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<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Educ.</journal-id>
<journal-title>Frontiers in Education</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Educ.</abbrev-journal-title>
<issn pub-type="epub">2504-284X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
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<article-meta>
<article-id pub-id-type="doi">10.3389/feduc.2024.1493356</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Education</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Strengthening the STEM pipeline: impact of project-based synthetic biology program on high school students&#x2019; science identity and competency</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<name><surname>Mims</surname> <given-names>Pamela J.</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
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<contrib contrib-type="author">
<name><surname>Lee</surname> <given-names>Lindsay E.</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
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<contrib contrib-type="author">
<name><surname>Kuldell</surname> <given-names>Natalie</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
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<contrib contrib-type="author">
<name><surname>Franklin</surname> <given-names>Chloe</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
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<aff id="aff1"><sup>1</sup><institution>Department of Educational Foundations and Special Education, East Tennessee State University</institution>, <addr-line>Johnson City, TN</addr-line>, <country>United States</country></aff>
<aff id="aff2"><sup>2</sup><institution>BioBuilder Educational Foundation</institution>, <addr-line>Boston, MA</addr-line>, <country>United States</country></aff>
<author-notes>
<fn fn-type="edited-by" id="fn0001">
<p>Edited by: Brian Paul Ingalls, University of Waterloo, Canada</p>
</fn>
<fn fn-type="edited-by" id="fn0002">
<p>Reviewed by: Sasithep Pitiporntapin, Kasetsart University, Thailand</p>
<p>Pumtiwitt McCarthy, Morgan State University, United States</p>
<p>Zerrin Mercan, Bartin University, T&#x00FC;rkiye</p>
</fn>
<corresp id="c001">&#x002A;Correspondence: Pamela J. Mims, <email>mimspj@etsu.edu</email></corresp>
</author-notes>
<pub-date pub-type="epub">
<day>14</day>
<month>02</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="collection">
<year>2024</year>
</pub-date>
<volume>9</volume>
<elocation-id>1493356</elocation-id>
<history>
<date date-type="received">
<day>11</day>
<month>09</month>
<year>2024</year>
</date>
<date date-type="accepted">
<day>26</day>
<month>12</month>
<year>2024</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2025 Mims, Lee, Kuldell and Franklin.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Mims, Lee, Kuldell and Franklin</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>This study investigates the impact of a project-based science education intervention, BioBuilderClub, on high school students&#x2019; science identity, self-beliefs, and content knowledge in synthetic biology. Addressing the critical &#x201C;leaky pipeline&#x201D; issue in biotechnology education, this intervention focused on fostering scientific engagement and competency through hands-on, interdisciplinary projects. Using descriptive and correlational statistics (i.e., paired <italic>t</italic>-tests, residual change regression), we found that the project-based intervention resulted in significant improvements in students&#x2019; self-perceived scientific engagement, competency, and content knowledge regardless of gender, locale, and first generation status. Across expert raters, we also found an improvement in the understanding of synthetic biology and students reported an increased interest in biotechnology and related fields. These findings underscore the potential of project-based learning to enhance STEM retention by building strong science identities, particularly among underrepresented groups. Future research should explore the long-term impacts of such interventions and their integration into standard curricula to further bolster the biotechnology pipeline.</p>
</abstract>
<kwd-group>
<kwd>project-based teaching</kwd>
<kwd>synthetic biology</kwd>
<kwd>STEM education</kwd>
<kwd>STEM career awareness</kwd>
<kwd>research</kwd>
</kwd-group>
<counts>
<fig-count count="14"/>
<table-count count="10"/>
<equation-count count="0"/>
<ref-count count="46"/>
<page-count count="21"/>
<word-count count="9470"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>STEM Education</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="sec1">
<title>Introduction</title>
<p>Synthetic biology&#x2019;s focus on creative bio-design processes and real-world applications makes it a promising field for educational interventions aimed at addressing the &#x201C;leaky pipeline&#x201D; issue, where students drop out of the pathway from high school to post-secondary education and careers in science, technology, engineering, and math (STEM) fields. The COVID-19 pandemic has renewed calls to improve student retention in the STEM pipeline by providing access to high-quality, equitable STEM education opportunities both inside and outside of school. The pandemic underscored the importance of scientific advancement and a robust STEM workforce while exposing the education system&#x2019;s struggle to recover lost ground (<xref ref-type="bibr" rid="ref38">White House, 2022</xref>). Recent educational initiatives, including those by the U.S. Department of Education, seek to address various factors&#x2014;both cognitive and non-cognitive&#x2014;that influence students&#x2019; decisions to remain in STEM pathways at critical stages of their education (<xref ref-type="bibr" rid="ref9006">Marten, 2022</xref>; <xref ref-type="bibr" rid="ref34">U.S. Department of Education, 2023</xref>).</p>
<p>Many students who initially express an interest in pursuing STEM careers lose that intention during high school. For example, a longitudinal study of over 24,000 high school students revealed a 48% decrease in those intending to pursue STEM careers between 9th and 11th grade (<xref ref-type="bibr" rid="ref26">Mangu et al., 2015</xref>). Since students&#x2019; post-secondary STEM choices are closely tied to their high school science experiences and self-perceptions, educational interventions that provide meaningful science experiences and foster positive self-perceptions may enhance retention and equity within the STEM pipeline (<xref ref-type="bibr" rid="ref37">Wang, 2013</xref>; <xref ref-type="bibr" rid="ref30">National Science Board and National Science Foundation, 2021</xref>).</p>
<p>Career trajectories in STEM fields and the factors influencing related decisions are complex and dynamic. However, students with positive self-perceptions related to science&#x2014;those who identify as a &#x201C;science person&#x201D;&#x2014;are more likely to persist in STEM pathways (<xref ref-type="bibr" rid="ref28">Metcalf, 2010</xref>; <xref ref-type="bibr" rid="ref36">Vincent-Ruz and Schunn, 2018</xref>; <xref ref-type="bibr" rid="ref10">Chen et al., 2021</xref>). Science identity, particularly among underrepresented student populations in STEM, is one of the strongest predictors of persistence in studying STEM subjects throughout high school and college, as well as commitment to a STEM career (<xref ref-type="bibr" rid="ref2">Aschbacher et al., 2010</xref>; <xref ref-type="bibr" rid="ref3">Barton et al., 2013</xref>; <xref ref-type="bibr" rid="ref9">Chemers et al., 2011</xref>; <xref ref-type="bibr" rid="ref25">Le et al., 2014</xref>). Understanding how educational interventions can promote science identity is crucial for educators, policymakers, and STEM professionals to positively impact students&#x2019; self-perceptions and, ultimately, their persistence in STEM pathways.</p>
<p>In human development, identity refers to an individual&#x2019;s &#x201C;sense of self,&#x201D; which is shaped by their participation in specific activities, societal roles, group affiliations, interests, and personal characteristics (<xref ref-type="bibr" rid="ref6">Burke and Stets, 2009</xref>; <xref ref-type="bibr" rid="ref33">Renninger, 2009</xref>). Science identity, being both social and contextual, involves a student&#x2019;s self-perception of &#x201C;who they are, what they believe they are capable of, and what they want to do and become with regard to science&#x201D; (<xref ref-type="bibr" rid="ref5">Brickhouse, 2001</xref>; <xref ref-type="bibr" rid="ref21">Kim et al., 2018</xref>). According to the model described by <xref ref-type="bibr" rid="ref7">Carlone and Johnson (2007)</xref>, science identity comprises three dimensions: competence, performance, and recognition. Competence refers to possessing and understanding scientific knowledge and methods; performance involves demonstrating this competence to others; and recognition involves being acknowledged as a &#x201C;science person&#x201D; by oneself and by peers and significant others. Educational interventions that foster a sense of community and affiliation, promote positive attitudes, and align school science activities with authentic scientific practices have been shown to enhance science identity among adolescents (<xref ref-type="bibr" rid="ref36">Vincent-Ruz and Schunn, 2018</xref>). A strong science identity can empower students to view themselves as active and valued contributors to science, rather than passive learners.</p>
<p>One strategy that has shown some promise for increasing students&#x2019; science identity is Project-based learning (PBL). PBL is an educational strategy that holds significant potential for enhancing science identity and increasing STEM retention, particularly among underrepresented groups. PBL emphasizes collaborative, student-centered learning through projects that are meaningful, relevant, and connected to real-world challenges. Research has shown that PBL fosters deeper engagement, improves problem-solving skills, and cultivates a sense of ownership over learning (<xref ref-type="bibr" rid="ref23">Krajcik and Shin, 2014</xref>; <xref ref-type="bibr" rid="ref27">Mergendoller and Thomas, 2013</xref>). Among underrepresented groups, PBL can provide a culturally responsive approach to STEM education by incorporating students&#x2019; lived experiences and interests into the learning process, thereby enhancing their sense of belonging and self-efficacy in science (<xref ref-type="bibr" rid="ref3">Barton et al., 2013</xref>; <xref ref-type="bibr" rid="ref24">Ladson-Billings, 1995</xref>). Additionally, PBL supports the development of science identity by allowing students to see themselves as active participants in the scientific process, gaining recognition for their contributions and developing confidence in their scientific abilities (<xref ref-type="bibr" rid="ref11">Chin and Osborne, 2008</xref>; <xref ref-type="bibr" rid="ref29">Moote et al., 2020</xref>).</p>
<p>Building on these general benefits of PBL, synthetic biology and biotechnology education provide fertile ground for applying PBL principles, offering authentic, interdisciplinary challenges that can further enhance science identity and engagement. Synthetic biology offers unique opportunities for educational interventions aimed at fostering science identity, while also benefiting from the increased diversity and strength of a more robust STEM pipeline. Educational interventions in synthetic biology often involve interdisciplinary projects that challenge students to tackle real-world problems from diverse contexts and to evaluate or create biological solutions using engineering design thinking (<xref ref-type="bibr" rid="ref18">iGEM Foundation, 2024</xref>; <xref ref-type="bibr" rid="ref31">NISE Network, 2024</xref>). These interventions, which integrate life sciences with the engineering design-build-test-learn cycle, highlight creativity, innovation, real-world relevance, and authenticity&#x2014;factors that are known to enhance science identity and increase student persistence in STEM fields (<xref ref-type="bibr" rid="ref35">Shanahan and Nieswandt, 2009</xref>; <xref ref-type="bibr" rid="ref36">Vincent-Ruz and Schunn, 2018</xref>). Engaging high school students in authentic, original research has been linked to increased research identity, motivation, and a higher likelihood of pursuing and sustaining a career in STEM, compared to students who do not engage in original research until college (<xref ref-type="bibr" rid="ref15">Deemer et al., 2022</xref>). Synthetic biology research interventions at the secondary education level may be especially crucial in addressing the &#x201C;leaky pipeline,&#x201D; as they infuse science education with elements that promote science identity at a critical juncture for STEM student retention (<xref ref-type="bibr" rid="ref17">Graham et al., 2013</xref>). <xref ref-type="bibr" rid="ref9001">Walker (2021)</xref> conducted a survey of 66 middle school students, followed by interviews, to explore what this age group knows and thinks about synthetic biology and modern biotechnology applications. The study found that while students had minimal knowledge in these areas, their attitudes were similar to those of high school students, suggesting that these attitudes can be shaped during their remaining years of schooling. Walker also highlighted the need for further research to support student learning throughout their educational journey, emphasizing the importance of developing a strong pipeline to meet the growing demand in these fields. Additionally, Walker&#x2019;s analysis of prior research indicates that factors such as age, science learning experiences, and the geopolitical landscape significantly influence students&#x2019; knowledge of and interest in biotechnology.</p>
