Many people in the United States do not have positive experiences in STEM (science, technology, engineering, and mathematics) education that foster the development and maintenance of STEM identities throughout their lifetimes. STEM identity refers to a person’s self-conception as someone who understands, uses, and contributes to a STEM field.
Many perspectives can be found as to what constitutes STEM education. Ellis et al. (2020) recognized consensus on four aspects of integrated STEM education: (a) incorporates real-world contexts to promote student engagement and meaningful learning (Bryan et al., 2015; Burrows et al., 2017; Kelley & Knowles, 2016; Sanders, 2009), (b) focuses on student-centered pedagogies (Bryan et al., 2015; Kelley & Knowles, 2016), (c) emphasizes developing 21st-century competencies (e.g., creativity, critical thinking, communication, and collaboration) (Bryan et al., 2015; Honey et al., 2014), and (d) makes explicit connections between STEM disciplines (Bryan et al., 2015; Burrows et al., 2017; English, 2016; Herschbach, 2011; Honey et al., 2014; Kelley & Knowles, 2016).
For this paper, STEM is understood as representing any of the individual fields in science, technology, engineering, and math. Of the four fields, technology is the one that lacks a clearly defined role in STEM education. Ellis et al. (2020) found that a technology perspective, where students use authentic STEM tools and techniques, had the greatest impact on learning science content and practices. This finding aligns with a definition of technology from the Project 2016 Phase I Technology panel report (Johnson, 1989) that defined technology as a process that applies knowledge, skills, and tools to solve problems (see also Ellis et al., 2020).
One of the greatest challenges in science teacher education is understanding how to design STEM programming that provides opportunities for positive experiences that promote identification with STEM fields. Developing a person’s STEM identity can lead to increased participation and sustained engagement in these disciplines (Archer et al., 2010; Basu & Barton, 2007; Calabrese Barton et al., 2013; Carlone & Johnson, 2007; Stets et al., 2017). According to the National Research Council (NRC & Bell, 2009), “It is an important goal that all members of society identify themselves as being comfortable with, knowledgeable about, or interested in science” (p. 46).
The NRC’s recommendation that learners in informal environments develop the capacity to “think about themselves as science learners and develop an identity as someone who knows about, uses, and sometimes contributes to science” (NRC & Bell, 2009, p. 4) is theoretically and empirically grounded in the conceptualization of identity as connected to engagement in social contexts (Carlone, 2012).
A STEM identity is one type of social identity where one develops an affinity toward a STEM field. Gee (2000) described multiple types of identities people have throughout their lifetimes that are foregrounded depending on differing social environments and continually changing as a social process. Affinity identities are recognized by groups that share a common interest and develop a set of shared distinctive practices. Members are often more connected to the practices and experiences than to other group members. They connect to other people and sustain their membership through distinctive group practices.
Our research involved the continued development and implementation of the Conservation Science and Technology Identity (CSTI) survey, by which we sought to provide an empirical method to determine STEM identity profiles of informal science program participants. The STEM identity profiles were based on previously determined identity constructs of competence, performance, recognition, and a newly emergent construct, ways of seeing and being. The surveys provided a means for (a) making identity constructs empirically accessible, (b) revealing STEM identities of recruited participants in informal science learning opportunities, and (c) revealing the positive outcomes of participation for those taking advantage of informal programs like our workshop. Building on our previous research (Rodriguez et al., 2020), this paper presents the first 2 years of data from a multiyear study and was exploratory.
Our research is important as it supports the ability to characterize the historical STEM identities of those who access informal STEM programs and the impact of the program on their STEM identities. More specifically, the CSTI survey can assist programs in revealing the historical STEM identities of participants to determine if programs are effective in promoting newly forming STEM identities or supporting already well-established STEM identities. In other words, equity in informal science programs can be supported by empirically assessing STEM identity to determine program accessibility and effectiveness. This information is especially important, since if informal science programs are only accessed by students with already well-developed science identities these programs may serve to increase inequities for underrepresented students (Dawson, 2017; Feinstein & Meshoulam, 2014).
STEM Identity Authoring
The theoretical lens used to frame this research is STEM identity authoring, which evolved out of broader research on identity, specifically Gee’s (2000) theory of multiple identities. Gee postulated that individuals have many identities that are continuously changing as a social process throughout their lifetimes. Different identities are foregrounded depending on different social situations (Varelas et al., 2011).
Lave and Wenger (1991) noted how ‘‘one way to think of learning is as the historical production, transformation, and change of persons’’ (pp. 51–52). Developing identities throughout one’s lifetime is, in effect, learning as it encompasses a transformation and change of persons (see also Varelas et al., 2011). Developing a STEM identity refers to the ways individuals come to recognize themselves as feeling comfortable engaging in STEM pursuits and being around others who engage in similar pursuits. This identity includes seeing oneself as being able to understand science concepts, engage in science performances, and be recognized by others as belonging in that field (Carlone & Johnson, 2007).
Three factors found to contribute to identification with a STEM field are (a) competence – knowledge and understanding of core disciplinary concepts, (b) performances – engagement in disciplinary practices to accomplish consequential pursuits, and (c) recognition – acknowledging one’s competences and performances and having others acknowledge them (Carlone & Johnson, 2007; Hazari et al., 2015). A fourth – emerging – construct examined in this research that may contribute to STEM identity authoring is ways of seeing and being – that is, the values, attitudes, and behaviors that result from immersion within a scientific discipline such as conservation science (Hill et al., 2017; Jaber & Hammer, 2016).
Science competences are scientific skills, knowledge, and understandings gained through education, training, or other salient experiences (Klieme et al., 2008) and should not be considered an intrinsic trait of individuals. Developing competence involves opportunities to participate in scientific performances and have those performances interpreted and recognized as demonstrating competence in scientific understandings (Carlone 2012; Carlone et al., 2011; Gresalfi et al., 2008).
A person’s self-recognition of competence may be defined according to a priori definitions of what constitutes good science in a specific situation (Carlone 2012; Kelly et al., 1998). Group level meanings of competence are situational and determine who is recognized as competent or not (Carlone 2012; Gresalfi et al., 2008; Lottero-Perdue & Brickhouse, 2002). According to Erikson (1968), individuals are inclined to seek mastery in social interactions, but competence becomes part of identity only when it is recognized by meaningful others (Cote & Levine, 2002; Josselson, 1996) and internalized (Hazari et al., 2015). Further, and specifically related to this research focused on exploring informal learning spaces, McLaughlin et al. (2001) found that students who were unsuccessful demonstrating competence in formal learning environments – many from nondominant backgrounds – may have more success showing competence on the same content in informal learning spaces.
Performances are actions involved in creating and sharing new competences in scientific knowledge and understandings. Members of a group with common purposes and expectations develop specific practices for shared ways of talking and using tools (Carlone, 2012; Kelly, 2007; Lave & Wenger, 1991). Individuals with common interests and shared distinctive practices develop into affinity groups (Gee, 2000), or communities of practice (Wenger, 1998), where members may be more connected to the practices and experiences than to other members of the group. Often their membership is sustained through the practices.
