How Do 2-Year College Students Beginning in STEM View Themselves as Learners?

by Xueli Wang, Ning Sun, Brit Wagner & Brett Ranon Nachman - 2019

Background: Two-year colleges are uniquely positioned to diversify science, technology, engineering, and mathematics (STEM) education. Yet limited existing scholarship sheds light on how 2-year college students view themselves as learners as they experience STEM courses and programs. An in-depth and nuanced understanding of 2-year college STEM students’ self-perceptions as learners presents a powerful vehicle for identifying venues of interventions aimed at cultivating and supporting the STEM talent pool toward success through and beyond the 2-year college sector.

Purpose of the Study: We address the following research question: How do 2-year college students participating in STEM classes and programs perceive themselves as learners? Our inquiry is aimed at revealing the fundamental structure underlying these students’ experiences as their self-perceptions as STEM learners are formed and transformed.

Study Setting and Participants: We collected the data for this study as part of an ongoing longitudinal mixed methods study of students beginning in STEM programs or courses in Fall 2014 at three large 2-year institutions in a Midwestern state. The sample selection of the present qualitative study drew on maximum variation sampling, yielding a final sample size of 31.

Research Design: We adopted descriptive phenomenology to answer our research question. In-person interviews were conducted with each participant. Data were transcribed verbatim and analyzed using the procedures aligned with the descriptive phenomenological method proposed by Colaizzi (1978). In addition, we adopted analytical techniques from grounded theory in order to effectively organize our process of documenting, describing, and making sense of the data.

Findings: Our findings show that self-perceptions as 2-year college STEM learners are deeply intertwined with self-perceptions as mathematics learners, constantly evaluated and reevaluated in relation to others, driven by an internal process of recognizing the rewards and negotiating the challenges of studying STEM, and shaped by an external process of validation. While these themes stand on their own as prominent defining elements of the phenomenon of our interest, they are also inherently interwoven pieces of a cohesive, complex whole.

Conclusions: Our study captures how students’ self-perceptions as learners are formed and transformed, and illustrates how their prior and current learning experiences, self-perceptions as mathematics learners, background characteristics, and relationships with others interweave to shape and reshape how they view themselves as learners. Future work should further determine what specific measures and venues 2-year colleges can capitalize upon to develop confident and collaborative learners who embrace the rewards and challenges of studying STEM.

INTRODUCTION

Broadening participation of undergraduate students from diverse backgrounds in science, technology, engineering, and mathematics (STEM) fields of study continues to be a key national priority for education policy and research (Augustine, 2007; Glenn Commission, 2000; Presidents Council of Advisors on Science and Technology [PCAST], 2012). In this effort, 2-year colleges are uniquely positioned to grow and diversify the pipeline of STEM education and professions (Hagedorn & Purnamasari, 2012; Hoffman, Starobin, Laanan, & Rivera, 2010). Historically, these institutions have served a disproportionately large group of students underrepresented in higher education (Cohen, Brawer, & Kisker, 2014). The same pattern holds in the STEM context, with many students of color, individuals from low-income families, and first-generation students who started at public 2-year colleges interested in pursuing STEM programs and credentials (Wang, 2013, 2015).

Granted, STEM, as an umbrella term, encompasses a wide range of fields of study that are distinct in their nature, disciplinary norms, and applicability.¹ Regardless of their differences, STEM disciplines are characterized by a set of common features, such as abstractness, rigor, and precision (D. A. Kolb, 1981), as well as the cumulative nature of the knowledge structures in these disciplines that often require sequential learning in establishing the knowledge base (Becher, 1994). In addition, students enrolled in STEM invariably are expected to develop problem-solving and analytical skills (Biglan, 1973; D. A. Kolb, 1981; Neumann, Parry, & Becher, 2002). These shared features across STEM position the learning of these subjects as especially demanding of students time and effort and are even further pronounced in the 2-year college context, with a considerable proportion of students enrolled part time and dealing with academic and financial barriers (Cohen et al., 2014). In fact, 2-year college students initially enrolled in STEM programs and courses encounter similar barriers and challenges often attributed to this shared abstract and cumulative nature of STEM subjects, which is especially true for students who are academically underprepared or have been away from school for a long period of time (Dowd, 2012; Hagedorn & DuBray, 2010; Perin, 2002). Consequently, despite the relatively broad access to STEM for underrepresented students at 2-year colleges, these students often experience low completion and transfer rates (PCAST, 2012; Wang, 2015), resulting in a missed opportunity where a diverse pool of aspiring STEM students are lost along the pathway.

A growing body of empirical research aims to identify factors contributing to community college students success in STEM fields of study (e.g., Anderson, Sun, & Alfonso, 2006; Bensimon & Dowd, 2009; Bragg, 2011; Cole & Espinoza, 2008; Crisp, Nora, & Taggart, 2009; Hagedorn & DuBray, 2010; Jackson, Starobin, & Laanan, 2013; Malcom, 2010; McGee & Martin, 2011; Packard, 2012; Reyes, 2011; Wang, 2013, 2015, 2016). Specifically, research in this vein has explored how STEM attainment is associated with student background characteristics (e.g., Crisp et al., 2009; Wang, 2013), course-taking patterns (e.g., Bragg, 2011; Hagedorn & DuBray, 2010; Wang, 2016), interaction with faculty and peers (e.g., Thompson, 2001), advising and mentoring programs (Association of American Colleges and Universities [AACU], 2012; Packard, 2012), and partnerships with K12 and 4-year institutions (e.g., Malcom, 2010; Zinser & Hanssen, 2006).

Despite the great value of this budding area of inquiry, a critical facet along community college students STEM pathway has been conspicuously missing: Very limited scholarship sheds light on how 2-year college students view themselves as learners as they participate in and experience STEM courses and programs. The lack of such knowledge represents a significant gap in the literature because students perceptions of themselves as learners play a crucial role in shaping their behavior and approaches to learning (Burns, 1982; Rayner, 2001). This is especially true for community college students, who engage with college primarily through their classroom learning experiences, as opposed to the social domain beyond classroom settings (Hagedorn & DuBray, 2010; Hagedorn & Kress, 2008). Further, given the challenging nature and high level of rigor of STEM coursework, as well as the sometimes insufficient prior academic preparation, STEM students at 2-year colleges may experience barriers in understanding, finding relevance, or feeling motivated in their learning experiences (Lloyd & Eckhardt, 2010). Accordingly, an in-depth and nuanced understanding of 2-year college STEM students self-perceptions as learners presents a powerful vehicle for identifying venues of interventions aimed at cultivating and supporting the STEM talent pool toward success through and beyond the 2-year college sector.

Specifically, we seek to answer the following research question: How do 2-year college students participating in STEM classes and programs perceive themselves as learners? Through rich interview data collected from students enrolled in 2-year colleges in a Midwestern state, we describe these students self-perceptions as learners as they participate in and experience STEM courses and programs. Adopting a descriptive phenomenological research approach, our inquiry is aimed at revealing the fundamental structure underlying these students experiences as their self-perceptions as STEM learners are formed and transformed. By delving deep into students self-perceptions as learners, our study is a step toward resolving the issue of low persistence, completion, and upward transfer rates in STEM fields at 2-year colleges. In particular, engaging in this study enables us to identify potential spaces for constructing effective teaching practices and meaningful learning experiences, as well as to tap into students own agency, backgrounds, prior knowledge, and motivational beliefs to better engage them as STEM learners.

BACKGROUND LITERATURE

The empirical base on issues of success and attrition along the 2-year college STEM pathway is small but growing. Researchers have adopted several lenses when tackling related inquiry. At the policy level, articulation agreements play a role in creating a seamless transfer pathway (Zinser & Hanssen, 2006). However, articulation agreements alone are not enough to ensure successful transfer (Anderson et al., 2006; Jackson et al., 2013). Collaboration between local 4-year institutions and community colleges, such as aligned program curriculum, has been found to be an essential component (Jackson & Laanan, 2011). When it comes to practices at the institutional level, a few scholars focus on identifying course and program pathways most contributive to the persistence, completion, and upward transfer in STEM among 2-year college students (e.g., Bahr, Jackson, McNaughtan, Oster, & Gross, 2016; Hagedorn & DuBray, 2010; Hagedorn, Maxwell, Cypers, Moon, & Lester, 2007; Malcom, 2010; Starobin & Laanan, 2008; Wang, 2016).  

In regard to specific instructional approaches and modes, previous scholarship has highlighted participation in undergraduate research programs at 4-year institutions as an empowering foundation for 2-year college students to successfully transition to baccalaureate STEM programs (Leggett-Robinson, Mooring, & Villa, 2015). Within the classroom, research has addressed issues of maintaining student interest in the subject matter and peer learning as strategies for improving retention of community college students in sciences (Lloyd & Eckhardt, 2010). In addition, providing classroom advising by STEM faculty who can speak to the necessity of knowing particular content knowledge served as motivators for transfer-bound students in STEM (Packard, Tuladhar, & Lee, 2013).

