• epistemology;
  • identity;
  • retention


  1. Top of page
  2. Abstract
  3. Introduction
  4. Literature Review
  5. Methods and Analytic Workflow
  6. Findings and Analysis
  7. Discussion
  8. Conclusion
  9. Acknowledgments
  10. References
  11. Appendix
  12. Biographies


Students' identities and sense of belonging in a program affect whether they stay in engineering. Research suggests that students' ways of knowing and beliefs about what counts as knowing and learning – their personal epistemologies – can be aspects of their identities, or sense of self as knowers and learners.


Combining personal epistemology and identity theories suggests epistemological aspects of students' identities can influence whether they feel they belong in their engineering program. We have two research questions: Can a high-achieving engineering student be in danger of leaving a program because of a mismatch between epistemological aspects of his identity and his perceptions of the intellectual climate of their program? How does such a mismatch affect the student's day-to-day academic experiences?


For three years, we followed Michael, an electrical engineering student, through interviews and in-class observations. From more than 12 hours of semistructured clinical interviews, more than 10 hours of videotaped discussion sections, and two in-class observations in lectures, we produced a case study to characterize epistemological aspects of Michael's identity and how they influenced his perception of his program.


Michael expressed and enacted a sense-making epistemology that is a fundamental aspect of his identity as a learner. Due to this sense-making aspect of Michael's identity, he often felt alienated from the intellectual climate of his program, and he considered leaving engineering.


Researchers focused on student retention should attend to epistemological aspects of student identities. Instructors and administrators focused on retention should attend to the epistemological messages students hear from their programs.


  1. Top of page
  2. Abstract
  3. Introduction
  4. Literature Review
  5. Methods and Analytic Workflow
  6. Findings and Analysis
  7. Discussion
  8. Conclusion
  9. Acknowledgments
  10. References
  11. Appendix
  12. Biographies

People take these different [engineering] classes and they're like, “OK, I have to memorize these procedures for this problem and these procedures for that problem,” and they're missing this fundamental connection that everything has … And you know what though? I'm {sigh}—I've oftentimes sort of thought, like, to drop engineering and just do math. And then there'd be less classes and it'd give me more time to think about things in my own way. — Michael1 (Interview 6)

An extensive body of research shows that students' personal epistemologies – how they think about the nature of knowledge and knowing (Hofer & Pintrich, 1997) – affect how they approach learning in science and mathematics (Hammer, 1989, 1994b, 1994b; Muis, Bendixen, & Haerle, 2006; Muis, 2004; Schoenfeld, 1988, 1992; Schommer, Crouse, & Rhodes, 1992). Less studied, however, is whether and how epistemologies affect student decisions to stay in science, technology, engineering, or mathematics (STEM) majors. In this article, we explore links between epistemology and retention through a case study of Michael, a high-achieving engineering major who considered leaving engineering because his courses did not support his personal search for deep conceptual understanding.

Through seven clinical interviews and multiple classroom observations spread over three years, we obtained a sense of why Michael wanted to leave engineering. Michael's identity – his sense of self – was deeply entangled with his personal epistemology, his approach toward learning and knowing in engineering (Felder & Brent, 2004; Hofer & Pintrich, 1997). Michael identified strongly with a set of practices we and others (Redish & Smith, 2008; Schoenfeld, 1991, 1992; Warren, Ballenger, Ogonowski, Rosebery, & Hudicourt-Barnes, 2001) term sense-making: pursuing a deep understanding that integrates formalisms, concepts, and everyday or intuitive thinking. But Michael felt that his sense-making identity clashed with the norms and expectations of his engineering program. He felt out of place. As previous research has shown, students are disproportionately likely to switch out of engineering majors, and technical majors more generally, when they feel their identities clash with the prevailing culture of the program or field (Foor, Walden, & Trytten, 2007; Marra, Rodgers, Shen, & Bogue, 2012; Seymour & Hewitt, 1997; Stevens, O'Connor, & Garrison, 2005; Stevens, O'Connor, Garrison, Jocuns, & Amos, 2008).

In Michael's case, several predictors of retention suggested he would persist in the major. He was academically successful with near-perfect grades; his father and older brother were engineers; and he secured multiple summer internships that he says he enjoyed and benefited from. Despite these factors, Michael felt alienated from his engineering program. His sense of not fitting in intellectually was so strong he considered switching his major to math. We will argue that the entanglement between Michael's personal epistemology (Hammer & Elby, 2002) and his disciplinary identity (Stevens et al., 2005, 2008) highlights important implications for both research and programming focused on engineering student retention.

Two brief quotations highlight the increasing tension Michael felt as an engineering major and illustrate why his experiences speak to retention issues. In spring 2009, when we began interviewing him, Michael resisted compromising himself for the sake of an exam. Specifically, he vowed to focus on deeper understanding rather than computational quickness, even if he lost points.

Michael: You know, I just … would hate for my professor to be looking at my exam; and even if there was one conceptual question and I screwed up {sweeping hand gesture} everything else on the exam, all the computations, but [the professor] read [my conceptual answer] and it made sense and I got credit for that. I would feel {laughs} I would feel good. Where—as opposed to, . . . if I got some computations right but in the conceptual part where you have to show if you actually understand what's going on and you just say something completely wrong, {shakes head} I would just feel terrible. (Interview 1)

By spring 2010, however, Michael acknowledged the need to adapt to maintain his grade point average in light of the increasing workload:

Michael: For the record, I got straight A's last semester. A lot of people who use this rhetoric try to find excuses for defending their poor GPAs. Like, “oh, it's because I'm …” you know. So, you know, I'm not one of those students… . I'm just tryin' to, you know, add my perspective. So, I think the reason it actually hasn't affected my GPA is because I view learning as a hobby. So, as with any hobby, you shouldn't let it interfere [with] your GPA. But it is one of my hobbies, and I do enjoy learning, I just—up to the point where I get my grades done {raises eyebrow}. You know what I mean? (Interview 5)

Michael's demotion of sense-making to a hobby reflects compromises he felt he had to make. When needed, he pushed aside his commitment to deep learning, a part of his identity, to maintain good grades. In doing so, he illustrated a pattern suggested by previous research: students whose identities clash with their academic programs are more likely to stay if they can forge an adapted identity that represents a compromise between prevailing norms in the program and the student's original identity (Foor et al., 2007; Stevens, Amos, Jocuns, & Garrison, 2007; Stevens et al., 2005, 2008). Ironically, Michael's adaptations included suppressing his attachment to the kinds of sense-making practiced by professional engineers: seeking alignment among mathematical equations and models, formal and informal concepts, and real-world behaviors of systems (Gainsburg, 2006; Stevens & Hall, 1998). Were these compromises enough? At the end of this case study, we disclose whether Michael ultimately decided to leave engineering.

In this article, we use our analysis of Michael's experiences to argue three related points.

  1. Engineering education researchers and practitioners should broaden our sense of retention to include both people and knowledge practices. Engineering education already has the goal of increasing the diversity of people across categories such as race, ethnicity, gender, and socioeconomic status. We contend that engineering education reforms should also strive to support diverse, disciplinary-authentic ways of sense-making.
  2. Researchers and practitioners should include epistemological aspects of students' identities as an analytical focus for retention studies.
  3. Researchers and practitioners should increase the integration of studies that address program improvement and studies that address retention. Prior work and our current data both point to productive, underutilized methods for studying how programs can be improved and why students leave.