Gee (2011) defined performance as “socially recognized and institutionally or culturally supported endeavor that usually involves sequencing or combining actions in certain specified ways” (p. 17). Scientific performances involve practices that support building explanations or solving problems and include investigative, communicative, and epistemic practices. Investigative performances are those of inquiry (e.g., observation, questioning, collecting and analyzing data, testing ideas, and developing solutions). Communicative practices are ways of sharing information and ideas. Kelly and Licona (2018) referred to epistemic practices as those used to make sense of phenomena (e.g., inferring, justifying, evaluating, and legitimizing scientific knowledge). These scientific performances constitute the act of doing science, which is at the core of being a scientist (Todd & Zvoch, 2017).
The third construct found to be important in developing STEM identity is recognition. Recognition includes both recognition by others and self-recognition of competences and performances. Engaging in scientific performances provides opportunities for others to recognize an individual’s competence in a STEM field (Barton et al., 2008; Carlone, 2004; Kang et al., 2019; Polman & Miller, 2010). Recognition can be positive feedback (e.g., praise, special privileges, or gifts) that acts to integrate STEM identity or negative feedback (e.g., criticism, slights, or penalties) that acts to inhibit STEM identity integration (Kerpelman et al., 1997; Todd & Zvoch, 2017).
For recognition from others to foster STEM identification, it must be internalized as self-recognition (Hazari et al., 2015). Recognition that depends on demonstrations of scientific competence and performances connects the constructs of STEM identity. Recognition of other identities, however, may work to promote or constrain identification with STEM fields (Archer et al., 2010; Brown et al., 2017; Carlone & Johnson, 2007; Ceglie, 2011).
Ways of Seeing and Being
The final construct, ways of seeing and being, is an emerging construct that needs further examination to determine what role, if any, it plays in STEM identification. Ways of seeing and being involves the reciprocating interaction between attitudes, values, and beliefs toward a STEM field (i.e., ways of seeing) that motivate a person’s actions in that field (i.e., ways of being).
Ways of seeing and being adds the affective domain to demonstrations of competences and performances. Hill et al. (2017) proposed discovery orientation as a similar construct examining the affective domain of learning. Feelings of interest, curiosity, and the enjoyment of discovery were found to be important to science learning (Farrington et al., 2012; Trujillo & Tanner, 2014; Watt et al., 2012). Jaber and Hammer (2015) examined the link between epistemic affect – the feelings involved when engaged in science performances that come from knowledge building – and epistemic motivation – the desire to continue with these sense-making activities.
These two studies undergird the first half of this new construct (ways of seeing). Ways of being involves behaviors that reciprocally reinforce these feelings and motivations. Carlson (2010) looked at how immersion, participatory engagement, and struggle in nature affects a sense of aesthetic appreciation. To generalize to any STEM field, when a person is immersed in a field of science, participates in, and struggles to make sense of it, they develop an appreciation for that field of study. Ways of seeing and being combines these ideas and applies them to the development of STEM identity.
In the case of conservation science, when a person is learning about nature through participatory engagement (i.e., performances) to make sense of natural phenomena (developing competence), they develop certain attitudes, values, and beliefs, such as aesthetic appreciation (ways of seeing), that motivate them to take actions, such as engagement in projects, to protect or conserve natural areas (ways of being). Through their actions, the person develops a STEM identity in that field as they are recognized by others and themselves as being a certain kind of person (e.g., naturalist, conservation scientist, or environmentalist).
For each of these constructs, our research examined their relationship to identification with conservation science and technology. Further, in this current research, especially in the context of the conservation projects undertaken where the application of technology (e.g., geospatial and mapping technologies) was used extensively to support intergenerational teams’ accomplishment of their pursuits, we also recognized the role technologies could play in shaping STEM identity authoring. Next is a review of the literature on STEM identity authoring in informal STEM programs
STEM Identity Authoring in Informal STEM Programs
The NRC (2009) described informal STEM learning (ISL) programs as places where all people, regardless of age or background, can explore science, technology, engineering, and math to develop their identification and agency in these fields. Identification with a field refers to how people see themselves as being able to understand, use, and contribute to the field. Agency is the capacity to act independently, make decisions and contributions to the field. McLaughlin et al. (2001) found that many learners who experienced failure in formal school science may demonstrate competence in informal settings. The NRC further detailed two goals of ISL programs: (a) to develop and nurture STEM identities, and (b) to increase participation by historically underrepresented populations in STEM.
Bell et al. (2017) recognized the need for ISL programs to be designed intentionally to promote practice-linked identification. ISL programs have many features that contribute to their potential to promote STEM identification. Dierking et al. (2003) discussed the correlation between participant choice and participant needs and interests. Learners often choose ISL programs because they are already interested in the subject, or they recognize a need to learn more about aspects of the field. ISL programs are attractive to many learners because they are often learner-motivated, open-ended, and collaborative (Falk & Dierking, 2000; Griffin, 1998).
Many ISL programs emphasize increasing motivation and confidence over factual knowledge (Fields, 2007; Johnsen, 1954). Other features of ISL programs that may influence the development of participants’ STEM identities are (a) unique locations, (b) authentic projects that promote exploration and curiosity, (c) apprenticeship models based on inquiry and hands-on activities (Barab & Hay, 2001; Gibson & Chase, 2002; Markowitz, 2004; Sondergeld et al., 2008), and (d) access to scientists and specialized equipment (Barab & Hay, 2001; Markowitz, 2004; Robbins & Schoenfisch, 2005).
ISL environments have been found to promote STEM identification in underrepresented groups who may not have engaged in disciplinary practices in formal science spaces. Many girls have been found to lack opportunities to engage in science practices in school (Alexander et al., 2012; Hill et al., 2010; Jovanovic & King, 1998; Tan et al., 2013), but when engaged in informal science, they have been found to develop science identities (see also Todd & Zvoch, 2017).
Measuring STEM Identity
Development of a STEM identity has been conceptualized with both intrinsic and extrinsic factors (Aschbacher et al., 2010), reflecting cognitive and social constructs. This conceptualization has led to a variety of methods of assessing STEM identities. Much of the research on STEM identity has used qualitative methods, which provide a rich understanding of identity as a social construct (Carlone & Johnson, 2007; Herrera et al., 2012; Sfard & Prusak, 2005). Intrinsic factors such as interest (Hazari et al., 2010), self-efficacy, and competence beliefs (Eccles et al., 2015), as well as extrinsic features such as participation (Crowley et al., 2015), recognition, sense of community, and affiliation (Carlone & Johnson, 2007) are all thought to be involved (Vincent-Ruz & Schunn, 2018) and present a variety of features to measure.
Researchers have attempted to quantify aspects of STEM identity through various methods (McDonald et al., 2019; Starr, 2018; Young et al., 2013). McDonald et al. (2019) developed a single-item STEM professional identity overlap measure for assessing STEM identity emphasizing typicality. STEM Typicality refers to how much a person feels similar to people who work in STEM fields (Tobin et al., 2010). McDonald et al.’s assessment looks at the overlap between students’ perception of themselves and STEM professionals. While the measure has been able to differentiate between majors and nonmajors in STEM, it lacks the nuances of examining individual constructs and how they may intersect.