With the mounting empirical interest in identifying factors underlying community college students pathways to success in STEM fields, it is imperative to develop a holistic understanding of how 2-year college students in STEM fields view themselves as learners, accounting for the broad-ranging backgrounds, academic and career goals, and learning needs and styles distinct to the 2-year college student population. In that light, a number of learning identity theories, including engineering identity (Meyers, Ohland, Pawley, Silliman, & Smith, 2012), mathematics identity (Cobb, 2004; Lesko & Corpus, 2006), science identity (Carlone & Johnson, 2007), learning identity (A. Kolb & D. A. Kolb, 2009), and STEM identity (Herrera, Hurtado, Garcia, & Gasiewski, 2012) lend important context to situate our study. These theories demonstrate that a number of factors influence how students make sense of their learning experiences. For one, students may need to feel affiliation with and interest in the subject matter, like mathematics, to develop mathematics identities (Cobb, 2004). Engineering students indicated that competence in making decisions, taking responsibility for their actions, and making moral or ethical choices were viewed as important skills to possess in pursuing this career (Meyers et al., 2012). Gaining and demonstrating competence in STEM, complemented by being recognized by others, is especially important for marginalized populations, such as women of color (Carlone & Johnson, 2007; Herrera et al., 2012). Despite their value, none of these theories purposefully deals with community college STEM students, whose characteristics and experiences may vastly differ from those of their 4-year college counterparts. Given the centrality of classroom learning in community college students success, a holistic yet nuanced understanding of how STEM students at 2-year colleges view themselves as learners is much warranted, especially based on their classroom learning experiences. Responding to this pivotal gap in the literature, we draw upon a phenomenological approach in analyzing originally collected qualitative data from interviews with STEM students enrolled at 2-year institutions, in order to capture ways in which community college students perceive themselves as STEM learners.

CONCEPTUAL FOUNDATION AND METHODOLOGY

PHENOMENOLOGY

Our study was executed within the framework of phenomenology. Tracing back to the branch of philosophy dealing with the phenomenon of human consciousness (Moustakas, 1994; von Eckartsberg, 1986), phenomenology as a qualitative research methodology is concerned with understanding the meanings of human experiences. The main purpose of phenomenology is to discover and describe patterns or structures of social and psychological phenomena as lived experiences of people (Giorgi, 1985; Greene, 1997; Husserl, 1970). Through this reflective analysis, a phenomenological approach allows the researcher to unravel the essence of experience of a given phenomenon for those who experience it (Patton, 1990). Phenomenological inquiry is particularly appropriate for our research focus because, as indicated earlier, there is extremely scarce prior knowledge on how 2-year college students perceive themselves as STEM learners as they participate in and experience STEM courses and programs. By collecting and analyzing interview data featuring students in-depth descriptions of their experiences and how their self-perceptions are formed and transformed as they navigate their learning experiences, we are able to yield deep insights into what it means to be 2-year college STEM learners.

Specifically, we adopted descriptive phenomenology (Colaizzi, 1978; Giorgi, 2009; Moustakas, 1994), which focuses on capturing and describing the essence or essential structure underlying a phenomenon (Giorgi, 1985). As there exists little to no prior empirical work that provides strong knowledge on 2-year college students lived experiences participating in STEM programs and courses, our goal for this inquiry is toward the description of such a phenomenonthat is, to reveal essential general meaning structures of this phenomenon. In light of this goal, a descriptive approach to phenomenology is appropriate, as it allows us to stay faithful to the rich and complex descriptions that participants provided us and, to the extent possible, restrict ourselves to making assertions which are supported by appropriate intuitive validations (Giorgi, 1986, p. 9). In the later section on data analysis, we further detail the procedures we adopted in alignment with conducting descriptive phenomenological research.

STUDY SAMPLE AND DATA COLLECTION

Research Sites

We collected the data for this study as part of an ongoing longitudinal mixed methods study of students beginning in STEM programs or courses in Fall 2014 at three large 2-year institutions in a Midwestern state. Specifically, research site A includes 2-year branch campuses of the state university system and enrolls nearly 14,000 students; its primary mission is preparing students of all backgrounds to transfer into baccalaureate programs. Research sites B, enrolling slightly over 16,000 postsecondary students, and C, enrolling approximately 18,000 postsecondary students, are the two largest institutions within the states 2-year technical college system that have both transfer and workforce development as part of their comprehensive mission. Well over 50% of the students enrolled in the three research sites are first-generation students, enrollment of students of color ranges from 13% to 47%, and female students constitute slightly over 50% of the student body. These 2-year colleges are also diverse in terms of their geographical location, spanning all major urban, suburban, and rural regions of the state.

Sample

The current study is situated within the larger longitudinal research project that follows a cohort of first-time students beginning in STEM at the participating 2-year colleges in Fall 2014 for 4 years (20142018). To account for differences across disciplines while maintaining analytical viability, STEM fields are classified into four categories based on the National Science Foundations (NSF, 2012) Science and Engineering Indicators: (a) biological/agricultural/environmental life sciences, (b) computer/mathematical sciences, (c) engineering/engineering technologies, and (d) physical sciences.² This Fall 2014 cohort includes both students who had already declared a program of study in any of the above STEM fields and students who had not declared a major but were enrolled in STEM courses that are designated for the defined STEM programs (i.e., excluding basic skills courses that are also required for other non-STEM majors) at participating colleges. During Fall 2014, roughly 3,000 students³ were selected to participate in the projects baseline survey that measures a range of factors pertaining to students backgrounds, motivation, and learning experiences during the first semester of college (See Appendix A for the survey content domains and sample items). Nearly 1,600 students completed the survey, for a response rate of 56.6%.

The sample selection of the present qualitative study drew on maximum variation sampling (Patton, 2002). Given its emphasis on selecting a wide range of cases to achieve rich variation on important dimensions, maximum variation sampling allows us to capture the most pronounced patterns and core experiences underlying students STEM learning experiences and identities that cut across a wide range of variation among students, disciplines, and institutions. Given the large initial sample size, when implementing maximum variation sampling, we combined techniques from both random and purposive sampling approaches. We first stratified the survey respondents by research sites, and then by STEM fields, followed by their responses to survey items measuring their learning experiences.⁴ We then randomly selected an initial pool of 100 survey participants from the joint distributions. Following that, we created an Excel spreadsheet listing this initial pool of potential interview participants and added their self-reported demographic information from the survey, such as gender, race/ethnicity, and age. Prior to recruiting interview participants, we purposively examined this full set of characteristics of the initial pool and identified students that we believe, as a whole, to possess a wide spectrum of attributes and experiences among STEM learners at 2-year colleges.

Data Collection

From May 2015 to August 2015, a team of four researchers conducted a total of 31 interviews for this study. Prior to the interviews, all researchers underwent a comprehensive process of training and calibration. First, the research team attended a day-long workshop specifically designed for team members to receive training on how to address all facets of the interview process, including principles and practices of ethical research conduct, and to review and practice interview protocols. Second, during and after the workshop, the researchers engaged in multiple rounds of activities where they worked in small groups to practice the interview procedures and techniques, rotating roles as the interviewer or interviewee. Upon completion of each round, the group listened to the recorded interviews, reflected on the interview process, and discussed both the techniques and styles that were effective and those that could be improved. Finally, throughout the data collection process, particularly during the first few interviews, the lead author, who also serves as Principal Investigator of the larger project, held post-interview sessions with the team members where reflections and feedback were offered to inform the ongoing interview process in a timely fashion. Through these procedures, the research team as a whole was able to streamline the interview procedures and ensure consistency of the interview process across different interviewers.

Based on our research purpose, we drew upon a semistructured interview protocol that centers on student perceptions of themselves as learners and their learning experiences within STEM classes. This interview protocol was also informed by and complemented the survey items addressing student experiences and motivational beliefs, but afforded a much more open space that encourages participants to share their thoughts and experiences as STEM learners (see Appendix B for the full protocol). Apart from the standard consent process approved by the Institutional Review Board, all researchers utilized a common interview fact sheet where they recorded participants self-identified race/ethnicity and/or other identities from the survey, as well as their chosen pseudonyms. Further, interviewers took detailed field notes to capture noteworthy environmental contexts, behaviors, and nonverbal cues that would not have been adequately captured by the audio recording. All interviews occurred at a location and time of participants own preferences. Most of the interviews lasted between 4070 minutes. With participants consent, all interview data were recorded and transcribed verbatim upon completion. See Table 1 for a list of the interview participants and their background characteristics.