<p>In light of <xref ref-type="bibr" rid="ref9001">Walker (2021)</xref> findings, there is a need for additional research on effective instructional formats for teaching synthetic biology content. Project-based science interventions introduced at earlier educational stages may be beneficial, but research is required to assess their overall effectiveness. One such project-based science intervention is the BioBuilderClub, an extracurricular program offered by the BioBuilder Educational Foundation, which emphasizes authenticity in synthetic biology education. The BioBuilderClub engages high school students worldwide in experiential learning, allowing them to tackle real-world challenges with local or global significance. Students work virtually with a practicing bioengineer mentor as they design biological solutions using the design-build-test-learn engineering cycle. While some teams advance to the build and test phases, the BioBuilderClub season culminates in a celebration of student achievements. Here, all teams have the opportunity to present their bio-design processes and research findings through various formats, including oral reports, poster presentations, written abstracts, and publication in peer-reviewed journals.</p>
<sec id="sec2">
<title>Purpose</title>
<p>To date, there is a limited number of studies investigating the impact of project-based science education interventions like BioBuilderClub on student outcomes. Consequently, this study aimed to assess the effectiveness of such an intervention on high school students&#x2019; science self-beliefs and content knowledge over time (i.e., 2023&#x2013;2024). Such research could guide teachers&#x2019; use of evidence based approaches for teaching STEM education in high schools. The study was guided by the following research questions:</p><list list-type="order">
<list-item>
<p>How do high school students perceive their scientific engagement, competency, and content knowledge after participating in a project-based after-school science program?</p>
</list-item>
<list-item>
<p>To what extent does students&#x2019; content knowledge of synthetic biology change after their participation in a project-based after-school science program?</p>
</list-item>
</list>
</sec>
</sec>
<sec sec-type="materials|methods" id="sec3">
<title>Materials and methods</title>
<p>Prior to the study, institutional review board approval was obtained. The following study used multiple methods to assess the effectiveness of the project-based science education intervention. Specifically, we used a quasi-experimental one-group pre-posttest design to assess students&#x2019; engagement, competency, and content knowledge before and after the project-based science program. We explored the factor structure and internal consistency of our developed survey on scientific self-beliefs, and we assessed the interrater reliability of the developed rubric of understanding synthetic biology.</p>
<p>Since 2015, over 1,500 students from diverse schools in 22 states have participated in BioBuilderClub. In the 2023&#x2013;2024 school year, there were a total of 285 students who participated in the BioBuilderClub. From that participation in the 2023&#x2013;2024 school year, we used a convenience sampling method and included students enrolled to participate in the project-based science program. Both consent by parents and assent from high school students were obtained during the registration process prior to participation in the program. Students were recruited by BiobuilderClub (i.e., program coordinator, instructors) to complete the pre-survey and post-survey online. To maintain anonymity, surveys were de-identified by BioBuilderClub prior to being shared with external evaluators. Students were incentivized to complete the post-survey by entering students into a raffle for an Amazon Gift Card if they completed the post-survey. There were 246 students (86.3%) who completed the pre-survey and 137 students (48.1%) completed the post-survey. However, there were only 124 students (43.5%) who had completed both the pre and post-survey (see <xref ref-type="table" rid="tab1">Table 1</xref> for participation rates and demographic information).</p>
<table-wrap position="float" id="tab1">
<label>Table 1</label>
<caption>
<p>Demographic background frequency counts.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th/>
<th align="center" valign="top">Pre<break/>23&#x2013;24<break/>(<italic>n</italic>&#x202F;=&#x202F;246)</th>
<th align="center" valign="top">Post<break/>23&#x2013;24<break/>(<italic>n</italic>&#x202F;=&#x202F;137)</th>
<th align="center" valign="top">Pre/Post<break/>23&#x2013;24<break/>(<italic>n</italic>&#x202F;=&#x202F;124)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="bottom" colspan="4">Gender</td>
</tr>
<tr>
<td align="left" valign="bottom">Female</td>
<td align="center" valign="bottom">142 (58%)</td>
<td align="center" valign="bottom">79 (58.1%)</td>
<td align="center" valign="bottom">73 (58.9%)</td>
</tr>
<tr>
<td align="left" valign="bottom">Male</td>
<td align="center" valign="bottom">92 (37.6%)</td>
<td align="center" valign="bottom">52 (38.2%)</td>
<td align="center" valign="bottom">46 (37.1%)</td>
</tr>
<tr>
<td align="left" valign="bottom">Non-binary</td>
<td align="center" valign="bottom">1(0.4%)</td>
<td align="center" valign="bottom">&#x2013;</td>
<td align="center" valign="bottom">1(0.8%)</td>
</tr>
<tr>
<td align="left" valign="bottom">My answer is not listed here</td>
<td align="center" valign="bottom">3(1.2%)</td>
<td align="center" valign="bottom">1 (0.7%)</td>
<td align="center" valign="bottom">1(0.8%)</td>
</tr>
<tr>
<td align="left" valign="bottom">Prefer not to answer</td>
<td align="center" valign="bottom">7(2.9%)</td>
<td align="center" valign="bottom">4 (2.9%)</td>
<td align="center" valign="bottom">3(2.4%)</td>
</tr>
<tr>
<td align="left" valign="bottom" colspan="4">Race</td>
</tr>
<tr>
<td align="left" valign="bottom">Asian (South Asian, Asian American, Pacific Islander)</td>
<td align="center" valign="bottom">104 (42.4%)</td>
<td align="center" valign="bottom">59 (43.3%)</td>
<td align="center" valign="bottom">53 (42.7%)</td>
</tr>
<tr>
<td align="left" valign="bottom">Black or African American</td>
<td align="center" valign="bottom">10 (4.08%)</td>
<td align="center" valign="bottom">&#x2013;</td>
<td align="center" valign="bottom">5 (4%)</td>
</tr>
<tr>
<td align="left" valign="bottom">Hispanic or Latino</td>
<td align="center" valign="bottom">12 (4.8%)</td>
<td align="center" valign="bottom">5 (3.6%)</td>
<td align="center" valign="bottom">8 (6.5%)</td>
</tr>
<tr>
<td align="left" valign="bottom">White (origins in Europe, the Middle East, or North Africa)</td>
<td align="center" valign="bottom">75 (30.6%)</td>
<td align="center" valign="bottom">43 (31.6%)</td>
<td align="center" valign="bottom">39 (31.5%)</td>
</tr>
<tr>
<td align="left" valign="bottom">Two or more races</td>
<td align="center" valign="bottom">&#x2013;</td>
<td align="center" valign="bottom">&#x2013;</td>
<td align="center" valign="bottom">9 (7.3%)</td>
</tr>
<tr>
<td align="left" valign="bottom">Other</td>
<td align="center" valign="bottom">26 (10.6%)</td>
<td align="center" valign="bottom">21 (15.4%)</td>
<td align="center" valign="bottom">&#x2013;</td>
</tr>
<tr>
<td align="left" valign="bottom">Prefer not to say</td>
<td align="center" valign="bottom">18 (7.3%)</td>
<td align="center" valign="bottom">8 (5.8%)</td>
<td align="center" valign="bottom">10 (8.1%)</td>
</tr>
<tr>
<td align="left" valign="bottom" colspan="4">Locale (NCES)</td>
</tr>
<tr>
<td align="left" valign="bottom">City (Large)</td>
<td align="center" valign="bottom">44 (17.9%)</td>
<td align="center" valign="bottom">13 (9.5%)</td>
<td align="center" valign="bottom">13 (10.5%)</td>
</tr>
<tr>
<td align="left" valign="bottom">City (Midsize)</td>
<td align="center" valign="bottom">14 (6.7%)</td>
<td align="center" valign="bottom">8 (5.9%)</td>
<td align="center" valign="bottom">8 (6.5%)</td>
</tr>
<tr>
<td align="left" valign="bottom">City (Small)</td>
<td align="center" valign="bottom">18 (7.3%)</td>
<td align="center" valign="bottom">14 (10.3%)</td>
<td align="center" valign="bottom">12 (9.7%)</td>
</tr>
<tr>
<td align="left" valign="bottom">Suburb (Large)</td>
<td align="center" valign="bottom">164 (66.9%)</td>
<td align="center" valign="bottom">101 (74.2%)</td>
<td align="center" valign="bottom">91(73.4)</td>
</tr>
<tr>
<td align="left" valign="bottom">Rural (Distant)</td>
<td align="center" valign="bottom">1 (0.4%)</td>
<td align="center" valign="bottom">&#x2013;</td>
<td align="center" valign="bottom">&#x2013;</td>
</tr>
<tr>
<td align="left" valign="bottom">Rural (Fringe)</td>
<td align="center" valign="bottom">4 (1.6%)</td>
<td align="center" valign="bottom">&#x2013;</td>
<td align="center" valign="bottom">&#x2013;</td>
</tr>
<tr>
<td align="left" valign="bottom" colspan="4">Grade</td>
</tr>
<tr>
<td align="left" valign="bottom">9th</td>
<td align="center" valign="bottom">9 (3.7%)</td>
<td align="center" valign="bottom">6 (4.4%)</td>
<td align="center" valign="bottom">4 (3.2%)</td>
</tr>
<tr>
<td align="left" valign="bottom">10th</td>
<td align="center" valign="bottom">32 (13.1%)</td>
<td align="center" valign="bottom">19 (14%)</td>
<td align="center" valign="bottom">16 (12.9%)</td>
</tr>
<tr>
<td align="left" valign="bottom">11th</td>
<td align="center" valign="bottom">110 (44.9%)</td>
<td align="center" valign="bottom">64 (47.1%)</td>
<td align="center" valign="bottom">59 (47.6%)</td>
</tr>
<tr>
<td align="left" valign="bottom">12th</td>
<td align="center" valign="bottom">94 (38.4%)</td>
<td align="center" valign="bottom">47 (34.6%)</td>
<td align="center" valign="bottom">45 (36.3%)</td>
</tr>
<tr>
<td align="left" valign="bottom" colspan="4">First generation status</td>
</tr>
<tr>
<td align="left" valign="top">No</td>
<td align="center" valign="bottom">107 (43.7%)</td>
<td align="center" valign="bottom">61 (44.9%)</td>
<td align="center" valign="bottom">54 (43.5%)</td>
</tr>
<tr>
<td align="left" valign="top">Prefer not to say</td>
<td align="center" valign="bottom">30 (12.2%)</td>
<td align="center" valign="bottom">12 (8.8%)</td>
<td align="center" valign="bottom">12 (9.7%)</td>
</tr>
<tr>
<td align="left" valign="top">Yes</td>
<td align="center" valign="bottom">108 (44.1%)</td>
<td align="center" valign="bottom">63 (46.3%)</td>
<td align="center" valign="bottom">58 (46.8%)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>For student&#x2019;s race/ethnicity, the Pre-22-23 Data included 83 students (11 missing) and the Post 22&#x2013;23 Data included 21 students (3 missing).</p>
</table-wrap-foot>
</table-wrap>
<sec id="sec4">
<title>Measures</title>
<p>The pre- and post-survey included questions to assess the self-perceptions of student scientific engagement, competency, and content knowledge before and after participation in the project-based science program (see <xref ref-type="table" rid="tab2">Table 2</xref>). The development of the survey items was influenced by prior measures, specifically Competency Beliefs in Science (<xref ref-type="bibr" rid="ref12">Chung et al., 2016</xref>), the Measuring Activation &#x0026; Engagement (<xref ref-type="bibr" rid="ref9005">Moore et al., 2011</xref>), and the Classroom Undergraduate Research Experience (CURE) Survey (<xref ref-type="bibr" rid="ref9007">Lopatto, 2009</xref>). The quantitative questions used a Likert style format options ranging from: &#x201C;1&#x202F;=&#x202F;Strongly Disagree&#x201D; to &#x201C;5&#x202F;=&#x202F;Strongly Agree.&#x201D; The pre-and post-survey also included open-ended responses to indicate specific content knowledge of defining synthetic biology and student experiences in the project-based science program (<xref ref-type="table" rid="tab3">Table 3</xref>).</p>
<table-wrap position="float" id="tab2">
<label>Table 2</label>
<caption>
<p>Likert style survey items.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="bottom">Scientific competency items (Pre/Post)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="bottom">I can understand scientific information on websites</td>
</tr>
<tr>
<td align="left" valign="bottom">I think I am very good at: Giving evidence when I tell my opinion about science</td>
</tr>
<tr>
<td align="left" valign="bottom">I think I am very good at: Coming up with new ways to solve technical problems in science</td>