Hazari et al. (2015) also focused on typicality by asking students whether they see themselves as a biology, chemistry, or physics person. One issue with this study is its suggestion that the construct of science identity is static, conceived of as an all-or-nothing proposition, and being a scientist cannot be learned (McDonald et al., 2019). In a different approach, Young et al. (2013) created a multi-item scale examining the importance of science to one’s self-concept. Their main objective was to see the effect of female science professors on the science cognitions of female undergraduates, including attitude, identification, and stereotypes. Their survey was specific to their goal and not meant to measure individual constructs of STEM identity.
Vincent-Ruz and Schunn (2018) examined the role of science identity on middle and high school student participation in optional science experiences. Their survey examined only two constructs, self-recognition as a science person, and recognition from others. While previous studies have assessed different aspects of STEM identity, none have sought to measure all the constructs included in our CSTI survey or to develop identity profiles.
Purpose and Research Questions
In our previous research (Rodriguez et al., 2020), we recognized the value in developing a survey instrument that could empirically assess a person’s STEM identity as a tool for informal science learning researchers and programmers (i.e., individuals who plan and lead ISL programs). More specifically, we identified the need for the CSTI survey we developed in relation to (a) the importance of the development and maintenance of a STEM identity for persistence in engaging in science-related work (Carlone & Johnson, 2007), (b) the lack of reliable, quantitative measures supported by research on the constructs of identity, (c) the value of empirical instruments to help determine who is accessing informal STEM programs, and (d) the impact of informal science learning programs on STEM identification.
While our initial research helped us to provide early evidence of the promise of the CSTI survey, we recognized how this current research would be important to further explore the reliability and functionality of the survey. Research Question 1 addressed the further testing of the instruments: How does an increase in sample size (n) affect the reliability of the instrument?
We also wanted to begin exploring what the survey could help us understand about our informal STEM learning program. Our overarching question was, How can the conservation identity instruments inform ISL programmers of the effects of their programs on the STEM identity of participants? This question includes whether the STEM identity characterizations of participants were different across the different sites where we held our workshops and about ways STEM identity constructs might change over time from our participants’ engagement in long-term conservation projects.
Research Questions 2-5 addressed our overarching question:
2. What can the pre-workshop surveys tell us about how the historical science and technology identities of adults and teens participating in the workshops compare?
4. How do four identity constructs (i.e., science and technology competence, and science and technology ways of seeing and being) compare from pre- to postsurvey?
5. How do all identity constructs compare from pre- to delayed postsurveys?
Research Context and Design
This research is part of a larger project funded by the National Science Foundation advancing informal stem learning (AISL) aimed at studying STEM identification in teens and adults working in intergenerational partnerships on authentic conservation projects. This project is a collaboration between the natural resources department, center for land-use education, and school of education in a large public university in the northeastern United States, in which we developed and implemented 2-day workshops on conservation science and geospatial technologies.
In the workshops, high school teens were paired with adult community partners and supported in developing collaborative community conservation projects over the year. The projects culminated in poster presentations at local and state conservation conferences. One goal of this study was to continue to develop and test the empirical instrument (i.e., CSTI survey) that we developed and reported on in our earlier research (Rodriguez et al., 2020).
The first research question addressed the goal of further testing the instruments’ reliability. Research Questions 2-5 guided examination of the use of the instruments to reveal how the constructs of STEM identity intersected in the participants’ historical STEM identities and how these constructs may be affected by an informal science learning program. To this end, the CSTI surveys were administered to high school students and their adult partners three times: (a) before the workshops, (b) after the workshops, and (c) at the conclusion of their community project. To answer Research Questions 2 and 3 we used a pretest-only design comparing historical STEM identity constructs between adults and teens and site locations. To answer Research Questions 4 and 5, we compared constructs over time and used a repeated measures design (Kraska, 2010).
The workshops aimed to promote mutual learning through instructional modules and field experiences in conservation science and geospatial technologies in preparation for the intergenerational partners to design and implement community-based conservation projects (Chadwick et al., 2018; see Appendix: Workshop Agenda). The workshops and overall program are explained in the STEM for all 2019 video at this link: https://stemforall2019.videohall.com/presentations/1465 (Rodriguez et al., 2019).
In the workshops, the partners explored conservation science concepts such as changes in (a) land-use, (b) forest health, (c) water resources, and biodiversity while learning how to use online mapping tools (Chadwick, et. al., 2018). Field activities included learning geospatial technologies such as epicollect, a mobile data gathering app to collect and organize water quality data from nearby streams, and Track Kit, a smartphone app that drops waypoints as you walk creating a trail map and allows users to add photographs to the waypoints. The data can then be uploaded to Google Maps to create an interactive trail map. A list of mapping tools used in the workshops and projects are at the website Maps & Apps for Community Conservation Project (https://uconnclear.maps.arcgis.com/apps/MapSeries/index.html?appid=ddb72c20c2074562aec32682d8350be5). Final projects are posted on the University of Connecticut Conservation Training Partnerships website (https://nrca.uconn.edu/students-adults/projects.htm).
The delayed posttest mirrored the pretest and was administered after participants concluded their projects with a conference presentation. The aim of administering the delayed postsurvey was to provide additional data on the impact of engagement in the yearlong community conservation project on the intergenerational partners’ STEM identities. Figure 1 illustrates how the research design aligns program goals, research questions, and data analysis.
Research Design Logic Model
Setting and Participants
This study examined data from five workshops during the first 2 years of the program. The workshops were held at five different sites across a New England state, two the 1st year and three the 2nd. The first workshop took place in a rural area in the eastern region and the second in an urban area in the south-central section. The third workshop took place in a rural western area, the fourth in an urban central area, and the fifth in a rural northwestern section.
Ninety-eight participants, 44 adults and 54 teens, from 54 towns in the focal state and two neighboring states attended the workshops. Teen participants were recruited through high school science teachers and counselors and nonprofit youth service organizations. Adult participants were recruited through land trusts, conservation commissions, and nonprofit environmental organizations. Fifty percent of the participants were female, 78% were White, 11% were Black, 9% were Asian American, and 6% were Latinx. The teens came from 13 high schools and the adults represented 14 conservation groups. Adults ranged in age from 30 to 73 (Table 1).
Demographics of Participants by Workshop Year
|Participants||Adults Year 1||Adults Year 2||Teens Year 1||Teens Year 2|
|% African American||7||7||12||14|
|% Asian American||0||0||12||8|
|% More than 1 Ethnicity||0||0||12||0|
|% Not designated||7||7||0||3|
This study is a continuation of a previous pilot study from the 1st year of implementation of the CSTI instruments described in Rodriguez et al. (2020). The development of the instrument involved an eight-step process:
- Category development adapted from the literature on science identity.
- Addition of technology categories.
- Formation of an item pool for science constructs, followed by the formation of a comparative item pool for technology constructs.
- Vetting from national experts on STEM identity research to establish content validity.
- Vetting from our external evaluator on the structure and wording of the instrument to reduce bias.
- Modification and reduction of item pool to four for each construct based on reviewer comments.
- Comparison of construct items among pre-surveys, post-surveys and delayed-post surveys.
- Finalization of all instruments and modification to an online format.
