Abstract
This qualitative study was conducted to explore gifted students’ conceptions of their high school science, technology, engineering, and mathematics (STEM) education. Participants were seven male and female college freshmen selected from the Honors College of a large research university. In-depth interviews captured students’ retrospective accounts of their conceptualizations of their high school STEM education. Interview transcripts were analyzed inductively using a phenomenographic analysis framework. Findings comprised an outcome space composed of six core categories of meaning representing STEM learning environment, institutional supports, social supports, teacher qualities, active involvement in learning, and students’ self-perceptions of their STEM capability. Findings from this study offer a deep understanding of contemporary STEM education of gifted secondary students and help inform future curriculum design, program evaluation, and educational policy.
Research on science, technology, engineering, and mathematics (STEM) educational outcomes among gifted students is limited, and stakeholders in STEM talent development have yet to reach consensus on what constitutes ideal STEM programming for gifted students in schools. Substantial efforts have been made to create challenging STEM programs for gifted students: These include specialized residential and magnet schools, early college entrance or dual-enrollment programs, in-school programs such as Advanced Placement (AP) and International Baccalaureate (IB), summer enrichment programs, distance education, internship and mentoring programs, and extracurricular academic competitions (Olszewski-Kubilius, 2010). Effective strategies used within schools include differentiation strategies such as acceleration (Assouline, Colangelo, VanTassel-Baska, & Lupkowski-Shoplik, 2015), curriculum compacting (Stamps, 2004; Yang & Siegle, 2006), tiered instruction (Kettler & Curliss, 2003), self-directed instruction (Ysseldyke, Tardrew, Betts, Thill, & Hannigan, 2004), and integrated curricula (Ngoi & Vondracek, 2004). Although some programs or strategies have been widely adopted, some have serious limitations and fail to consistently develop the talents of gifted students. For instance, residential and early entrance programs are not viable for students who prefer to attend a 4-year high school to participate in arts, sports, or leadership activities (Tyler-Wood, Mortenson, Putney, & Cass, 2000). Furthermore, specialized and magnet schools may offer only limited enrollment or may be unavailable in some districts due to funding issues such as curricular development or provision of high-quality laboratories with modern equipment (Thomas & Williams, 2010). Mentoring programs depend upon the availability of mentors to collaborate with students, which is often limited (VanTassel-Baska & MacFarlane, 2008), whereas summer programs often involve tuition and travel expenses that exceed the means of some families.
Although STEM education standards outlined by the National Research Council (NRC, 1996, 2002) recommend an active, student-centered, inquiry-based approach to learning, STEM education in the prevailing high-stakes environment remains fixated on achievement (Ngoi & Vondracek, 2004). The only advanced secondary STEM programs of national scope are the AP and IB programs (NRC, 2002). AP and IB are college preparatory programs, but have evolved into convenient “one-size-fits-all” approaches for meeting needs of gifted students (Sriraman & Steinthorsdottir, 2008, p. 403). Unfortunately, AP and IB programs frequently fail to emphasize conceptual understanding, collaboration, or interdisciplinary contexts (NRC, 2002). Thus, gifted secondary students who choose to remain in public school may receive disproportionate opportunities in STEM relative to gifted students who participate in out-of-school programs, and such disproportionality signifies that opportunities to fully develop gifted students’ potential are being missed (Gallagher, 2015).
Purpose of the Study
This study’s purpose is to describe gifted students’ conceptions of their high school STEM education; findings from this study serve the larger goal of informing the gifted education community on how educators can best design advanced STEM instruction and programming appropriate to develop the talents of gifted high school math and science students.
The research approach for this study is phenomenography. Phenomenography is a method for mapping the qualitatively different ways in which people experience, conceptualize, perceive, and understand phenomena in the world around them (Marton, 1986). The following research questions guided the study:
Literature Review
To the authors’ knowledge, this is the first phenomenographic study focused on gifted students’ conceptions of advanced STEM education. Given the limited literature on the specific topic, we adopted an abductive approach and reviewed literature on academically gifted students’ experiences across a variety of advanced high school subjects. The literature revealed six factors that influenced students’ experiences in advanced high school academics: (a) teacher influence, (b) advanced curriculum, (c) learning environment, (d) ability grouping, (e) academic self-efficacy and self-esteem, and (f) guidance counseling.
Teacher Influence
According to the National Association for Gifted Children’s (NAGC, 2013) Teacher Preparation Standards in Gifted Education, teachers of gifted students must be able to (a) recognize gifted students’ learning and cultural differences, academic needs, and social-emotional needs; (b) design modified learning experiences that enhance creativity, acceleration, depth, and complexity in content matter; and (c) rely on evidence-based instructional strategies. The literature indicates that gifted students perceived advanced course teachers as a source of motivation and support (Vanderbrook, 2006) and described their best teachers as dedicated, hardworking, skilled, and knowledgeable (Hertberg-Davis & Callahan, 2008). Students recognized that teachers worked hard to make the class successful, and were more likely to apply extra effort when they observed the teacher putting forth extra effort (Siegle, Rubenstein, & Mitchell, 2014). According to students, excellent teachers possessed passion for both their subject and for teaching (Vanderbrook, 2006); these teachers demonstrated a level of enthusiasm for the content that students found contagious (Siegle et al., 2014). Students believed that outstanding teachers recognized their students’ intelligence and valued each student as an individual; correspondingly, outstanding teachers displayed characteristics similar to those their gifted students possessed or desired to possess (Siegle et al., 2014; Vanderbrook, 2006). Students regarded these teachers as highly intelligent and open to ideas that challenged their personal views (Vanderbrook, 2006).
Students favored teachers who were experts in their content areas (Siegle et al., 2014; Vanderbrook, 2006); knowledgeable teachers were flexible thinkers with both a deep understanding of their subject and a broader knowledge base that enabled them to make interdisciplinary connections (Siegle et al., 2014). Although students were generally satisfied with teachers of advanced courses, many students indicated that not all teachers were equally suited to teaching advanced content and recognized that teacher competence could affect the level of challenge in the course (Hertberg-Davis & Callahan, 2008). Teachers perceived as having weak content knowledge inhibited students’ motivation to excel (Siegle et al., 2014), and students of less competent teachers felt deprived of a qualified teacher able to meet their intellectual needs (Vanderbrook, 2006). According to gifted students, less competent teachers failed to accommodate differing rates of mastery, and students felt frustrated when these teachers demanded repetition of previously mastered content (Gallagher, Harradine, & Coleman, 1997). In comparison with other teachers, students perceived teachers of advanced courses as effective, enthusiastic teachers who treated students with more respect (Hertzog, 2003).