Our explication of these claims spans the next four sections. First, we review three key strands of literature (epistemology, identity, and student retention) that contextualize and ground our analysis. Next, we describe how we gathered and interpreted our data. Then, we present our data and analysis to show (1) Michael engaged in disciplinarily-authentic practices of sense-making; (2) his commitment to such sense-making was part of his identity; and (3) his sense-making identity led him to feel in opposition to the intellectual climate of his engineering program. Finally, we discuss the potential implications of this case study for research and programming aimed at engineering student retention.

Literature Review

  1. Top of page
  2. Abstract
  3. Introduction
  4. Literature Review
  5. Methods and Analytic Workflow
  6. Findings and Analysis
  7. Discussion
  8. Conclusion
  9. Acknowledgments
  10. References
  11. Appendix
  12. Biographies

Since Michael believed his “way of thinking” made him feel out of place in his engineering major (Interview 6), we appeal to three areas of study to explain that marginalization. First, research on disciplinary practice explores the ways of knowing, seeing, and interacting that characterize how individuals approach problems within domains. In reviewing that research we pay particular attention to relationships between disciplinary practice and personal epistemologies, or individuals' stances toward knowledge and knowing. Second, identity research asks how students define themselves as individuals and how they come to belong (or not belong) as members of a community. Lastly, retention research asks what factors keep students in the discipline, why students choose to leave it, and what we might do to keep them.

To motivate and contextualize our data analysis, we argue from the literature that sense-making is an epistemological aspect of disciplinary practice, identity and disciplinary ways of knowing are deeply connected (i.e., a student can identify as someone who approaches learning and problem solving in a certain way), and engineering retention research has focused on students' identities but has not foregrounded the epistemological aspects of those identities.

Sense-Making: An Epistemological Aspect of Disciplinary Practice

Research suggests that successful engineers (and some successful engineering majors) take a sense-making approach to learning and using disciplinary knowledge. Again, by sense-making, we mean that practicing engineers and scientists often try to seek coherence and meaning across multiple representations and sources of knowledge. Documented instances of practitioners engaged in such sense-making include architects debating acceptable seismic loading thresholds for a building (Hall, Stevens, & Torralba, 2002), engineers designing and validating computational models of physical systems (Ball, Onarheim, & Christensen, 2010; Bucciarelli, 1994; Gainsburg, 2006; Jackson, 2010; Rooksby, 2010; Tang, Aleti, Burge, & van Vliet, 2010), engineers coordinating cartographic and schematic representations of roadways (Hall & Stevens, 1995; Stevens & Hall, 1998), and scientists reconciling mathematics across gestural and pictographic space (Hall et al., 2002).

An example helps illustrate the depth of participants' sense-making and its connection to epistemology. In Bucciarelli's (1994) ethnography of a firm designing a photovoltaic system, Beth, an engineer, is building a computer model to help reveal the source of a mysterious performance fault in a solar array. She runs her model against sensor data from the field data; the results reveal a discrepancy. The sensors report the array is overefficient: it is outputting more energy than Beth's model predicts it should (p. 60). Beth ultimately discovers her model was right; a faulty sensor was overstating the array power. Crucially, Bucciarelli argues that Beth's thinking entangles mathematical relationships, graphical representations, and the real behavior of physical hardware as she works her way through the solar array malfunction:

To Beth the object photovoltaic module is as much the symbolic, mathematical relationships describing how the current produced by the module depends upon the sun's intensity, the module's temperature, and the battery voltage as it is the artifactual, physical panel in itself. The “I-V” (current versus voltage curve) as a whole can be read as a module's signature, an image Beth can sketch out from memory in a few seconds. (p. 63)

In brief, Beth sense-makes by coordinating and reconciling among multiple kinds of knowledge, including a mathematical model and sensor output. Furthermore, her sense-making reflects sophisticated epistemological stances toward the complex but integrated nature of knowledge, in this case knowledge encoded by a mathematical model and knowledge of physical hardware, and the need to monitor the comparative tentativeness of different bits of knowledge, in this case the sensor output versus her model (Buehl & Alexander, 2001; Elby & Hammer, 2001; Hammer & Elby, 2003; Hofer & Pintrich, 1997; Muis et al., 2006). Bucciarelli's (1994) detailed analysis of her practices gives insight into the associated disciplinary ways of knowing. Moreover, this contextual, practice-centered approach is methodologically different from those of other kinds of epistemology research. Specifically, the ways Bucciarelli, Hall and Stevens, Gainsburg, and others explore disciplinary ways of knowing is distinct from epistemology research that categorizes students along relatively static, context-independent epistemological dimensions (Carey & Smith, 1993; Marra, Palmer, & Litzinger, 2000; Palmer & Marra, 2004; Schommer et al., 1992; Smith, Maclin, Houghton, & Hennessey, 2000) or group students into clusters to describe their behavior (Bernold, Spurlin, & Anson, 2007; Lumsdaine & Lumsdaine, 1995).

We discussed Bucciarelli's example in detail because it epitomizes the nuanced multimodal nature of sense-making in engineering. Furthermore, it is not unique. Hall and Stevens (Hall & Stevens, 2000; Stevens & Hall, 1998) document two civil engineers engaged in intense sense-making about a proposed roadway design. As the engineers interact through talk, gesture, and inscriptions, they “make visible” features of the roadway that were otherwise obscured or flattened in existing schematic representations (Stevens & Hall, 1998, p. 133). Gainsburg (2006) finds similar phenomena when Tim, a structural engineer in her study, struggles to create an accurate model of weight loading on floor beams. At the heart of Tim's struggle is his attempt to reconcile how his physical intuitions about the world should guide how he computationally models the loads on the floor.

Ultimately, these in-the-wild findings mirror the conclusions of expert-novice studies more generally, which emphasize how experts possess deep, interconnected knowledge (Chi, Feltovich, & Glaser, 1981; Reif, 2007) and how successful students blend intuitive conceptual reasoning with symbolic mathematics (Sherin, 2001). Our point here, though, is that sense-making is an authentic epistemic practice with respect to “making and evaluating knowledge” in science and engineering (Sandoval & Reiser, 2004, p. 368). In the next section, we argue that particular strands of identity-based research theorize strong, educationally-consequential relationships among identity, knowledge, and practice.

Identity Interrelates with Domain Knowledge and Disciplinary Practice

How students identify as engineers matters for their academic and personal development (Jocuns, Stevens, Garrison, & Amos, 2008; Stevens et al., 2005, 2008), for retention (Foor et al., 2007; Walden & Foor, 2008), and for the kinds of engineers they may become (Downey & Lucena, 2003; Tonso, 2006a, 2006b). Within engineering education, research has focused specifically on the developing professional identities of undergraduate students (Eliot & Turns, 2011; Loui, 2005), students' sense of identification with the discipline (Foor et al., 2007; Murphy et al., 2007; Stevens et al., 2005, 2008; Tonso, 2006a, 2006b), and students' identification with the culture and values of engineering as a profession (Tonso, 2006a, 2006b; Walden & Foor, 2008). Since our analysis of Michael will connect his identity to disciplinary knowledge and practices, this section focuses on work that relates students' identities to the ways they interact with domain knowledge.

Stevens and colleagues (2005, 2008) presented a model in which “becoming an engineer” is a journey through a complex landscape that couples learners' identification with engineering, their developing disciplinary knowledge, and their trajectories of experiences in engineering education. Stevens and colleagues rely on an ethnographic conceptualization of disciplinary knowledge called “accountable disciplinary knowledge,” defined in terms of what counts as a student knowing something in engineering, when, and to whom. This ethnographic view of disciplinary knowledge offers perspective on how institutional structures present students “with different images of engineering knowledge across the many contexts they inhabit and over the four years of their engineering education careers” (Stevens et al., 2008, p. 357).

