tr><th align="left">Subject</th><th align="left"><italic>FIRST</italic></th><th align="left">Comparison</th><th align="left">Sig.</th><th align="left">Odds ratio</th></tr></thead><tbody valign="top"><tr><td>Arts and Humanities</td><td><italic>14.1</italic>%</td><td><italic>23.5</italic>%</td><td><italic>0.050</italic></td><td><italic>0.651</italic></td></tr><tr><td><italic>Biological Sciences</italic></td><td><italic>18.4%</italic></td><td><italic>26.7%</italic></td><td><italic>0.002</italic></td><td><italic>0.535</italic></td></tr><tr><td>Business</td><td>19.7%</td><td>23.8%</td><td>0.665</td><td>0.915</td></tr><tr><td><italic>Computer Science</italic></td><td><italic>40.7%</italic></td><td><italic>19.7%</italic></td><td><italic>0.000</italic></td><td><italic>2.165</italic></td></tr><tr><td>Education</td><td>9.5%</td><td>14.0%</td><td>0.257</td><td>0.720</td></tr><tr><td><italic>Engineering</italic></td><td><italic>53.0%</italic></td><td><italic>20.7%</italic></td><td><italic>0.000</italic></td><td><italic>3.012</italic></td></tr><tr><td><italic>Health Professions</italic></td><td><italic>16.8%</italic></td><td><italic>28.2%</italic></td><td><italic>0.001</italic></td><td><italic>0.514</italic></td></tr><tr><td>Mathematics</td><td>19.3%</td><td>16.8%</td><td>0.195</td><td>0.740</td></tr><tr><td>Physical Sciences</td><td>24.2%</td><td>19.8%</td><td>0.420</td><td>0.845</td></tr><tr><td>Social Sciences</td><td>16.2%</td><td>25.0%</td><td>0.253</td><td>0.786</td></tr><tr><td>Tech/Vocational</td><td>13.5%</td><td>9.2%</td><td>0.304</td><td>1.324</td></tr><tr><td>Other Professional</td><td>12.2%</td><td>16.4%</td><td>0.350</td><td>0.748</td></tr><tr><td><italic>Robotics</italic></td><td><italic>36.7%</italic></td><td><italic>12.4%</italic></td><td><italic>0.000</italic></td><td><italic>2.844</italic></td></tr></tbody></table> </ephtml> </p> <p>4 <emph>Note</emph>: Logit Regression controlling for Gender, Race, Honors Courses at Baseline, Family Income, Parental Support for STEM and baseline STEM interest. Italics are statistically significant at <emph>p</emph> ≤ 0.05 or less. "Highly Interested" is based on responding 6, 7, or "already declared" on a scale of 1–7 for each major field.</p> <p>A5 TABLE First year in college course‐taking</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left" /><th align="left">Percent taking at least one course (unadjusted)</th><th align="left">Relative likelihood of taking a course (logit)</th></tr><tr><th align="left">Subject</th><th align="left"><italic>FIRST</italic></th><th align="left">Comparison</th><th align="left">Sig.</th><th align="left">Odds ratio</th></tr></thead><tbody valign="top"><tr><td><italic>Arts and Humanities</italic></td><td><italic>49.9%</italic></td><td><italic>59.9%</italic></td><td><italic>0.002</italic></td><td><italic>0.587</italic></td></tr><tr><td><italic>Biological Sciences</italic></td><td><italic>19.7%</italic></td><td><italic>30.8%</italic></td><td><italic>0.001</italic></td><td><italic>0.519</italic></td></tr><tr><td><italic>Computer Science/Programming</italic></td><td><italic>31.1</italic>%</td><td><italic>19.9</italic>%</td><td><italic>0.048</italic></td><td><italic>2.118</italic></td></tr><tr><td><italic>Business</italic></td><td><italic>9.2</italic>%</td><td><italic>16.9</italic>%</td><td><italic>0.049</italic></td><td><italic>0.605</italic></td></tr><tr><td>Education</td><td>1.8%</td><td>4.3%</td><td>0.317</td><td>0.609</td></tr><tr><td><italic>Engineering</italic></td><td><italic>32.2%</italic></td><td><italic>12.6%</italic></td><td><italic>0.000</italic></td><td><italic>2.300</italic></td></tr><tr><td>Health Professions</td><td>4.72%</td><td>7.6%</td><td>0.504</td><td>0.786</td></tr><tr><td>Mathematics</td><td>51.7%</td><td>48.0%</td><td>0.408</td><td>1.161</td></tr><tr><td>Physical Sciences</td><td>39.6%</td><td>32.1%</td><td>0.796</td><td>1.123</td></tr><tr><td><italic>Social Sciences</italic></td><td><italic>29.3%</italic></td><td><italic>42.1%</italic></td><td><italic>0.004</italic></td><td><italic>0.519</italic></td></tr><tr><td>Technical/Vocational</td><td>3.1%</td><td>2.6%</td><td>0.743</td><td>1.174</td></tr><tr><td><p><italic>Other Professional Fields</italic></p><p><italic>(Law, medicine, etc.)