Table 1. Demographic Background of Participants

Pseudonym	Race/Ethnicity	Gender	Program of Study
Alexander	Hispanic/Latino	Male	COMP/MAT
Bethany	White	Female	BIO/AG/ENV
Bill	White	Male	PHYS
Callan	Black	Male	BIO/AG/ENV
Elizabeth	Asian	Female	PHYS
Greer	White	Female	ENG
Gwyneth	White	Female	PHYS
Jasmine	White	Female	BIO/AG/ENV
Jennifer	White	Female	BIO/AG/ENV
Jennipher	White	Female	COMP/MAT
Jim	White	Male	PHYS
J. J.	White	Male	ENG
Joshua	White	Male	PHYS
Kanda	Native American	Female	COMP/MAT
Katy	White	Female	PHYS
Kelly	White	Female	BIO/AG/ENV
Kevin	Native American	Male	ENG
Kirsten	White	Female	ENG
Kooks	Hispanic/Latino	Male	ENG
Kwesi	Black	Male	COMP/MAT
Lotty	White	Female	BIO/AG/ENV
Mathais	Native American	Male	ENG
Nelkowicz	White	Male	ENG
Nico	White	Male	PHYS
Norman	White	Male	COMP/MAT
Ruiz	Hispanic/Latino	Male	COMP/MAT
Seamus	Multiracial	Female	BIO/AG/ENV
Stella	White	Female	BIO/AG/ENV
Temperance	White	Female	ENG
Tom	Hispanic/Latino	Male	COMP/MAT
Vern	White	Male	COMP/MAT

Note. ENG: Engineering & engineering technology; BIO/AG/ENV: Biological/agricultural/

environmental sciences; PHYS: Physical sciences, COMP/MAT = Computer science/math

DATA ANALYSIS AND TRUSTWORTHINESS

Our data analysis procedures aligned with the descriptive phenomenological method proposed by Colaizzi (1978). This approach relies on a distinct set of steps of data analysis often based on rich first-person accounts of experience collected from in-person interviews. We should note that, as Colaizzi (1978) pointed out, these procedural steps should be approached flexibly and are open to modification when appropriate depending on a given research context. Accordingly, with the fairly large number of interviews we conducted for this study, we adopted certain techniques from grounded theory (described later) in order to effectively organize our process of documenting, describing, and making sense of the data. In the following, we delineate the specific procedures we followed in analyzing the data based on the Colaizzi method (1978).

Step 1Familiarization with the data. Upon completion of verbatim transcription of the recorded interviews, all transcripts were read and reread several times in order to gain a holistic sense of the interview, the participant, and their experiences in STEM classes and programs.

Step 2Identifying significant statements. We returned to each interview transcript and extracted all significant statementsthat is, phrases and sentences that are of direct relevance to the phenomenon: 2-year college students experiences and self-perceptions as learners in STEM. An example listing of the significant statements we extracted can be found in Appendix C, along with how we moved from these statements to codes, categories, and themes in our data analysis process (with the first theme around mathematics as an example).

Step 3Formulating meanings. In this step, we engaged in a careful analysis of the significant statements we extracted and coded meaning underlying these statements. As Colaizzi (1978) noted, this is a precarious leap, in that the researcher must illuminate meanings that are not explicit in the original transcripts while trying to remain faithful to the original contexts of the data. In order to do so, the researcher must reflexively bracket their presuppositions, although complete bracketing is never possible. To facilitate this process of formulating meanings while keeping our presuppositions in check, we employed open coding from grounded theory (Strauss & Corbin, 1998) to identify concepts and categories describing participants lived experiences by segmenting the interview data into smaller chunks. The open coding process, involving both in vivo codes and codes that are more descriptive in nature, aligns well with our purpose of seeking meaning in STEM learners experiences and self-perceptions, essentially allowing us to adopt codes to identify and differentiate among various facets of the meaning structure.

Step 4Clustering themes. During this stage, the identified meanings, as organized by the codes and categories, were clustered into themes that are common across participants. To help bracket our presuppositions and stay close to the common themes across participants, we referred the identified themes back to the interviews for validation, a process guided by asking ourselves two questions: First, is there anything in the original interview transcripts about STEM learners experiences and self-perceptions that is not captured in the identified themes? Second, do the identified themes indicate anything that is not implied in the original transcripts? All four authors of the study took part in this process by individually reviewing the coded transcripts and the formulated meanings as outlined above. When engaging in this step, we also paid close attention to how prevalent the identified themes were across varying student backgrounds, particularly different STEM fields of study, in order to identify any major or subtle disciplinary differences within STEM that may shape the themes in substantial ways. Each member brought forth their reflections in response to these questions and considerations, along with any new observations, all of which were thoroughly considered by all researchers. The team then decided whether any merited an additional read-through of the transcripts, or whether they fell under any of the previously determined themes. Once it was determined that all potential new themes had been thoroughly considered and that, to the best of our ability, we had captured all implied themes that were core to participants experiences regardless of their disciplinary and other backgrounds, our themes were thus validated.

Step 5Developing an exhaustive description. Based on our analysis, we developed a full description of the phenomenon. We present this description in the results section, starting with a high-level narrative that synthesizes the core themes characterizing students self-perceptions and experiences as STEM learners. Later in the results section, we further illustrate the themes through an exhaustive elaboration of the specific findings as evidenced in students own voices, lending rich texture and context as we depict the phenomenon.

Step 6Identifying the fundamental structure. Closely related to and building upon Step 5, we pinpointed the fundamental structure underlying our findings through an integration and synthesis of the key themes and elements captured in the exhaustive description. This essential structure of the phenomenon was crystalized into a brief statement, as also shown at the beginning of the results section, following the high-level narrative description of the phenomenon.

Step 7Verifications of the findings. A final validating step recommended by Colaizzi (1978) involves returning to participants to seek their opinion on how the descriptive findings align with their experiences. We were able to incorporate this procedure to a certain extent during the larger projects follow-up interviews. In Summer 2016, the lead author conducted follow-up interviews with 14 of the 31 participants involved in this study in which each participant was provided a descriptive account of how their previous interviews were interpreted by the research team, along with the major themes gleaned so far. In all cases, participants confirmed that the main meanings we were making of their first-year interview data were accurate in capturing their experiences.⁵

In addition to these follow-up interviews, we adopted a number of other techniques to further ensure the trustworthiness of our data. To establish interrater reliability, we first independently coded at least a quarter of the total transcripts so that we could compare our coding process using the same data. Upon completion of the coding of every one or two interviews, we met to cross-check our initial codes, discussed any questions we had come across, and resolved discrepancies in our coding. For example, during these meetings, one researcher would read segments of the transcript aloud and explain how the data were coded. Other researchers explained how they coded the same data, and the team as a whole finalized the appropriate codes that would be applied. When discrepancies in the coding arose, we documented inconsistencies, recounted our individual coding processes, and discussed how to better align individual coding schemes to achieve reliability, which sometimes took additional reflection time after the meeting. To illustrate, one discrepancy among researchers was centered on how much context to include in each code. We decided to capture more context in order to fully capture the gist of the phenomenon under study, and practiced this together upon subsequent sections of the transcript until our coding schemes became more aligned. Throughout this process, we were able to establish interrater reliability in both the codes and the coding schemes used between multiple researchers.

Furthermore, because all interviewees also completed a comprehensive survey, we were able to draw upon participants survey responses to gauge their alignment with what participants shared with us during the interviews. When applicable, common aspects of students experiences and self-perceptions addressed by both the survey and interviews were cross-checked. For example, if a study participant described themselves as being poor at mathematics, we resorted to relevant survey items, such as those measuring mathematics self-efficacy (see Appendix A) to examine whether the student self-reported a low score on these items. Any inconsistencies or discrepancies were noted accordingly. Similar steps were performed in other areas common to the survey and interviews, such as learning experiences and attitudes toward math and science. Although it is impossible to determine the alignment between the two data sources with complete accuracy, given that both are reasonably characterized by subjectivity and their self-report nature, overall, there was a clear alignment between the two. Accordingly, such triangulation added to the trustworthiness of our interview data.

Finally, we must acknowledge our positionality as researchers and explain how we bracketed our presuppositions and assumptions as we made meaning of the data, especially given the descriptive phenomenological approach that we used. The lead author is a faculty member with a sustained research agenda focusing on community colleges and STEM education. Coupling this background with her role as Principal Investigator of the longitudinal research project that situated this study, she held a priori knowledge and assumptions based on her research expertise and familiarity with the larger topic under investigation, which may not hold in the current study and which may impose certain preconceived directions in the findings. The second author is a graduate student interested in the study of teaching and learning at community colleges. Notwithstanding her current knowledge of the broad academic and career trajectories community colleges provide for students, her prior educational background, situated in a system with limited opportunity for college students to alter their educational paths and where technical training is the sole mission of 2-year colleges, may have engendered presuppositions about the students under study that may not be true. Being both educated and holding professional positions in 4-year institutional settings in the Midwest, the third author is currently a graduate student participating in research on 2-year college students. She was previously exposed to assumptions that after high school, those who elected to attend the 2-year college in her hometown, a city with multiple types of postsecondary education institutional options, lacked ambition or were unable to obtain admission from a 4-year institution. Also a graduate student focusing on 2-year colleges, the fourth author attended and graduated from a 2-year college in the Southwest. This prior experience also came with assumptions and presuppositions about certain types of students (particularly based on age, gender, socioeconomic status, and race/ethnicity) who entered, persisted through, and succeeded in STEM programs at and beyond 2-year colleges.