The presurvey for teens was finalized with 40 Likert-scaled items. The Likert scale for questions on competence used the following rating: 1 = No Understanding, 2 = Little Understanding, 3 = Fair Understanding, and 4 = Strong Understanding. All other constructs used the following Likert scale responses: 1 = Strongly Disagree, 2 = Somewhat Disagree, 3 = Somewhat Agree, and 4 = Strongly Agree.
The presurveys had four questions for the 10 constructs related to STEM identification (i.e., competence, performances, external recognition, self-recognition, and ways of seeing and being), five for conservation science, and five for technology. The postsurvey contained questions related only to four constructs (i.e., science competence, science ways of seeing and being, technology competence, and technology ways of seeing and being) thought to be more malleable over the short time frame between pre- and postsurveys.
A delayed post-survey was also developed to be administered after the yearlong project mirroring exactly the presurvey. The adult surveys were modified with only minor changes to accommodate their different life stage. For example, questions about school experiences were written in past tense rather than present.
This study extended our previous research by determining how an increase in sample size might affect the reliability of the instrument and participant results and included data from the delayed postsurvey. The increase in the number of workshop locations allowed for an additional question to be explored about the effects of workshop location on historical STEM identity of the participants.
To answer the first research question, we used the internal test of reliability, Cronbach coefficient alpha. The second analysis strategy, used to answer the second research question, involved determining the descriptive statistics for teen and adult CSTI surveys and using One Way ANOVA comparing STEM identity constructs with age. For Research Question 3, One Way ANOVA was used to compare STEM identity constructs for the five workshop locations. Repeated Measures Design looking at between-subject factors (age and site) was used to answer Research Questions 4 and 5. For Research Question 4, only four constructs (i.e., science and technology competence, and science and technology ways of seeing and being) were compared in the pre- and postsurvey results. For Research Question 5, all constructs were compared in the pre- and delayed postsurvey results.
The findings section is organized by the five research questions.
Finding 1: Reliability
Findings suggest the CSTI instrument is valid, reliable, and appropriate for future use, both in the subsequent phases of our current research and as a resource for others. The sample size increased from 44 participants the first year to 98 participants combining both years. Cronbach coefficient alpha increased for all but two constructs (technology performance and self-recognition) with the larger sample size. With the combined data from the 2 years, all constructs had a Cronbach alpha coefficient > 7.00, which is considered an acceptable level of internal consistency (Nunnally & Bernstein, 1994). (Insert Table 2)
Cronbach Coefficient Alpha for Both Years Combined
|Science Construct||Cronbach Year 1||Cronbach 2 Years||Technology Construct||Cronbach Year 1||Cronbach 2 Years|
|External Recognition||0.852||0.887||External Recognition||0.840||0.883|
|Ways of Seeing and Being||0.391||0.704||Ways of Seeing and Being||0.751||0.775|
Finding 2: Comparisons
All participants scored significantly higher on the prescience portion than the pretechnology portion. Significant differences were also found in overall science identity constructs between teens and adults (F = 4.757, p = .032). Adults scored significantly higher on the prescience portion than teens. Looking at the scores on individual constructs, we found significant differences in the mean scores for: science competence (F = 9.513, p = .003), science performance (F = 7.699, p = .007), and technology self-recognition (F = 5.581, p = .020). Adults scored higher on the two science constructs (Figure 2) while teens scored higher on the technology construct (Figure 3).
Adult vs. Teen Prescience Identity Constructs
Adult vs. Teen Pretechnology Identity Constructs
Finding 3: Historical STEM Identity by Workshop Site
A one-way ANOVA was performed to examine any difference in the mean presurvey scores of participants from the five sites where the CTP workshops were held. No significant difference was found in overall mean scores between participants in the five locations. Also, no significant differences were found in overall prescience constructs and pretechnology constructs or any of the individual constructs by site location (Table 3).
Comparison of STEM Identity by Workshop Location
|Presurvey Comparisons||Site 1 Mean||Site 2 Mean||Site 3 Mean||Site 4 Mean||Site 5 Mean|
|Overall STEM Identity||118.00||114.50||117.00||114.16||119.00|
|All Science Identity Constructs||67.35||65.87||65.47||62.96||67.80|
|All Technology Identity Constructs||50.65||48.67||51.53||51.20||51.30|
|Science External Recognition||13.24||11.67||11.47||12.44||13.05|
|Science Ways of Seeing and Being||15.06||15.53||14.76||14.16||15.15|
|Technology External Recognition||10.71||8.47||9.65||10.32||9.90|
|Technology Ways of Seeing and Being||12.12||13.33||11.94||12.04||12.50|
Finding 4: Identity Construct Increases Pre-Post
A one-way repeated measures analysis of variance (ANOVA) was conducted to evaluate the null hypothesis of no change in participants’ survey scores for the four STEM identity constructs included in both pre- and postsurveys (i.e., science competence, technology competence, science ways of seeing and being, and technology ways of seeing and being). A significant increase was found in the overall mean scores between pre- and postsurveys, Wilks lambda = .314, F (1,77) = 168.023, p < .001, partial eta = .686, power = 1.000.
Three out of four of the individual constructs also had significant increases in mean score in the postsurvey: science competence, Wilks lambda = .876, F (1,77) = 10.906, p = .001, partial eta = .124, and power = .903; technology competence, Wilks lambda = .322, F (1,77) = 162.017, p < .001, partial eta = .678, power = 1.00; and technology ways of seeing and being, Wilks lambda = .880, F (1,77) = 10.502, p = .002, partial eta = .120, power = .892; see Figure 4). No significant differences were found between age groups or locations.
Pre- vs. Postsurvey for Four Constructs
Finding 5: Construct Increases Pre- to Delayed Post
Although only 36 of the 98 participants completed the delayed postsurvey, all mean science identity constructs significantly increased from pre- to delayed postsurvey except science external recognition and science ways of seeing and being (Figure 5).The scores for science ways of seeing and being were negatively skewed. All participants scored close to the highest possible score of 16. The scores could not be transformed into a normal curve to see if the increase was significant. The mean scores for science competence increased from 13.56 to 14.33 (Wilks lambda= .761, F = 10.650, p = .003, partial eta = .239, power = .877). Mean science performance increased from 13.69 to 14.67 (Wilks lambda = .636, F = 19.431, p < .001, partial eta = .364, power = .990). Mean science self-recognition increased from 12.31 to 13.14 (Wilks lambda = .777, F = 9.755, p = .004, partial eta = .223, power = .859). While mean science external recognition increased from 12.64 to 12.97, the increase was not significant (Wilks lambda = .972, F = .985, p =.328, partial eta = .028, power = .162).
Pre- vs Delayed Postsurvey Identity Construct Mean Scores
All mean technology scores significantly increased from pre- to delayed postsurvey (Figure 6). Mean technology competence increased from 8.17 to 12.56 (Wilks lambda = .261, F = 96.407, p < .001, partial eta =, .739, power = 1.000). Mean technology performance increased from 9.36 to 11.17 (Wilks lambda = .489, F = 35.468, p < .001, partial eta = .511, power = 1.000). Mean technology self-recognition increased from 10.19 to 11.36 (Wilks lambda = .700, F = 14.551, p = .001, partial eta = .300, power = .959). Mean technology external recognition increased from 9.33 to 10.50 (Wilks lambda =.750, F = 11.352, p = .002, partial eta = .250, power = .905). Mean technology ways of seeing and being increased from 12.31 to 13.11 (Wilks lambda = .792, F = 8.913, p = .005, partial eta = .208, power = .826).