</tr>
<tr>
<td align="left" valign="bottom">I think I am very good at: Coming up with my own science investigations.</td>
</tr>
<tr>
<td align="left" valign="bottom">Critiquing the scientific work of other students</td>
</tr>
<tr>
<td align="left" valign="bottom">Scientific engagement items (Pre/Post)</td>
</tr>
<tr>
<td align="left" valign="bottom">I enjoy learning about science</td>
</tr>
<tr>
<td align="left" valign="bottom">I engage in science on weekends and during breaks from school.</td>
</tr>
<tr>
<td align="left" valign="bottom">I would like to know more about jobs that use science.</td>
</tr>
<tr>
<td align="left" valign="bottom">I will miss studying science when I leave school.</td>
</tr>
<tr>
<td align="left" valign="bottom">Scientific content knowledge items (Pre/Post)</td>
</tr>
<tr>
<td align="left" valign="bottom">Working on a lab or project where no one knows the outcome</td>
</tr>
<tr>
<td align="left" valign="bottom">Working on student-designed projects</td>
</tr>
<tr>
<td align="left" valign="bottom">Becoming responsible for a part of a project</td>
</tr>
<tr>
<td align="left" valign="bottom">Reading primary scientific literature</td>
</tr>
<tr>
<td align="left" valign="bottom">Writing a research proposal</td>
</tr>
<tr>
<td align="left" valign="bottom">Collecting data</td>
</tr>
<tr>
<td align="left" valign="bottom">Analyzing data</td>
</tr>
<tr>
<td align="left" valign="bottom">Presenting scientific ideas or results orally (spoken presentation)</td>
</tr>
<tr>
<td align="left" valign="bottom">Presenting scientific ideas or results in written papers or reports</td>
</tr>
<tr>
<td align="left" valign="bottom">Presenting scientific posters</td>
</tr>
<tr>
<td align="left" valign="bottom">Maintaining a laboratory notebook</td>
</tr>
<tr>
<td align="left" valign="bottom">Experience items (Post)</td>
</tr>
<tr>
<td align="left" valign="bottom">I would recommend a high school class that has BioBuilder content over one that does not</td>
</tr>
<tr>
<td align="left" valign="bottom">BioBuilder has supported my interest in pursuing advanced scientific coursework</td>
</tr>
<tr>
<td align="left" valign="bottom">BioBuilder has supported my interest in pursuing a career in the life sciences</td>
</tr>
<tr>
<td align="left" valign="bottom">In my college selection process, I will be looking for places with biotechnology, biomanufacturing, or synthetic biology opportunities.</td>
</tr>
<tr>
<td align="left" valign="bottom">BioBuilder has increased the importance of finding biotechnology, biomanufacturing, or synthetic biology opportunities in my college selection process.</td>
</tr>
<tr>
<td align="left" valign="bottom">In my future job search, I will be looking for places with biotechnology, biomanufacturing, or synthetic biology opportunities.</td>
</tr>
<tr>
<td align="left" valign="bottom">BioBuilder has increased the importance of finding biotechnology, biomanufacturing, or synthetic biology opportunities in my future job search.</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>The item of &#x201C;Critiquing the scientific work of others&#x201D; was initially thought of as a scientific content knowledge item but showed more relation to scientific competency (see <xref ref-type="table" rid="tab4">Table 4</xref>).</p>
</table-wrap-foot>
</table-wrap>
<table-wrap position="float" id="tab3">
<label>Table 3</label>
<caption>
<p>Pre-posttest open-ended questions.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Pre-post questions</th>
<th align="left" valign="top">Type of question</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="bottom">What is synthetic biology?</td>
<td align="left" valign="bottom">Content knowledge</td>
</tr>
<tr>
<td align="left" valign="bottom">Provide an example of synthetic biology. You may provide more than one example.</td>
<td align="left" valign="bottom">Content knowledge</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="sec5">
<title>Data analysis</title>
<p>All quantitative analyses were conducted using R (Version 4.3.1; <xref ref-type="bibr" rid="ref32">R Core Team, 2023</xref>). We used listwise deletion to remove missing pre and post-test surveys, thus we initially examined all complete paired pre-and-posttest surveys (<italic>n</italic>&#x202F;=&#x202F;124). Using the lavaan package (<xref ref-type="bibr" rid="ref9004">Rosseel, 2012</xref>), exploratory factor analysis was conducted using oblique rotation (Promax), which is appropriate for examining correlated factors (<xref ref-type="bibr" rid="ref9002">Tabachnick and Fidell, 2001</xref>). We assessed eigenvalues, scree plots, and factor loadings to evaluate a two and three-factor solution.</p>
<p>For the initial pre-and-posttest quantitative analyses, we assessed item-level data. Using paired samples t-tests, we initially conducted descriptive statistics to investigate mean score differences from each item of the pre-post survey responses with complete cases (<italic>n</italic>&#x202F;=&#x202F;124). Descriptive statistics were used to summarize frequencies among demographics, measures of central tendency, and variability of demographics on the items used to create the factors of scientific engagement, competency, and content knowledge before/after participation in the BioBuilder program. We also reported mean difference scores, percentage difference, and Cohen&#x2019;s <italic>d</italic> as a measure of effect size (<xref ref-type="bibr" rid="ref14">Cohen, 1988</xref>; see <xref ref-type="table" rid="tab1">Table 1</xref>).</p>
</sec>
<sec id="sec6">
<title>Residual change score differences</title>
<p>Using the composite factors (i.e., Scientific Competency, Engagement, and Content Knowledge), we investigated the relationship between pre and post scores with residual change score regressions. Residual change regressions assesses alterations in the outcome (i.e., post-test) from a prior occasion (i.e., pre-test), with other predictors of interest. <xref ref-type="bibr" rid="ref8">Castro-Schilo and Grimm (2018)</xref> state &#x201C;the autoregressive effect <italic>residualizes</italic> the outcome leaving only variability that is unexplained by [the pre-test], which can be construed as the variability due to change (see <xref ref-type="bibr" rid="ref8">Castro-Schilo and Grimm, 2018</xref>, p. 36). Prior studies have explored residualized change regressions to understand longitudinal outcomes of participation in interventions over time (<xref ref-type="bibr" rid="ref1">Allen et al., 1994</xref>; <xref ref-type="bibr" rid="ref20">Kang, 2022</xref>) and others have compared its&#x2019; usage to traditional ANCOVA and difference scores (<xref ref-type="bibr" rid="ref19">Jennings and Cribbie, 2016</xref>). To further investigate the relation of covariates (i.e., first-generation status, gender, NCES Locale designations) to post scores on three different outcome variables (i.e., Competency, Engagement, &#x0026; Content Knowledge Beliefs), we conducted three multiple regressions to assess residual change on only complete cases with demographic variables of interest (<italic>n</italic>&#x202F;=&#x202F;103). Prior to analyses, we used listwise deletion to use complete cases of demographics of interest (i.e., gender, locale, first generation status) and specifically did not include international students from large cities (<italic>n</italic>&#x202F;=&#x202F;7), students who did not report if they were first-generation (<italic>n</italic>&#x202F;=&#x202F;12), or students who chose a gender other than male or female designations (i.e., non-binary [<italic>n</italic>&#x202F;=&#x202F;1], my answer is not listed [<italic>n</italic>&#x202F;=&#x202F;1], prefer not to answer [<italic>n</italic>&#x202F;=&#x202F;3]), as there were only a few cases. There was overlap in students omitting responses within these designations. We used a Benjamini Hochberg correction to account for multiple comparisons and provide conservative estimates to avoid possible Type I error (<xref ref-type="bibr" rid="ref4">Benjamini and Hochberg, 1995</xref>).</p>
</sec>
<sec id="sec7">
<title>Synthetic biology content knowledge: definition and examples</title>
<p>The accuracy of the student responses to content knowledge questions (e.g., what is synthetic biology, provide examples of synthetic biology; see <xref ref-type="table" rid="tab2">Tables 2</xref>, <xref ref-type="table" rid="tab3">3</xref>) was assessed with a specific rubric. To assess the content knowledge of the question &#x201C;what is synthetic biology?,&#x201D; we developed a rubric to reflect poor, emerging, or sophisticated responses. Two content expert raters, external to the research team, were asked to rate student submissions. We went over the rubric individually with each rater before they rated submissions. The first content expert rater rated all 124 submissions. The second content expert rater rated a random sampling of 20% of the 124 submissions. To determine agreement, we calculated interrater nominal agreement and Cohen&#x2019;s Kappa (<xref ref-type="bibr" rid="ref13">Cohen, 1960</xref>). Using the randomly sampled 20% of pre and post scores, we report means and standard deviations for each rater to show changes from pre to post scores of content knowledge.</p>
</sec>
<sec id="sec8">
<title>Recommendations, college selection, and future job searches</title>
<p>Using a 1-to-5 Likert scale from strongly disagree to strongly agree, we asked students a series of conclusive survey items regarding their experiences and recommendations of the BioBuilder Program, as well as their interest in pursuing biotechnology, biomanufacturing, or synthetic biology in college selection or job searches. We reported frequencies of student responses (see <xref ref-type="fig" rid="fig1">Figures 1</xref>&#x2013;<xref ref-type="fig" rid="fig7">7</xref>).</p>
<fig position="float" id="fig1">
<label>Figure 1</label>
<caption>
<p>Experience: recommendation of BioBuilder.</p>
</caption>
<graphic xlink:href="feduc-09-1493356-g001.tif"/>
</fig>
<fig position="float" id="fig2">
<label>Figure 2</label>
<caption>
<p>Experience: supported my interest in pursuing advanced scientific coursework.</p>
</caption>
<graphic xlink:href="feduc-09-1493356-g002.tif"/>
</fig>
<fig position="float" id="fig3">
<label>Figure 3</label>
<caption>
<p>Experience: supported my interest in pursuing a career in the life sciences.</p>
</caption>
<graphic xlink:href="feduc-09-1493356-g003.tif"/>
</fig>
<fig position="float" id="fig4">
<label>Figure 4</label>
<caption>
<p>Experience: college selection process&#x2014;looking for places with biotechnology, biomanufacturing, or synthetic biology opportunities.</p>
</caption>
<graphic xlink:href="feduc-09-1493356-g004.tif"/>
</fig>
<fig position="float" id="fig5">
<label>Figure 5</label>
<caption>
<p>Experience: college selection process&#x2014;importance of finding biotechnology, biomanufacturing, or synthetic biology opportunities.</p>
</caption>
<graphic xlink:href="feduc-09-1493356-g005.tif"/>
</fig>
<fig position="float" id="fig6">
<label>Figure 6</label>
<caption>
<p>Experience: future job search&#x2014;looking for places with biotechnology, biomanufacturing, or synthetic biology opportunities.</p>
</caption>
<graphic xlink:href="feduc-09-1493356-g006.tif"/>
</fig>
<fig position="float" id="fig7">
<label>Figure 7</label>
<caption>
<p>Experience: future job search - importance of finding biotechnology, biomanufacturing, or synthetic biology opportunities.</p>
</caption>
<graphic xlink:href="feduc-09-1493356-g007.tif"/>
</fig>
</sec>
</sec>
<sec sec-type="results" id="sec9">
<title>Results</title>
<p>For the 2023&#x2013;2024 school year, there were 286 students enrolled in the project-based science program. Of that total 286, 246 individuals responded to the pre-survey and 137 individuals responded to the post-survey. Of the 137 students, there was a higher response rate for the same individuals who completed both the pre-and post-survey (<italic>n</italic>&#x202F;=&#x202F;124). For the frequency of demographics across pre and post survey results in the 2023&#x2013;2024 School Year (see <xref ref-type="table" rid="tab1">Table 1</xref>).</p>
<sec id="sec10">
<title>Exploratory factor analysis and reliability</title>
<p>We examined the factor structure of the items in the survey related to Engagement, Competency, and Content Knowledge (<xref ref-type="table" rid="tab4">Table 4</xref>). The three-factor model showed some indication of good fit, X<sup>2</sup> (133, 124)&#x202F;=&#x202F;247.9, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.001, and Root Mean Square Error of Approximation (RMSEA&#x202F;=&#x202F;0.08), but the root mean square of the residuals (RMSR&#x202F;=&#x202F;0.06) and the Tucker Lewis Index (TLI&#x202F;=&#x202F;0.83) were not within goodness of fit thresholds (see <xref ref-type="bibr" rid="ref9008">Kline, 2015</xref>). However, both the factor loadings (see <xref ref-type="fig" rid="fig8">Figure 8</xref>) and the Parallel Analyses Scree Plot showed an indication of a three-factor model (see <xref ref-type="fig" rid="fig9">Figure 9</xref>). Thus, we continued with a three-factor model. One item asking about Critiquing the Scientific Work of Others showed indication of loading within the factor related to Scientific Competency rather than Scientific Content Knowledge (as originally intended). We named these factors: Scientific Engagement (4 items), Scientific Competency (5 items), and Scientific Content Knowledge (11 items). Standard internal consistency estimates for Scientific Engagement (<italic>&#x03B1;</italic>&#x202F;=&#x202F;0.79), Scientific Competency (<italic>&#x03B1;</italic>&#x202F;=&#x202F;0.80), and Content Knowledge (<italic>&#x03B1;</italic>&#x202F;=&#x202F;0.91) were found to be in the range of acceptable reliability.</p>