Gifted students attributed motivation and interest in their high school classes to positive relationships with teachers (Siegle et al., 2014). Students stressed the importance of personal connections with teachers and described their educational experiences as highly positive when such personal connections existed (Vanderbrook, 2006). Teachers who connected with students knew their students personally, helped them succeed, and demonstrated that they cared; these teachers connected with students through humor, attended students’ extracurricular events, and used actual students’ names in problem sets (Siegle et al., 2014). When a positive relationship existed, students felt respected, understood, and accepted by their teacher (Hertberg-Davis & Callahan, 2008), perceiving the relationship as an adult-like mentorship (Park, Caine, & Wimmer, 2014). Teachers who failed to connect with students impeded students’ engagement in class (Siegle et al., 2014), and over time, gifted students with distant or dismissive teachers eventually gave up and refused to participate (Vanderbrook, 2006).
Advanced Curriculum
Gifted programming in secondary schools is often provided through AP, IB, or dual-enrollment courses (Olszewski-Kubilius, 2010), and gifted students who earned advanced degrees in adulthood were nearly twice as likely as other gifted students to have taken AP courses in high school (Bleske-Rechek, Lubinski, & Benbow, 2004). Indeed, gifted high school students perceived their advanced courses as superior, and believed advanced coursework offered advantages over traditional curricula and prepared them for college (Hertberg-Davis & Callahan, 2008; Perrone, Wright, Ksiazak, Crane, & Vannatter, 2010). Advanced courses helped students improve study skills, develop a strong work ethic, refine time management and organization skills, and build self-esteem by accomplishing difficult tasks (Hertzog, 2003). Students also believed that advanced courses contributed to academic skills and competencies relevant to future career success, such as writing skills (Park et al., 2014; Siegle et al., 2014); awareness of these useful competencies sometimes motivated some gifted students to endure boring content (Siegle et al., 2014).
Challenging, meaningful content motivated gifted students to excel. Students described challenge as an essential aspect of advanced classes (Perrone et al., 2010); to challenge students, content had to be interesting and relevant (Siegle et al., 2014). Students perceived challenge in many forms, including difficulty mastering subject matter quickly or greater amounts of work (Vanderbrook, 2006), complexity, fast pace, or extreme depth and breadth of content (Siegle et al., 2014). Most gifted students found advanced courses challenging (Gallagher et al., 1997) and experienced genuine challenge for the first time in advanced courses (Hertberg-Davis & Callahan, 2008). Advanced science presented a particular challenge to some students due to a lack of prior instruction in the area (Vanderbrook, 2006). However, students rarely described challenge in terms of developing thinking skills or potential (Vanderbrook, 2006), and sometimes felt that the workload in advanced courses was too heavy (Hertberg-Davis & Callahan, 2008). Meaningful content motivated gifted students; when it was meaningful, students perceived learning tasks as valuable and worthwhile (Siegle et al., 2014). For some students, content was meaningful when it was personally significant; for others, meaning was situated in interdisciplinary connections that revealed how concepts were related within the bigger picture (Siegle et al., 2014).
Gifted students desired content delivery through a variety of methods. Some students enjoyed authentic learning experiences such as labs or field trips (Siegle et al., 2014), and others preferred classroom discussions and Socratic dialog; for those students, discussions motivated them to come to class prepared and were helpful after reading major literary works (Siegle et al., 2014). Students preferred active discussion to passive activities such as watching film renditions of literary works, because discussion allowed valuable time for analysis (Vanderbrook, 2006). In accordance with this trend of active learning found in other subjects, Gavin and Casa (2013) noted that to develop a deeper understanding of mathematics, gifted students needed to grapple with challenging problems, try different strategies, engage in dialog with peers and teachers, find new ways of solving problems, and explain their reasoning to others.
Learning Environment
The NAGC (2010) Pre-K–Grade 12 Gifted Programming Standards recommend learning environments for gifted students that recognize the impact of giftedness on social-emotional development and encourage independence, motivation, and self-efficacy for students of all backgrounds. The literature indicates that students preferred the atmosphere in their advanced classes and described the learning environment as more supportive than in other classes (Hertberg-Davis & Callahan, 2008), as well as more relaxed and less troubled by disruptive behaviors (Hertzog, 2003). Teachers of advanced classes conveyed high expectations and engaged students in higher level thinking through discussion, hands-on problem solving, and collaboration (Hertzog, 2003). For example, one group of gifted students of low socioeconomic status attending a STEM summer camp wished that their teachers at home believed in them more, focused less on test preparation, allowed technology for research and simulation, and relied less on textbooks (Dieker, Grillo, & Ramlakhan, 2012).
Ability Grouping
Ability grouping allows students to learn alongside peers who learn at similar rates, possess similar levels of knowledge, share similar goals, and challenge one another (Olszewski-Kubilius, 2013). The research, however, is somewhat contradictory—ability grouping can contribute to both positive and negative experiences. Many gifted students perceived homogeneous grouping in a positive light with respect to academic outcomes (Adams-Byers, Whitsell, & Moon, 2004); for instance, being grouped with intellectual peers motivated and encouraged students to work harder (Gallagher et al., 1997; Hertberg-Davis & Callahan, 2008). Students perceived intellectual peers as a source of academic support (Vanderbrook, 2006), and those students who felt bound by the gifted label in regular classrooms felt more comfortable speaking out in groups of similar-ability peers (Park et al., 2014). Ability grouping freed gifted students from the fear of being judged by lower ability students and helped them form close peer alliances (Vanderbrook, 2006). However, some aspects of ability grouping were perceived as less advantageous. For example, some gifted students had mixed feelings about whether homogeneous or heterogeneous settings best met their social needs (Adams-Byers et al., 2004). Moreover, segregation from peers could lead to feelings of isolation and social maladjustment (Perrone et al., 2010)—some students attached stigma to advanced classes, and that stigma deterred social acceptance by students who did not take part in advanced classes (Hertzog, 2003; Perrone et al., 2010). Students who took both advanced and on-level classes found the stigma more salient, and students who were ostracized or bullied in on-level classes believed that total segregation would resolve the problem (Hertzog, 2003).
Relationships with intellectual peers were an important aspect of gifted students’ advanced courses, and most students experienced positive interpersonal experiences in this environment (Perrone et al., 2010; Vanderbrook, 2006). Park et al. (2014) observed, “A cohesive cohort seems to be related to a homogeneous cohort” and noted that positive peer relationships were more likely in homogeneous groups (p. 135). Students felt emotional safety and belonging with intellectual peers; they described advanced courses as a special, shared experience apart from the world outside their advanced program (Vanderbrook, 2006). Within this close community, students collectively understood the pressures associated with advanced courses and drew support from one another (Vanderbrook, 2006). However, not all gifted students experienced positive peer relationships in ability groups. For example, gifted students from traditionally underserved populations felt isolated and lacked a sense of belonging in ability groups; for these students, sensitizing factors were different: Advanced courses represented an opportunity to disprove stereotypes, be the first in their family to graduate college, or escape a path others in their families had chosen (Hertberg-Davis & Callahan, 2008).