Pre- vs Delayed Posttechnology Identity Construct Mean Score
Like the Findings section, the Discussion section is organized by the research question. More specifically, findings for each research question are discussed by (a) making a claim for each research question developed from data analysis, (b) justifying each claim, and (c) considering our findings in light of this study’s context and the existing literature.
We found that continued testing of the CSTI instruments supports earlier research that the instrument is a reliable measure of STEM identity. One goal of our larger funded project was to develop a valid, reliable, quantitative instrument that could give insight into the historical STEM identities of participants who access informal STEM programs. Our instrument was designed to provide information about established intersecting identity constructs (Carlone & Johnson, 2007; Hazari et al., 2015, Carlson, 2010, Jaber & Hammer, 2016) that comprise a STEM identity. In Year 1, we focused on (a) developing the instrument and establishing content validity through a vetting process by experts in the field of science identity and (b) analyzing internal reliability with Cronbach coefficient alpha (Rodriguez et al., 2020). In Year 2, we continued evaluating the instrument with a larger sample size to establish a better reliability estimate using Cronbach coefficient alpha.
All measures of internal reliability improved with a larger sample size, suggesting CSTI is a valuable resource for characterizing a person’s identification with the STEM fields of conservation science and technology and is appropriate for future use in our research and as a resource for informal science learning researchers and programmers, as no equivalent survey exists.
The CSTI instrument enabled comparisons of individual STEM identity constructs between adults and teens. Our results found no significant differences between overall teen and adult historical STEM identities but did find significant differences in individual constructs. This finding highlights the importance of examining individual constructs in addition to overall STEM identity.
We found adults rated themselves higher in science competences and performances than did teens. Participating in scientific performances has been linked to the development of competence in scientific understandings (Carlone, 2012; Carlone et al., 2011; Gresalfi et al., 2008). The higher adult scores in these two constructs were anticipated, as adults who chose to participate in this program had more opportunities in connection to education, training, or other salient experiences that contribute to the development of competence, especially when compared to teens (Klieme et al., 2008). Interestingly, the adults did not rate themselves higher than the teens in conservation science self-recognition or recognition from others.
The teens rated themselves higher in technology self-recognition, although not in technology competence and performances. While we predicted the teens would rate themselves higher in the technology constructs than the adults would, due to perceptions that young people are more competent with technology than older adults (Vaterlaus et al., 2015), this was the only construct with a significant difference.
These results indicate a disconnect in participants’ answers to questions about competences and performances and questions about self-recognition of those competences and performances. A person’s recognition of their competence may be influenced by prior conceptions of what is considered good science in a particular situation (Carlone, 2012; Kelly et al., 1998). Participants may answer questions about specific competences differently than how they see themselves as competent in a field of science. This disconnect between ratings in competence and performances and self-recognition needs to be further explored.
Hazari et al. (2015) discussed how studying only external performances in trying to understand identity development can result in a mismatch between recognition by others (i.e., the observer) and internal designations (i.e., self-recognition) and recommended following up with surveys and interviews. When looking at self-reported survey data, follow-up interviews could provide data to resolve these discrepancies.
Our findings indicate there were no significant differences in STEM identities between the participants at the different workshop locations. The five sites were chosen to include diverse population patterns (i.e., urban, suburban, and rural) in different geographic regions (i.e., northwest corner, southwest corner, central, eastern, and southeast corner) across the New England state where this research took place. Urban and rural areas have higher underrepresented populations in STEM than suburban areas (NRC, 2009). Still, each workshop attracted participants with similar STEM identity profiles.
In all workshops the historical STEM construct with the highest mean score was science ways of seeing and being. This result suggests that participants self-selected to take part in this program because they had already developed values and attitudes (i.e., ways of seeing) that made them want to get involved in conservation work in their communities (i.e., ways of being). They chose to get involved in a program where they would work on a community project over the course of a year.
This finding may overlap with research showing participation in informal science learning programs has been mostly those from advantaged groups (Dawson, 2014a, b; Dawson, 2017; National Science Foundation, 2012; OECD, 2012). This population often comes to informal science programs with already well-developed interests, (Lipstein & Renninger, 2006; Renninger & Hidi, 2002; Renninger et al., 2004) and the monetary resources to engage in projects unrelated to earning income.
Another factor affecting the results of workshop location is that the workshops were marketed across the state with no regional restrictions. Some participants chose to travel across the state to participate in a more conveniently timed workshop, so the workshops did not necessarily draw from the communities in which they were located.
Most identity constructs significantly increased over the course of the program. The informal science learning program in which this research was nested had two main short-term curricular goals for the workshop: (a) to increase competence in conservation science and the application of technology and (b) to increase an understanding of the value of using technology to help understand conservation issues and solve community problems. Two longer-term goals were to promote STEM identity authoring and increase understanding and engagement in community conservation work.
All constructs but one increased over the length of the program, suggesting the program contributed to strengthening the participants’ STEM identities. The one construct that did not increase was science ways of seeing and being, which was highly negatively skewed in the pretest (i.e., all scores close to the highest possible score.) This ceiling effect makes it difficult to increase the mean score significantly.
Most participants arrived at the workshops with a strong aesthetic appreciation for nature (ways of seeing) and the desire to protect and preserve natural areas (ways of being). This skewed score may indicate that our program attracted only participants who already had positive experiences in conservation science. This finding echoes concerns that informal programs may serve to increase inequities for underrepresented students when they are accessed only by those with already well-established STEM identities. (Dawson, 2017; Feinstein & Meshoulam, 2014). It also suggests a need to reexamine recruitment strategies to attract diverse students without prior experiences in conservation science.
Science external recognition increased, though not significantly. Recognition of competence and performances has been found to be important for the development of STEM identity (Barton et al., 2008; Carlone, 2004; Kang et al., 2019; Polman & Miller, 2010) but only if the recognition is positive (Kerpelman et al., 1997; Todd & Zvoch, 2017) and internalized (Hazari et al., 2015). Negative recognition of learners’ other identities can interfere with how learners identify with STEM (Archer et al. 2010; Brown et al., 2017; Carlone & Johnson, 2007; Ceglie, 2011). Although a positive finding, the way participants were recognized, by whom, and for what needs further exploration.
Overall, by the end of the program, participants indicated (a) a stronger understanding of conservation science and technology, (b) a greater ability to engage in conservation science and technology performances, (c) an increase in their self-recognition of science and technology competences and performances and (d) an increase in their view of the value of using technology in conservation pursuits.
Conclusions and Implications
Our research, as part of a larger informal science learning program, sought to understand how intergenerational partnerships working on community conservation projects affected the development and maintenance of STEM identities. One of the most important goals of science teacher education is to develop and maintain identification with STEM disciplines for learners to cultivate an interest in STEM into lifelong agency in STEM pursuits of consequence.