<table-wrap position="float" id="tab4">
<label>Table 4</label>
<caption>
<p>Factor loadings, eigenvalues, and variance (<italic>n</italic>&#x202F;=&#x202F;124).</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" rowspan="2">Items</th>
<th align="center" valign="top" colspan="3">Standardized Factor Loadings (Pattern Matrix)</th>
<th align="center" valign="top">Communality</th>
<th align="center" valign="top">Uniqueness</th>
<th align="center" valign="top">Complexity</th>
</tr>
<tr>
<th align="center" valign="top">Scientific content knowledge</th>
<th align="center" valign="top">Scientific competency</th>
<th align="center" valign="top">Scientific engagement</th>
<th/>
<th/>
<th/>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="bottom">I can understand scientific information on websites</td>
<td/>
<td align="center" valign="bottom"><bold>0.72</bold></td>
<td/>
<td align="center" valign="bottom">0.49</td>
<td align="center" valign="bottom">0.51</td>
<td align="center" valign="bottom">1</td>
</tr>
<tr>
<td align="left" valign="bottom">Giving evidence when I tell my opinion about science</td>
<td/>
<td align="center" valign="bottom"><bold>0.63</bold></td>
<td align="center" valign="bottom">0.13</td>
<td align="center" valign="bottom">0.47</td>
<td align="center" valign="bottom">0.53</td>
<td align="center" valign="bottom">1.1</td>
</tr>
<tr>
<td align="left" valign="bottom">Coming up with new ways to solve technical problems in science</td>
<td/>
<td align="center" valign="bottom"><bold>0.70</bold></td>
<td/>
<td align="center" valign="bottom">0.50</td>
<td align="center" valign="bottom">0.50</td>
<td align="center" valign="bottom">1</td>
</tr>
<tr>
<td align="left" valign="bottom">Coming up with my own science investigations.</td>
<td/>
<td align="center" valign="bottom"><bold>0.56</bold></td>
<td align="center" valign="bottom">0.14</td>
<td align="center" valign="bottom">0.37</td>
<td align="center" valign="bottom">0.63</td>
<td align="center" valign="bottom">1.1</td>
</tr>
<tr>
<td align="left" valign="bottom">I enjoy learning about science</td>
<td/>
<td/>
<td align="center" valign="bottom"><bold>0.82</bold></td>
<td align="center" valign="bottom">0.67</td>
<td align="center" valign="bottom">0.33</td>
<td align="center" valign="bottom">1</td>
</tr>
<tr>
<td align="left" valign="bottom">I engage in science on weekends and during breaks from school.</td>
<td/>
<td align="center" valign="bottom">0.26</td>
<td align="center" valign="bottom"><bold>0.57</bold></td>
<td align="center" valign="bottom">0.49</td>
<td align="center" valign="bottom">0.51</td>
<td align="center" valign="bottom">1.4</td>
</tr>
<tr>
<td align="left" valign="bottom">I would like to know more about jobs that use science.</td>
<td/>
<td/>
<td align="center" valign="bottom"><bold>0.77</bold></td>
<td align="center" valign="bottom">0.59</td>
<td align="center" valign="bottom">0.41</td>
<td align="center" valign="bottom">1</td>
</tr>
<tr>
<td align="left" valign="bottom">I will miss studying science when I leave school.</td>
<td/>
<td align="center" valign="bottom">0.17</td>
<td align="center" valign="bottom"><bold>0.51</bold></td>
<td align="center" valign="bottom">0.35</td>
<td align="center" valign="bottom">0.65</td>
<td align="center" valign="bottom">1.2</td>
</tr>
<tr>
<td align="left" valign="bottom">Working on a lab or project where no one knows the outcome</td>
<td align="center" valign="bottom"><bold>0.55</bold></td>
<td align="center" valign="bottom">0.10</td>
<td/>
<td align="center" valign="bottom">0.39</td>
<td align="center" valign="bottom">0.61</td>
<td align="center" valign="bottom">1.1</td>
</tr>
<tr>
<td align="left" valign="bottom">Working on student-designed projects</td>
<td align="center" valign="bottom"><bold>0.81</bold></td>
<td align="center" valign="bottom">&#x2212;0.27</td>
<td align="center" valign="bottom">0.16</td>
<td align="center" valign="bottom">0.48</td>
<td align="center" valign="bottom">0.52</td>
<td align="center" valign="bottom">1.3</td>
</tr>
<tr>
<td align="left" valign="bottom">Becoming responsible for a part of a project</td>
<td align="center" valign="bottom"><bold>0.79</bold></td>
<td align="center" valign="bottom">&#x2212;0.21</td>
<td/>
<td align="center" valign="bottom">0.47</td>
<td align="center" valign="bottom">0.53</td>
<td align="center" valign="bottom">1.2</td>
</tr>
<tr>
<td align="left" valign="bottom">Reading primary scientific literature</td>
<td align="center" valign="bottom"><bold>0.59</bold></td>
<td/>
<td align="center" valign="bottom">0.13</td>
<td align="center" valign="bottom">0.37</td>
<td align="center" valign="bottom">0.63</td>
<td align="center" valign="bottom">1.1</td>
</tr>
<tr>
<td align="left" valign="bottom">Writing a research proposal</td>
<td align="center" valign="bottom"><bold>0.72</bold></td>
<td/>
<td align="center" valign="bottom">&#x2212;0.19</td>
<td align="center" valign="bottom">0.54</td>
<td align="center" valign="bottom">0.46</td>
<td align="center" valign="bottom">1.1</td>
</tr>
<tr>
<td align="left" valign="bottom">Collecting data</td>
<td align="center" valign="bottom"><bold>0.65</bold></td>
<td/>
<td/>
<td align="center" valign="bottom">0.41</td>
<td align="center" valign="bottom">0.59</td>
<td align="center" valign="bottom">1</td>
</tr>
<tr>
<td align="left" valign="bottom">Analyzing data</td>
<td align="center" valign="bottom"><bold>0.66</bold></td>
<td/>
<td/>
<td align="center" valign="bottom">0.48</td>
<td align="center" valign="bottom">0.52</td>
<td align="center" valign="bottom">1</td>
</tr>
<tr>
<td align="left" valign="bottom">Presenting scientific ideas or results orally (spoken presentation)</td>
<td align="center" valign="bottom"><bold>0.66</bold></td>
<td/>
<td/>
<td align="center" valign="bottom">0.46</td>
<td align="center" valign="bottom">0.54</td>
<td align="center" valign="bottom">1</td>
</tr>
<tr>
<td align="left" valign="bottom">Presenting scientific ideas or results in written papers or reports</td>
<td align="center" valign="bottom"><bold>0.56</bold></td>
<td align="center" valign="bottom">0.32</td>
<td align="center" valign="bottom">&#x2212;0.15</td>
<td align="center" valign="bottom">0.60</td>
<td align="center" valign="bottom">0.40</td>
<td align="center" valign="bottom">1.8</td>
</tr>
<tr>
<td align="left" valign="bottom">Presenting scientific posters</td>
<td align="center" valign="bottom"><bold>0.59</bold></td>
<td align="center" valign="bottom">0.27</td>
<td/>
<td align="center" valign="bottom">0.60</td>
<td align="center" valign="bottom">0.40</td>
<td align="center" valign="bottom">1.5</td>
</tr>
<tr>
<td align="left" valign="bottom">Critiquing the scientific work of other students</td>
<td align="center" valign="bottom">0.36</td>
<td align="center" valign="bottom"><bold>0.52</bold></td>
<td align="center" valign="bottom">&#x2212;0.32</td>
<td align="center" valign="bottom">0.60</td>
<td align="center" valign="bottom">0.40</td>
<td align="center" valign="bottom">2.5</td>
</tr>
<tr>
<td align="left" valign="bottom">Maintaining a laboratory notebook</td>
<td align="center" valign="bottom"><bold>0.34</bold></td>
<td align="center" valign="bottom">0.17</td>
<td/>
<td align="center" valign="bottom">0.22</td>
<td align="center" valign="bottom">0.78</td>
<td align="center" valign="bottom">1.5</td>
</tr>
<tr>
<td align="left" valign="bottom" colspan="7">Properties</td>
</tr>
<tr>
<td align="left" valign="bottom">SS loadings</td>
<td align="center" valign="bottom">4.76</td>
<td align="center" valign="bottom">2.60</td>
<td align="center" valign="bottom">2.18</td>
<td/>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="bottom">Proportion variance</td>
<td align="center" valign="bottom">0.24</td>
<td align="center" valign="bottom">0.13</td>
<td align="center" valign="bottom">0.11</td>
<td/>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="bottom">Cumulative variance</td>
<td align="center" valign="bottom">0.24</td>
<td align="center" valign="bottom">0.37</td>
<td align="center" valign="bottom">0.48</td>
<td/>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="bottom">Proportion explained</td>
<td align="center" valign="bottom">0.50</td>
<td align="center" valign="bottom">0.27</td>
<td align="center" valign="bottom">0.23</td>
<td/>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="bottom">Cumulative proportion</td>
<td align="center" valign="bottom">0.50</td>
<td align="center" valign="bottom">0.77</td>
<td align="center" valign="bottom">1.00</td>
<td/>
<td/>
<td/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>Bolded values indicate which items we determined were best explained under each factor (see columns for Scientific Content Knowledge, Scientific Competency, &#x0026; Scientific Engagement). We first considered moderate correlations higher than a general rule of thumb of 0.32 (<xref ref-type="bibr" rid="ref9002">Tabachnick and Fidell, 2001</xref>). If an item loaded on to two factors, we determined that the item loaded on to the factor with the higher standardized factor loading (i.e., greater than 0.32). See <xref ref-type="fig" rid="fig8">Figure 8</xref> for final model.</p>
</table-wrap-foot>
</table-wrap>
<fig position="float" id="fig8">
<label>Figure 8</label>
<caption>
<p>Three factor model: scientific engagement, competency, and content knowledge. Standardized factor loadings were rounded to the nearest whole number.</p>
</caption>
<graphic xlink:href="feduc-09-1493356-g008.tif"/>
</fig>
<fig position="float" id="fig9">
<label>Figure 9</label>
<caption>
<p>Parallel analysis scree plots. The blue lines and triangles indicate the actual data. The red dotted and dashed lines overlap. The red dotted line indicates the simulated data, and the red dashed line indicates resampled data. The &#x201C;elbow&#x201D; of the simulated and resampled data draws a line through the 3 factors to include. This was analyzed using only the post-scores.</p>
</caption>
<graphic xlink:href="feduc-09-1493356-g009.tif"/>
</fig>
</sec>
<sec id="sec11">
<title>Mean difference scores</title>
<p>Initially, we analyzed the mean score differences of the pre-post survey items and found some of the specific scientific competency, engagement, and content knowledge showed higher differences across pre-post.</p>
<sec id="sec12">
<title>Scientific competency</title>
<p>For students&#x2019; competency beliefs, we found students scored higher on the following items: understanding scientific websites, giving evidence when telling their opinion, coming up with new ways to solve a problem, and critiquing the scientific work of other students. For instance, we found students, after the project-based science program, scored higher on their self-beliefs of being able to understand scientific information on websites (<italic>M</italic>&#x202F;=&#x202F;4.04, <italic>SD</italic>&#x202F;=&#x202F;0.68) than before they participated in the program (<italic>M</italic>&#x202F;=&#x202F;3.82, <italic>SD</italic>&#x202F;=&#x202F;0.86), <italic>t</italic>(123)&#x202F;=&#x202F;3.31, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.01. We found a mean score difference of 0.23 and had a small effect (<italic>d</italic>&#x202F;=&#x202F;0.30). Also, after participation in the project-based science program, students scored higher on their self-belief of giving evidence when telling their opinion about science (<italic>M</italic>&#x202F;=&#x202F;3.9, <italic>SD</italic>&#x202F;=&#x202F;0.79), than before they participated in the program (<italic>M</italic>&#x202F;=&#x202F;3.74, <italic>SD</italic>&#x202F;=&#x202F;0.93), <italic>t</italic>(123)&#x202F;=&#x202F;2.17, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.05; This showed a mean score difference of 0.16 and showed a minimal effect (<italic>d</italic>&#x202F;=&#x202F;0.18). After participation students also rated their self-belief of coming up with new ways to solve technical problems (<italic>M</italic>&#x202F;=&#x202F;3.66, <italic>SD</italic>&#x202F;=&#x202F;0.81) than before participation in the project-based science program (<italic>M</italic>&#x202F;=&#x202F;3.46, <italic>SD</italic>&#x202F;=&#x202F;0.90), <italic>t</italic>(123)&#x202F;=&#x202F;2.49, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.05. This shows a mean difference of 0.20 and a small effect (<italic>d</italic>&#x202F;=&#x202F;0.24). They also rated their self-belief of coming up with their own science investigations higher after participation in the project-based science program (<italic>M</italic>&#x202F;=&#x202F;3.65, <italic>SD</italic>&#x202F;=&#x202F;0.80), <italic>t</italic>(123)&#x202F;=&#x202F;2.82, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.01. This showed a mean difference of 0.27 and had a small effect (<italic>d</italic>&#x202F;=&#x202F;0.29).</p>