Academic Self-Esteem and Self-Efficacy
According to the literature, students associated advanced course experiences with personal growth; overcoming challenges and mastering difficult content helped students build self-esteem (Hertzog, 2003). Students acquired organizational and time management skills that helped them accomplish increasingly complex tasks, and the resultant success strengthened their self-esteem (Hertzog, 2003). Self-efficacy improved when they worked hard, achieved significant competencies, and experienced personal satisfaction—students saw outstanding accomplishments as the outcome of hard work, and thus put forth more effort. Advanced courses taught by knowledgeable teachers deepened students’ confidence in their capabilities by helping them master difficult content; students recognized and valued advanced courses that built up their self-efficacy (Siegle et al., 2014). Although self-confidence is not a primary focus of education in a standards-based climate, self-confidence had a substantial impact on students’ achievement in STEM (Dieker et al., 2012).
Guidance Counseling
Gifted individuals are assumed capable of making important career decisions for themselves (Greene, 2006), but despite their high intellectual capabilities, gifted secondary students experience unique obstacles and challenges in their career planning (Chen & Wong, 2013). Perfectionism, for example, can delay career decisions or lead to less optimal choices focused on avoiding failure (Greene, 2006). Multipotentiality also brings challenges; gifted students tend to narrow their career options to those with high prestige, and may not realize their potential to excel in other fields (Kher-Durlabhji, Lacina-Gifford, Carter, & Lalande, 1997). Researchers in gifted education have long advised incorporating counseling in gifted education programs (Moon & Hall, 1998). For one group of gifted high school students, experiences with counseling and guidance were much less positive compared with their social and academic experiences. For these AP and IB students, contact and quality of time spent with guidance counselors were both very low, and students discussed with counselors neither their future career ideas nor the impact of their current courses on their career plans. Interactions with counselors were limited to discussing college applications and excluded discussion of current coursework or future career plans (Vanderbrook, 2006).
Method
Phenomenography is a research approach for “mapping the qualitatively different ways in which people experience, conceptualize, perceive, and understand various aspects of, and phenomena in, the world around them” (Marton, 1986, p. 143). The goal of phenomenography is to identify a structural framework, or outcome space that describes various categories of understanding; that goal is accomplished by categorizing the descriptions provided by the participants. The outcome space is a structured, multidimensional set of descriptions, in which each dimension is cross-referenced to the original accounts from which it stems (Alsop & Tompsett, 2006).
Phenomenography is descriptive, strictly empirical, and nonconstructivist (Svensson, 1997); it is, however, distinct from traditional science in its absence of any intention to describe an objective world independent of the participants. Instead, phenomenography is used to examine relationships between participants and the objective world, and aims to describe the taken-for-granted ways in which participants understand particular phenomena in their world (Marton, 1986). Sampling in phenomenography is purposeful and aims to capture diversity, rather than to produce a statistically balanced representation (Alsop & Tompsett, 2006). Semistructured interviews are the main data source in phenomenographic research, and phenomenographers use open-ended questions to allow participants to address their choice of dimensions of each research question (Marton, 1986). Unlike other qualitative analytical approaches, phenomenography regards the analysis of participants’ accounts as a distinct stage that is unaffected by the data collection process (Alsop & Tompsett, 2006).
A criticism of phenomenography concerns the investigator’s ability to set aside preconceived notions of the phenomenon and maintain a second-order perspective (Ashworth & Lucas, 2000). Bracketing is a methodical strategy that allows the investigator to set aside his or her presumptions as far as possible, to register the participant’s perspective. Presuppositions that must be bracketed in phenomenographic research relate to prior research findings, existing theories, the investigator’s knowledge and beliefs, assumptions inherent in research techniques, and the investigator’s compulsion to explain rather than describe participants’ experiences (Ashworth & Lucas, 2000). In phenomenography, bracketing can be accomplished by allowing participants maximum freedom in describing their experiences (e.g., using open-ended interview questions). Aside from bracketing, trustworthiness of phenomenographic findings depends on avoiding premature closure of the analysis, for instance, by engaging in constant comparative analysis that proceeds to the point of saturation (Glaser & Strauss, 1967). Furthermore, describing the analytical process in detail enables the investigator to reflect on trustworthiness, and also allows readers to assess the investigator’s attempt to achieve bracketing.
Participants
Participants were recruited from the Honors College of a large southwestern research university. Honors enrollment served as a proxy for giftedness; enrollment required a combined score of at least 1200 on the SAT math and verbal sections, a grade point average (GPA) of at least 3.75 on a 4.00 scale, and high school rank in the upper 20%. Students were recruited through email announcements and flyers posted in the Honors dormitory. Interested students completed a survey to verify classification, Honors enrollment, graduation from a U.S. high school, and participation in secondary advanced STEM courses. The survey also solicited demographic information (age, sex, and ethnicity) and information on secondary STEM coursework.
In phenomenography, the selection of participants is guided by an interest in collecting participants’ conceptions of the phenomenon of study, and with describing variation in those conceptions. Generally, the number of participants has been 15 to 30 people, but there are examples of both smaller and larger numbers (Limburg, 2008). The depth sought in the current study warrants a smaller number of participants to allow time for a thorough analysis; thus, we limited our sample to seven participants who were all enrolled in the Honors College. Five participants were female and two were male college freshmen. Participants were selected to encompass as wide a range of demographic variation as possible while still meeting the selection criteria. Freshmen students were given priority to make detailed recall of experiences more likely. Study participants are described in Table 1.
Participants.
Note. AP = Advanced Placement; F = female; M = male. AP Calculus AB is equivalent to one semester of college calculus; AP Calculus BC is a full year course that includes all AB content and additional topics.
Data Sources
Two investigators collected retrospective data from in-depth interviews focused on a bracketed topic and questions; one investigator conducted the interview while the other took notes and facilitated. Interview questions (see the appendix) were broad and limited in number to elicit depth rather than superficial answers. Each participant was interviewed once in an audio-recorded session lasting 1 hour, and the recordings were transcribed verbatim by a professional transcription service. Each participant received a small gift (school supplies and gift card) after completing the interview. In addition to interviews, demographic data were collected from an online survey, and the investigators kept memos documenting their reflections during the data collection stage.
Analytical Framework
Marton (1986) pointed out, “we cannot specify exact techniques for phenomenographic research” (p. 153); thus, specific methods are left to the discretion of the phenomenographer. In this study, we formulated a five-stage analytical framework (see Table 2) based on a set of general guidelines proposed by Marton (1986). Our analytical approach is empirical and inductive, driven by the data, and free of a priori assumptions.
Phenomenographic Analysis Framework.
Trustworthiness
In addition to documenting procedural rigor throughout the project, participants were debriefed to verify accurate synthesis of their experiences. Further credibility was established through a process of reflection, exploration, and bracketing to ensure that the analysis brought the participants’ perspectives to the forefront. Thick description of the results provided readers with a basis for making judgments about transferability, and confirmability was demonstrated by linking data to their original sources. To protect the privacy and rights of participants, we implemented procedural safeguards that conform to the Department of Health and Human Services requirements for the protection of human participants (Public Welfare, 2009).