This research is important as it presents a way to empirically determine participants’ level of identification with specific STEM fields as they enter an ISL program while allowing for pre/post comparisons to determine the effectiveness of the program. The CSTI Instruments provide a means: (a) of making STEM identity constructs empirically accessible to researchers and practitioners, (b) of revealing STEM identities of recruited participants to address recruitment strategies leading to inequities, and (c) of revealing positives outcomes of participation in informal science learning opportunities to evaluate program effectiveness.
This study showed (a) the CSTI instruments increased in reliability with an increase in sample size from 2 years of data, (b) differences in the identity constructs comprising the historical STEM identities of adult and teens, (c) no differences in historical STEM identities of participants at the different workshops, (d) increases in STEM identity construct scores from pre- to posttest for all but one construct (ways of seeing and being), and (d) increase in all identity constructs from pre to delayed post survey.
Although we increased recruitment of racially diverse participants in the 2nd year, our recruitment efforts fell short of enlisting significant numbers of participants with less developed STEM identities. The ability to determine a person’s STEM identity is essential for promoting equity in informal science education and informing program designers of the effectiveness of the program and is also valuable for classroom teachers in evaluating growth in STEM identification of their students through the school year and across school years. The CSTI instruments enabled a more nuanced quantitative examination of STEM identity by helping make more apparent the influence of each individual STEM identity construct.
Limitations of this study included sample size, the varying time frames between pre- and delayed postsurveys, and a relatively homogeneous cohort concerning STEM identity. The data for this study was from the first 2 years of a multiyear program. While the sample size for the pre- and postsurveys increased with 2 years of data (n = 97) from the initial 1st year study (n = 37), it was still small enough to warrant caution in making more generalizable claims and points to the exploratory nature of this study. Also, the sample size for comparing pre- and delayed postsurvey was smaller (n = 36), again limiting the strength of our claims until more data can be collected.
Participants had varying timeframes for working on their community projects. The time between attending the workshop and presenting their final projects at a conservation conference varied from 6-9 months, depending on the date of each workshop. Even though some participants were engaged in completing their projects over a shortened timeline, eight out of 10 STEM identity constructs significantly increased, indicating that differences in timespan of the project was not a significant factor in increasing identification with conservation science and technology. While ethnic and racial diversity of the participants increased from the 1st to 2nd year of the study (Table 2), the STEM identities of the participants remained fairly homogeneous. Participants entered the program with already well-developed STEM identities, but even so, the delayed postsurvey indicated an improvement in most constructs of STEM identity.
The authors declare that they have no conflict of interest. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study. This research was funded by National Science Foundation Grant No. AISL1612650.
Alexander, J. M., Johnson, K. E., & Kelley, K. (2012). Longitudinal analysis of the relations between opportunities to learn about science and the development of interests related to science. Science Education, 96(5), 763-786.
Archer, L., DeWitt, J., Osborne, J., Dillon, J., Willis, B., & Wong, B. (2010). “Doing” science versus “being” a scientist: Examining 10/11-year-old schoolchildren’s constructions of science through the lens of identity. Science Education, 94(4), 617–639. https://doi.org/10.1002/sce.20399
Aschbacher, P. R., Li, E., & Roth, E. J. (2010). Is science me? High school students’ identities, participation and aspirations in science, engineering, and medicine. Journal of Research in Science Teaching, 47(5), 564–582. https://doi.org/10.1002/tea.20353
Barab, S. A., & Hay, K. E. (2001). Doing science at the elbows of experts: Issues related to the science apprenticeship camp. Journal of Research in Science Teaching, 38(1), 70-102. Barton, A. C., Tan, E., & Rivet, A. (2008). Creating hybrid spaces for engaging school science among urban middle school girls. American Educational Research Journal, 45(1), 68–103. https://doi.org/10.3102/0002831207308641
Basu, S. J., & Barton, A. C. (2007). Developing a sustained interest in science among urban minority youth. Journal of Research in Science Teaching, 44(3), 466–489. https://doi.org/10.1002/tea.20143
Bell, P., Van Horne, K., & Cheng, B. H. (2017). Special issue: Designing learning environments for equitable disciplinary identification. Journal of the Learning Sciences, 26(3), 367–375. https://doi.org/10.1080/10508406.2017.1336021
Brown, B. A., Mangram, C., Sun, K., Cross, K., & Raab, E. (2017). Representing racial identity: Identity, race, the construction of the African American STEM students. Urban Education, 52(2), 170–206. https://doi.org/10.1177/0042085916661385
Bryan, L. A., Moore, T. J., Johnson, C. C., & Roehrig, G. H. (2015). Integrated STEM education. In C. C. Johnson, T. J. Moore, & E. E. Peters-Burton (Eds.), STEM roadmap: A framework for integrated STEM education (pp. 23-37). Routledge.
Burrows, A. C., Garofalo, J., Barbato, S., Christensen, R., Grant, M., Kinshuk, Parrish, J., Thomas, C., & Tyler-Wood, T. (2017). Editorial: Integrated STEM and current directions in the STEM community. Contemporary Issues in Technology and Teacher Education, 17(4), 478-482. https://citejournal.org/volume-17/issue-4-17/science/editorial-cite-journal-science-education-3-0/
Calabrese Barton, A., Kang, H., Tan, E., O’Neill, T. B., Bautista-Guerra, J., & Brecklin, C. (2013). Crafting a future in science: Tracing middle school girls’ identity work over time and space. American Educational Research Journal, 50(1), 37–75. https://doi.org/10.3102/0002831212458142
Carlone, H. B. (2004). The cultural production of science in reform-based physics: Girls’ access, participation, and resistance. Journal of Research in Science Teaching, 41(4), 392–414. https://doi.org/10.1002/tea.20006
Carlone, H. B., & Johnson, A. (2007). Understanding the science experiences of successful women of color: Science identity as an analytic lens. Journal of Research in Science Teaching, 44(8), 1187–1218. https://doi.org/10.1002/tea.20237
Carlone, H. B., Haun‐Frank, J., & Webb, A. (2011). Assessing equity beyond knowledge- and skills-based outcomes: A comparative ethnography of two fourth-grade reform-based science classrooms. Journal of Research in Science Teaching, 48(5), 459–485. https://doi.org/10.1002/tea.20413
Carlson, A. (2010). Contemporary environmental aesthetics and the requirements of environmentalism. Environmental Values, 19(3), 289–314. https://doi.org/10.3197/096327110X519844
Ceglie, R. (2011). Underrepresentation of women of color in the science pipeline: The construction of science identities. Journal of Women and Minorities in Science and Engineering, 17(3), 271–293. https://doi.org/10.1615/JWomenMinorScienEng.2011003010
Chadwick, C., Dickson, D., Arnold, C., Cisneros, L., Volin, J., Campbell, T., Moss, D., & Rodriguez, L. (2018) Intergenerational STEM learning: Connecting generations throughinformal geospatial and conservation education. Journal of Extension, 56(5). https://archives.joe.org/joe/2018september/iw2.php
Cote, J., & Levine, C. (2002). Identity formation, agency, and culture: A social psychological synthesis. Lawrence Erlbaum.