Structures that hold students accountable for knowing things can also work to inhibit or restrict students' access to domain practices. Nasir and Hand (2008) argue that identity formation is tied to access to practice and to social recognition. Studying how the same high school students identify while playing varsity basketball versus doing mathematics, the authors show that students' identity with respect to each practice is in part tied to what participation structures are available to them. For example, a basketball practice drill afforded players socially valued ways to express themselves through finesse and technique in a way that the rigid call-and-response assessment of their math classroom did not (Nasir & Hand, 2008). These differences in recognized practice in turn shape how students perceived their roles (as an empowered agent on the court versus constrained in the classroom) and how they were perceived by their peers.

Ultimately these contextual, practice-centered analyses reflect “a shift from a focus only upon knowledge, to one that attends to the inter-relationships of knowledge, practice and identity” (Boaler, 2002, p. 47). In other words, learners' perceptions of which practices constitute knowing and performing in a discipline can link to their identification or what we term disidentification with the discipline. In the next section, we argue that disidentification with certain epistemic practices (Sandoval & Reiser, 2004, p. 368) embodied by an academic program may make students feel marginalized; such marginalization puts them at risk of abandoning the discipline.

Retention Research Has Underemphasized Epistemology

Engineering retention research has sought to identify factors that predict whether students stay in the major (Felder, Felder, & Dietz, 1998; Felder, Forrest, Baker-Ward, Dietz, & Mohr, 1993; Moller-Wong & Eide, 1997), assess the impact of curricular changes (Felder, 1995; Froyd & Ohland, 2005; Olds & Miller, 2004), and understand what works to retain students and increase diversity in engineering majors (Murphy et al., 2007; Walden & Foor, 2008). Large-N studies include multi-institution ethnographic research on why students decide to switch or leave (Seymour & Hewitt, 1997), multiyear mixed methods studies on student persistence (Felder et al., 1993 and subsequent work; Marra et al., 2012; Ohland et al., 2008), and the creation of quantitative models to help understand whether and when students switch or leave (Min, Zhang, Long, Anderson, & Ohland, 2011).

Over the past decade, however, researchers have also analyzed small groups or even a single student in detail to reveal underexplored facets of student retention (Foor et al., 2007; Stevens et al., 2007, 2005, 2008; Tonso, 2006a, 2006b; Walden & Foor, 2008). Many of these studies point to the role of students' developing sense of self, i.e., their identities. Bryn, a student in Stevens et al. (2005), chose to leave engineering not because of academic difficulties or lack of internship opportunities but because the engineering work she had done “behind a desk” clashed with her identification as a “people person” (p. 6). Stevens et al. (2005) also argue Bryn felt “engineering education is not a site for personal development” (p. 7).

Students in other studies also express identity-linked alienation toward their engineering programs. Surveying 113 students who left engineering, Marra, Rodgers, Shen, and Bogue (2012) found that lack of belonging was the only significant predictor of whether those students switched to a nontechnical major (p. 16). More pointedly, Foor, Walden, and Trytten (2007) offer a case study of Inez, a student who in her own words wished she “belonged more” (p. 104) in engineering. Those researchers show the cultural and institutional obstacles Inez faced in her engineering major: her strenuous (and financially necessary) work hours that made it difficult to see faculty (p. 108); a physics professor who told her she should quit the major (p. 110); and the fact that she had not yet participated in co-op or internship programs, which cost her cultural capital in her classes (p. 110). Her experiences show how students from nondominant backgrounds with respect to socioeconomic class, gender, ethnicity, or other social categories can be disenfranchised within the education system. This disenfranchisement stems in part from assumptions and structures, including the myth that we need not change pedagogy to accommodate different ways of knowing, that are embedded within the education system and reflect the experiences of those from dominant backgrounds (Foor et al., 2007, p. 112).

So far in this section, we have shown how mismatches between a student's identity and various aspects of an academic program can lead to marginalization and a student's desire to leave. We now concentrate on one particular aspect of academic programs: the epistemic practices they enact and value. In doing so, we build on our earlier argument that a student's identity can be coupled to their stance toward knowledge and knowing in a discipline. This epistemic aspect of students' identities and of academic programs, and the possible mismatches between them, has received little attention in the retention literature. Yet we see glimpses of this pathway to marginalization in some of the studies mentioned above and in studies of mathematics students.

Boaler's prominent line of mathematics education research suggests that epistemological aspects of the classroom culture can lead to learners' forming a sense of self that is alienated from the discipline (Boaler & Greeno, 2000; Boaler, 1998, 2000). Studying 76 students across six British schools, Boaler (2000) argues:

for many [students], mathematics was of another world and to fully engage in that world, students needed to suspend their knowledge of the real world, suppress their desire to interact with others, and strive to reproduce standard procedures that held little meaning for them. (p. 392)

Epistemological issues come to the fore when students report feeling that mathematics classrooms relegate their roles to those of calculating “robots,” where “being good at mathematics appeared to some students to involve being less than human” (p. 386).

In another study, Boaler and Greeno (2000) documented that high school students' reactions to their math classes – and their likelihood of taking math in the future – were strongly influenced by whether the classroom pedagogy aligned with their senses of themselves as knowers. Students who viewed themselves as creative thinkers and defined themselves in part by this characteristic tended to dislike a traditionally taught math class. They perceived the traditional math class as too authority-driven and inhibiting their agency over their own thinking, but they tended to like a reform-oriented math class in which students worked together to figure out how to solve problems. By contrast, students who identified as good rule-followers in some cases found the reform-oriented course disconcerting. Boaler and Greeno (2000) ultimately argue that how students develop their senses of identity and agency with respect to mathematics pedagogy shapes their decisions about studying mathematics in the future. In other words, students decided whether to persist in mathematics in part by judging whether their identities resonated with the classroom's “epistemic climate” (Bendixen & Rule, 2004; Feucht, 2010; Haerle & Bendixen, 2008).

Within engineering education research, Inez's story (Foor et al., 2007) highlights the need to explore epistemological aspects of identity and their role in student retention. Explaining why she found a physics course particularly challenging, Inez noted, “They say: ‘Here's the equation, plug and chug.' But it wasn't like that for me. I pretty much failed every test I took” (p. 109). By contrast, Inez enjoyed laboratory and project-based courses that allowed more opportunities for collaborative sense-making. Describing one such course, Inez said:

I am a more hands-on person than a test taker … and it really interested me. I like a lot of discussion. I don't mean when the teacher asks the class and someone answers. Like I like it when five kids know the answer and want to share the answer. And we are supposed to give back examples. I think it helps us interact better with the teacher. And then of course when we are given labs to do things … to know how to use the things we are learning to do in some classes. (p. 110)

While Foor et al. (2007) do not label this episode as being about Inez's personal epistemology or epistemological aspects of her identity, Inez is referring to exactly that. Her interest and success in a course were tied to the alignment, or lack thereof, between her personal approaches to knowing and learning and the epistemic practices valued within the course. By contrast, she perceived physics class as rewarding “plug and chug” (memorization and rote use of equations), and she gives hints of disidentifying with that epistemic practice: “It wasn't like that for me.” Such epistemological disidentification with the culture of a classroom or program does not just create “barriers to [students'] knowing” (Boaler, 2000, p. 387); it potentially augments or diminishes students' conviction to pursue STEM (Boaler & Greeno, 2000). Our case study of Michael contributes to this argument.