</sec>
<sec id="sec13">
<title>Scientific engagement</title>
<p>For scientific engagement, students scored higher on engaging in science on the weekends and during breaks from school (<italic>M</italic>&#x202F;=&#x202F;3.8, <italic>SD</italic>&#x202F;=&#x202F;1.16), <italic>t</italic>(123)&#x202F;=&#x202F;3.05, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.01. There was a mean score difference of 0.30 and this had a small effect (<italic>d</italic>&#x202F;=&#x202F;0.26). Students did not have significant differences on enjoyment of learning science, wanting to know more about jobs that use science, and missing science when they leave school. However, all those students&#x2019; self-beliefs were above average before starting the program.</p>
</sec>
<sec id="sec14">
<title>Scientific content knowledge</title>
<p>For student&#x2019;s beliefs of their scientific content knowledge, we found after the project-based science program students scored higher on working on a lab or project with an unknown outcome (<italic>M</italic>&#x202F;=&#x202F;3.42, <italic>SD</italic>&#x202F;=&#x202F;1.12) than before the program (<italic>M</italic>&#x202F;=&#x202F;3.03, <italic>SD</italic>&#x202F;=&#x202F;1.24), <italic>t</italic>(123)&#x202F;=&#x202F;3.49, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.001. There was a mean difference of 0.39 and had a small effect (<italic>d</italic>&#x202F;=&#x202F;0.33). We also found that students scored higher on working on student-design projects (<italic>M</italic>&#x202F;=&#x202F;3.82, <italic>SD</italic>&#x202F;=&#x202F;1.02) than before participating in the program (<italic>M</italic>&#x202F;=&#x202F;3.51, <italic>SD</italic>&#x202F;=&#x202F;1.13), <italic>t</italic>(123)&#x202F;=&#x202F;2.81, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.01. This had a mean difference of 0.32 and showed a small effect (<italic>d</italic>&#x202F;=&#x202F;0.29). We also found after participation in the project-based science program, students scored higher on becoming responsible for a project (<italic>M</italic>&#x202F;=&#x202F;4.46, <italic>SD</italic>&#x202F;=&#x202F;0.77) than before participating in the program (<italic>M</italic>&#x202F;=&#x202F;4.16, <italic>SD</italic>&#x202F;=&#x202F;1.02), <italic>t</italic>(123)&#x202F;=&#x202F;3.04, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.01. This had a mean difference of 0.30 and showed a large effect (<italic>d</italic>&#x202F;=&#x202F;0.33).</p>
<p>Students&#x2019; beliefs on specific tasks within the program showed a significant increase after participation in the project-based science program. For instance, we found after participation in program students scored higher on their self-beliefs of reading primary scientific literature (<italic>M</italic>&#x202F;=&#x202F;3.89, <italic>SD</italic>&#x202F;=&#x202F;0.94) than before participating in the program (<italic>M</italic>&#x202F;=&#x202F;3.47, <italic>SD</italic>&#x202F;=&#x202F;1.14), <italic>t</italic>(123)&#x202F;=&#x202F;4.17, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.001. This had a larger mean difference of 0.42 and showed a small-medium effect (<italic>d</italic>&#x202F;=&#x202F;0.40). Students also reported higher on their beliefs of their ability to write a research proposal (<italic>M</italic>&#x202F;=&#x202F;3.49, <italic>SD</italic>&#x202F;=&#x202F;1.06) than before participating in the program (<italic>M</italic>&#x202F;=&#x202F;2.99, <italic>SD</italic>&#x202F;=&#x202F;1.26), <italic>t</italic>(123)&#x202F;=&#x202F;4.42, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.001. This had the largest mean difference of 0.50 and showed a small-medium effect (<italic>d</italic>&#x202F;=&#x202F;0.43). Students did not have significant mean differences on how they believed they could collect and analyze data after the duration of the investigation-centered science program.</p>
<p>In terms of externalizing their ideas, we found significant mean differences in their written reports, and creating posters. For instance, after participation in BioBuilder students scored higher on presenting scientific ideas or results in written papers or reports (<italic>M</italic>&#x202F;=&#x202F;3.61, <italic>SD</italic>&#x202F;=&#x202F;1.03) than before participating in the program (<italic>M</italic>&#x202F;=&#x202F;3.41, <italic>SD</italic>&#x202F;=&#x202F;1.20), <italic>t</italic>(123)&#x202F;=&#x202F;3.06, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.01. This showed a mean difference of 0.32 and showed a small effect (<italic>d</italic>&#x202F;=&#x202F;0.27). For scientific posters, we found that post-participation in the program, students scored higher on their self-beliefs of presenting a poster (<italic>M</italic>&#x202F;=&#x202F;3.55, <italic>SD</italic>&#x202F;=&#x202F;1.09) than before participating in the program (<italic>M</italic>&#x202F;=&#x202F;3.22, <italic>SD</italic>&#x202F;=&#x202F;1.27), <italic>t</italic>(123)&#x202F;=&#x202F;2.68, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.01. This showed a mean difference of 0.33 and a small effect (<italic>d</italic>&#x202F;=&#x202F;0.27). Students did not have significant mean differences on their self-beliefs of maintaining a laboratory notebook (see <xref ref-type="table" rid="tab5">Table 5</xref>).</p>
<table-wrap position="float" id="tab5">
<label>Table 5</label>
<caption>
<p>Pre-post intervention paired samples mean score.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Items</th>
<th align="center" valign="top">Pre<break/>23&#x2013;24</th>
<th align="center" valign="top">Post<break/>23&#x2013;24</th>
<th align="center" valign="top" rowspan="2">Mean difference</th>
<th align="center" valign="top" rowspan="2">% Change</th>
<th align="center" valign="top" rowspan="2"><italic>df</italic></th>
<th align="center" valign="top" rowspan="2"><italic>T</italic>-test</th>
<th align="center" valign="top" rowspan="2">Cohen&#x2019;s <italic>d</italic></th>
<th align="center" valign="top" rowspan="2">CI % 95</th>
</tr>
<tr>
<th/>
<th align="center" valign="top">Mean (SD)</th>
<th align="center" valign="top">Mean (SD)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="bottom" colspan="9">Scientific competency items</td>
</tr>
<tr>
<td align="left" valign="bottom">I can understand scientific information on websites</td>
<td align="center" valign="bottom">3.82 (0.86)</td>
<td align="center" valign="bottom">4.04 (0.68)</td>
<td align="left" valign="top">0.23</td>
<td align="left" valign="top">6.14%</td>
<td align="center" valign="top">123</td>
<td align="left" valign="top">3.31&#x002A;&#x002A;</td>
<td align="left" valign="top">0.30</td>
<td align="center" valign="top">[0.09, 0.37]</td>
</tr>
<tr>
<td align="left" valign="bottom">Giving evidence when I tell my opinion about science</td>
<td align="center" valign="bottom">3.74 (0.93)</td>
<td align="center" valign="top">3.9 (0.79)</td>
<td align="left" valign="top">0.16</td>
<td align="left" valign="top">4.09%</td>
<td align="center" valign="top">123</td>
<td align="left" valign="top">2.17&#x002A;</td>
<td align="left" valign="top">0.18</td>
<td align="center" valign="top">[0.01, 0.29]</td>
</tr>
<tr>
<td align="left" valign="bottom">Coming up with new ways to solve technical problems in science</td>
<td align="center" valign="bottom">3.46 (0.90)</td>
<td align="center" valign="top">3.66 (0.81)</td>
<td align="left" valign="top">0.20</td>
<td align="left" valign="top">6.07%</td>
<td align="center" valign="top">123</td>
<td align="left" valign="top">2.49&#x002A;</td>
<td align="left" valign="top">0.24</td>
<td align="center" valign="top">[0.04, 0.38]</td>
</tr>
<tr>
<td align="left" valign="bottom">Coming up with my own science investigations.</td>
<td align="center" valign="bottom">3.38 (1.01)</td>
<td align="center" valign="top">3.65 (0.80)</td>
<td align="left" valign="top">0.27</td>
<td align="left" valign="top">7.86%</td>
<td align="center" valign="top">123</td>
<td align="left" valign="top">2.82&#x002A;&#x002A;</td>
<td align="left" valign="top">0.29</td>
<td align="center" valign="top">[0.08, 0.45]</td>
</tr>
<tr>
<td align="left" valign="bottom">Critiquing the scientific work of other students</td>
<td align="center" valign="bottom">2.89 (1.23)</td>
<td align="center" valign="bottom">3.25 (1.10)</td>
<td align="left" valign="top">0.36</td>
<td align="left" valign="top">12.57%</td>
<td align="center" valign="top">123</td>
<td align="left" valign="top">2.86&#x002A;&#x002A;</td>
<td align="left" valign="top">0.31</td>
<td align="center" valign="top">[0.11, 0.61]</td>
</tr>
<tr>
<td align="left" valign="bottom" colspan="9">Scientific engagement items</td>
</tr>
<tr>
<td align="left" valign="bottom">I enjoy learning about science</td>
<td align="center" valign="bottom">4.63 (0.62)</td>
<td align="center" valign="top">4.7 (0.59)</td>
<td align="left" valign="top">0.06</td>
<td align="left" valign="top">1.22%</td>
<td align="center" valign="top">123</td>
<td align="left" valign="top">1.12</td>
<td align="left" valign="top">0.09</td>
<td align="center" valign="top">[&#x2212;0.04, 0.16]</td>
</tr>
<tr>
<td align="left" valign="bottom">I engage in science on weekends and during breaks from school.</td>
<td align="center" valign="bottom">3.5 (1.15)</td>
<td align="center" valign="top">3.8 (1.16)</td>
<td align="left" valign="top">0.30</td>
<td align="left" valign="top">8.52%</td>
<td align="center" valign="top">123</td>
<td align="left" valign="top">3.05&#x002A;&#x002A;</td>
<td align="left" valign="top">0.26</td>
<td align="center" valign="top">[0.10, 0.49]</td>
</tr>
<tr>
<td align="left" valign="bottom">I would like to know more about jobs that use science.</td>
<td align="center" valign="bottom">4.22 (0.95)</td>
<td align="center" valign="top">4.15 (1.06)</td>
<td align="left" valign="top">&#x2212;0.08</td>
<td align="left" valign="top">&#x2212;1.91%</td>
<td align="center" valign="top">123</td>
<td align="left" valign="top">&#x2212;0.95</td>
<td align="left" valign="top">0.08</td>
<td align="center" valign="top">[&#x2212;0.25, 0.08]</td>
</tr>
<tr>
<td align="left" valign="bottom">I will miss studying science when I leave school.</td>
<td align="center" valign="bottom">3.91 (0.98)</td>
<td align="center" valign="top">4.00 (0.97)</td>
<td align="left" valign="top">0.09</td>
<td align="left" valign="top">2.27%</td>
<td align="center" valign="top">123</td>
<td align="left" valign="top">1.03</td>
<td align="left" valign="top">0.09</td>
<td align="center" valign="top">[&#x2212;0.08, 0.26]</td>
</tr>
<tr>
<td align="left" valign="bottom" colspan="9">Scientific content knowledge items</td>
</tr>
<tr>
<td align="left" valign="bottom">Working on a lab or project where no one knows the outcome</td>
<td align="center" valign="bottom">3.03 (1.24)</td>
<td align="center" valign="bottom">3.42 (1.12)</td>
<td align="left" valign="top">0.39</td>
<td align="left" valign="top">13.06%</td>
<td align="center" valign="top">123</td>
<td align="left" valign="top">3.49&#x002A;&#x002A;&#x002A;</td>
<td align="left" valign="top">0.33</td>
<td align="center" valign="top">[0.17, 0.62]</td>
</tr>
<tr>
<td align="left" valign="bottom">Working on student-designed projects</td>
<td align="center" valign="bottom">3.51 (1.13)</td>
<td align="center" valign="bottom">3.82 (1.02)</td>
<td align="left" valign="top">0.32</td>
<td align="left" valign="top">8.94%</td>
<td align="center" valign="top">123</td>
<td align="left" valign="top">2.81&#x002A;&#x002A;</td>
<td align="left" valign="top">0.29</td>
<td align="center" valign="top">[0.09, 0.54]</td>
</tr>
<tr>
<td align="left" valign="bottom">Becoming responsible for a part of a project</td>
<td align="center" valign="bottom">4.16 (1.02)</td>
<td align="center" valign="bottom">4.46 (0.77)</td>
<td align="left" valign="top">0.30</td>
<td align="left" valign="top">6.96%</td>
<td align="center" valign="top">123</td>
<td align="left" valign="top">3.04&#x002A;&#x002A;</td>
<td align="left" valign="top">0.33</td>
<td align="center" valign="top">[0.10, 0.48]</td>
</tr>
<tr>
<td align="left" valign="bottom">Reading primary scientific literature</td>
<td align="center" valign="bottom">3.47 (1.14)</td>
<td align="center" valign="bottom">3.89 (0.94)</td>
<td align="left" valign="top">0.42</td>
<td align="left" valign="top">12.06%</td>
<td align="center" valign="top">123</td>
<td align="left" valign="top">4.17&#x002A;&#x002A;&#x002A;</td>
<td align="left" valign="top">0.40</td>
<td align="center" valign="top">[0.22, 0.62]</td>
</tr>
<tr>
<td align="left" valign="bottom">Writing a research proposal</td>
<td align="center" valign="bottom">2.99 (1.26)</td>
<td align="center" valign="bottom">3.49 (1.06)</td>
<td align="left" valign="top">0.50</td>
<td align="left" valign="top">16.75%</td>
<td align="center" valign="top">123</td>
<td align="left" valign="top">4.42&#x002A;&#x002A;&#x002A;</td>