Analysis
The first stage of analysis involved multiple close readings of transcripts and reviews of audio recordings; at this stage, the investigators noted initial reflections on content and meanings in the margins of the transcripts. In the second stage, the investigators again read each transcript line by line and highlighted relevant segments, where a segment constituted the smallest possible unit of meaning, usually one or two sentences. In this stage, 417 segments were documented in a data pool and cross-referenced by transcript and line number. In the third stage, the segments were categorized based on similarities; here, the investigators abandoned boundaries between individual participants and, instead, focused on collective meanings across the data. Each segment was assigned to a preliminary category based on the meaning contained in the segment. For example, the quotation “Certain students were more responsive in class, those who were smarter or cared more” was assigned to a category named “student responsiveness.” When a segment fit an existing category, the segment was assigned to that category; otherwise, a new category was created. Twenty-nine preliminary categories and their assigned segments were documented in a data pool; Table 3 summarizes the 29 preliminary categories. In the fourth stage, the categories were reduced by rearranging segments and collapsing, dividing, or eliminating categories. First, segments within each category were reexamined and either retained or moved to a different category. Next, similar categories were collapsed, and categories with multiple meanings were divided, such that the resulting set of categories represented unique core meanings. The result of the fourth stage was a set of six core categories. In the fifth and final stage, the six core categories and their assigned segments were reexamined and refined in a constant comparative process. First, meanings were articulated for each core category, and then, segments were sorted into subcategories within each category. Second, segments were resorted for better alignment with the categories and subcategories. Analysis was terminated once the system of meanings had stabilized.
Preliminary Categories.
Note. STEM = science, technology, engineering, and mathematics.
Results
The analysis brought forth evidence supporting an outcome space comprised of six major categories of meaning describing these gifted students’ conceptions of their advanced secondary STEM education. All categories were derived empirically from the data. Figure 1 illustrates the outcome space, or final set of core categories and subcategories, and the overall frequencies by which the categories were described by the participants. Table 4 lists and describes the core categories and subcategories and their descriptions, supported by examples from the data with example segments from the data. The results are expanded here in the form of a thick description of the outcome space.

Outcome space with distribution of the number of descriptions by category.
Core Categories.
Note. STEM = science, technology, engineering, and mathematics.
Category I: Learning Environment
The students’ conceptions of the quality and value of their STEM education depended on the learning environment, particularly affective aspects, intellectual challenge, epistemological underpinnings, and academic freedom. Students’ descriptions of STEM learning environments appeared 81 times in the analysis—more frequently than any other category.
Affective aspects of the learning environment
Climates of intellectual safety motivated students and created a sense of belonging. For instance, Caleb (all names used are pseudonyms) perceived the community in his academy as close-knit; he “knew everyone there.” Iris described the learning environment in her AP courses as intellectually safe; for example, in Iris’s AP Calculus class, she and her classmates “always felt comfortable asking questions.” Iris’s AP Biology teacher “definitely made it easier for us to not think of it as something big and scary, but as ‘it’s just science.’” Learning environments also could be threatening, though, and cause feelings of insecurity or frustration. For instance, Olivia had a chemistry teacher who “hated kids,” and when talking to students, he “wouldn’t be supportive.” She described her chemistry class as “naturally cold,” a place hard to weather without the support of good friends—her teacher was “not one of those teachers that says there are no dumb questions,” but rather, seemed to see every question as dumb. Olivia remembered, “If you ask him a question, he was like, ‘you should know this. My 11-year-old daughter can do this.’” Olivia’s chemistry experience had a strong impact on her academic trajectory; she explained, “That’s why I didn’t go into AP Chemistry.”
Social underpinnings of the STEM learning environment also affected students’ experiences. Asynchrony was an issue for Quinn, who “just wasn’t comfortable being a ninth grader in classes with 11th and 12th graders. Academic-wise, it gave us opportunities but didn’t allow us to really be in a comfortable environment.” Students also felt frustrated in environments where classroom management was weak. For example, Olivia’s anatomy teacher “didn’t have such a firm hold. There was so much talking in that class and there was so much of people not really caring that you didn’t really get anything done,” whereas Benjamin’s biology teacher often arrived 15 minutes late, leaving empty time spent socializing when learning could have taken place. The stigma of giftedness was a factor for gifted students in mixed-ability groups. For instance, Quinn refrained from speaking out in class; she “felt like if I said something, I would make people feel like I was a know-it-all.”
Intellectual challenge
Intellectual challenge was the most frequently described aspect of the learning environment (41 instances; see Figure 1). These students expressed a strong desire for intellectual challenge, and perceived the value of their education in terms of the challenge it offered. Challenge sometimes took the form of fast pacing; Benjamin enjoyed AP Calculus because it was challenging, yet also felt rushed by the pace. In a similar manner, Olivia felt rushed in statistics: “We went pretty quickly on stats.” Challenge also took the form of heavy workloads: Willow had the unpleasant experience of gifted classes where students were expected to “be challenged by having to manage time and not kill ourselves.” In other instances, gifted students hit intellectual ceilings; in one such instance, Quinn noted the absence of social learning: “Nobody can check on anybody because we’re all at the same level learning from the same person. Our knowledge only goes up to as much as she taught us.” However, intellectual challenge was often lacking; for instance, in Ariana’s physics class: “the concepts came really easy to me.” Benjamin’s experience in AP Chemistry “seemed sort of slow”: he recalled “a lot of days just roasting marshmallows on the Bunsen burners.” He reflected, “They would try to, I want to say, dumb it down, but not exactly; just try to make it more accessible to more students.” Willow, who had a very strong Algebra 1 background, got to Algebra 2 and found, “a lot of it was extending the techniques we had already learned. I saw almost all of that course as review and elaboration.” Course offerings represented another ceiling for accelerated students; for instance, AP Calculus and AP Statistics were the highest offerings available for students who wanted to expand their knowledge of mathematics.
Students’ perceptions of the value of their STEM education varied. Many students felt that their STEM education prepared them well for college; for instance, Ariana was “able to go straight into microbiology, organic chemistry, and physics” in college, and Benjamin’s advanced STEM courses “helped develop study skills” that he needed in college. Some students, however, felt less prepared; for example, Olivia’s experiences in statistics left her feeling shaky in college psychology courses: “I didn’t realize there was so much math and science in [Psychology]. I wish I was more introduced to that.” Iris, likewise, felt she “definitely could have learned more,” but felt that overall, her STEM experience in high school prepared her well for college.