Methods and Analytic Workflow

  1. Top of page
  2. Abstract
  3. Introduction
  4. Literature Review
  5. Methods and Analytic Workflow
  6. Findings and Analysis
  7. Discussion
  8. Conclusion
  9. Acknowledgments
  10. References
  11. Appendix
  12. Biographies

Background and Participant Selection

Our study of Michael emerged from an institutional review board-approved research project at Flagship State University (pseudonym) focused on electrical engineering (EE) students' use of mathematics while solving problems. For a sense of what EE at Flagship State entails, the curriculum involves a mixture of lecture courses (which often include smaller break-out discussion sections led by undergraduate or graduate teaching assistants), laboratory courses, and two courses explicitly designated as design courses. In 2009, the year Michael took Basic Circuits, the course was a lecture-discussion model with an undergraduate student leading Michael's discussion section. As of that year an EE major required 102 credits (not counting general education requirements). With nearly 75% of those credits comprising required lecture-laboratory courses, there was relatively little room for electives. Moreover, required design courses occurred only at the beginning (a three-credit introduction to engineering design) and end (capstone design course) of the four-year curriculum.

In the spring of 2009, as part of our research on engineering students' use of mathematics, we viewed videotapes of weekly Basic Circuits discussion sections. We first noticed Michael because he participated regularly. More than all but one or two other students, he consistently asked questions and participated in discussions. During informal time at the beginning or end of the discussion section, he often went to the blackboard to discuss the meanings of equations and graphs or debate the merits of a particular approach to analyzing a circuit. At the end of the semester, the first author invited Michael and seven other highly participating students to participate in one-on-one interviews.

We intended the interviews to explore the relations between the students' approaches to mathematical problem solving in engineering and their epistemological views about what counted as learning and understanding mathematics and circuit concepts. Many of our interviewees exhibited sense-making stances toward aspects of their classes. But Michael stood out as someone deeply committed to sense-making across multiple contexts. Michael spontaneously talked not just about his approach to problem solving but also how his sense-making is part of who he is. Intrigued by our first interview, we decided to continue exploring the relationship between Michael's epistemology and his identity. Michael accepted our invitation to participate in a series of subsequent interviews.

Though we interviewed many students who engaged in mathematical sense-making and appeared to enjoy doing so, Michael was unusually vocal about his views. His articulate discussion of his epistemological commitments and how they conflicted with the prevailing engineering school culture was uncommon in our data corpus. We stress, though, that our argument in this article does not rely on Michael's being typical. Rather, it relies merely on the empirically supported assumption that a nontrivial percentage of students have the capacity (Warren et al., 2001) and propensity (Redish, Saul, & Steinberg, 1998) to engage in conceptual and/or mathematical sense-making.

Data Sources


Our data had three sources:

Interviews Brian (the first author) conducted seven sessions, totaling over 12 hours, of one-on-one, semistructured clinical interviews (diSessa, 2007) with Michael, from May 2009 to December 2011. These interviews were held in a private room in the basement of an academic building. Interviews typically lasted 60 to 90 minutes. All transcript evidence we present includes the interview number. Interviews occurred on the following dates:

Interview 1May 13, 2009Interview 5March 17, 2010
Interview 2October 23, 2009Interview 6January 21, 2011
Interview 3December 4. 2009Interview 7December 1, 2011
Interview 4December 7, 2009

Recorded classroom discussions Our research team videotaped 11 of Michael's Basic Circuits course discussion sections, which totaled about 11 hours, in the spring of 2009.

Ethnographic observations In fall 2009, Brian conducted two ethnographic observations of Michael in a large, lecture-based, third-semester physics course focusing on optics, electromagnetic radiation, and relativity. Brian took field notes on the lectures and interviewed Michael immediately following one of those lectures (Interview 2).

Theoretical Assumptions

In analyzing Michael's epistemology, we did not assume that his epistemological views consist of relatively stable beliefs about knowledge (for examples of researchers who assume coarse-grained stable beliefs, see Haerle & Bendixen, 2000; Palmer & Marra, 2004; Schommer, Calvert, Gariglietti, & Bajaj, 1997). Instead, drawing upon a theoretical framework developed by Hammer and colleagues (Hammer, Elby, Scherr, & Redish, 2005; Hammer & Elby, 2002, 2003), we assume that Michael has multiple ways of thinking about the nature of knowledge, knowing, and learning, and that he might take on different epistemological stances in different contexts. The high degree of epistemological consistency we claim to document in Michael is therefore an empirical result rather than an a priori assumption.

Similar considerations apply to our analysis of Michael's identity. Identity research spans a spectrum in how it construes and operationalizes that construct. At one end of the spectrum, identity is treated as a relatively stable thing, changing or developing slowly in stages, and often considered internal to the individual (Meyers, Ohland, Pawley, Silliman, & Smith, 2012; Ohland et al., 2008). At the other end, identity is conceptualized as emerging from an unfolding of interactional processes; it is positional, contextual, dynamic, emergent, and multiply authored (Esmonde, Brodie, Dookie, & Takeuchi, 2009; Evans, Morgan, & Tsatsaroni, 2006). Crucially, the choice of a theoretical perspective for identity affects the sorts of phenomena one can capture and explicate.

Instead of assuming his identity was unitary and stable, we looked for evidence of how Michael (as well as other students, professors, and institutional forces) actively authored his identity over time (Holland, Lachiotte Jr., Skinner, & Cain, 1998). We drew on Gee's (2000) use of “authorization” and “recruitment” of identity as well as Stevens et al.'s (2005, 2008) idea of dynamic “identifications” to look for evidence that how Michael identifies in a given moment, while engaging in a particular activity, could depend on the social and material context. Since we presumed identity to be fluid and dynamic, we stress again that the consistency we find in some (but not all) aspects of Michael's “identity” is an empirical result, not an a priori assumption.

Interview Structure and Analytical Workflow

We need to discuss interview protocols and analysis together because they evolved in tandem. Our clinical interviewing strategy was, in the words of diSessa (2007), both “opportunistic” and “cumulative” (p. 526). By generating and modifying prompts both during an interview and in research meetings between interviews, we aimed to “evoke rich, informative responses” as a basis for understanding Michael and his way of thinking (diSessa, 2007, p. 526).

For our first interview, we had prepared a mix of protocol prompts. Some asked Michael to think aloud while solving circuits problems, while others were direct questions about how he studied and learned. Our original aim was to probe his approach to circuit problems and his associated epistemological views about how mathematical formalism and manipulations relate to physical concepts. Within the first few minutes, however, Michael's identity-rich comments caught Brian's attention. Consequently, Brian asked follow-up questions that drew out hints of a relation between Michael's epistemology, his identifications, and his dissatisfaction with his engineering program.

Brian reviewed the video, making a content log (Jordan & Henderson, 1995) of conversation topics, and then shared video clips with our research group (the three authors plus two more graduate students). Watching the video as a group (Jordan & Henderson, 1995), we looked for patterns indicative of Michael's epistemology and identity, and we received our first indications that Michael identified as a sense-maker and that this identification led him to feel like an outsider in his engineering program.