<td align="left" valign="top">0.43</td>
<td align="center" valign="top">[0.28, 0.72]</td>
</tr>
<tr>
<td align="left" valign="bottom">Collecting data</td>
<td align="center" valign="bottom">4.01 (0.95)</td>
<td align="center" valign="bottom">4.06 (0.99)</td>
<td align="left" valign="top">0.05</td>
<td align="left" valign="top">1.21%</td>
<td align="center" valign="top">123</td>
<td align="left" valign="top">0.53</td>
<td align="left" valign="top">0.05</td>
<td align="center" valign="top">[&#x2212;0.13, 0.23]</td>
</tr>
<tr>
<td align="left" valign="bottom">Analyzing data</td>
<td align="center" valign="bottom">3.93 (0.94)</td>
<td align="center" valign="bottom">4.07 (0.80)</td>
<td align="left" valign="top">0.14</td>
<td align="left" valign="top">3.70%</td>
<td align="center" valign="top">123</td>
<td align="left" valign="top">1.68</td>
<td align="left" valign="top">0.17</td>
<td align="center" valign="top">[&#x2212;0.03, 0.32]</td>
</tr>
<tr>
<td align="left" valign="bottom">Presenting scientific ideas or results orally (spoken presentation)</td>
<td align="center" valign="bottom">3.41 (1.20)</td>
<td align="center" valign="bottom">3.61 (1.03)</td>
<td align="left" valign="top">0.20</td>
<td align="left" valign="top">6%</td>
<td align="center" valign="top">123</td>
<td align="left" valign="top">1.93</td>
<td align="left" valign="top">0.18</td>
<td align="center" valign="top">[&#x2212;0.004, 0.41]</td>
</tr>
<tr>
<td align="left" valign="bottom">Presenting scientific ideas or results in written papers or reports</td>
<td align="center" valign="bottom">3.39 (1.22)</td>
<td align="center" valign="bottom">3.71 (1.11)</td>
<td align="left" valign="top">0.32</td>
<td align="left" valign="top">9.55%</td>
<td align="center" valign="top">123</td>
<td align="left" valign="top">3.06&#x002A;&#x002A;</td>
<td align="left" valign="top">0.27</td>
<td align="center" valign="top">[0.11, 0.53]</td>
</tr>
<tr>
<td align="left" valign="bottom">Presenting scientific posters</td>
<td align="center" valign="bottom">3.22 (1.27)</td>
<td align="center" valign="bottom">3.55 (1.09)</td>
<td align="left" valign="top">0.33</td>
<td align="left" valign="top">10.00%</td>
<td align="center" valign="top">123</td>
<td align="left" valign="top">2.68&#x002A;&#x002A;</td>
<td align="left" valign="top">0.27</td>
<td align="center" valign="top">[0.08, 0.56]</td>
</tr>
<tr>
<td align="left" valign="middle">Maintaining a laboratory notebook</td>
<td align="center" valign="middle">3.49 (1.24)</td>
<td align="center" valign="middle">3.37 (1.23)</td>
<td align="left" valign="middle">&#x2212;0.12</td>
<td align="left" valign="middle">&#x2212;3%</td>
<td align="center" valign="middle">123</td>
<td align="left" valign="middle">&#x2212;1.26</td>
<td align="left" valign="middle">0.10</td>
<td align="center" valign="middle">[&#x2212;0.31, 0.07]</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>There was a total of 124 students who gave both pre/post data in 23&#x2013;24. We used paired samples t-tests to assess differences in pre/post scores on each item. CI, Confidence Interval. &#x002A;<italic>p</italic>&#x202F;&#x003C;&#x202F;0.05, &#x002A;&#x002A;<italic>p</italic>&#x202F;&#x003C;&#x202F;0.01, &#x002A;&#x002A;&#x002A;<italic>p</italic>&#x202F;&#x003C;&#x202F;0.001.</p>
</table-wrap-foot>
</table-wrap>
</sec>
</sec>
<sec id="sec15">
<title>Residual change score differences</title>
<p>For the entire sample (<italic>n</italic>&#x202F;=&#x202F;124), we analyzed descriptive and correlational statistics for pre and post survey scores across composite factors (i.e., Scientific Engagement, Scientific Competency, Scientific Content Knowledge; see <xref ref-type="fig" rid="fig10">Figure 10</xref>; <xref ref-type="table" rid="tab6">Table 6</xref>). We found there were moderate to strong relationships between several pre and post scores across factors.</p>
<fig position="float" id="fig10">
<label>Figure 10</label>
<caption>
<p>Pre-post mean scientific competency, engagement, and content knowledge beliefs (<italic>n</italic>&#x202F;=&#x202F;124).</p>
</caption>
<graphic xlink:href="feduc-09-1493356-g010.tif"/>
</fig>
<table-wrap position="float" id="tab6">
<label>Table 6</label>
<caption>
<p>Means, standard deviations, and correlations with confidence intervals.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Variable</th>
<th align="center" valign="top"><italic>M</italic></th>
<th align="center" valign="top"><italic>SD</italic></th>
<th align="center" valign="top">1</th>
<th align="center" valign="top">2</th>
<th align="center" valign="top">3</th>
<th align="center" valign="top">4</th>
<th align="center" valign="top">5</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">1. Scientific engagement (Pre)</td>
<td align="center" valign="middle">4.07</td>
<td align="center" valign="middle">0.73</td>
<td/>
<td/>
<td/>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="middle">2. Scientific competency (Pre)</td>
<td align="center" valign="middle">3.45</td>
<td align="center" valign="middle">0.79</td>
<td align="center" valign="middle">0.56&#x002A;&#x002A;</td>
<td/>
<td/>
<td/>
<td/>
</tr>
<tr>
<td/>
<td/>
<td/>
<td align="center" valign="middle">[0.42, 0.67]</td>
<td/>
<td/>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="middle">3. Scientific content knowledge (Pre)</td>
<td align="center" valign="middle">3.51</td>
<td align="center" valign="middle">0.84</td>
<td align="center" valign="middle">0.49&#x002A;&#x002A;</td>
<td align="center" valign="middle">0.76&#x002A;&#x002A;</td>
<td/>
<td/>
<td/>
</tr>
<tr>
<td/>
<td/>
<td/>
<td align="center" valign="middle">[0.34, 0.61]</td>
<td align="center" valign="middle">[0.68, 0.83]</td>
<td/>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="middle">4. Scientific engagement (Post)</td>
<td align="center" valign="middle">4.16</td>
<td align="center" valign="middle">0.75</td>
<td align="center" valign="middle">0.68&#x002A;&#x002A;</td>
<td align="center" valign="middle">0.40&#x002A;&#x002A;</td>
<td align="center" valign="middle">0.37&#x002A;&#x002A;</td>
<td/>
<td/>
</tr>
<tr>
<td/>
<td/>
<td/>
<td align="center" valign="middle">[0.57, 0.77]</td>
<td align="center" valign="middle">[0.24, 0.54]</td>
<td align="center" valign="middle">[0.20, 0.51]</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="middle">5. Scientific competency (Post)</td>
<td align="center" valign="middle">3.70</td>
<td align="center" valign="middle">0.62</td>
<td align="center" valign="middle">0.32&#x002A;&#x002A;</td>
<td align="center" valign="middle">0.58&#x002A;&#x002A;</td>
<td align="center" valign="middle">0.49&#x002A;&#x002A;</td>
<td align="center" valign="middle">0.36&#x002A;&#x002A;</td>
<td/>
</tr>
<tr>
<td/>
<td/>
<td/>
<td align="center" valign="middle">[0.15, 0.47]</td>
<td align="center" valign="middle">[0.45, 0.69]</td>
<td align="center" valign="middle">[0.34, 0.61]</td>
<td align="center" valign="middle">[0.19, 0.50]</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">6. Scientific content knowledge (Post)</td>
<td align="center" valign="middle">3.77</td>
<td align="center" valign="middle">0.70</td>
<td align="center" valign="middle">0.14</td>
<td align="center" valign="middle">0.45&#x002A;&#x002A;</td>
<td align="center" valign="middle">0.60&#x002A;&#x002A;</td>
<td align="center" valign="middle">0.17</td>
<td align="center" valign="middle">0.60&#x002A;&#x002A;</td>
</tr>
<tr>
<td/>
<td/>
<td/>
<td align="center" valign="middle">[&#x2212;0.04, 0.31]</td>
<td align="center" valign="middle">[0.30, 0.58]</td>
<td align="center" valign="middle">[0.48, 0.70]</td>
<td align="center" valign="middle">[&#x2212;0.00, 0.34]</td>
<td align="center" valign="middle">[0.47, 0.70]</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>M and SD are used to represent mean and standard deviation, respectively. Values in square brackets indicate the 95% confidence interval for each correlation. The confidence interval is a plausible range of population correlations that could have caused the sample correlation (<xref ref-type="bibr" rid="ref9003">Cumming, 2014</xref>). &#x002A;<italic>p</italic>&#x202F;&#x003C;&#x202F;0.05, &#x002A;&#x002A;<italic>p</italic>&#x202F;&#x003C;&#x202F;0.01.</p>
</table-wrap-foot>
</table-wrap>
<p>For residual change score differences, we found gender, first generation status, or locale did not significantly predict post-scores across each factor of scientific engagement, scientific competency, and scientific content knowledge (see <xref ref-type="table" rid="tab7">Table 7</xref>). After controlling for each of these covariates, we did find significant residual differences from pre- to post-scores across each factor of scientific engagement, competency, and content knowledge (see <xref ref-type="table" rid="tab6">Table 6</xref>). For instance, we found pre-scores (<italic>b&#x202F;=</italic> 0.46<italic>, p</italic>&#x202F;&#x003C;&#x202F;0.001) of students&#x2019; beliefs of Scientific Content Knowledge did significantly predict post-scores, R<sup>2</sup>&#x202F;=&#x202F;0.57, F(6, 96)&#x202F;=&#x202F;13.73, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.001; This means the model accounted for 46% of the variance in students&#x2019; beliefs of their Scientific Content Knowledge. All three factors of Scientific Engagement, Scientific Competency, Scientific Content Knowledge, showed no significant differences across demographic covariates. Scientific Engagement (<italic>R</italic><sup>2</sup>&#x202F;=&#x202F;0.46) and Scientific Content Knowledge (<italic>R</italic><sup>2</sup>&#x202F;=&#x202F;0.46) showed the largest effect; however Scientific Competency (<italic>R</italic><sup>2</sup>&#x202F;=&#x202F;0.36) also showed a large effect.</p>
<table-wrap position="float" id="tab7">
<label>Table 7</label>
<caption>
<p>Pre-post residual change score differences: competency, engagement, and content knowledge beliefs (<italic>n</italic>&#x202F;=&#x202F;103).</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" rowspan="2">Outcome variables</th>
<th align="center" valign="top" colspan="3">Intercept</th>
<th align="center" valign="top" colspan="3">Pre</th>
<th align="center" valign="top" colspan="3">Female</th>
<th align="center" valign="top" colspan="3">First generation</th>
<th align="center" valign="top" colspan="3">City: Large</th>
<th align="center" valign="top" colspan="3">City: Midsize</th>
<th align="center" valign="top" colspan="2">City: Small</th>
<th colspan="2"/>
</tr>
<tr>
<th align="center" valign="top">B</th>
<th align="center" valign="top">SE</th>
<th align="center" valign="top">CI 95%</th>
<th align="center" valign="top">B</th>
<th align="center" valign="top">SE</th>
<th align="center" valign="top">CI 95%</th>
<th align="center" valign="top">B</th>
<th align="center" valign="top">SE</th>
<th align="center" valign="top">CI 95%</th>
<th align="center" valign="top">B</th>
<th align="center" valign="top">SE</th>
<th align="center" valign="top">CI 95%</th>
<th align="center" valign="top">B</th>
<th align="center" valign="top">SE</th>
<th align="center" valign="top">CI 95%</th>
<th align="center" valign="top">B</th>
<th align="center" valign="top">SE</th>
<th align="center" valign="top">CI 95%</th>
<th align="center" valign="top">B</th>
<th align="center" valign="top">SE</th>
<th align="center" valign="top">CI 95%</th>
<th align="center" valign="top"><italic>R</italic><sup>2</sup></th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">Scientific competency</td>
<td align="center" valign="middle"><bold>2.11&#x002A;&#x002A;</bold></td>
<td align="center" valign="middle">0.24</td>
<td align="center" valign="middle">[1.64, 2.59]</td>
<td align="center" valign="middle"><bold>0.46&#x002A;&#x002A;&#x002A;</bold></td>
<td align="center" valign="middle">0.07</td>
<td align="center" valign="middle">[0.33, 0.59]</td>
<td align="center" valign="middle">0.05</td>
<td align="center" valign="middle">0.10</td>
<td align="center" valign="middle">[&#x2212;0.15, 0.25]</td>
<td align="center" valign="middle">&#x2212;0.03</td>
<td align="center" valign="middle">0.10</td>
<td align="center" valign="middle">[&#x2212;0.23, 0.17]</td>
<td align="center" valign="middle">&#x2212;0.12</td>
<td align="center" valign="middle">0.23</td>
<td align="center" valign="middle">[&#x2212;0.58, 0.34]</td>
<td align="center" valign="middle">0.36</td>
<td align="center" valign="middle">0.20</td>
<td align="center" valign="middle">[&#x2212;0.04, 0.75]</td>
<td align="center" valign="middle">0.03</td>
<td align="center" valign="middle">0.16</td>
<td align="center" valign="middle">[&#x2212;0.29, 0.35]</td>
<td align="center" valign="middle"><bold>0.36&#x002A;&#x002A;&#x002A;</bold></td>
</tr>
<tr>
<td align="left" valign="middle">Scientific engagement</td>
<td align="center" valign="middle"><bold>1.53&#x002A;&#x002A;&#x002A;</bold></td>
<td align="center" valign="middle">0.33</td>
<td align="center" valign="middle">[0.87,<break/>2.19]</td>
<td align="center" valign="middle"><bold>0.64&#x002A;&#x002A;&#x002A;</bold></td>
<td align="center" valign="middle">0.08</td>
<td align="center" valign="middle">[0.478, 0.80]</td>
<td align="center" valign="middle">0.09</td>