Willow described her school’s AP program as “so incredible”; she took 12 AP exams and began college with 73 hours of credit. She described coming to college and “being told that I could take a graduate biochemistry class when I was a 20-year-old junior.” Institutional support in the form of grants and incentives contributed to Willow’s positive experiences in AP STEM courses—Willow’s district had “fantastic district-wide voluntary review days” where students were encouraged to attend with “extra credit and pizza—almost everybody went.” In addition, Willow’s school “won a grant from a tech company. They offered $100 cash prize per exam to students who passed math and science AP exams. They offered the same prize to teachers.” Cash was a compelling incentive: “We had teachers earning sometimes $5,000 for teaching AP classes” and students felt “encouraged to actually study for our AP exams.” The coordinated efforts at Willow’s district gave students “a date that we could count down to” and galvanized students to develop the time and material management skills they needed to prepare for comprehensive exams. The quality and format of AP preparation at Benjamin’s school was less effective; he “had study sessions pretty much for every AP class,” but unlike Willow’s coordinated district effort, Benjamin’s sessions were sponsored by individual teachers and held outside school at locations or times incompatible with his schedule. Benjamin also felt that the pacing of his combined AP Calculus AB/BC class was excessive: “The one I took combined the AB and BC curricula. Some schools split it up, which I think is good because it gives you time to learn. It felt pretty rushed.” However, Ariana felt comfortable with the pace of her accelerated dual-enrollment program, where she “found which science I wanted to go into more.”
Epistemological orientation
Students’ conceptions of their STEM education were marked by an essentialist orientation. For instance, students perceived memorization as an obstacle to higher learning and resented having to memorize material; Olivia recalled, “It was more memorization with chemistry. Disappointingly, we didn’t do any chemical stuff. It was really annoying.” Olivia explained, “You know everything separately. You don’t know how to connect the dots together and use it in critical thinking.” Along with the objections to memorization and academic compartmentalization, students also felt that the essentialist orientation inhibited creativity; Iris thought,
Because science is about life, you’d think it’d be more fun, but people tend to shy away from science and math. In English classes it was all discussion-based. Math and science were very “this is how you do things.” That doesn’t really foster creativity.
Benjamin felt uncomfortable with the fast pacing because he felt that it placed achievement of AP credits over and above personal growth and reflection; for instance, in AP Biology where the pace was more relaxed, he “felt like I grew in that stage of my life, in that class particularly.” Students felt frustrated by essentialism and recognized the advantages of constructivist approaches, such as situated learning. For example, Olivia worried that without real-life learning situations, she “wouldn’t be able to go into a situation where you’re using chemistry to actually do something, because you’re not sure about how things would work in real life.”
Academic freedom
Gifted students were sensitive to academic autonomy in STEM. Iris described her AP Biology class as an “open and free” place where she and her classmates “had a bit more freedom to take our own education into our hands.” Benjamin enjoyed autonomy in his AP Biology class: “I liked my biology teacher because she left the students a lot of freedom, like it was basically up to us to do things. That’s fine for me because I learn best, you know, on my own.” Willow experienced a high degree of autonomy in a chemistry course, where she self-selected a topic and designed a project with minimal direction:
We had to find something that we liked and actually troubleshoot the way to do it effectively in the lab . . . she offered a few ideas, but I think a lot of us were more excited to find other ones.
Category II: Institutional Supports
Students’ conceptions of their STEM education were colored by their school’s institutional supports such as institutional organization, support for diversity, and resources available to gifted students. This category appeared in 39 data segments, and, thus, represents a prominent category in the data corpus.
Organizational obstacles
Material resources confined students’ experiences in high-level STEM courses. Olivia’s school “put a massive amount of money to football and all of the math and science courses and art classes were like, ‘Ah, whatever.’” Olivia recalled that in her STEM classes, she had “rip-off textbooks” and “all these models around the classroom of the Oxygen element and Glucose but he doesn’t bring them down and say like, ‘Hey, this is it.’” Students were also limited by time constraints imposed by school activities and heavy academic workloads. Willow “was supposed to independent study math, but I actually just focused on succeeding in my other classes.” Similarly, Benjamin “was so busy with other things. Music was taking up most of my time, and just AP, you know, trying to get those credits takes a lot of time.” He also felt limited by a lack of STEM research opportunities: “It would be cool if there were some more research opportunity type deals. You know, they’re constantly pushing research here in college.” Teachers who taught “to the middle” posed an obstacle for Quinn:
It was just really counterproductive because we just kind of go along. Somebody would find something and then, they’d maybe think of the right answer. It might be wrong or it might be right . . . Nobody can check on anybody because we’re all at the same [level].
Other students described unreasonably high expectations. For instance, although Caleb attended a selective science academy, one of his teachers restricted participation in academic competitions to only the highest achievers. Caleb explained, “If you’re not good, you can’t be in computer science. Yeah. You can’t go to competitions.” At times, teachers’ personal or health issues inhibited students’ experiences; for instance, Caleb’s physics teacher “didn’t know what he was teaching most of the time. He had a lot of medical problems. He was out of it so much.” Caleb also described an administrative vacuum left after the death of an influential teacher: “There wasn’t really anyone taking charge over the internships and stuff as much anymore.”
Diversity
Students’ experiences with diversity were sometimes uncomfortable. For instance, Ariana described a STEM teacher’s racism: “She was an advisor for one of the clubs I was doing. Myself [sic] and my friends realized she was racist. It was pretty hard because we were a very diverse school.” Ariana, the only White student on the club’s executive board, explained, “She would only talk to me and not everyone collectively.” After the experience, Ariana’s relationship with the teacher changed: “It was a negative association. I didn’t enjoy being around her as much.” Quinn described an intersection of racism and elitism that she found difficult to tease apart. Quinn’s math teacher struggled to maintain her authority in a mixed-ability class, where the majority of students were Black. Quinn (also a Black student) believed that students’ conduct, rather than their race, drove the teacher’s behavior. Quinn explained, “I was a shy kind of person. A lot of the Black people, they were more out there. They were ready to be against that authority if they didn’t agree.” Quinn’s teacher attempted to maintain control by targeting less resistant students such as Quinn:
She would treat them differently than she would me and some of the White people in our class. If I’d come to school wearing jeans, she’d write me up, but if one of the other Black people in my class came wearing the same thing, she would just kind of sit there.
Quinn’s enthusiasm for math changed after this experience: “She’s kind of the one who made me stop liking math.” However, students described positive experiences related to sex or gender. For example, Willow “had some great experiences as a woman in a male-dominated field. Many of the classes, especially biology, girls outnumbered boys.” Furthermore, Willow and her peers “had a lot of really great female role models in our teachers.”
Academic and career counseling experiences
Educators provided minimal academic and career counseling. For instance, Iris visited the counselor “only to do my schedule or something like that, where we were required to go.” Students compensated for the lack of career counseling. Benjamin, for instance, found his career path without the help of a counselor:
I just sort of realized that I wanted to do something with the environment, by reading on my own. I sort of liked math. I don’t know, I just thought, like environmental engineering. I just sort of figured that out.