</italic></p></td><td><italic>4.0%</italic></td><td><italic>10.9%</italic></td><td><italic>0.007</italic></td><td><italic>0.363</italic></td></tr></tbody></table> </ephtml> </p> <p>5 <emph>Note</emph>: Logit Regression controlling for Program, Race, Honors Courses at Baseline, Family Income, Parental Support for STEM and Baseline STEM interest. Italics are statistically significant at <emph>p</emph> = 0.05 or less.</p> <p>A6 TABLE STEM‐related activities in first year in college</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Activity</th><th align="left"><italic>FIRST</italic></th><th align="left">Comparison</th></tr></thead><tbody valign="top"><tr><td>STEM‐Related Internship</td><td>15.9%</td><td>5.8%*</td></tr><tr><td>Joined Computer Club</td><td>15.3%</td><td>6.0%*</td></tr><tr><td>Joined Engineering Club</td><td>26.3%</td><td>10.2%*</td></tr><tr><td>Participated in a Computer Competition</td><td>7.3%</td><td>3.2%*</td></tr><tr><td>Participated in an Engineering Competition</td><td>9.8%</td><td>3.5%*</td></tr><tr><td>Received Engineering‐Related Grant or Scholarship</td><td>7.5%</td><td>3.8%*</td></tr><tr><td>STEM‐Related Summer Job</td><td>13.5%</td><td>6.7%*</td></tr></tbody></table> </ephtml> </p> <p>6 <emph>Note</emph>: Asterisk (*) indicates difference that are statistically significant at <emph>p</emph> ≤ 0.05. Significance tests do not include adjustments for baseline differences.</p> <p>A7 TABLE STEM scale sources and details</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Domain</th><th align="left">Source</th><th align="left">Items</th></tr></thead><tbody valign="top"><tr><td><p>Interest in STEM</p><p>Alpha = 0.67</p></td><td>Brandeis University</td><td>How interested are you in science, technology, engineering and/or math (STEM)? Please mark on a scale from 1 (Not interested) to 5 (Very interested).<list list-type="Bullet"><list-item><p>Science</p></list-item><list-item><p>Technology</p></list-item><list-item><p>Engineering</p></list-item><list-item><p>Math</p></list-item></list></td></tr><tr><td><p>Involvement in Science and Technology Activities</p><p>Alpha = 0.76</p></td><td>Adapted from US Department of Education, High School Longitudinal Study of 2009 (Items c–f added)</td><td>Other than for school, how much do you like to do the following? Please mark on a scale from 1 (Do not like at all) to 5 (Like a lot).<list list-type="Bullet"><list-item><p>Read science books and magazines?</p></list-item><list-item><p>Visit web sites for information on computers and technology?</p></list-item><list-item><p>Talk with friends or family about science and technology?</p></list-item><list-item><p>Watch programs on science and technology on television (for example: Science Channel, National Geographic, Discovery Channel)?</p></list-item><list-item><p>Design web pages?</p></list-item><list-item><p>Take apart things (like motors, computers, toasters) to see how they work?</p></list-item></list></td></tr><tr><td><p>STEM Careers</p><p>Alpha = 0.81</p></td><td>Adapted from Barker, Nebraska 4‐H study (items d‐g added)</td><td>How interested are you in each of the following jobs related to STEM (science, technology, engineering, and mathematics)? Please mark one response in each row using the scale from 1 (Not interested at all) to 7 (Very interested). If you are not sure, please give us your best answer.<list list-type="Bullet"><list-item><p>Scientist</p></list-item><list-item><p>Engineer</p></list-item><list-item><p>Mathematician</p></list-item><list-item><p>Computer or Technology Specialist</p></list-item><list-item><p>STEM Educator/ Teacher</p></list-item><list-item><p>Inventor</p></list-item><list-item><p>Skilled technician (for example: auto or aircraft mechanic, machinist, electrician, construction)</p></list-item></list></td></tr><tr><td><p>Science, Math and Technology Identity</p><p>Alpha = 0.70</p></td><td>Adapted from US Department of Education, High School Longitudinal Study of 2009 (Items i‐l added)</td><td>Now we are going to ask you a few questions about your beliefs about math and science. How much do you agree or disagree with the following?