To put these interpretations to the test, we formulated questions for the second interview that focused on how he felt about specific experiences inside and outside school. Many of these prompts arose from spontaneous statements Michael had made in his first interview. For example, we invited Michael to reflect at length on the distinction he hinted at between his own sense-making practices and those of his classmates. Similarly, in Interview 5 we revisited this issue, probing Michael's views about how his father helped him with math homework as a child (and insisted on sense-making) after Michael in Interview 3 had complained about how his father wanted Michael to deprioritize sense-making as an undergraduate. With each interview, the research design evolved (Maxwell, 2005) to pursue emergent questions about both Michael's identification with sense-making practices and his subsequent identifications (or disidentifications) with his program (Jocuns et al., 2008; Stevens et al., 2005, 2008).

In our analytic workflow, Brian watched and reviewed all these clinical interviews, as well as video clips from Michael's discussion section. All three authors selected and agreed upon episodes that highlight the interplay between Michael's beliefs about knowledge and his sense of identity. Brian then transcribed the selected episodes, striving for faithfulness in capturing both Michael's verbal nuances and his gestures. All three authors met weekly with the full research group to review and discuss the selected episodes while looking at both the video and the transcript. Our ongoing aim was to produce a rich, detailed analysis of Michael's epistemology and identity by synthesizing specific interview and in-class moments.

Ethnographic Orientation and Methodological Rigor

We describe our study of Michael as ethnographically oriented because our aim was to provide what Stevens (2010) calls an endogenous view of learning phenomena, one that tries to understand learning “from the perspective of learners” (p. 82) and “within the broader frame of becoming” a particular kind of person (Stevens et al., 2008, p. 355). Within engineering education, we are not alone in such methodological commitments. Downey and Lucena (2003) use an ethnographic case study “to examine and describe the dominant tradition in engineering education from the students' points of view” (p. 169). Similarly, Foor et al. (2007) champion Abu-Lughod's (1991) “ethnography of the particular” because such a stance “provides a microphone for the voices of the marginalized to be heard” (Foor et al., 2007, p. 113). Finally, Stevens et al. (2008), reacting to analytical traditions that measure students quantitatively and without rich context, employ what they call “person-centered ethnography.” The aim of such ethnographic work is, in Richard Jessor's (1996) words, “to recover persons – to retrieve their individuality from the matrix of relationships that continue to be established among variables of scientific interest” (p. 4).

Since we study one student in great detail, our work aims at a different kind of rigor than is traditionally sought in larger-scale experimental and quasi-experimental work. Throughout our research process, we strove for what Guba and Lincoln (2005) call “interpretive rigor,” which they define as “defensible reasoning, plausible alongside some other reality that is known to author and reader – in ascribing salience to one interpretation over another and for framing and bounding an interpretive study itself” (p. 205). We also strove to capture the detail of participants' speech in interviews and classroom episodes. Some readers may find that the inclusion of stutters, false starts, and ungrammatical phrases make speakers in our study seem inarticulate. We understand that sentiment, but we believe those features of speech reflect both the structure and messiness of interactional events (Duranti & Goodwin, 1992; Ochs, Schegloff, & Thompson, 1996; Sacks, Schegloff, & Jefferson, 1974). Hence, our bias was to present as faithfully as possible the interactions that occurred, even when such presentations reveal the inconsistencies of real speech.

Part of our commitment to interpretive rigor manifests in our attempts at triangulation (Atkinson & Delamont, 2008, p. 300; Fontana & Frey, 2008, p. 300; Miles & Huberman, 1984, pp. 234–235). We sampled Michael across diverse contexts: in discussion section, in lectures, in interviews, and through analysis of both his written classwork and his verbal responses to conceptual questions during interviews. We also sampled longitudinally across six semesters of Michael's college experience. Consequently, across the three years of our study some of Michael's prospective experiences in interview i became present experiences in interview i + 1, and ultimately past experiences in interview i + 2. As Stevens et al. (2005) have argued, “The value of this approach is that we are generating data that allow us to explore how students progressively recontextualize experiences, which we take as a key manner in which people construct their identities” (p. 2).

In addition to triangulation, we also practiced what Miles and Huberman (1984, pp. 240–242) call “checking out rival explanations,” “looking for negative evidence,” and “getting feedback from informants.” We regularly included interview questions designed to test our ideas about what patterns we were seeing or to tease apart competing accounts. In finding patterns in the data, we carefully checked the data corpus for counterexamples. We gave Michael opportunities to accept, modify, or reject the interpretations we drew about him. In interviews, Brian often “revoiced” (O'Connor & Michaels, 1993) Michael's statements, giving Michael the chance to “challenge or affirm” the inferences Brian was making (p. 324). When Brian's inferences were not accurate, Michael challenged them. Finally, we sent Michael our completed manuscript for his review. “Overall,” Michael wrote to us by e-mail, “I think your paper accurately represents my views.” He added, “Thank you for constantly emphasizing that my gripes are not with any individuals, but are directed at an institution” (personal e-mail correspondence with Michael, January 12, 2012).

N = 1 Case Studies

We believe Michael is a “revelatory case,” what Yin (1984, p. 43) describes as an opportunity to observe and analyze an understudied phenomenon. Michael's story reveals the entanglement of epistemology and identity and how that entanglement can affect an engineering student's reactions to his engineering courses and program. Though Michael may be a lone individual, our case study throws into relief interactions and concerns about engineering education that transcend his specific experience. As Erickson (1986) argues,

the discovery of fully specified models of the organization of teaching and learning in a given classroom must precede the testing of generalization of those models to other classrooms. The paradox is that to achieve valid discovery of universals one must stay very close to concrete cases. (p. 130)

The value of N = 1 work is well illustrated by medical research. Leading medical journals predominantly publish large-N controlled studies, but they also continue to publish small-N and even N = 1 case studies that illuminate mechanisms and lead to hypotheses (Harkema et al., 2011; Jungebluth et al., 2011). Education research has also benefited from small-N and N = 1 studies. Most famously, Piaget's early clinical interviews with children (Piaget, 1960, 1970) led to hypotheses about cognitive development that later researchers explored in large-N studies. Constructivist theories of cognitive development and learning that trace their ancestry back to Piaget's early work continue to play a central role in education research. More recently, in math and science education research, small-N and N = 1 studies of teachers trying to implement reform-oriented curricula suggested a possible disconnect between teachers' instructional visions and what they actually do in their classrooms (Cohen, 1990). That disconnect was subsequently explored in larger-N studies (Desimone, Porter, Garet, Yoon, & Birman, 2002; Wilson & Berne, 1999). This line of work has greatly informed teacher educators and curriculum developers. Our point is that, just as N = 1 studies have a valuable place in medical research, they have a valuable place in education research. They can illuminate mechanisms and suggest new theoretical perspectives and hypotheses to explore in large-N studies.

Findings and Analysis

  1. Top of page
  2. Abstract
  3. Introduction
  4. Literature Review
  5. Methods and Analytic Workflow
  6. Findings and Analysis
  7. Discussion
  8. Conclusion
  9. Acknowledgments
  10. References
  11. Appendix
  12. Biographies

In this section, we present our analysis of segments from interviews and classroom discussions. We first argue that Michael consistently expresses and enacts a sense-making epistemology and that this epistemology is part of his identity as a learner. We further contend that his entangled identity and epistemology oppose what he perceives to be valued by his engineering program, an opposition that led him to consider switching out of engineering. We also present the complex story of how Michael dealt with his sense of marginalization in the How Michael Coped section. Later, in our Discussion and Conclusion, we use this case study to ground an argument that in order to support sense-making and retain those who engage in it, engineering programs should value sense-making as an authentic engineering practice in their courses and reward structures.