As a research team, we adopted several methods to keep these presuppositions and potential biases in check. To begin, throughout our research process, we wrote memos documenting our engagement with the data, which allowed us to reveal and negotiate previously held assumptions and withdraw from making conclusions about the data based on those assumptions. To capture our positionality and ensure accuracy within our data, we used methods of multiple rounds of coding and triangulation, using the aforementioned coding techniques to enhance interrater reliability and address preconceived notions of these students that might not be true.   We also used reflexive debriefing sessions as an additional platform to discuss our memos, consulted with one another regarding our potential biases, and developed a shared documentation process to note these observations. Overall, by engaging with these procedures, we made a consistent and robust effort for bracketing.

LIMITATIONS OF THE STUDY

Our research has a few limitations that should be taken into consideration when interpreting our findings. To begin, given this studys particular focus and scope, we collected our data toward the end of participants first year of college. As time passes, it is possible that their learning experiences and perceptions of themselves as learners may change. Thus, our results do not necessarily capture the kind of transformations that potentially take longer to complete. Second, while our study features a robust number of interview participants, given our studys focus on the general essence of the phenomenon, we did not set out to examine distinct subgroups of students based on background characteristics, such as race, gender, and disability status. Accordingly, while our study yields a common structure of the phenomenon under investigation with our sample, future work needs to focus on important subpopulations of 2-year college students in order to reveal the potential nuances and differences in the experiences and self-perceptions of STEM learners across different subpopulations.

FINDINGS

Upon completion of the data analysis following the procedures detailed above, we arrived at a rich picture revealing the phenomenon under study. In this section, we first provide an exhaustive summary of the phenomenon, coupled with an integrated description of its underlying structure (see Figure 1 for a visual representation of the thematic structure underlying the phenomenon). Following that, we detail the four large themes that emerged to fully depict how 2-year college STEM students view themselves as learners as they experience STEM classes and programs.

EXHAUSTIVE DESCRIPTION OF THE PHENOMENON AND ITS FUNDAMENTAL STRUCTURE

To summarize, the experiences and self-perceptions of 2-year college STEM learners are characterized by the following features: (a) the students self-perceptions as STEM learners are deeply intertwined with self-perceptions as mathematics learners, rooted in students past experiences with mathematics learning, but are subject to change through current instructional practices they are exposed to; (b) as students navigate their learning experiences, they constantly evaluate and reevaluate who they are as learners in relation to others; (c) students sense-making of their STEM learning experiences is shaped by an internal process of recognizing the rewards and negotiating the challenges of studying STEM; and (d) students self-perceptions as STEM learners are also influenced by an external process of validation through milestone accomplishments, encouragement, and knowledge transfer.

While these four themes stand on their own as prominent defining elements of the phenomenon of our interest, they are also inherently interwoven pieces of a cohesive, complex whole. By further disentangling the structure within and across the themes, we are able to unfold the nuanced ways in which these themes interlace to underline students self-perceptions and experiences. To illustrate, it is evident that students self-beliefs as mathematics learners are central to their self-perceptions as STEM learners and often infiltrate other themes, such as by serving as a key reference point when students evaluate and reevaluate themselves as learners in relation to others, or by lending a key context through which external validation is offered. Similarly, the internal and external processes that shape students self-perceptions and experiences are deeply intertwined, in that students evolving awareness of their capacity to navigate these challenging fields of study is often activated or reinforced by validating experiences with external sources or signals, such as achieving tangible academic milestones, receiving encouraging remarks from instructors, and being able to transfer and teach the knowledge they have learned to a peer or friend. In the following, we present a full and exhaustive description of our findings underlying each distinct theme.

Figure 1. Visual representation of the structural elements of the phenomenon under study

MATHEMATICS LEARNING AT THE CORE

First, we found that students self-perceptions as STEM learners were largely embedded within their self-perceptions as mathematics learners, and such perceptions were deeply rooted in their past and present experiences with learning mathematics. Across the interviews, when participants described their academic and career aspirations and potential trajectories, they constantly positioned their perceived mathematics ability as a defining element. Fully aware that mathematics skills are foundational for most STEM disciplines, participants with negative self-assessment of their mathematics abilities tended to also consider themselves as unsuccessful learners in their specific STEM fields. For example, Katy Gordon, when reflecting on her learning experiences, commented on how mathematics influenced her perceptions of majoring in engineering: I think the idea of, of being an engineer myself, getting through a dense like, you know, a math dense program, that's terrifying. Like makes my heart beat faster just thinking about it. And on the idea of, of being on this treadmill that's going faster than I can walk, it just, I feel terrified.

For Katy, the intensity of mathematics required in an engineering program was the first thing that stood out to her, making her terrified at the idea of being in the field of engineering. Gwyneth, a student in an environmental science program, mentioned how mathematics presented a challenge for her: Math isn't one of my strongest points, which is also a bit challenging for going into something science related because there's a lot of math. But, I definitely think I can do it. I just have to try a little bit harder. Gwyneths self-perception as not being a strong mathematics learner translated into her view of the pursuit of science as a challenging path where she needed to put in extra effort.

As a recurring finding, the majority of our participants had expressed low self-efficacy in mathematics at least at one point, and often attributed it to their negative past learning experiences. Jennipher, a student starting in information technology (hereafter referred to as IT), reflected on how she used to have a poor self-image as a mathematics learner because of her high school teacher: When I was in high school, my math teacher said I would never accomplish anything in math because I was so bad at it, but she didn't realize like other people also suffered under her reign. Similarly, Nelkowicz, a returning adult enrolled in an industrial maintenance technician program, also illustrated this finding: For a long time I just had a poor self-image of myself, not being very good at math or not being very good at school the first few times around. Having struggled academically both in high school and when he first started college over a decade ago, Nelkowicz harbored a persistent self-doubt of himself ever succeeding in a STEM field.

On the other hand, students self-perceptions as struggling mathematics learners are subject to change, largely through more recent positive learning experiences, which many of the interview participants relayed as having transformed their self-perceptions as a mathematics and STEM learner. A central component of instructional practices that helps redefine these learners self-perceptions often boils down to how much the STEM subjects were taught using a hands-on, applied, or contextualized approach. Going back to Nelkowicz, when describing his blueprint class, he expressed his initial intimidation resulting from his self-doubt with regard to mathematics: I was really worried about it just because I'm really bad at math and I know that part of that class would be the math work, and so I was stressed about that. Despite his initial fear and stress, Nelkowiczs learning experiences turned out to be rewarding and validating: [the instructors] took me into their wing, like showing me stuff, like I've gotten more hands-on training than I ever would have like working a job for a year or more, so it's been invaluable&It's been extremely helpful and just as showing me that I can do a lot more than I thought I could. He went on to accentuate how such experiences transformed his mathematics self-image: I've always thought my math skills would hold me back. [My instructors are] actually showing me that it's not holding me back in reality; it's just in my head. So they've kind of helped me get over that stuff and helped me with opportunities.

Kooks, a student in electronic engineering, described becoming a stronger mathematics learner through the connections made between mathematics concepts and content in prior classes and real-life scenarios:

I definitely felt, you know, by this time I learned a lot more in math. I felt like I was stronger and my understanding of the concepts in the basic mathematics. But also I saw how certain concepts could link with other things in other classes. So since those classes were together, these concepts in one class would help with concepts in the other. And I also saw you know it made me realize that math was not just used in the classroom. It was used in things in real, you know, everyday life and so that made me a lot more interested in pursuing the mathematical and scientific field, you know? The technical fields and yeah. I guess I just felt, you know, I learned a lot more in those classes and just felt stronger as a learner overall.

Similarly, Bill, a student starting in chemistry and an aspiring pharmacist, elaborated on how his self-perception as a learner was transformed through mathematics contextualization:

Usually the way [my math instructor] explains things seems to really click for me. I'm a lot better when dealing with like the calculus concepts of real world application compared to just calculus as solving a problem that doesn't really relate to anything. And he relates most of it like almost all the exam questions are all like real world related, which works out a lot better for me. & It seems like he cares more than other professors, you seem like more of a person instead of just another number on his sheet.

Through these experiences, it becomes clear that such transformations in students self-perceptions as mathematics learners extend into their self-perceptions as a learner in their larger field of study and self-confidence in pursuing and succeeding in the field, a finding best captured in Nelkowiczs reflection:

Like I kind of viewed myself as sort of like poor, lower class, you know. That's it. That's where I would stay. But I don't think that's the case anymore. The sky is definitely the limit, so I'm just going to keep going. I mean it was just a couple years ago; I was just playing in bands around town playing music, had no future and no real desire to think about a future. But things change. People get older. So, time to grow up, I think. Just lucky that I found something that I can do.