Crowley, K., Barron, B.J., Knutson, K., & Martin, C. (2015). Interest and the development of pathways to science. InK. A. Renninger, M. Nieswandt, & S. Hidi (Eds.), Mathematics and science learning (pp. 297-313). American Educational Research Association.
Dawson, E. (2014a). Equity in informal science education: Developing an access and equity framework for science museums and science centres. Studies in Science Education, 50(2), 209–247. https://doi.org/10.1080/03057267.2014.957558
Dawson, E. (2014b). “Not designed for us”: How science museums and science centers socially exclude low-income, minority ethnic groups. Science Education, 98, 981–1008.
Dawson, E. (2017). Social justice and out-of-school science learning: Exploring equity in science television, science clubs and maker spaces. Science Education, 101(4), 539–547. https://doi.org/10.1002/sce.21288
Dierking, L. D., Falk, J. H., Rennie, L., Anderson, D., & Ellenbogen, K. (2003). Policy statement of the “informal science education” ad hoc committee. Journal of Research in Science Teaching, 40, 108-111.
Eccles, J. S., Fredricks, J. A., & Baay, P. (2015). Expectancies, values, identities, and self-regulation. In G. Oettingen & P. M. Gollwitzer (Eds.), The Jacobs Foundation series on adolescence (pp. 30–56). Cambridge University Press
Ellis, J., Wieselmann, J., Sivaraj, R., Roehrig, G., Dare, E., & Ring-Whalen, E. (2020). Toward a productive definition of technology in science and STEM education. Contemporary Issues in Technology and Teacher Education, 20(3), 472-496. https://citejournal.org/volume-20/issue-3-20/science/toward-a-productive-definition-of-technology-in-science-and-stem-education
English, L. D. (2016). STEM education K-12: Perspectives on integration. International Journal of STEM Education, 3(1), 1-8.
Erikson, E. H. (1968). Identity: Youth and crisis. W.W. Norton.
Falk, J., & Dierking, L. (2000). Learning from museums: Visitor experiences and the making of meaning (American Association for State and Local History book series). AltaMira Press.
Farrington, C. A., Roderick, M., Allensworth, E., Nagaoka, J., Keyes, T. S., Johnson, D. W., & Beechum, N. O. (2012). Teaching adolescents to become learners: The role of noncognitive factors in shaping school performance: A critical literature review. University of Chicago Consortium on Chicago School Research.
Feinstein, N. W., & Meshoulam, D. (2014). Science for what public? Addressing equity in American science museums and science centers. Journal of Research in Science Teaching, 51(3), 368–394. https://doi.org/10.1002/tea.21130
Fields, D. A. (2007). What do students gain from a week at science camp? Youth perceptions and the design of an immersive, research-oriented astronomy camp. International Journal of Science Education, 30, 1-21.
Gee, J. P. (2000). Identity as an analytic lens for research in education. Review of Research in Education, 25, 99-125. https://doi.org/10.2307/1167322
Gee, J. P. (2011) An introduction to discourse analysis: Theory and method. (3rd ed.). Routledge.
Gibson, H. L., & Chase, C. (2002). Longitudinal impact of an inquiry-based science program on middle school students’ attitudes toward science. Science Education, 86, 693-705.
Gresalfi, M., Martin, T., Hand, V., & Greeno, J. (2009). Constructing competence: An analysis of student participation in the activity systems of mathematics classrooms. Educational Studies in Mathematics, 70(1), 49–70. https://doi.org/10.1007/s10649-008-9141-5
Griffin, J. (1998). Learning science through practical experiences in museums. International Journal of Science Education, 20(6), 655–663. https://doi.org/10.1080/0950069980200604
Hazari, Z., Cass, C., & Beattie, C. (2015). Obscuring power structures in the physics classroom: Linking teacher positioning, student engagement, and physics identity development. Journal of Research in Science Teaching, 52(6), 735–762. https://doi.org/10.1002/tea.21214
Hazari, Z., Sonnert, G., Sadler, P. M., & Shanahan, M.-C. (2010). Connecting high school physics experiences, outcome expectations, physics identity, and physics career choice: A gender study. Journal of Research in Science Teaching, 47(8), 978–1003. https://doi.org/10.1002/tea.20363
Herrera, F. A., Hurtado, S., Garcia, G. A., & Gasiewski, J. (2012). A model for redefining STEM identity for talented STEM graduate students [Paper presentation]. American Educational Research Association Annual Conference, Vancouver, BC, Canada. http://www.heri.ucla.edu/nih/downloads/AERA2012HerreraGraduateSTEMIdentity.pdf
Herschbach, D. R. (2011). The STEM initiative: Constraints and challenges. Journal of STEM Teacher Education, 48(1), 96-112.
Hill, C., Corbett, C., & St. Rose, A. (2010). Why so few? Women in science, technology, engineering and mathematics. American Association of University Women.
Hill, P. W., McQuillan, J., Spiegel, A. N., & Diamond, J. (2017). Discovery orientation, cognitive schemas, and disparities in science identity in early adolescence. Sociological Perspectives, 61(1), 99-125.
Honey, M., Pearson, G., & Schweingruber, H. (Eds.). (2014). STEM integration in K-12 education: Status, prospects, and an agenda for research. The National Academies Press.
Jaber, L. Z., & Hammer, D. (2016). Engaging in science: A feeling for the discipline. Journal of the Learning Sciences, 25(2), 156–202. https://doi.org/10.1080/10508406.2015.1088441
Johnson, J. R. (1989). Technology: Report of the Project 2061 Phase I Technology Panel. AAAS Books.
Johnsen, R.H. (1954). The summer science camp as a means of attracting talented students to science careers. The Scientific Monthly, 64(1), 37-39.
Josselson, R. (1996). On writing other people’s lives: Self-analytic reflections of a narrative researcher. In R. Josselson (Ed.), The narrative study of lives, Vol. 4. Ethics and process in the narrative study of lives (pp. 60-71). Sage
Jovanovic, J., & King, S. (1998). Boys and girls in the performance-based science classroom: Who’s doing the performing? American Educational Research Journal, 35(3), 477-496.
Kang, H., Barton, A. C., Tan, E., Simpkins, S. D., Rhee, H., & Turner, C. (2019). How do middle school girls of color develop STEM identities? Middle school girls’ participation in science activities and identification with STEM careers. Science Education, 103(2), 418–439. https://doi.org/10.1002/sce.21492
Kelly, G. J. (2007). Discourse in science classrooms. In S.K. Abell & N.G. Lederman (Eds.), Handbook of research on science education (pp. 443-469). Lawrence Erlbaum.
Kelly, G. J., Chen, C., & Crawford, T. (1998). Methodological considerations for studying science-in-the-making in educational settings. Research in Science Education, 28(1), 23–49.
Kelly, G. J., & Licona, P. (2018). Epistemic practices and science education. In M. R. Matthews (Ed.), History, philosophy and science teaching (pp. 139–165). Springer International Publishing. https://doi.org/10.1007/978-3-319-62616-1_5
Kelley, T. R., & Knowles, J. G. (2016). A conceptual framework for integrated STEM education. International Journal of STEM Education, 3(1), 11.