Willow, who started college pursuing medicine and then switched to education, recalled, “There was a career counselor. I don’t remember seeing him. Most of our career guidance took place through the classroom teachers. The counselors were most helpful with more academic registrar duties.” Overall, the students described counseling experiences that failed to meet their needs, and left them on their own to find other means by which to crystallize a career path.
Category III: Social Supports
Students’ conceptions were influenced by social factors including ability grouping, peer support and friendship, and teacher support. Although this category appeared less frequently than others, it represents a meaningful presence with 25 instances.
Ability grouping
Grouping gifted students with intellectual peers motivated them academically and created a sense of support and belonging. Olivia found that a supportive environment helped her learn:
It was really nice because if you had a problem, someone would be up there to help you. I don’t know if that’s a way we can install an education system, “Hey, make sure everyone gets along,” but it really helps you learn.
In parallel with Olivia’s experiences, Ariana’s dual-enrollment program
helped me, along with the other honors people from my high school. By having that support system there, it helped everyone to push each other . . . I would not have enjoyed the courses as much if I were surrounded by people who weren’t as motivated with STEM.
Ability grouping created a climate of friendly competition that elevated goals and performance standards. For Ariana, being grouped with intellectual peers “helped me because it pushed me to compete with others—not aggressively, but it’s good motivation to keep each other up.” Intellectual peers provided scaffolding for one another; for instance, Ariana found it “helpful when you knew other people who were maybe a little bit more ahead or behind you, that way either they could help you or you them.” However, ability grouping had detrimental consequences for accelerated students making the transition from middle to high school. For instance, Willow described the transition as “very stressful. I still caught some teasing for being 13 years old in the high school building. I got nicknamed, including by the teacher.” Willow’s situation improved later that year after she “learned to become more comfortable [being with older students] and had quite a bit of fun.”
Teacher support
Caring teachers made a deep impression on gifted students; these teachers’ everyday interactions with their students made students feel esteemed. Caleb spoke of a teacher who “talked to students more like friends.” Olivia had a similar positive experience, with her favorite teacher being
one of those teachers you know he cares. He always cared for the stupidest reasons. Someone would be, “Oh yeah, I went to Forever 21.” He’s like, “Oh my God, really?!” Until this day I’ll go back, and he’ll know my name.
Students were aware when teachers were honestly invested; for instance, Olivia noted that her teacher “liked being there with you.” Although these caring teachers had a deeply positive impact on their gifted students, teachers who were less committed had the opposite effect. For instance, Ariana had a physics teacher who failed to understand gifted students’ needs:
I was finishing my work ahead of time, and then I was talking with my friend because she had also finished. By the end of the semester our teacher had decided to separate us and I felt like that was a problem. We were a good paired group.
Benjamin described a teacher who held a philosophical position on environmental protection that contradicted his own views: “I didn’t really like his environmental science views; I don’t support building dams, and he thought that was a good idea.” Nonetheless, Benjamin described the teacher as “a receptive guy” who projected a sense of mutual respect and support for differing viewpoints: “He encouraged debate.”
Friendship and peer support
These gifted students described close friendships with other students from their advanced STEM programs. Caleb developed lasting friendships at his academy, which he described as “a close-knit kind of foundation.” Quinn described close friendships with AP classmates: “We always hung out most of the time. I always saw them outside of class.” Sharing common goals and taking classes together helped students form close friendships; for example, Ariana recalled,
the ones I had become good friends with were also at the top of the class . . . we were pursuing STEM majors and so we were all taking similar classes, having classes together, and working on the same homework.
Category IV: Teacher Qualities
Students’ conceptions of their STEM education were more positive when their teachers were highly skilled, held high expectations, and showed personal interest in students. Teacher qualities appeared 75 times in our analysis (see Figure 1), thus representing one of the most prominent categories of meaning.
Interactional style
Students preferred teachers with a relaxed interactional style; for instance, one of Olivia’s teachers “was always joking around. It really helped,” and one of Benjamin’s teachers “was very geeky, always making jokes,” yet still kept up the pace. Authoritative teachers also contributed to positive experiences; Olivia remembered,
No matter how off subject we’d get, he’d always turn it back around to math. He was really down on the rules. He was literally like, “Guys, you have to listen. Get off your phones.” That was really good. Everyone concentrated.
The students described their best teachers as inclusive; for example, although Willow’s teacher “did call on specific people a fair amount,” she also “offered different types of opportunities for people to get involved. She might call on somebody to read their answer and make it less intimidating for quieter students.”
Students spoke of negative experiences with socially awkward, passive, or pernicious STEM teachers. For instance, although Iris’s teacher “was very intelligent,” he “didn’t recognize when people weren’t understanding. He wouldn’t leave room for people to ask questions. He would make them feel like they were stupid.” Iris emphasized her teacher’s failed attempts at humor: “Sometimes he thought he was joking or being funny. I think it was just him misunderstanding.” Quinn highlighted her teacher’s passivity: “She didn’t really work hard because she would just sit at the desk. Teachers are supposed to check up on the group, see if you’re doing it right.”
Teacher competence
Students described feeling inspired by expert teachers who were passionate about their subjects. Ariana explained, “If the teachers didn’t absolutely love what they were teaching, then it kind of bored me because it bored them.” Iris described her biology and chemistry teachers as “very knowledgeable over what they were teaching. They loved what they were teaching, and it inspired me to love it, too.” Iris particularly respected her biology teacher, who had worked in the field as a marine biologist for many years. Iris believed that her teacher’s knowledge of her subject reflected that real-world experience: “She definitely had a very good understanding.” Willow sensed that her chemistry teacher’s enthusiasm helped students “keep up with all of the material.” The students’ experiences with expert teachers, however, were not always positive. For example, Ariana’s physics teacher knew her subject at such a high level that “she wasn’t able to then relate it back to us, for us to understand.”
Some students described experiences with teachers who lacked skill or knowledge, especially in physical sciences and math. For instance, Quinn recounted visiting her math teacher before school for extra tutoring on a difficult assignment: “She couldn’t figure it out. I’m like, ‘You’re the teacher.’ She invited another teacher to help us figure it out. She had the key, but she didn’t know how to work it out.” Quinn described a sense of futility: “I felt like there was no reason for me to go to tutoring. She wasn’t going to help me.” Caleb, who struggled in computer science, felt shortchanged by his teacher, who also lacked competence. Caleb believed the teacher failed to provide the strong foundation in computer science that he needed to pass the AP exam: “I didn’t do well on that AP test, though, because I didn’t have that good foundation. He definitely, I think, should have taken more time with the students in computer science.” Willow recalled, “For AP Physics students, year after year, there were just never good teachers. Actually, we had one great physics teacher, but they assigned him to the remedial students.” Willow described her physics teacher’s inexperience: The teacher “seemed to be relearning the material with us.”