SELF IN RELATION TO OTHERS

This large theme reveals the process of forming STEM learners self-perceptions as one that is constantly evaluated in relation to others. In other words, students self-perceptions as learners are shaped by their perceived differences between themselves and their peers. These perceived differences come in many different forms, such as age, gender, ability, skills, and disability status, but differences based on age and gender emerged to be the resounding patterns underlying participants self-assessment as learners. Taking age as an example, Norman, an older adult pursuing an IT program, commented on how he perceived his much younger student peers to be outperforming and outpacing him in academics:

There are a couple other classmates that were kind of like my son, you know, it's like, the knowledge sponge. We'd get done with a test, and I'd get beads of sweat, walk out and say, oh yeah, I thought the test went pretty good. So, there were definitely a lot of people in there who are much better academically than [me] they learned things faster, and they seemed to be able to retain it and apply it too, without even doing the projects and stuff. They were just light years ahead of me.

Norman associated age with the capacity to learn and considered his younger peers to be more capable of learning and especially learning faster. However, Norman did not ascribe to age as the only yardstick to gauge academic performance. Viewing being older as also his strength, Norman believed that his perseverance would make up for the fact that he was not that fast: So yeah, I can say, I'm not the smartest person on the planet, I struggle, but I can learn it if I put enough time and effort into it.

Like Norman, other older adults also tended to associate being older with other strengths such as perseverance and maturity as a learner. At the same time, this age-referenced self-perception was also fluid as students learning progressed. Callan, a student enrolled in agriculture, is a case in point:

I'm so much older than all of the students in the class& I felt they're still living at home with their moms; I'm taking care of kids at home. But it actually was pretty good. My teacher, I didn't she knew I didn't want to interact with [them], you know, I'm sorry I can see these kids over here and I'm like, okay, I just do my work, I'm good, I can just and she's not that kind of person: Everybody in this room is going to interact. Okay, then you need to read her [referring to a younger student peer] essay and she needs to read yours and give input. And I had to find out something about the person that was taking how many sisters and brothers you got? So by the end of the class some of the people I knew, and it was better for me to meet them. They were doing things that I wanted to do. And the ones that I thought were snobs they're just like me, too. So they were just younger. Just like me, they were scared of the class; they didn't want to fail. Some of them had a bunch of kids that were behind, then they tried to be strong for them. It was cool.

Callan initially viewed himself as a more mature and independent learner given his older age and more life responsibilities, as he perceived. However, through collaborative group work, he began to appreciate the commonalities he shared with his younger peers as learners and human beings, and eventually identified with his younger peers in stronger ways than he did when initially recognizing the differences in age.

Other than age, gender represents another salient reference point when students described themselves as STEM learners, particularly among women in our study. Often, female participants alluded to the chilly environment women students or instructors encountered in STEM fields included in our study. As Gwyneth described:

I think just being who I am makes a difference. Being a girl and being kind of small and whatever I think makes a big difference; I don't think people always take me very seriously. I have gotten some condescending comments just from, even from the classmates that I like in the program, that I'm kind of friends with, have made references that, you know, I'm not as smart as them, you know. There's only, there are only three girls in the program, and the rest are guys. So there's already, I can already see the difference there and then. I know there's some people that give the instructor a hard time, I think just because she's a woman. I can kind of see a difference between the classes also, so that definitely sticks out in my mind as a barrier.

Gwyneth was highly cognizant of the hostile climate for female students and instructors, sometimes leaving her both intimidated and pressured to act super smart as a woman. She stressed that such challenges were unique in STEM classrooms where women are severely underrepresented:

I feel like there was less pressure in the English class, cause there was more, more of an equal mix of girls and boys. And it wasn't a science class, so there wasn't as much pressure to get things right and to sound super smart, and there wasn't the gender inequality factor. So yeah, there's definitely more pressure in the science classes.

It should be noted that, for Gwyneth, whether in English or science classes, it is when women are equally represented in the classroom that the gender dynamic starts to shift toward a more welcoming and equal one. Echoing Gwyneths experiences, Greer shared that female students in her engineering program largely encountered similar barriers:

I feel like they're always watching me, almost just because I am a girl& In like the video classes, I wouldn't really say it too much. I just don't want like people or guys necessarily to look down upon me for any like little things that I say, because I feel like they wouldn't let it go. Like, even if they like make a mistake, like everybody has to let it go, because everybody's a guy and they just kind of joke around about it. But if I would, they would kind of think I'm not kind of smart as them almost. And that makes me kind of mad so I just, I dont really say too much besides the guys that I had every class with.

Wrestling with these gender biases, the female participants in our study clearly experienced self-doubt and intimidation as learners in STEM fields, as they shared with us. On the other hand, they also had developed coping mechanisms to forge forward with their learning. For example, Kanda chose to not let the gender dynamic dictate how she viewed and approached learning in her IT classes: I was also the only girl in some of [the classes], and I didnt let that get to my head too much. I was just like okay it is what it is, I can work with this and I, I think I managed to do well. Taking a more aggressive approach, Gwyneth took the pressure of having to act super smart as a motivating force that kept her going:

So, I try to show up and do what I have to do. I dont want to be a show-off, but when people, but when some of the guys try to compare their test scores and their grades with me, I say, yeah, you know I got an A too, or I, there was one time that one of the guys said, you know, oh, I got 102 on this test, what did you get? And I said, I got 106 [Laughs] and it felt pretty good. So, yeah there's...sometimes it feels a little bit like a game, like playing a game, but I think as long as I stay focused to do what I have to do and stay on top of things and not look stupid and not look like I'm falling apart and can't handle it, that I'll get respect from the rest of the class and get what, get everything that I need to do done, get where I want to go.

Regardless of the specific types of being different and ways in which such self-other references shaped these students self-perceptions as learners, many of the participants still managed to find value in the diversity in their peers as a factor that helps strengthen their own self-beliefs in learning. Tom, a student in computer science, demonstrated this point: Classmates have influenced how I see myself as a learner. Some of them are very good in the class that we had. I was like, If he can do it, I can do it. So I think that's my motivation. If others can do it, why not me?

INTERNALIZING THE REWARDS AND CHALLENGES OF STEM

The third theme characterizing our findings is that STEM students self-perceptions as learners were driven by an internal process of recognizing the rewards and negotiating the challenges of studying STEM. The majority of the interviewed students categorized their areas of study as challenging, but expressed appreciation of the rewarding nature of engaging with STEM subjects. For example, Kelly, a student in biological sciences, expressed how science inspired her as a learner:

Scientists have always been interesting, like reading science books and autobiographies on sciences. But I think that Newtonian physics was the first thing I learned that I could immediately apply to my life, you know? And that, like learning about momentum, torque, it just made sense. Oh, that's why that works, you know. So yeah science inspired me a lot.

Seeing the application of science concepts in real life was the root cause for Kellys continued enthusiasm about learning in the field:

That's why, I mean learning stuff and going, oh my goodness, that's why. That's why. Like glycerol, I really learned how to like clean up even my own house, because I know how like glycerol works and how ethanol disinfects and stuff. Just every, you can almost apply to every day and when you can't apply it to every day, you know it's answering the big questions in the world, at least for me.

Similarly, other students became or remained enthused and gratified learners when seeing the applied nature of STEM subjects. Kirsten spoke to this point when comparing her engineering classes with some humanities classes she took, and described how as a learner she valued applicable learning:

[Engineering classes] are pretty challenging. I don't know how to explain it. They're obviously like really different than like the humanities credits. I took a lot of humanities, last semester especially. They're pretty straightforward classes. I find it really gratifying to be taking classes that have marketable skills. I think that's really fun. Like when I took the last engineering class that I was in, we worked with like auto-CAD and stuff like that. I just thought that was so exciting, because it felt like for the first time I was learning something that was like real world applicable stuff that like when you get hired they actually care about.

As Kirsten explained, although classes in humanities were easier and more straightforward, she enjoyed her engineering classes more and found them to be gratifying due to their applicability:

I get a lot of gratification from doing something that is difficult and different. Something that's... I like to do something that is applicable and realistic. I value STEM [subjects] a lot. I had a big change and about my senior year I realized that STEM [subjects] are really important, and I just have a lot of respect for that.

It became clear that as learners, students highly prized the applicable nature of STEM content and its associated marketable skills. When they were able to see these elements through their learning experiences, these perceived rewards offset the challenging nature they also attributed to STEM subjects. Further, our analysis of the interviews shows that the challenging nature of STEM subjects often fueled participants drive to learn instead of acting as a barrier, not only because of their perceived rewards of engaging in these areas of study, but also due to their internal drive to take on challenges, as well as their resilience and effort. For example, Tom commented on how he felt about studying in IT, a field of which he had no prior knowledge:

Because one of the things that I like about the class is that it is something new to me that I never thought about before. I didn't know the field of networking exists or that someone would work in that field of networking. I think that's a thing that I like, because it's something new to me. Plus, it's like it is a challenge to learn new things.