Michael Expressed and Enacted a Sense-Making Epistemology

In interviews with Brian and in classroom discussions with peers, Michael consistently exhibited sense-making, what we described above as seeking coherence among mathematical equations, formal concepts, and everyday or intuitive thinking. Here, we present just a few illustrative episodes. The first shows how Michael approached assessment in his Basic Circuits course. The second describes how Michael sought intuitive explanations in a Basic Circuits discussion section. The third shows how he continued trying to make sense of concepts in later courses.

Michael tried to sense-make on basic circuits exams

On a basic circuits exam in spring 2009, Michael was asked to solve for an unknown current in a circuit with multiple current and voltage sources. During the exam, Michael concluded that he must have set up his equations incorrectly because, according to his own math, the key unknown current seemed not to depend on all the voltage sources. (Michael was correct about his mistake; the unknown current did depend on all the voltage sources.) On the exam he wrote that he thought his equations were wrong and added that he could not figure out his mistake. Michael recalled this experience in the first interview:

Michael: Uh, and so what I ended up getting was that all I needed to do was to multiply this row by this vector to get [the unknown current]. And all of those [row values] were knowns. And that couldn't have possibly been the case. Because that was saying {points to the matrix equation} that we don't care about all these voltage sources. ’Cause this is actually a voltage source vector. These are just unknown currents. But these are specific voltage sources. So what that was saying was none of these voltage sources affected this … [unknown] current. And that didn't make any sense. (Interview 1)

We draw attention to two aspects of Michael's speech. First, his inability to reconcile his mathematical equation with the physical setup – why should his math ignore the effects of voltage sources he knew to be present? – drove him to re-evaluate his answer. Second, when Michael said “that was saying that we don't care about all these voltage sources,” he was pointing at a matrix equation. Michael treated the equation as saying something (Hammer, 1994a, p. 165) about the circuit's behavior, as expressing conceptual meaning rather than just serving as a problem-solving tool. In this respect, Michael's epistemological orientation toward the relation between mathematical formalism and the physical world mirrored the orientation of successful engineers (Gainsburg, 2006; Stevens & Hall, 1998).

Michael sought intuitively convincing physical explanations in basic circuits discussion

During one basic circuits discussion section in spring 2009, the class was reviewing for an exam. Adam asked the teaching assistant for the formula for energy stored in a resistor. Michael's follow-up questions reflected Michael's commitment to sense-making.

Adam: And what's the energy equation for a resistor? Or is there not one? There isn't one, right? Because it doesn't—

TA: There's no energy stored.

Adam: OK.

{The TA continues solving the problem and the class is silent until Michael cuts in about ten seconds later.}

Michael: Why is that so obvious? That there's no energy stored in a resistor? Is it just because all the energy dissipates as heat, right away, or? Like …

Angie (another student): There's no field to store it in.

Michael: Heat doesn't … Heat doesn't count as—that's what I'm saying. When it heats up it doesn't count as storing energy?

TA: No. It dissipates. It's given off. It's not keeping it in.

Adam: That was like, from our first homework.

TA: Y—yeah. Or second. First or second. I dunno, so, yeah. (Basic Circuits discussion section, February 27, 2009)

In this episode we see Michael questioning the teaching assistant's response to Adam. Michael refused to take it as obvious that there is no energy stored in the resistor. Michael's response, “Why is it obvious,” is significant because it reflects Michael's perception that the TA's answer, “There is no energy stored,” is unsatisfactory or at least incomplete. Michael's challenging that response stood in contrast to what the rest of the class did. Michael then tentatively offered the possibility that maybe resistors cannot store energy because all of the energy is dispersed as heat.

We see Michael's offering of heat “count[ing] as … energy” as an attempt to stay in dialogue – with both the TA and Angie – in order to hammer out a seeming conceptual inconsistency. But, Adam's response that it was “like, from our first homework” shifts the discussion away from “mechanistic reasoning” (Russ, Coffey, Hammer, & Hutchison, 2008). Adam's attempt to resolve Michael's difficulty appeals not to the substance of Michael's idea but to a sense that this material was already covered in class. The TA's agreement with Adam legitimates that warrant. A claim that material was already covered is, in this moment, an accepted response to one student's challenge that the concepts don't appear to make sense.

To us, Michael's interactions in that moment reflect the intensity of his search for a more causal explanation of the phenomenon. Even when Angie offered a technically correct answer (“no field to store it in”), that explanation failed to satisfy Michael. He continued to try to make sense of the phenomenon by expressing puzzlement that the heating up of the resistor does not count as storing energy. This episode illustrates that Michael's epistemological orientation toward sense-making was not something that emerged only in the context of interviews. He also enacted this stance in the classroom.

Michael continued sense-making in later science courses

In fall 2009, Brian observed two lectures of the third-semester physics course Michael was taking. Brian interviewed Michael immediately following the second observed lecture, which covered geometric optics and the production of real and virtual images.

The lecture had proceeded without student interruptions until the professor showed ray diagrams depicting real and virtual image formation, which included arrows that did not represent light rays. Then, Michael's hand shot up. “So what do those arrows mean?” (Field notes, October 23, 2009). After receiving an answer that didn't satisfy him, Michael approached the professor after class. Michael later recalled that interaction:

Interviewer: So what was it you wanted to ask him?

Michael: Well, so this thing with the uh—the light rays when it uh—when you draw the extended rays. So, when you have a virtual image as opposed to a real image. It, that wasn't … it wasn't really clear to me where you [the observer] were looking from, uh, in respect to the diagram with the—so—with the lens—and so—all, all that was sort of posted was this object is here and then here's the image. And so, I wasn't sure where you are—where your eye is. It would have been helpful if there were an eye in this diagram. (Interview 2)

Michael continued, elaborating on a physically intuitive meaning of the virtual image:

Michael: It's the virtual image because you're not actually, um {eight second pause} it's because it's sort of—it's like where you're tricked into thinking the image is. Because you know that light—that light rays are straight. As opposed to here with the real image where the light rays physically all converge here. So phys—{makes gripping gesture, pulling his hand down} like i—the physical image is there, as opposed to where you just think it is. (Interview 2)

Michael correctly explained that virtual images are a sort of “trick”: the rays change direction due to reflection or refraction, but as observers we infer the rays to have traveled straight, making us see the image at a place from which rays do not actually emanate. With real images, by contrast, rays actually come from where we perceive them to originate. As Michael continued, he arrived at an even clearer articulation:

Michael: Yeah, so I was trying to understand where this light source was, and where the eye is. And [the instructor] didn't really answer that {laughs} and I—cuz I was trying to basically understand … thi—like the what this—the difference between a real image and a virtual image is. Now it's pretty clear. I mean, so here, in the—in the real image case if you were to throw {gestures throwing with his right hand} a ball you would see it—it would look like it's going through this [real] image. As opposed to here, you'd see this [virtual] image and you'd throw a ball, and it would hit the lens before it ever got to the image. So that's the difference between a real image and a virtual image. (Interview 2)

Later in the interview, when we asked whether the ball-throwing analogy came from his class, Michael shrugged and said, “I just came up with [that] now while talking to you” (Interview 2).

Michael's question during lecture and his thought processes in the interview afterward reflect a commitment toward making sense of image-formation diagrams. In Michael's view, the physics instructor, in his lecture and in his after-lecture answer, was holding Michael accountable only for using diagrams to solve assigned problems. For Michael, this rote use of diagrams was unsatisfying; he strove to understand the relationships between the inscriptions and the underlying concepts.