<td align="center" valign="middle">0.11</td>
<td align="center" valign="middle">[&#x2212;0.13, 0.31]</td>
<td align="center" valign="middle">&#x2212;0.04</td>
<td align="center" valign="middle">0.11</td>
<td align="center" valign="middle">[&#x2212;0.26, 0.18]</td>
<td align="center" valign="middle">0.11</td>
<td align="center" valign="middle">0.26</td>
<td align="center" valign="middle">[&#x2212;0.40, 0.62]</td>
<td align="center" valign="middle">0.40</td>
<td align="center" valign="middle">0.22</td>
<td align="center" valign="middle">[&#x2212;0.03, 0.83]</td>
<td align="center" valign="middle">0.05</td>
<td align="center" valign="middle">0.17</td>
<td align="center" valign="middle">[&#x2212;0.30, 0.39]</td>
<td align="center" valign="middle"><bold>0.46&#x002A;&#x002A;&#x002A;</bold></td>
</tr>
<tr>
<td align="left" valign="middle">Scientific content knowledge</td>
<td align="center" valign="middle"><bold>1.80&#x002A;&#x002A;&#x002A;</bold></td>
<td align="center" valign="middle">0.24</td>
<td align="center" valign="middle">[1.32, 2.28]</td>
<td align="center" valign="middle"><bold>0.57&#x002A;&#x002A;&#x002A;</bold></td>
<td align="center" valign="middle">0.07</td>
<td align="center" valign="middle">[0.44, 0.71]</td>
<td align="center" valign="middle">0.04</td>
<td align="center" valign="middle">0.11</td>
<td align="center" valign="middle">[&#x2212;0.18, 0.25]</td>
<td align="center" valign="middle">&#x2212;0.01</td>
<td align="center" valign="middle">0.11</td>
<td align="center" valign="middle">[&#x2212;0.01, 0.11]</td>
<td align="center" valign="middle">&#x2212;0.3</td>
<td align="center" valign="middle">0.24</td>
<td align="center" valign="middle">[&#x2212;0.91, 0.05]</td>
<td align="center" valign="middle">0.12</td>
<td align="center" valign="middle">0.21</td>
<td align="center" valign="middle">[&#x2212;0.29, 0.53]</td>
<td align="center" valign="middle">&#x2212;0.22</td>
<td align="center" valign="middle">0.16</td>
<td align="center" valign="middle">[&#x2212;0.54, 0.11]</td>
<td align="center" valign="middle"><bold>0.46</bold><break/><bold>&#x002A;&#x002A;&#x002A;</bold></td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>There were a total of 124 students who gave both pre/post data in 23&#x2013;24. For this analysis, we only had 103 students with full demographic information. Residual Change scores show the average population level difference from after participation in the BioBuilder program. The intercept only model should closely resemble the Mean Differences found on <xref ref-type="table" rid="tab5">Table 5</xref>. Residual SE is the standard deviation of the residuals. Smaller residual SE provides indication of greater prediction. Benjamini Hochberg correction to account for multiple comparisons and provide conservative estimates. CI, confidence interval; SE, standard error; Residual SE, residual standard error. &#x002A;<italic>p</italic>&#x202F;&#x003C;&#x202F;0.05, &#x002A;&#x002A;<italic>p</italic>&#x202F;&#x003C;&#x202F;0.01, &#x002A;&#x002A;&#x002A;<italic>p</italic>&#x202F;&#x003C;&#x202F;0.001. Bolded values indicate statistically significance (<italic>p</italic> &#x003C;0.05 or lower).</p>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="sec16">
<title>Changes in synthetic biology knowledge</title>
<sec id="sec17">
<title>Promotor and gene expression</title>
<p>Students were asked if they could confidently identify the symbol for a promoter from a specified figure using a 1-to-5 Likert Scale (<italic>M</italic>&#x202F;=&#x202F;3.7, <italic>SD</italic>&#x202F;=&#x202F;1.4). Responses showed a left-skewed distribution (<xref ref-type="fig" rid="fig11">Figure 11</xref>). In other words, many students felt confident in identifying the promoter symbol. Students were also asked if the symbols in a figure were in the proper order for a gene expression (<xref ref-type="fig" rid="fig12">Figure 12</xref>). There were 83 students (66.9%) who rated this as TRUE, whereas there were 41 students who said they did not know (26.6%) or chose FALSE (6.5%).</p>
<fig position="float" id="fig11">
<label>Figure 11</label>
<caption>
<p>Confidence identifying promoter symbol. The item asked if they strongly agree (5) to strongly disagree (1) with the following statement &#x201C;I can confidently identify the promoter symbol.&#x201D;</p>
</caption>
<graphic xlink:href="feduc-09-1493356-g011.tif"/>
</fig>
<fig position="float" id="fig12">
<label>Figure 12</label>
<caption>
<p>Symbols in proper order for gene expression. This item asked, &#x201C;The symbols in the figure are in the proper order for a gene expression unit.&#x201D; The correct answer was true.</p>
</caption>
<graphic xlink:href="feduc-09-1493356-g012.tif"/>
</fig>
</sec>
<sec id="sec18">
<title>What is synthetic biology?</title>
<p>This first round of rating resulted in poor agreement for both raters across pre-definition responses (37.5%) and post-definition responses (58%), the same was true for pre-example responses (40%) and post-example responses (48%). The researchers and raters met for a consensual discussion of the developed rubric. During the discussion, we discovered that one rater was grading too rigorously, and another was being too lenient. Raters were given the same random sampling of 20% responses with blank scores and asked to separately re-rate submissions after re-interpretation of the rubric (see <xref ref-type="table" rid="tab8">Tables 8</xref>, <xref ref-type="table" rid="tab9">9</xref>). Across both raters, this second round of rating resulted in slight to moderate agreement across pre-definition responses (68%) and post-definition responses (64%), as well as pre-example responses (72%) and post-example responses (64%).</p>
<table-wrap position="float" id="tab8">
<label>Table 8</label>
<caption>
<p>Synthetic biology (SB) definition rubric.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">0</th>
<th align="left" valign="top">1</th>
<th align="left" valign="top">2</th>
<th align="left" valign="top">3</th>
</tr>
<tr>
<th align="left" valign="middle">&#x201C;Do not know&#x201D;</th>
<th align="left" valign="middle">Poor (wrong or so general as to be a description of any life science)</th>
<th align="left" valign="middle">Emerging (includes idea of design and/or engineering but not target, reason, or approach)</th>
<th align="left" valign="middle">Sophisticated</th>
</tr>
</thead>
<tbody>
<tr>
<td/>
<td align="left" valign="bottom">That appears to be the process of recreating biological processes and systems from synthetic materials.</td>
<td align="left" valign="middle">Engineering life</td>
<td align="left" valign="bottom">SB is a field of science that involves redesigning organisms for useful purposes by engineering them to have new abilities.</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Art</td>
<td align="left" valign="middle">Science of artificial man-made life</td>
<td align="left" valign="bottom">Synthetically creating or recreating an organism using pieces of other organisms to solve a problem or create a product.</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Medicine</td>
<td align="left" valign="middle">It is using things like enzymes, proteins, etc., to redesign existing biological systems.</td>
<td align="left" valign="bottom">Manipulating parts of gene expression units and combining them w/other ideas to solve a problem.</td>
</tr>
<tr>
<td/>
<td/>
<td/>
<td align="left" valign="bottom">Genetically engineering an organism to get it to do what you want.</td>
</tr>
<tr>
<td/>
<td/>
<td/>
<td align="left" valign="bottom">SB is idea of creating an engineered organism to accomplish something /to solve a problem.</td>
</tr>
<tr>
<td/>
<td/>
<td/>
<td align="left" valign="bottom">It is when biology or science is used to create something that can benefit humans.</td>
</tr>
</tbody>
</table>
</table-wrap>
<table-wrap position="float" id="tab9">
<label>Table 9</label>
<caption>
<p>Synthetic biology example rubric.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">0</th>
<th align="left" valign="top">1</th>
<th align="left" valign="top">2</th>
<th align="left" valign="top">3</th>
</tr>
<tr>
<th align="left" valign="middle">&#x201C;Do not know&#x201D;</th>
<th align="left" valign="middle">Poor (incomplete or incorrect)</th>
<th align="left" valign="middle">Emerging (ideas but not connected to process or current applications)</th>
<th align="left" valign="middle">Sophisticated (process, cell or molecular agent, application requires combination that nature would not provide)</th>
</tr>
</thead>
<tbody>
<tr>
<td/>
<td align="left" valign="middle">The creation of DNA or genetic</td>
<td align="left" valign="middle">Crisper</td>
<td align="left" valign="middle">An example is redesigning <italic>E. coli</italic> at a transcriptional level so that it will make its media smell like bananas.</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Prosthetics</td>
<td align="left" valign="middle">Production of drugs from cells.</td>
<td align="left" valign="middle">An example could be adding a protein to a cell to make it more useful, like making a color changeable bandages that can react to the pH of our skin wounds.</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Heart monitors</td>
<td align="left" valign="middle">Vaccines.</td>
<td align="left" valign="middle">COVID vaccine (Made using a novel approach that needed synthetic biology)</td>
</tr>
<tr>
<td/>
<td/>
<td align="left" valign="middle">Genetically modified food</td>
<td/>
</tr>
</tbody>
</table>
</table-wrap>
<p>Although there was improved agreement in the second round, we decided to have a consensual discussion to discuss specific disagreements across raters. We found that Rater 1 was rating post-scores more harshly than Rater 2 because they thought students should have more advanced, nuanced answers after the program. Rater 2 referred to specific language used within the rubric to justify their scores. After this discussion, there were still disagreements, however we found substantially better agreement across pre-definition responses (100%) and post-definition responses (92%), pre-example responses (96%), and post-example responses (88%) (for Cohen&#x2019;s Kappa, see <xref ref-type="table" rid="tab10">Table 10</xref>). Overall, students showed an emerging to sophisticated understanding of synthetic biology from pre-to-post responses, as well as pre-to-post examples (see <xref ref-type="fig" rid="fig13">Figures 13</xref>, <xref ref-type="fig" rid="fig14">14</xref>).</p>
<table-wrap position="float" id="tab10">
<label>Table 10</label>
<caption>
<p>Interrater reliability of responses on synthetic biology content knowledge.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th/>
<th align="center" valign="top" colspan="2">Definition</th>
<th align="center" valign="top" colspan="2">Example</th>
</tr>
<tr>
<th/>
<th align="center" valign="top">Pre</th>
<th align="center" valign="top">Post</th>
<th align="center" valign="top">Pre</th>
<th align="center" valign="top">Post</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="bottom">Nominal agreement</td>
<td align="center" valign="bottom">100%</td>
<td align="center" valign="bottom">92%</td>
<td align="center" valign="bottom">96%</td>
<td align="center" valign="bottom">88%</td>
</tr>
<tr>
<td align="left" valign="bottom">Kappa</td>
<td align="center" valign="bottom">1.00&#x002A;&#x002A;&#x002A;</td>
<td align="center" valign="bottom">0.85&#x002A;&#x002A;&#x002A;</td>
<td align="center" valign="bottom">0.95&#x002A;&#x002A;&#x002A;</td>
<td align="center" valign="bottom">0.83&#x002A;&#x002A;&#x002A;</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>This agreement is based on two expert raters and 25 of 124 responses. Definition&#x202F;=&#x202F;Item asked &#x201C;What is Synthetic Biology?&#x201D;; Example&#x202F;=&#x202F;Item asked &#x201C;Give an Example of Synthetic Biology.&#x201D; &#x002A;indicates <italic>p</italic> &#x003C;0.05, &#x002A;&#x002A;indicates <italic>p</italic> &#x003C; 0.01; &#x002A;&#x002A;&#x002A;indicates <italic>p</italic> &#x003C;0.001.</p>
</table-wrap-foot>
</table-wrap>
<fig position="float" id="fig13">
<label>Figure 13</label>
<caption>
<p>Pre-post test ratings of student definitions of synthetic biology (<italic>n</italic>&#x202F;=&#x202F;25). This was a random sampling of 25 students from the 124 responses rated by two expert raters.</p>
</caption>
<graphic xlink:href="feduc-09-1493356-g013.tif"/>
</fig>
<fig position="float" id="fig14">
<label>Figure 14</label>
<caption>
<p>Pre-post test ratings of student examples of synthetic biology (<italic>n</italic>&#x202F;=&#x202F;25). This was a random sampling of 25 students from the 124 responses rated by two expert raters.</p>
</caption>
<graphic xlink:href="feduc-09-1493356-g014.tif"/>
</fig>
</sec>
</sec>
<sec id="sec19">
<title>Recommendations, college selection, and future job searches</title>