Similarly, J. J. shared how excited he was about his engineering program: I'm excited. It's going to be a challenge. I enjoy challenges because it's a good way to gauge and see your, you know, progression and see where you're at things. So in that sense, I'm excited. As learners, both Tom and J. J. put themselves in a position to be intellectually challenged, and perceived taking on something new and challenging as an integral part of being a learner that continues to grow.

As a dominant factor shaping students perceptions of themselves and their fields of study, the potential to thrive on challenges also rests on students efforts and resilience, which emerged to be indispensable traits that helped students negotiate an often demanding and rigorous program in STEM fields. Reflecting on his experiences in the IT classes, Tom said:

I think this is going to help me if I choose a class or go into a field that I have not enough knowledge or I'm new to the field, not to be so afraid of that subject or that class or that field. Because I know if I put my time and effort, I can be a good person in the field or be a good student or understand much better the field than just going blindfolded.

Temperance also gave us an example of how she pushed herself through her engineering program:

Just start putting myself out there and start working in it going, okay, yeah, this is making sense. Things are clicking. I'm becoming more comfortable, more familiar with it. And then I'm like, yeah, I've got this, this is nothing I can't figure out. So it's basically just one step in front of the other and pushing myself. Hey, now you've got to learn this; now you have to learn this. And just kind of working myself through it so like, okay, yeah, I can do this. This isn't as hard as I thought it was.

Similarly, Norman described his experiences of battling through his intense IT program:

I'm only pulling 12 credits. For some people, that's a pretty light load. But again, I'm not a fast learner, but it is work, that has been my focus, that's my job. I spend all my free time studying, doing my assignments. I am learning stuff, even though I say it vaporizes after I take the test, a lot of it's sticking, and a lot of if I go back and review it, it will come back to me, in somewhere there in my brain. So review will bring it back, and I'm learning stuff, and it feels good to learn stuff. You know, like to know that I still can do it.

The effort and resilience demonstrated by Tom, Temperance, Norman, and other students transformed how they viewed themselves as learners, now with a much stronger sense of self-efficacy in learning, growing, and working in their chosen field.

EXTERNAL VALIDATION

The fourth thematic element underlying our findings centers around an external process of validation through milestone accomplishments, encouragement, and knowledge transfer. Milestone accomplishments are defining moments such as completing a course, passing a midterm or final, and obtaining a good grade. Ruiz, an IT student, shared how being able to survive midterms and finals, along with achieving a great GPA, infused confidence in himself as a learner:

It's more of like sink or swim type of situation. You do it or you don't. If I didn't take the chances and show up to those finals or midterms, and had that little panic attack going, I probably wouldn't have that confidence. And now that especially now that I'm using this in the field, it kind of made me into it a bit more I know I can do it, but I'm not going to freak out anymore type of situation.

Similarly, making through a full semester provided Kelly a sense of accomplishing a milestone that boosted her self-perception as a learner:

Making it through that first semester, making it through that first semester I felt great. I, you know, I hadn't been doing great for a couple of years, and I had no direction or anything. So it's given me confidence, and especially making it through the second semester, because now I made it through two semesters, you know? But I guess just it's like a 15% confidence boost every semester I get through.

Apart from reaching these milestones, encouragement from others, especially from faculty, also served as a major form of external validation. Jim, a returning student and electrician, shared his experiences with receiving encouragement from his instructor:

Yeah, it was more my teacher. When he was talking about it and stuff he goes, you're 4-year college material. He goes, you could definitely go farther than just an associate's degree. I never really had thought about it and stuff. I just kind of wanted to get an associate's degree, take a few programming classes, and see where it took me. But then all of a sudden, he was like, wow, you could probably end up with a job somewhere if you just take a few more classes and work towards a 4-year degree.

In this case, Jim reevaluated his self-perception in that he saw his own potential and ability to pursue a 4-year degree. Ruiz also commented on the importance of having instructor encouragement when deciding whether a given field is the right path for him and other students:

I know I had to talk to a professor a few times in regards to is this really the field that I want to go into? And he did encourage some of us in order to stay in the program. Some of the students did drop out during the first semester of the cohort. They chose to take a different path because I guess they found the classes hard even though the professors were very encouraging in situations where they would take time out of their schedules. These teachers are very busy. I've seen I know their backgrounds, and I know what they can do. And for them to say like, Hey, do you need encouragement or do you need help with something, send me an email or call me. That made a really big difference in a lot of the students path of staying in the program.

External validation also took the form of being able to transfer the newly acquired knowledge to others. J. J., an engineering student, described how being able to teach his fellow students what he learned reinforced his own positive self-perceptions as a learner:

Anytime that I have an understanding of the concept or when I'm working with other people and I can explain it and I kind of have that instant gratification of knowing that I understand it enough to teach it, that's kind of that's when I know I'm successful at it, is when I can relay it to somebody else comfortably and have it make sense to them. And that's why I would work with other people, is because if they had a question about something, I mean, you might sound kind of braggadocios or whatever if you're trying to like convey too much to them, but it's a good way to really understand whatever it is, you know, when you're repeating it, learning it and then, you know, giving it to someone else. So that's when I would feel a confidence boost is when I was at that point.

Jasmine also spoke about the power of being able to transfer the IT knowledge she learned in forming her own self-perceptions:

I feel really good you know that a year ago I was basically like just a regular user, and now I'm like a super-user [laughter] ofthat's Linux terminology. I guess what I mean is I like being the person who can answer questions and help other people. I like knowing how things work. Everything that I've learned in the last year has taught me that I have way more out there to learn than I thought. Like everything that I've learned in the last year has taught me how little I actually know. So it's kind of humbling on one side, but there's still so much out there to learn. But it's also kind of uplifting to be able to answer my friends' questions about how stuff works on the smartphone or why Facebook changed their privacy policies again, or you know it's cool. I like knowing how stuff works. So I like being able to help people and have the answers.

In the cases of J. J. and Jasmine, along with some other students, they saw self-worth when their capacity to transfer knowledge was evidenced by teaching others what they themselves had learned, which served as empowering experiences that validated their own learner identity.

DISCUSSION AND IMPLICATIONS OF THE FINDINGS

This study offers a comprehensive description of how STEM students at 2-year colleges view themselves as learners. Our findings serve as a sounding board for higher education practitioners and researchers to discover innovative ways to better assist STEM students beginning at 2-year colleges by tapping into their self-perceptions as learners. In particular, the quality of mathematics instruction, pedagogy, classroom climate, and support mechanisms are especially pivotal in this endeavor. In the following sections, we offer an in-depth discussion of our findings implications.

MATHEMATICS AT THE CORE OF STEM IN SHAPING LEARNERS SELF-PERCEPTIONS

To begin, one of our studys most prominent findings underscores the fundamentally inseparable nature of mathematics in forming STEM students self-perceptions as learners. Although prior studies have repeatedly pointed to the critical role of mathematics preparedness in charting a successful STEM educational pathway (Calcagno, Crosta, Bailey, & Jenkins, 2007; Crisp et al., 2009; Hagedorn & DuBray, 2010), little empirical work exists on exactly how 2-year college students self-perceptions as mathematics learners fit into their self-perceptions and self-assessment as they embark on an educational pathway in STEM areas. Our study reveals that mathematics is often perceived by students as a barrier to success, often due to their previous negative experiences in high school and in prior courses. This finding is critical, as students feeling anxious about mathematics typically underperform in mathematics courses (Beilock & Maloney, 2015). This may impact 2-year college students in more detrimental ways, as many of the students are adult learners who tend to have lower levels of mathematics self-efficacy compared with traditional-age students (Jameson & Fusco, 2014). Our findings show that students arriving in STEM programs and courses tend to already harbor mathematics-related anxiety; thus, it is of paramount importance that instructors teaching mathematics or STEM courses featuring a heavy mathematics component convey to students who describe themselves as being poor at mathematics that low self-efficacy and high anxiety represent more of a barrier than mathematics ability itself.

An encouraging finding of our study is that students initial self-perceptions as poor mathematics learners can be transformed into positive ones through learning experiences that situate mathematics within real-life contexts that matter to students. Ideally then, instructors should design their courses in incremental ways that guide students to practice hands-on learning activities and apply concepts to real-world situations. According to Perin (2011), contextualization of skills taught in a course increases the likelihood that those skills would transfer to a particular setting. Therefore, contextualization of course material, especially mathematics-related, could be a useful strategy to practice mathematics abilities and increase mastery of mathematics-related concepts that will be beneficial later. One suggestion for accomplishing this, for example, would be to enlist working professionals in STEM industries to serve as guest speakers and connect students with internship and career opportunities. This would demonstrate to students the applicability of course concepts to the fields in which they aspire to enter.