Teachers’ awareness of students’ needs
The students recounted positive experiences with STEM teachers who were attentive to their needs. For instance, Iris found it easier to grasp concepts more easily with teachers who “tended to be more involved and invested in their students’ lives.” Iris described her AP calculus teacher as an example: “She was really good at building relationships with students. She would always take time at the beginning of class to talk to everyone.” Beyond personal attention, Iris’s teacher anticipated students’ intellectual needs: “She already knew what would confuse us, and so we didn’t really have to ask for the extra examples.” Likewise, Caleb’s statistics teacher went the extra mile to help struggling students: “He helps you get better grades. He’ll go through everything and stay after school with you.” Students also perceived the positive influence of teachers’ organizational supports; for instance, Caleb’s biology teacher’s organizational support enabled his participation in extracurricular academics. Caleb explained that his teacher’s support ensure that “you got your stuff done on time and your forms turned in.”
Teacher expectations
Gifted students described negative experiences related to teachers’ low expectations. Quinn remarked,
I didn’t like a lot of my teachers because I felt like they expected little from me. I was used to being treated like an Honors child and I wasn’t at that school. That’s what I really didn’t like from my teachers.
Quinn elaborated on one particular teacher: “She’d be like, ‘Oh, Quinn, I didn’t know you could do this.’ That got to me sometimes.” However, students describe feeling empowered by high expectations. For instance, Olivia “had one teacher that was really adamant” about students mastering material; that teacher “would actually try harder than most teachers instead of just assuming, okay, you’re going to get this no matter what.” Willow appreciated her chemistry teacher, who “was keeping us from treating the subject like a spectator sport. We weren’t allowed to just sit and watch her work out problems.” Olivia described a comparable experience with her statistics teacher: “She really tried to make us work through” difficult concepts. Similarly, Iris’s calculus teacher “would explain everything clearly and step-by-step, with a lot of examples.”
Category V: Active Involvement in Learning STEM
Students’ conceptions of their STEM education clustered around the nature of their STEM learning experiences, particularly their involvement in authentic, active, or collaborative learning. Appearing 46 times, this category represented one of the most frequent categories (see Figure 1).
Authentic learning
Willow described strong, positive feelings about her authentic STEM learning experiences. One of Willow’s authentic experiences was in chemistry, where students were required to “find and execute some fun chemistry demonstration for a class of fifth graders.” Willow and her classmates were free to design and present the demonstration as they wished, but had to accurately explain the theory behind it. Willow also gained practical experience in her health science course. She recalled, “There was a sports medicine module where students actually went on field trips to athletic trainers to learn how to wrap injured or weakened joints,” and she also made weekly observations at a hospital and “loved it.” Ariana’s independent study class required students to find a mentor in their field of interest. Ariana explained,
I found an internship with a local police department. I was able to study the forensics behind one of the cases this lady had recently closed. I wrote a paper over what was done, what tests were done, the science behind the tests, which was really interesting.
Furthermore, Ariana’s dual enrollment gave her access to college lab facilities: “We got to do labs on Fridays in the college labs. Having those real lab experiences really helped.” Willow’s and Ariana’s authentic experiences were exceptional—other students’ authentic learning experiences came in the form of simulations and presentations. For example, Benjamin “had to, like, build the whole DNA reproduction process with clay and animate it,” and Iris “did this presentation over I think it was DNA replication.”
Students perceived a void of interdisciplinary learning experiences, and believed the lack of such experiences subtracted from their STEM education. Willow explained, “We had biology teachers who didn’t know very much chemistry. We would either bring in the chemistry teacher or sometimes AP Chemistry veteran students to serve as consultants.” Olivia recognized gaps in the STEM curriculum that obscured concepts common to both math and science. She explained using an exponential decay function as an analogy:
You know that curve, and how we’ll never reach zero? I’m always there like, “Why would it never reach zero?” At least put more depth to it so I can see, you know? I think it’s more of the sciences.
Willow believed that biology and chemistry should have been combined in a single block class and pointed out, “there are so many things, both topics, and math and cognitive skills that carry back and forth.”
Collaborative learning
Many of the students described negative experiences with collaborative learning. For instance, Iris believed it was “definitely a challenge time-wise and logistically.” Quinn explained, “It’s like nobody in the group knew what to do. We didn’t have roles like ‘This is a leader.’ Oh, no. We didn’t do that at all.” Benjamin believed that group work imposed an unnecessary additional cognitive load:
It would take us a long time to get started and try to figure out what we were supposed to be doing, like a combination of focusing and figuring out what we were supposed to be doing at the same time.
Only one student, Iris, described positive collaborative learning experiences; Iris explained that group work
definitely challenges me more, because I’m really good at working on my own. In group projects it helps because if there’s a conflict about whether something is correct or not, you have to explain it more and research it more, and working together you get a lot of different points of view.
Iris believed she would have benefitted from more collaborative learning experiences: “It would have been cool to do group projects and stuff in math, because you would really have to think about the concepts and understand them more fully.”
Active learning
Students described many positive experiences involving active learning. For instance, Ariana’s algebra teacher presented realistic problems with consequences attached. Ariana explained, “If you have wrong answers, then some someone would be building a bridge, it’d be 2 inches off, and then the whole bridge crumbles.” Olivia’s anatomy class, which she described as the best class she had, was extremely active: “We dissected a cat; we did all the hands-on stuff, connected fake neurons.” Students recognized when they would have benefitted from more active learning experiences. Ariana felt that more hands-on lab work in her science classes would have helped her learn more effectively. Olivia also believed that her science learning experience should have been more active. For example, she found balancing chemical equations on paper difficult to conceptualize, and needed a more hands-on, concrete learning experience: “If we would have seen it, not just memorized the numbers, more like seeing it and bringing in more models.” Similarly, Caleb thought his chemistry teacher “didn’t do projects and experiments as much as we should.” However, despite the majority of students’ strong positive perceptions of active learning, one student believed that she benefitted from traditional drill and practice in math; Quinn believed that a reason for her positive experiences in precalculus was that her teacher “gave us a lot of worksheets.” Quinn explained that worksheets required many repetitions of complex problem-solving strategies; working through those strategies repeatedly helped her retain and apply the strategies.
Conceptual learning supports were a part of students’ positive experiences. For example, Willow recalled,
one of the first times in my education when I felt that my gifted classes were giving me a cognitive challenge. The teacher showed us a unit circle and taunted us saying, “This is what you have to memorize when you take pre-cal. You have to understand it.”
What worked for Willow were important formulas and concepts briefly described, printed large, and with “sometimes funny names for them like ‘the big mamma equation.’” Organizational strategies were also helpful; for example, Quinn’s chemistry teacher had students “do index cards. She would be like, ‘Go check your index cards this day.’ She made sure that we were accountable at home—she checked up on us.”