The episodes of sense-making we have presented from multiple semesters are not idiosyncratic. Across topics and levels of sophistication, from basic circuits to advanced signal analysis, Michael tried to coordinate common sense, physical intuition, and mathematical formalisms. We can briefly mention other instances where Michael sought meaning making in contexts of circuit behavior, Fourier transforms, and sampling theory. In a basic circuits problem Michael tried to explain why a circuit that contained a variable-length wire of resistivity ρ could be modeled with the equation V=V0−ρIl (Interview 1). Later that year Michael tried to understand the surprising result that the convolution of two signals f(t) and g(t) is simply the product of their Fourier transforms (Interview 2). Finally, in our fourth interview together Michael explained how to convince oneself that, under the Nyquist-Shannon sampling theorem, one need only sample a signal at twice the maximum frequency component to get a high-fidelity reconstruction of the original signal from the sample (Interview 4).

Michael's Sense-Making Identity Developed in Opposition to His Program

In the previous section we argued that Michael both expressed and enacted a stable epistemological stance about how deeper understanding of phenomena involves integrating mathematical, formal conceptual, and intuitive reasoning. Such a stance aligns with those of successful engineers (Bucciarelli, 1994; Gainsburg, 2006; Stevens & Hall, 1998). In this section, we expand that claim and connect it to issues of student retention. First, we argue that Michael's epistemology has become part of his identity. Therefore, we think it would be an analytical mistake to separate Michael's identity from how he approaches engineering tasks (Nasir & Hand, 2008). Second, we argue that Michael's identity was developing in opposition to key intellectual aspects of his engineering program. That is, Michael identified himself as a deep sense maker, but he thought the larger institutional forces of his engineering program did not support that identity.

Michael's sense-making practice was deeply intertwined with his identity

For Michael, sense-making was not just a practice; it also enabled him to define himself in relation to his peers and the engineering culture on campus. An illustrative example comes from just six minutes into the first interview. Michael was talking about intuiting the conceptual meaning of first-order differential equations for circuits:

Michael: You can look at [the circuit] and sort of say, “OK, I know what's gonna happen even before I do the calculations.” So, you know you get an answer, and you can tell if it makes sense or not. (Interview 1)

When Brian asked Michael whether he often tried to check whether his mathematics and answer made intuitive sense, Michael interrupted:

Michael: You're asking me as an individual, or me as a representative of the people of my class? (Interview 1)

Michael here positioned himself against what he saw as “representative” of his class. The spontaneity of his clarifying question and its emergence in response to a question that did not target his relation to other students also suggest that Michael had previously thought about this distinction between himself and his fellow students. Furthermore, Michael's mention of this distinction in response to a question about his sense-making suggests that disidentification with his fellow students in this moment has epistemological undertones.

Further clarifying his stance toward sense-making, Michael expressed strong identification with essay tests that encourage explanation of physical processes (something he discusses in many interviews), while simultaneously disidentifying with the rote use of formulas. The transcript continues:

Interviewer: You as an individual. I'm interested in “Michael.”

Michael: Oh. You're interested in Michael? OK. So. Yes, I always do that to see if it makes sense. I always—in fact I don't even really like doing the formulas to begin with. I hate the computation aspect of the class. I would much rather have it be an essay test and be able to talk about everything that's goin' on.

Interviewer: Did you feel that way before you started the [Basic Circuits] course?

Michael: Yeah. I've always felt that way, even going back to high school. I never liked doing calculations. (Interview 1)

The episode illustrates a tension in Michael's identification with sense-making: he felt that valuing sense-making and acting on those values in class set him apart from fellow students. And, as discussed below, his stance toward sense-making made him feel at odds with the institutional culture. These issues carried deep personal import for Michael; when discussing the role of sense-making in Basic Circuits homework or exams, his language was often emotionally charged, as reflected in inflection and gesture.

It is tempting to think Michael's preference for essays reflected a weakness in his ability to do calculations. But his performance suggested otherwise. A look at his homework and exams showed that he generally scored well on computation-intensive problems, and he earned an A in Basic Circuits. Indeed, he maintained a near-perfect grade point average during the six semesters we followed him.

In another excerpt, Michael explained that he spent far more time working on conceptual questions than he did on computational ones. He did so not because the conceptual questions were harder but because they represented something more important to him:

Michael: I mean, on every homework problem there were—it was about half computations, half explain what this physically means. Um, and, you know the—doing the computations didn't take very long in the homework, but, the homeworks always took a long time because I really—you know I—I was, was interested in getting to the bottom of what was going on. I didn't wanna just make something up to get partial credit and then turn it in and move on. I—I actually wanted to say the right thing. And that was pretty tough. (Interview 1)

We stress that Michael's desire to “say the right thing” meant more than simply wanting to answer correctly. Rather, it represented his dedication to explaining well – a trait he half-joked was seen as problematic:

Michael: Some people say it's a good thing, some people say it's an illness. I generally have a lot of pride and I feel that—you know, you may, you don't know the formula right, you screw something up, whatever. It doesn't really—it's not really reflective of your intelligence per se. It's just reflective that “oh you didn't—you made a dumb mistake.” Or you didn't memorize something correctly. But I feel that if you say something that makes absolutely no sense, like that's just the worst thing for me. (Interview 1)

Michael's identification (Stevens et al., 2005, 2008) with his sense-making is central to our account and is strongly supported by Michael's choice of language: that he had “a lot of pride” in sense-making; that he would “feel good” if an answer made sense and terrible if it did not; that “screwing up” a calculation is not reflective of his intelligence but saying something nonsensical would be “the worst thing for him” (Interview 1). As noted above, he expressed similar sentiments over two and a half years of interviews. And, although he was half-joking, Michael's remark that some people call his dedication to sense-making “an illness” points to Michael's feeling that his sense-making stance put him in opposition to the intellectual climate of his engineering program.

In sum, Michael's deep engagement in sense-making was not just something he did; it part of who he was. His commitment to sense-making helped define him. But, that commitment also set him apart from others and created a clear distinction, in his mind, between his own values and the values he saw as enshrined in the broader institutional structures and practices of Flagship State.

Michael disidentified with school and the personal forces that pushed against his sense-making

Michael did not think most engineering courses or their math and science prerequisites supported his views about learning. On a Basic Circuits (spring 2009) exam, for example, he correctly answered the conceptual questions that required causal reasoning and argumentation. But the instructor designated those questions as extra credit, signaling to Michael that they tested the periphery, rather than the core, of what students should know:

Michael: What [that exam] was intended for was, so, if people got none of the conceptual things right they could still do well. But, it sorta was the opposite for me. The {sarcastic air quotes gesture} “extra credit” helped balance out for the things that I should have been able to just regurgitate. (Interview 1)

The “conceptual things” were personally important to Michael, but they seemed instructionally peripheral.

As we followed Michael into the fall 2009 semester, his concerns about the epistemological messages sent by his science and mathematics instruction grew deeper. Recall Michael's question in physics class about where the eye is located in diagrams depicting real and virtual image formation. Recall also the subsequent reasoning tool (thinking about throwing a ball at the image) he built to help him understand the diagrams and physical processes (Michael's continued sense-making section above). In that interview, his explication of the analogy led to a critique of his physics course:

Interviewer: So if in that moment in class he had just like—if he could just, you know if he could—if he had a tablet PC where he could doodle on the diagram. If he had drawn in an eye…?