SELF VERSUS OTHER? CULTIVATING INCLUSIVITY

Our study also highlights the intertwined nature of self- and other perceptions that holds particularly intricate implications for older adults and female students. These complex dynamics can either result in students lower levels of self-confidence in their academic performance, seeing others as being more capable than themselves, or serve as a motivation for students to persist in their learning despite the perceived differences between them and their peers.

These findings bear several implications. First, some of these results resonate with prior scholarship that identifies similar barriers facing older adults and female students in STEM fields (e.g., Seymour & Hewitt, 1997; Starobin, Laanan, & Burger, 2010), as well as the agency and resilience demonstrated by these students, especially those attending 2-year colleges (e.g., Bukoski & Hatch, 2016; Montero-Hernandez & Cerven, 2013). Further, our results pinpoint how older adults and women in 2-year college STEM fields negotiate a complex process where reference to and comparison with others allows them to both acknowledge their vulnerabilities and tap into their own strengths as learners. These findings, however, do not imply that students would necessarily arrive at their own success without the support of their institutions. On the contrary, these results demonstrate how much work remains to be done in order to cultivate an inclusive environment for STEM learners from diverse backgrounds, especially female students who have been, and continue to be, underrepresented in STEM fields of study and professions.

In light of these findings, institutions should practice building community, especially for those underrepresented and underserved students in STEM fields. This could be accomplished through community-building activities within the classroom as well as social and career-related opportunities outside the classroom, which could involve effective online strategies to facilitate peer-to-peer interaction, given that time spent on campus is limited for many students. In addition, 2-year colleges may connect students to role models in their field, which could be especially helpful for students who are in the sheer minority in STEM programs, such as women and older students.

Even more importantly, STEM instructors must ensure that they create welcoming and inclusive classroom settings for all students. Notably, gender biases are prevalent in STEM fields (Xu, 2008), resulting in a chilly climate for female students (Burke & Mattis, 2007; Lesko & Corpus, 2006). Accordingly, female students enrolled in STEM classes feel more of a stereotype threat in play (Lesko & Corpus, 2006; Thoman, White, Yamawaki, & Koishi, 2008). All of this is clearly evidenced in our study, which further demonstrates how these gender biases and stereotypes extend beyond the experiential part of students learning and into the inner workings of how they view themselves as learners. Based on our study, while female students encounter such stereotype threats and associated discomfort early in their program, their stories are also stories of hope and triumph, as these women approach their learning experiences with rigor and resilience. Such success stories of 2-year college women in STEM fields must be heard, seen, and celebrated by instructors, advisors, program leaders, and institutions as a whole, in order to resolve persistent gender biases that plague STEM fields and to ultimately achieve a truly inclusive learning environment.

RECOGNIZING REWARDS AND NEGOTIATING CHALLENGES OF STEM

Recognizing the utility of STEM subjects and being able to master these often challenging and demanding fields of study (Abrahamson & Lindgren, 2014; Seymour & Hewitt, 1997) is also key to the formation of students self-perceptions as learners. Our study reveals the value that students place in identifying how the knowledge they glean from their classrooms could apply to industrial settings. For one, this result corresponds with our earlier discussion of the appeal and effectiveness of contextualized learning, which in this case translates into a sense of gratification from the learning experience when students see more of the applied, and less of the abstract, nature of a STEM subject. In addition, this finding is undergirded by the strong workforce orientation demonstrated by our research participants, as well as in prior research (e.g., Cox, Bobrowski, & Spector, 2004; Levin & Kater, 2013; Wang, Sun, & Wickersham, 2017). This finding holds significant implications for 2-year colleges concerning the types of skills and content knowledge they emphasize in STEM programs and courses.

Essentially, as our study demonstrates, when learning the STEM subject, if students are able to imagine themselves in action within the given field, they become engaged, interested, and confident learners. Therefore, it is crucial that explicit, contextualized, and actionable connections be drawn between STEM course content and the workplace. In addition to seeing STEM as rewarding fields of study, students self-awareness of their ability to negotiate these challenging subjects equally adds to their strengthened perceptions of themselves as learners. As the tenacity and determination exhibited by the students prove to be a major internal force that propels students forward, institutions and instructors should find ways to capture and recognize such attributes and efforts to encourage students to continue with their learning and to internalize their success, seeing themselves as capable and successful learners.

THE INFLUENCE OF EXTERNAL VALIDATION ON SELF-PERCEPTIONS

Our results also address the importance of external validation through milestone accomplishments, encouragement, and knowledge transfer. In particular, achieving personalized academic milestones aligns with the momentum-building perspective of promoting 2-year college student success (Wang, 2017). Thus, 2-year colleges must continue to help cultivate STEM students momentum toward reaching specific academic milestones in a well-scaffolded way, which may consequently build STEM students positive self-perceptions as learners. In this regard, the experiences of post-transfer students in STEM fields may offer unique insights into how milestones change over an extended educational trajectory. Furthermore, instructors in STEM courses must find innovative ways to acknowledge the progress of students that extend beyond grades, such as successful completion of course projects, applying course concepts to practical work experiences, and recognizing students who acquire jobs and internships in their field. Alongside this incremental and instrumental approach to constructing and honoring milestones, it is essential to also offer timely encouragement, which should originate back before college and extend throughout students educational journey. As Parsons (2008) demonstrated in a study focusing on African American students pursuing science education, school teachers are one of the significant figures who assume prominent roles in the lives of students with a long-lasting influence. Indeed, prior research has consistently demonstrated the significant impact of teachers high expectations, encouragement, and validation on fostering students academic self-perceptions, especially for students who have been historically underrepresented in STEM fields (Ogbu, 1990; Rascoe & Atwater, 2005; Russell & Atwater, 2005). Lastly, creating collaborative learning opportunities where peer teaching and learning are maximized can be another source of external validation, as students gain confidence by transferring their knowledge when interacting with one another.

CONCLUSION

Delving into the lived learning experiences of aspiring STEM students across three large 2-year institutions through in-depth interviews, our findings illuminate how 2-year college STEM students view themselves as learners. Our study captures how these students self-perceptions as learners are formed and transformed and illustrates how their prior and current learning experiences, self-perceptions as mathematics learners, background characteristics, and relationships with others interweave to shape and reshape how they view themselves as learners. While, to a varying extent, each of these components was touched upon in prior research, they were often either examined in isolation from one another or investigated through a correlational approach, without accounting for the dynamic ways in which these factors may come together as a holistic whole to explain 2-year college STEM students self-perceptions as learners.

By thus portraying how students evaluate and re-evaluate their self-perceptions in dynamic and nuanced ways, our findings bear significant implications for identifying opportunities for 2-year institutions to become well equipped to positively influence STEM students perceptions of themselves as learners as they work toward achieving their educational goals. Future research can draw upon our study in understanding the nuances associated with the key dimensions shaping STEM learners self-perceptions, and new ways to strengthen student motivation in pursuing further STEM coursework, transferring into STEM programs at 4-year institutions, and potentially entering these professions. Additional research should further determine what specific measures and venues 2-year colleges can capitalize upon to develop confident and collaborative learners who embrace the rewards and challenges of studying STEM. Furthermore, robust empirical work must continue to identify practices that STEM faculty can utilize to create more inclusive classroom environments where students wide range of social and cultural backgrounds are valued and stereotypes are combated, especially when it comes to supporting historically marginalized students in STEM disciplines. Taken as a whole, our study contributes not only a comprehensive understanding of the topic at hand but also fresh ways to conceptualize, practice, and research issues that matter the most to cultivate and support strong STEM learners starting at 2-year colleges.

Acknowledgment

This study is based on work supported by the National Science Foundation under Grant No. DUE-1430642. The authors thank Falon French, Na Lor, Kelly Wickersham, and Amy Prevost for assistance with research. The anonymous reviewers and the editor provided insightful comments that helped strengthen this work.

Notes

1. For instance, mathematics is often viewed as abstract (Dossey, 1992) due to its methodical attempts to determine the principles of regularities in axiomatic or theoretical systems, and to derive models of systems from real-world objects using symbolic representation and symbolic manipulation (Schoenfeld, 1994; Winkelmann, 2002). Science, in a broad sense, concerns the discovery and description of the natural law and its application to improve human means and ends, as well as identifying solutions to problems presented by the task of getting from theory to practice (Feibleman, 1961). Interwoven with science, but more practice oriented, technology aims to resolve practical needs and is more apt to develop empirical laws, often as the product of generalization from practice (Feibleman, 1961). Pragmatic and practical in nature (Becher, 1981), engineering adopts and applies existing tools to find practical applications of ideas (Feibleman, 1961; D. A. Kolb, 1981).