Category VI: Self-Perceptions of STEM Capability
Persistence, resilience, and high STEM efficacy were all present in students’ positive STEM experiences. Olivia described her persistence: “I really struggled in math. I was like ‘Oh my gosh, I hate it.’ I will do well, because one of my things—I always do well, even though I never comprehend the material well.” Olivia described how her persistence helped build her STEM self-efficacy: “Something happened and I was like, ‘I got this. I’m no longer crying in class.’” Quinn’s persistence and belief in her math capability helped her compensate for a weak teacher: “I had to figure out a lot more. I just had to do more work on my own and learn on my own time.” Some students developed STEM self-efficacy at home. For instance, Ariana believed that her parents, who were both engineers, contributed to her interest in and capacity for STEM: “I’ve always been more inclined on the math and science side just because of having them around. I was in that environment so long that it just became my natural environment.”
Discussion
Our first objective was to describe gifted students’ conceptions of their secondary STEM education. The analysis revealed six broad categories encompassing learning environment, institutional supports, social supports, teacher qualities, active involvement in learning, and students’ self-perceptions of their STEM capability.
Learning environment represented the most prominent category of meaning. The students described their perceptions of their STEM learning environments in terms of intellectual safety, intellectual challenge, and epistemological orientation. Although the majority of students described advanced STEM learning environments that encouraged and supported their STEM talent, there were exceptions. One catastrophic exception involved a cold, unsupportive learning climate and resulted in a gifted student opting out of advanced science courses. Another concerned a student in a mixed-ability environment; the student felt compelled to hide her ability by withholding her responses in classroom discussions. The students all desired intellectual challenge, but described challenge in terms of heavy workloads and fast pacing, rather than in terms of complexity and critical thinking. This preference for complex thinking echoes previous studies that have indicated that gifted students prefer open-ended science learning environments involving inquiry and critical and creative thinking opportunities (Lang, Wong, & Fraser, 2005). Students perceived a complete lack of challenge in some classes, and described those classes as simple or repetitive. Furthermore, unless students were dually enrolled, they were limited by course offerings available in mathematics. Mathematics acceleration is essential for developing mathematics talent; however, so also is opportunity (Rambo-Hernandez, 2016). Gifted and talented mathematics curriculum ought to involve innovative options for students to combine acceleration with rich problem solving that creates a personal journey into the world of mathematics (Mann, 2006). Future research might look at ways the schools are successfully leveraging technology and developing personalized mathematics experiences beyond calculus to develop talent among advanced students.
Teacher qualities signified another substantial theme in our findings. Students felt engaged and motivated by teachers who showed personal interest in their lives, were attentive to their needs, and held them to high standards. These teachers were highly competent, passionate about teaching, experts in their subjects, and modeled dedication through hard work. According to Croft (2003), gifted students may be more affected by teachers’ behaviors and attitudes; subsequently, highly capable teachers are a crucial part of an effective STEM program for gifted students.
Direct, active learning was a recurring metaphor in students’ positive experiences. Contrary to the NRC (1996, 2002) recommendations for active, inquiry-based learning experiences, these students experienced few truly authentic learning experiences or opportunities to engage in meaningful research. Consistent with prior work (e.g., Siegle et al., 2014; Vanderbrook, 2006), our findings decidedly support incorporating a formal independent study component in advanced STEM programming for gifted students, such as that described by Ariana. Effective independent study assigns ownership of the entire research process—from problem definition to reporting results—to the student, yet also imparts structure and supervision by an expert teacher or mentor.
Teaching to the middle had a negative influence the students’ STEM learning. Some students perceived as meaningless certain active learning activities (e.g., model building); such activities are intended to help students grasp concepts and are inappropriate for gifted students, who grasp concepts more quickly than typical students.
Our findings indicate that ability grouping created an emotionally safe, supportive environment, and motivated these students to excel in STEM. Consistent with Vanderbrook’s (2006) findings, students in our study felt a sense of emotional safety and belonging when grouped with their intellectual peers. As with students described by Gallagher et al. (1997) and Hertberg-Davis and Callahan (2008), these students’ feelings of safety and belonging also helped them form close friendships and engage in friendly competition that elevated their goals and standards without compromising their social support system. These findings suggest that ability grouping is an important component in STEM programming for gifted students. An important consideration, however, is that underserved gifted students may not benefit from ability grouping in the same ways as traditional gifted students (Hertberg-Davis & Callahan, 2008). Further research is needed to understand underserved gifted students’ needs related to ability grouping in advanced STEM, and to determine how best to accommodate those needs in the STEM programming.
Although the students all struggled in STEM at some point, their persistence and high STEM self-efficacy helped them overcome challenges. Each of the students described experiencing only superficial academic and career guidance counseling. Assouline and Colangelo (2006) pointed out that although gifted students may have the academic credentials to succeed, capability and ambition do not necessarily translate into purposeful action; students need guidance to plan for a career.
Our second research objective sought to understand the ways in which students’ advanced secondary STEM experiences influenced their STEM talent development and achievement. At the college level, STEM talent manifests as high achievement and commitment to a career in STEM. Students in our study represented the upper 5% of undergraduate students at the university. These students all demonstrated high achievement; for instance, all students scored above 1200 on the SAT, and one of the students was valedictorian in a graduating class of more than 500 students. The students all took AP STEM courses and earned college credit for STEM courses by passing AP exams. However, only three students committed to majors in STEM; the other four students, all female, chose majors in other fields (see Table 1). One of those four initially majored in biochemistry, but later changed her major to education. Two students who pursued other fields felt unprepared for college STEM courses, and one felt uncertain of her ability to succeed in college statistics. One student, despite her ability in and love for mathematics, opted not to take STEM courses in college at all beyond her credits earned by AP exams. Iris, whose high school advanced STEM accomplishments were exceptional, brought an interesting thought; she suggested that bringing more subjectivity and interaction into learning science would make it more engaging for her. Iris felt put off by the high degree of structure and control, and wished for more discussion and more room for creative ways of working and thinking in science and math. Given that feminist philosophers of science have long suggested that Western science is masculine in its ethos and substance (Keller, 1985), Iris’s insight is provocative and warrants further research on practical ways of integrating subjectivity and creativity into advanced STEM instruction. Such an expansion in science epistemology has potential to keep gifted women in the pipeline. Although neither Iris nor the other students perceived gender bias in their STEM experiences, cultural gender bias in STEM is deep seated and implicit until revealed by a sensitizing event. Future research also should examine educational and career experiences of eminent women in STEM to better understand their success in masculine, male-dominated fields.
As with all qualitative research, the analysis is not absolute and is, therefore, subject to multiple interpretations. Relying on individual students’ perceptions and experiences limits generalization of the findings. However, the structure and depth of the interviews attempted to stretch discussions beyond individual experiences. None of the participants showed awareness of broader societal factors on their experiences as gifted students in high school STEM; thus, further research investigating students’ experiences across organizations and cultures is warranted.
Footnotes
Appendix
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research and/or authorship of this article.