<p>The majority of students &#x201C;would recommend a high school class that has the project-based science program over one that does not,&#x201D; with a mean score of 4.3 (<italic>SD</italic>&#x202F;=&#x202F;0.7; see <xref ref-type="fig" rid="fig1">Figure 1</xref>). We also asked students if the project-based science program supported their interest in advanced scientific coursework (<italic>M</italic>&#x202F;=&#x202F;4.3, <italic>SD</italic>&#x202F;=&#x202F;0.8; <xref ref-type="fig" rid="fig2">Figure 2</xref>) or pursuing a career in the Life Sciences (<italic>M</italic>&#x202F;=&#x202F;4.2, <italic>SD</italic>&#x202F;=&#x202F;1; <xref ref-type="fig" rid="fig3">Figure 3</xref>). For college selection, we asked if students were considering biotechnology, biomanufacturing, or synthetic biology (<italic>M</italic>&#x202F;=&#x202F;3.8, <italic>SD</italic>&#x202F;=&#x202F;1.1; <xref ref-type="fig" rid="fig4">Figure 4</xref>), as well as the importance of these fields of study for college selection (<italic>M</italic>&#x202F;=&#x202F;3.8, <italic>SD</italic>&#x202F;=&#x202F;1.2; <xref ref-type="fig" rid="fig5">Figure 5</xref>). When students were looking for future jobs, we asked if they were considering biotechnology, biomanufacturing, or synthetic biology (<italic>M</italic>&#x202F;=&#x202F;3.8, <italic>SD</italic>&#x202F;=&#x202F;1.2; <xref ref-type="fig" rid="fig6">Figure 6</xref>), as well as the importance of finding a job within these fields (<italic>M</italic>&#x202F;=&#x202F;3.8, <italic>SD</italic>&#x202F;=&#x202F;1.2; <xref ref-type="fig" rid="fig7">Figure 7</xref>). For all four of these items, students rated them similarly with left skewed distributions indicating more students choosing they would be likely seeking biotechnology, biomanufacturing, or synthetic biology in college selection and future job searches.</p>
</sec>
</sec>
<sec sec-type="discussion" id="sec20">
<title>Discussion</title>
<p>The findings of this study highlight significant positive outcomes for students participating in the project-based science education intervention, filling a critical gap in the existing literature regarding the effectiveness of such interventions in enhancing students&#x2019; science identity, self-beliefs, and content knowledge. Previous studies have emphasized the importance of fostering science identity as a key factor in retaining students in STEM pathways (<xref ref-type="bibr" rid="ref2">Aschbacher et al., 2010</xref>; <xref ref-type="bibr" rid="ref3">Barton et al., 2013</xref>; <xref ref-type="bibr" rid="ref9">Chemers et al., 2011</xref>). This study contributes to that body of knowledge by demonstrating that participation in a project-based intervention like BioBuilderClub not only increases students&#x2019; scientific engagement, competency, and content knowledge but also enhances their interest in biotechnology and related fields, aligning with the findings of prior research on the importance of authentic, hands-on learning experiences (<xref ref-type="bibr" rid="ref15">Deemer et al., 2022</xref>; <xref ref-type="bibr" rid="ref35">Shanahan and Nieswandt, 2009</xref>).</p>
<p>Our examination of high school students&#x2019; self-beliefs regarding their scientific engagement, competency, and content knowledge revealed that students who participated in the intervention during the 2023&#x2013;2024 school year demonstrated significant increases across these areas. This outcome is consistent with the theoretical framework suggesting that students who view themselves as competent and engaged in science are more likely to persist in STEM pathways (<xref ref-type="bibr" rid="ref7">Carlone and Johnson, 2007</xref>; <xref ref-type="bibr" rid="ref36">Vincent-Ruz and Schunn, 2018</xref>). The evidence of a three-factor structure in our exploratory factor analysis (<xref ref-type="table" rid="tab4">Table 4</xref>; <xref ref-type="fig" rid="fig8">Figure 8</xref>) supports the construct validity of these measures, with internal consistency values (<italic>&#x03B1;</italic>&#x202F;=&#x202F;0.79&#x2013;0.91) further confirming the reliability of our findings.</p>
<p>Increased scientific engagement was particularly noteworthy, as students reported greater involvement in scientific activities beyond the classroom, such as engaging with science during weekends and school breaks. This finding suggests that the project-based science education intervention successfully fosters a deeper interest in science, consistent with literature highlighting the importance of sustained engagement for the development of science identity (<xref ref-type="bibr" rid="ref28">Metcalf, 2010</xref>; <xref ref-type="bibr" rid="ref36">Vincent-Ruz and Schunn, 2018</xref>). Additionally, students demonstrated improved scientific competency, including their ability to understand scientific information, generate problem-solving methods, and conduct independent investigations&#x2014;skills that are critical for future scientific endeavors and align with the competencies described by <xref ref-type="bibr" rid="ref7">Carlone and Johnson (2007)</xref>.</p>
<p>The program also effectively enhanced students&#x2019; content knowledge in synthetic biology, a field with growing importance in the modern bioeconomy (<xref ref-type="bibr" rid="ref17">Graham et al., 2013</xref>). Students showed significant gains in understanding key concepts and techniques, such as reading primary scientific literature, writing research proposals, and presenting scientific ideas. This improvement was corroborated by both quantitative measures and qualitative feedback from students, who expressed confidence in their newfound knowledge and skills. These outcomes address the gaps identified by <xref ref-type="bibr" rid="ref9001">Walker (2021)</xref> and others who have called for more research on how to effectively teach synthetic biology and related fields at earlier educational stages.</p>
<p>Students overwhelmingly recommended the project-based science education intervention, noting that it provided valuable educational experiences. They particularly appreciated the opportunity to collaborate with peers and mentors, learn in a supportive environment, and engage in creative scientific projects. The program&#x2019;s emphasis on hands-on, practical learning experiences, which has been highlighted as a key factor in successful STEM education (<xref ref-type="bibr" rid="ref35">Shanahan and Nieswandt, 2009</xref>; <xref ref-type="bibr" rid="ref36">Vincent-Ruz and Schunn, 2018</xref>), was a critical element of its success.</p>
<p>In addition to the benefits for students, the program aimed to raise awareness of biomanufacturing and modern life sciences among community stakeholders. Engaging parents, teachers, college admissions officers, and relevant businesses is crucial for creating a supportive ecosystem for students pursuing careers in biotechnology, as noted in previous studies (<xref ref-type="bibr" rid="ref9006">Marten, 2022</xref>; <xref ref-type="bibr" rid="ref34">U.S. Department of Education, 2023</xref>). The program&#x2019;s efforts to communicate and celebrate student achievements publicly helped build a positive perception of biotechnology as a viable and rewarding career path.</p>
<p>However, while students demonstrated increases in engagement, competency, and content knowledge, the residual change regressions for each item (<italic>n</italic>&#x202F;=&#x202F;103) did not reveal significant differences by gender, locale, or first-generation status. This finding suggests that the intervention was broadly effective across different demographic groups, but it also indicates a need for future research to explore potential differences in outcomes among more diverse student populations, particularly those systematically excluded from STEM fields (<xref ref-type="bibr" rid="ref2">Aschbacher et al., 2010</xref>; <xref ref-type="bibr" rid="ref3">Barton et al., 2013</xref>).</p>
<p>For knowledge of synthetic biology, our raters found that students who participated in the intervention demonstrated increased understanding of synthetic biology (see <xref ref-type="fig" rid="fig13">Figures 13</xref>, <xref ref-type="fig" rid="fig14">14</xref>). These findings are consistent with the literature on the importance of providing authentic, interdisciplinary science experiences that connect students with real-world problems and solutions (<xref ref-type="bibr" rid="ref18">iGEM Foundation, 2024</xref>; <xref ref-type="bibr" rid="ref31">NISE Network, 2024</xref>).</p>
<sec id="sec21">
<title>Limitations and future directions</title>
<p>While the findings of this study are promising, caution should be exercised in interpreting the results. The quasi-experimental one-group pre-posttest design, without a control group or random assignment, limits our ability to infer causality. Likewise, using residualized regression without random assignment could have biased estimates (<xref ref-type="bibr" rid="ref16">Farmus et al., 2019</xref>; <xref ref-type="bibr" rid="ref19">Jennings and Cribbie, 2016</xref>; <xref ref-type="bibr" rid="ref22">Kisbu-Sakarya et al., 2013</xref>). Future research should employ more rigorous methodologies, such as randomized controlled trials, and other quantitative analyses to better assess the impact of project-based science education interventions on student outcomes. Likewise, qualitative methods should be explored to understand the specific nuanced lived experiences of students in BioBuilderClub. Additionally, the survey used in this study was a newly developed measure, and only exploratory factor analysis was conducted. Future research should include confirmatory factor analyses to validate the three-factor structure identified and compare it with alternative models using a larger, more diverse sample.</p>
<p>Moreover, while the data were deidentified and sent to independent researchers, the survey development and data collection were conducted by the project-based science education intervention team, which could have influenced the way students responded. Independent investigators should be involved in survey development and data collection in future studies to mitigate potential biases. Additionally, the sample was predominantly White and Asian, with insufficient representation of non-binary students, international students from large cities, and students from systematically excluded racial/ethnic groups (e.g., Black, Hispanic, Native American). Future research should include a more diverse and representative sample to better understand how project-based science education interventions relate to different self-beliefs in scientific engagement, competency, and content knowledge.</p>
<p>The success of the project-based science education intervention has important implications for the future of STEM education. It demonstrates the effectiveness of hands-on, project-based learning in engaging students and enhancing their scientific skills and knowledge. As the demand for skilled workers in the bioeconomy continues to grow, programs like this are essential for preparing the next generation of scientists and engineers. The results of this study support the continued expansion and funding of project-based science education interventions and similar initiatives. Future research should focus on long-term outcomes for participants, including their career trajectories and contributions to the bioeconomy. Additionally, exploring ways to integrate such programs into the standard curriculum could further enhance their impact and reach. By investing in innovative education and training programs, the United States can strengthen its position in the global bioeconomy and ensure a skilled workforce ready to tackle future scientific challenges. Overall, project-based science education interventions represent a promising approach to modernizing biology education and workforce training, with significant potential benefits for students and the broader scientific community.</p>
</sec>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="sec22">
<title>Data availability statement</title>
<p>The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.</p>
</sec>
<sec sec-type="ethics-statement" id="sec23">
<title>Ethics statement</title>
<p>Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent for participation in this study was provided by the participants' legal guardians/next of kin.</p>
</sec>
<sec sec-type="author-contributions" id="sec24">
<title>Author contributions</title>
<p>PM: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing. LL: Data curation, Formal analysis, Methodology, Software, Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing. NK: Funding acquisition, Methodology, Project administration, Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing. CF: Data curation, Project administration, Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing.</p>
</sec>
<sec sec-type="funding-information" id="sec25">
<title>Funding</title>
<p>The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. BioMADE 2.0 Education Workforce Development grant provided funding for implementation and subsequent study; FAIN #FA8650-21-2-5028.</p>
</sec>
<sec sec-type="COI-statement" id="sec26">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="disclaimer" id="sec27">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
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