<list list-type="Bullet"><list-item><p>I see myself as a math person.</p></list-item><list-item><p>Others see me as a math person.</p></list-item><list-item><p>Most people can learn to be good at math.</p></list-item><list-item><p>You have to be born with the ability to be good at math.</p></list-item><list-item><p>I see myself as a science person.</p></list-item><list-item><p>Others see me as a science person.</p></list-item><list-item><p>Most people can learn to be good at science.</p></list-item><list-item><p>You have to be born with the ability to be good at science.</p></list-item><list-item><p>I see myself as a technology person.</p></list-item><list-item><p>Others see me as a technology person.</p></list-item><list-item><p>Most people can learn to be good at technology.</p></list-item><list-item><p>You have to be born with the ability to be good at technology.</p></list-item></list></td></tr><tr><td><p>STEM Understanding and Pathways</p><p>Alpha = 0.94</p></td><td>Brandeis University, adapted from prior evaluation studies</td><td>We are interested in learning about how you think about yourself and your future. Using a scale from 1 (Not True at All for Me) to 7 (Very True for Me), please tell us how true each of the following statements are for you.<list list-type="Bullet"><list-item><p>I want to learn more about science and technology.</p></list-item><list-item><p>I can use math and science to do something interesting.</p></list-item><list-item><p>I have a good idea of what I want to study in college or technical school.</p></list-item><list-item><p>I am interested in having a job or career that uses science and technology.</p></list-item><list-item><p>I understand different ways that science and technology can be used to solve problems in the real world.</p></list-item><list-item><p>I have a good understanding of how engineers work to solve problems.</p></list-item><list-item><p>I know about a variety of jobs and careers in STEM (science, technology, engineering and/or mathematics).</p></list-item><list-item><p>I have the kinds of skills that are needed to be a scientist or engineer.</p></list-item><list-item><p>I can make a good living as a scientist or an engineer.</p></list-item><list-item><p>I would enjoy working as a scientist or an engineer.</p></list-item></list></td></tr></tbody></table> </ephtml> </p> <ref id="AN0160530016-19"> <title> Footnotes </title> <blist> <bibl id="bib1" idref="ref18" type="bt">1</bibl> <bibtext> The website for the University of Michigan's Gender & Achievement Research Program also provides an extensive bibliography of math and science achievement articles at <ulink href="http://www.rcgd.isr.umich.edu/garp/">http://www.rcgd.isr.umich.edu/garp/</ulink>.</bibtext> </blist> <blist> <bibl id="bib2" idref="ref2" type="bt">2</bibl> <bibtext> Funding information FIRST (For Inspiration and Recognition of Science and Technology); The Overdeck Family Foundation</bibtext> </blist> <blist> <bibl id="bib3" idref="ref6" type="bt">3</bibl> <bibtext> For the purposes of this study, low income is defined as obtaining an annual income of less than $50,000.</bibtext> </blist> </ref> <ref id="AN0160530016-20"> <title> REFERENCES </title> <blist> <bibtext> America Competes Act. 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  Data: Transforming STEM Outcomes: Results from a Seven-Year Follow-Up Study of an After-School Robotics Program's Impacts on Freshman Students
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  Data: <searchLink fieldCode="AR" term="%22Meschede%2C+Tatjana%22">Meschede, Tatjana</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-8019-7701">0000-0001-8019-7701</externalLink>)<br /><searchLink fieldCode="AR" term="%22Haque%2C+Zora%22">Haque, Zora</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-3256-0494">0000-0003-3256-0494</externalLink>)<br /><searchLink fieldCode="AR" term="%22Warfield%2C+Marji+Erickson%22">Warfield, Marji Erickson</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-3198-2348">0000-0002-3198-2348</externalLink>)<br /><searchLink fieldCode="AR" term="%22Melchior%2C+Alan%22">Melchior, Alan</searchLink><br /><searchLink fieldCode="AR" term="%22Burack%2C+Cathy%22">Burack, Cathy</searchLink><br /><searchLink fieldCode="AR" term="%22Hoover%2C+Matthew%22">Hoover, Matthew</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22School+Science+and+Mathematics%22"><i>School Science and Mathematics</i></searchLink>. Nov 2022 122(7):343-357.