2. We acknowledge that this is by no means a complete definition of STEM, which in and of itself is an issue of much contention and inconsistency in the policy and research literature. Given a confluence of factors such as resource constraints and how STEM is defined by participating institutions and the funding agencys specific program supporting this project, certain relevant fields of study, such as allied health and nursing, are not included in the study.

3. For the larger research project, the target population size is 3,884, including 1,571 from the 2-year campuses of the state university system, 1,318 from one of the two comprehensive 2-year institutions, and 995 from the other. Of the target population, about 3,000 students were selected to participate in the larger longitudinal project, with a random sample of approximately 1,000 from each of the three research sites. Note that because the target population size of one of the two comprehensive 2-year institutions is less than 1,000, we essentially drew the entire study population from the institution.

4. We computed a mean score based on the survey items measuring students learning experiences, which was classified into three levels: low, medium, and high.

5. We should note that several participants mentioned new directions or aspects of their educational plans that were different from those mentioned in their first interviews, and these were further explored in the follow-up interviews. However, these additions were largely around their future education and career and did not contradict their core experiences as first-year STEM learners reported herein. Thus, these new data fall beyond the scope and focus of this particular study and are explored in greater depth in our other research.

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APPENDIX A

Example Survey Items

Example Base Year Comprehensive Survey Content Domains	Example Survey Items
Demographic background (gender, race/ethnicity, age, SES, etc.)
High school preparation in math and science	How many years of high school coursework in math did you complete? How many years of high school coursework in science did you complete?
Initial attitudes toward math and science	How important will it be for you to& a. &know mathematics to succeed at college? b. &know science subjects to succeed at college? How much& a. &will you need math for your future career? b. &do you enjoy solving math problems? c. &do you enjoy applying math in your daily life? d. &will you need science for your future career? e. &do you enjoy solving science problems? f. &do you enjoy reading science articles, magazines, or news?
Self-efficacy in math and science	How confident are you that you& a. &have the ability to master the material taught in math? b. &can do well on math exams? c. &can complete math assignments successfully? d. &can receive a good grade in college math courses? e. &can perform well in course activities in math classes? How confident are you that you& a. &have the ability to master the material taught in science? b. &can do well on science exams? c. &can complete science assignments successfully? d. &can receive a good grade in college science courses? e. &can perform well in course activities in science classes?
Learning experiences
-Student engagement in active thinking	How often do courses require you to& a. &apply what you have learned to real-life situations? b. &present what you have learned to instructors and peers? c. &explore key concepts, data, beliefs, or values within small groups? d. &think about instructors question on your own first, and then discuss the question with peers before the instructor explains the answer to the class?
-Student engagement in problem-solving	How often do courses require you to& a. &identify what you already know, what you need to know, and how and where to access new information in order to solve a given problem? b. &consider, compare, and generate multiple potential solutions to a given problem? c. &integrate skills and knowledge learned to solve problems? d. &work in groups to research necessary background material in order to solve complex, realistic problems?
-Student engagement in analyzing information	How often do courses require you to& a. &draw diagrams to visually show the connection between a new concept and other concepts that you already learned? b. &gather information from a variety of sources? c. &draw conclusions and make decisions given a detailed description of a situation? d. &evaluate student peers written work?

APPENDIX B

Interview Questions

1.

 To begin, could you tell me a bit about your experiences as a student at [name of institution], since last fall?

Potential follow-up questions

a.

From your survey responses, it looks like last fall you were taking courses or enrolled in a program in science, technology, engineering, and mathematics, or STEM fields. How did you like that experience?

b.

Can you walk me through what it was like to be in one of your STEM classes?

c.

What courses are you taking this spring? How have you found them so far? What stands out to you? Can you explain?

2.

 Thinking about the classes you took in the fall, or even now this spring, lets talk about your classroom learning and how you felt or feel as a learner related to some of the classroom-based activities that you did or are doing.

Potential follow-up questions

a.

What kinds of class activities did you participate in? Were there instructor-led or guided sessions that you remember? If so, can you tell me about them?

b.

Was there any project work involved in your class(es)? If so, can you tell me about it?

c.

When you think about completing course work, would you/do you get together with your peers to do homework or group projects? What about others, outside of those in your class?  Who in particular? What kind of things did you/do you work on?

d.

Do you feel that any of these or other things contributed to your STEM course experiences as a learner? How so?

3.

 Thinking about those same classes, were there any additional or elective experiences that you could engage in as a student?

Potential follow-up questions

a.

Did you take any trips or visit anywhere off-campus related to these classes?

b.

Were you involved in any clubs or other groups of students as a result of being in any of these classes?

c.

What about any other activities that you were or are involved with, hobbies, or groups that relate to your classes? Do you do anything outside of your classes that was or is related to what you are doing in school?

4.

 As things are now, what are your future plans for school?

Potential follow-up questions

a.

As you think about or make plans related to school, who do you talk to and what resources do you use to help make these decisions? Could you give an example or two?

b.

What or who would you say is the biggest influence on your choices and decisions related to your education?

c.

Do you see any barriers to realizing your educational plans? If so, what are those barriers? How could they be addressed?

d.

What do you see as helping you achieve the plans you have with regard to your education?

1.

 What kind of work or jobs would you like to do after you are done with school?

2.

 Is there anything else you would like to share with me related to what we talked about, or any other aspects of your experiences as a college student?

APPENDIX C Examples of Significant Statements and Coding Process (Based on the Theme Mathematics Learning at the Core)
Significant Statements	Codes as Interim Steps toward Formatting Meanings	Categories/Formulated Meaning Units	Theme
I think the idea of, of being an engineer myself, getting through a dense like, you know, a math dense program, that's terrifying. Like makes my heart beat faster just thinking about it. And on the idea of, of being on this treadmill that's going faster than I can walk, it just, I feel terrified.	math terrifying; engineering math dense; being on this treadmill thats going faster than I can walk	engineering program terrifying due to math	Math learning at the core
Math isn't one of my strongest points, which is also a bit challenging for going into something science related because there's a lot of math.	math not a strong point; going into science challenging due to math	low math self-efficacy; science challenging due to math	Math learning at the core
When I was in high school, my math teacher said I would never accomplish anything in math because I was so bad at it.	high school teacher diminished math self-efficacy	negative prior math learning experience	Math learning at the core
For a long time I just had a poor self-image of myself, not being very good at math or not being very good at school the first few times around.	poor self-image as a math learner and learner	poor self-image due to math	Math learning at the core
I was worried about [the blueprint drawing class] just because I'm really bad at math and I know that part of that class would be the math work, and so I was stressed about that.	bad at math; worried and stressed about class due to math	low math self-efficacy; Stressed about class due to math	Math learning at the core
&[the math instructors] took me into their wing, like showing me stuff, like I've gotten more hands-on training than I ever would have like working a job for a year or more, so it's been invaluable&It's been extremely helpful and just as showing me that I can do a lot more than I thought I could.	instructors took me into their wing; hands-on experience invaluable; I can do a lot more than I thought I could	instructor and hands-on learning improve math self-confidence	Math learning at the core
I definitely felt, you know, by this time I learned a lot more in math. I felt like I was stronger and my understanding of the concepts in the basic mathematics.	learned more math; understanding math concepts made me feel stronger	improved self-perception due to understanding math better	Math learning at the core
And I also saw you know it made me realize that math was not just used in the classroom. It was used in things in real, you know, everyday life and so that made me a lot more interested in pursuing the mathematical and scientific field, you know? The technical fields and yeah.	class helps see math used in things; more interested in mathematical and scientific field	interested in pursuing STEM because of applicability of math	Math learning at the core
I learned a lot more in those [math] classes and just felt stronger as a learner overall.	learned more math; felt stronger as a learner overall	improved self-perception learning more math	Math learning at the core
Usually the way [my math instructor] explains things seems to really click for me. I'm a lot better when dealing with like the calculus concepts of real world application compared to just calculus as solving a problem that doesn't really relate to anything.	instructor teaching method click for me; a lot better when dealing with calculus concepts of real world application	math instructor teaching approach helpful by using real-world application of math	Math learning at the core
My instructor&would you know start saying math concepts or whatever and he'd probably see all of us in the class not understand it and then he would slow it down and sort of use objects in reality to explain things and that has helped a lot.	instructor slowing things down; instructor using objects in reality to explain math helpful	math instructor teaching approach helpful by using real-world application of math	Math learning at the core
I've always thought my math skills would hold me back, they're actually showing me that it's not holding me back in reality, it's just in my head. So [my instructors have] kind of helped me get over that stuff and helped me with opportunities.	math skills hold me back; instructor showed math is not holding me back	poor math self-efficacy; instructors helped improve self-perception	Math learning at the core

Cite This Article as: Teachers College Record Volume 121 Number 4, 2019, p. 1-44 https://www.tcrecord.org ID Number: 22607, Date Accessed: 12/7/2021 12:36:17 PM Purchase Reprint Rights for this article or review