Kerpelman, J. L., Pittman, J. F., & Lamke, L. K. (1997). Toward a microprocess perspective on adolescent identity development: An identity control theory approach. Journal of Adolescent Research, 12(3), 325–346. https://doi.org/10.1177/0743554897123002
Klieme, E., Hartig, J., & Rauch, D. (Eds.). (2008). The concept of competence in educational contexts. In J. Hartig, E. Klieme, & D. Leutner (Eds.), Assessment of competencies in educational contexts (pp. 3–22). Hogrefe & Huber Publishers.
Kraska. M. (2010). Repeated measures design. In N. Salkind (Ed.), Encyclopedia of research design. SAGE Publications, Inc. https://dx.doi.org/10.4135/9781412961288.n378
Lave, J., & Wenger, E. (1991). Situated learning: legitimate peripheral participation. Cambridge University Press.
Lipstein, R., & Renninger, K.A. (2006). “Putting things into words”: The development of 12-15-year-old students’ interest for writing. In S. Hidi & P. Boscolo (Eds.), Writing and motivation (pp. 113-140). Elsevier.
Lottero‐Perdue, P. S., & Brickhouse, N. W. (2002). Learning on the job: The acquisition of scientific competence. Science Education, 86(6), 756–782. https://doi.org/10.1002/sce.10034
Markowitz, D. G. (2004). Evaluation of the long-term impact of a university high school summer science program on students’ interest and perceived abilities in science. Journal of Science Education and Technology, 13(3), 395-407.
McDonald, M. M., Zeigler-Hill, V., Vrabel, J. K., & Escobar, M. (2019). A single-item measure for assessing STEM Identity. Frontiers in Education, 4(78). https://doi.org/10.3389/feduc.2019.00078
McLaughlin, M., Irby, M.A., & Langman, J. (2001). Urban sanctuaries: Neighborhood organizations in the lives and futures of inner-city youth. Jossey Bass.
National Research Council & Bell, P. (Eds.). (2009). Learning science in informal environments: people, places, and pursuits. National Academies Press.
National Science Foundation. (2012). Science and engineering indicators 2012. Author.
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
OECD. (2012). Education at a glance 2012: OECD indicators. http://www.oecd.org/education/educationataglance2012oecdindicators-chapteratheoutputofeducationalinstitutionsandtheimpactoflearning-indicators.htm
Polman, J. L., & Miller, D. (2010). Changing stories: Trajectories of identification among African American youth in a science outreach apprenticeship. American Educational Research Journal, 47(4), 879–918. https://doi.org/10.3102/0002831210367513
Renninger, K.A., & Hidi, S. (2002). Interest and achievement: Developmental issues raised by a case study. In A. Wigfield & J. Eccles (Eds.), Development of achievement motivation (pp. 173-195). Academic Press.
Renninger, K.A., Sansone, C., & Smith, J.L. (2004). Love of learning. In C. Peterson & M.E.P. Seligman (Eds.), Character strengths and virtues: A handbook and classification (pp. 161-179). Oxford University Press.
Robbins, M. E., & Schoenfisch, M. H. (2005). An interactive analytical chemistry summer camp for middle school girls. Journal of Chemical Education, 82(10), 1486-1488.
Rodriguez L., Campbell, T., Cisneros, L., Volin, J.C., Arnold, C., Chadwick, C., Dickson, D., Moss, D.M.. & Rubenstein, J. (2019) Intergenerational conservation STEM learning and identity. Fifth National Science Foundation STEM for All Video Showcase. https://stemforall2019.videohall.com/presentations/1465
Rodriguez, L. S., Morzillo, A., Volin, J. C., & Campbell, T. (2020) Conservation science and technology identity instrument: Empirically measuring STEM identities in informal science learning programs. School Science and Mathematics, 120 (4), 244- 257. https://doi.org/10.1111/ssm.12401
Sanders, M. (2009). STEM, STEM Education, STEMmania. The Technology Teacher, 68(4), 20- 26.
Sfard, A., & Prusak, A. (2005). Telling Identities: In search of an analytic tool for investigating learning as a culturally shaped activity. Educational Researcher, 34(4), 14–22. https://doi.org/10.3102/0013189X034004014
Sondergeld, T. A., & Schultz, R. A. (2008). Science, standards, and differentiation: It really can be fun! Gifted Child Today, 31(1), 34–40. https://doi.org/10.4219/gct-2008-694
Starr, C. R. (2018). “I’m not a science nerd!”: STEM stereotypes, identity, and motivation among undergraduate women. Psychology of Women Quarterly, 42(4), 489–503. https://doi.org/10.1177/0361684318793848
Stets, J. E., Brenner, P. S., Burke, P. J., & Serpe, R. T. (2017). The science identity and entering a science occupation. Social Science Research, 64, 1–14. https://doi.org/10.1016/j.ssresearch.2016.10.016
Tan, E., Barton, A. C., Kang, H., & O’Neill, T. (2013). Desiring a career in STEM-related fields: How middle school girls articulate and negotiate identities-in-practice in science. Journal of Research in Science Teaching, 50(10), 1143–1179. https://doi.org/10.1002/tea.21123
Tobin, D. D., Menon, M., Menon, M., Spatta, B. C., Hodges, E. V. E., & Perry, D. G. (2010). The intrapsychics of gender: A model of self-socialization. Psychological Review, 117, 601–622. doi:10.1037/a0018936
Todd, B., & Zvoch, K. (2017). Exploring girls’ science affinities through an informal science education program. Research in Science Education. https://doi.org/10.1007/s11165-017-9670-y
Trujillo, G., & Tanner, K. D. (2014). Considering the role of affect in learning: Monitoring students’ self-efficacy, sense of belonging, and science identity. CBE Life Sciences Education, 13(1), 6–15. https://doi.org/10.1187/cbe.13-12-0241
Varelas, M., Kane, J. M., & Wylie, C. D. (2011). Young African American children’s representations of self, science, and school: Making sense of difference. Science Education, 95(5), 824–851. https://doi.org/10.1002/sce.20447
Vaterlaus, J. M., Jones, R. M., & Tulane, S. (2015). Perceived differences in knowledge about interactive technology between young adults and their parents. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 9(4). https://doi.org/10.5817/CP2015-4-3
Vincent-Ruz, P., & Schunn, C. D. (2018). The nature of science identity and its role as the driver of student choices. International Journal of STEM Education, 5(1), 48. https://doi.org/10.1186/s40594-018-0140-5
Watt, H. M. G., Shapka, J. D., Morris, Z. A., Durik, A. M., Keating, D. P., & Eccles, J. S. (2012). Gendered motivational processes affecting high school mathematics participation, educational aspirations, and career plans: A comparison of samples from Australia, Canada, and the United States. Developmental Psychology, 48(6), 1594–1611. https://doi.org/10.1037/a0027838
Wenger, E. (1998). Communities of practice: Learning, meaning, and identity. Cambridge University Press. Young, D. M., Rudman, L. A., Buettner, H. M., & McLean, M. C. (2013). The influence of female role models on women’s implicit science cognitions. Psychology of Women Quarterly, 37(3), 283–292. https://doi.org/10.1177/0361684313482109
Conservation Training Partnerships Agenda