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  Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
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  Data: 15
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  Label: Publication Date
  Group: Date
  Data: 2022
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  Label: Document Type
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  Data: Journal Articles<br />Reports - Research
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  Label: Education Level
  Group: Audnce
  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
– Name: Subject
  Label: Descriptors
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  Data: <searchLink fieldCode="DE" term="%22Student+Attitudes%22">Student Attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Robotics%22">Robotics</searchLink><br /><searchLink fieldCode="DE" term="%22STEM+Education%22">STEM Education</searchLink><br /><searchLink fieldCode="DE" term="%22After+School+Programs%22">After School Programs</searchLink><br /><searchLink fieldCode="DE" term="%22Program+Effectiveness%22">Program Effectiveness</searchLink><br /><searchLink fieldCode="DE" term="%22College+Freshmen%22">College Freshmen</searchLink>
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  Data: 10.1111/ssm.12552
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  Data: 0036-6803<br />1949-8594
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  Label: Abstract
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  Data: Over the past two decades, educators and policymakers have expressed growing concerns over the low levels of math and science achievement among American students and the gradual decline in the numbers of young people moving into science, technology, engineering, and math (STEM) careers. While interest in expanding the numbers of young people moving into science and technology fields has grown, a relatively small proportion of STEM education research has focused on the role that after-school programs can play to reinforce STEM learning and help engage young people in educational pathways leading to STEM careers. This study examines the impacts of "FIRST," an after-school robotics program, upon students' interests in STEM, as well as the likelihood for participants to pursue STEM in their academic and professional careers. Data were collected in a 7-year follow-up study of intervention group participants and a matched comparison group. We find that "FIRST" college students reported significantly higher rates of STEM interests, attitudes, and college level behaviors than comparison students. These findings have implications for the role of after-school programming in STEM education involving hands-on learning experiences in science- and technology-related fields, when considering young people's decision-making regarding their STEM college and career choices.
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  Data: 2022
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      – SubjectFull: Student Attitudes
        Type: general
      – SubjectFull: Robotics
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      – SubjectFull: STEM Education
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      – SubjectFull: After School Programs
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      – TitleFull: Transforming STEM Outcomes: Results from a Seven-Year Follow-Up Study of an After-School Robotics Program's Impacts on Freshman Students
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              Value: 0036-6803
            – Type: issn-electronic
              Value: 1949-8594
          Numbering:
            – Type: volume
              Value: 122
            – Type: issue
              Value: 7
          Titles:
            – TitleFull: School Science and Mathematics
              Type: main
ResultId 1