Michael: {nods} Oh yeah.

Interviewer: Would that have just snapped it—

Michael: It probably would've just, yeah.

Interviewer: But the story about the ball where you—where you'd throw the ball through the image. That, like, he didn't talk about that in class. That's something that you just—

Michael: I just came up with now while talking to you. {shrugs} Uh. See, here's the—I mean, the main problem is, even if he drew it in class I dunno if it would've all clicked. It actually only completely clicked just now. The problem is I don't really understand how one is supposed to truly learn {pause} physics in a lecture format. Or math or anything technical for that matter. I mean, a lot of these things require you to—I mean the way I learn is I go at my own pace. And I don't go to the next topic until I completely understand the previous topic. Cuz in lecture, OK, here's some material, here's some more material and nothing really sinks in. And then you have to go back and think about it anyways. It just seems like lecture [is] a waste o' time, quite frankly. {laughs} I go because there are pop quizzes. (Interview 2)

Michael's frustration stemmed from a mismatch between the way classes were taught and how he viewed learning. In Michael's view, learning centered around his personal construction of a deeper understanding of the material by building up that understanding at his own pace. Lecture, by contrast, seemed to be driven by the instructor's pace and afforded few opportunities for students to construct deep understandings. To be clear: Michael consistently expressed interest in the course's content and in constructing his own understanding of it. His complaint was that lecture never seemed to be designed for students to start constructing a deeper understanding. So deep knowledge construction became a project Michael had to accomplish on his own.

When we asked Michael how a course could be taught in a way more helpful to him, his words and gestures highlighted both his epistemology and the way it placed him in opposition to the intellectual climate of his program. His comments here center on a fundamental implication of a refraction equation that went under-explained (from both Michael's and Brian's perspective) in that day's lecture.

Michael: Every professor sort of does it to a degree where I think they just get—like occasionally they get overambitious as far as what they wanna cover in lecture. And they just feel that—they just end up trying to cover too much in lecture than they can. And then it ends up hurting the—all the other material. So in this particular case, I mean the way I think it shoulda been done is, you know, basically, “from this {gestures to imagined formulas} you can do this on your own time, and the derivation's in the book; you end up getting this formula.” And then spend five minutes talk about what this formula {stabs hands forward} means when you look at it, and how you would actually {raises eyebrows} use it. (Interview 2)

Above, Michael made clear that the act of instructors presenting equations in class is not all that helpful to him; what matters is explaining “what this formula actually means when you look at it.” Our field notes from that lecture (October 23, 2009) show that Michael's critique is warranted. In the two lectures we observed, his Physics III professor spent almost no time helping students make sense of the structure of the equations presented or discussing how one could be convinced that they appropriately model physical behavior.

In summary, through the fall of 2009 Michael continued to experience tension between what he considered to be deep understanding and the kinds of “knowledge” expected and rewarded by his courses. Stevens et al. (2008) theorized this issue as one of “accountable disciplinary knowledge”: “actions that when performed are counted as engineering knowledge” (p. 357). Michael wanted to know how and why equations worked the way they do. He said, however, that such things were rarely or never tested on exams. So he deliberately spent considerable time trying to understand things he was certain his institutional program would not hold him accountable for knowing.

This tension between deeper understanding and exam preparation came to a head when Michael had a discussion with his father, a professional engineer, about the hours Michael was spending outside of class trying to understand derivations. While his father felt Michael's extra work was time consuming and unnecessary, Michael believed it to be worthwhile and personally important:

Michael: [My dad said] “you're just an undergraduate. Nobody expects undergraduates to understand how anything works. That's why you go to graduate school.” I was like “look, you know. I'm gonna be an unhappy person if I have to … I have life goals other than to just get a good grade on the exam. Other things are important to me.” (Interview 3)

Again, we see Michael connecting sense-making to personal happiness and life goals; sense-making is part of who he is. This scene encapsulates the tension between Michael's identification with sense-making and his disidentification with larger institutional forces – represented in that moment by his father – that push him away from sense-making.

In sum, Michael saw himself as an outsider because of what he jokingly called his “illness” (Interview 1), his need to make sense of things. Further, he was painfully aware that his views about learning constituted a kind of counterculture in his engineering program. Michael's sense of marginalization was so strong that he began a spring 2010 interview, unprompted, with the following warning:

Michael: I'm not sure how interviewing me is useful for your project … I dunno if you realize and maybe I did a bad job of explaining it. But, I'm probably like, a fringe as far as students go. As far as my views, you know, my ideals. And so, I'm just curious if you're trying to make like a statistical argument. I'm probably hurting your thesis, whatever it is. (Interview 5)

Michael's caution that he was “hurting [our] thesis” illustrates the pattern we saw throughout the interviews: Michael's sense-making identity being defined in part by its opposition to what he took to be the norm. He often offered comparisons – such as Michael versus what is “representative” of the people in his class (Interview 1) and typical students versus Michael's “fringe” (Interview 5) – that emphasized the oppositional status of his sense-making identity.

As discussed in our literature review, the claim that engineering programs put identity-based pressure on students is not new (Foor et al., 2007; Stevens et al., 2005). Michael, however, provides some of the first evidence that students can feel out of place – that they can experience tension between their identities and their engineering programs – for epistemological reasons as opposed to social, cultural, or personality-based reasons. And, as we subsequently learned, Michael's feelings of intellectual marginalization continued into his third year of the program. In the next section, we explore how Michael's “ideals” (Interview 5) met with friction in his upper-division coursework.

Michael had more “terrible” experiences in upper-division courses because those courses did not help students build from intuition or find coherence among concepts

Brian interviewed Michael again in the winter of 2010–2011. It had been almost one year since we last spoke in the spring of 2010. Before Brian and Michael could even get into the interview room, Michael began talking about an advanced electricity and magnetism (E&M) engineering course he had taken.

Michael: I took an electromagnetic theory class in the fall which was a both terrible and excellent of an experience.

Interviewer: Huh. OK.

Michael: It gave me more of a headache than any other class I've ever taken. The reason it gave me a headache: there were things that bothered me that didn't happen to bother anyone else. And that was what upset me even more. (Interview 6)

Michael then described what made the experience “terrible”: the course's routine avoidance of deep conceptual and epistemological issues. He cited an example where students had to calculate the current through an ideal conductor. The calculation, and its seemingly paradoxical implications, troubled Michael. He thought, if current is moving charge and the ideal conductor by definition has zero charge density at all points, how could one calculate the current through it? (Interview 6).

Resolving this perceived paradox was a challenge for Michael. He asked professors, checked out several E&M books, and even spent a weekend “where I did nothing except think about those sort of things” (Interview 6). Throughout his efforts, Michael noticed how learning resources, including textbooks, course lectures, and even engineering peers, were insensitive to the kinds of issues he was struggling to understand.

In presenting this episode, we want to stress that Michael did not fault his E&M professor. Quite the opposite: Michael described his professor as “really good,” saying “he spent a lot of time with me. I mean, I'm very grateful. Like, at night basically. Almost like in the evening he stayed like, past his office hours” (Interview 6). Rather, Michael's criticisms targeted a deeper, pervasive avoidance of sense-making in typical engineering education.

In our interview, Michael described how the goals of the course seemed to oppose the kind of deeper learning involved in his search for resolving the current-through-ideal-conductor problem. He chose, at times, to address that opposition by postponing the pursuit of deep learning:

Michael: So that [first contradiction] was what really caused me a lot of grief. And then finally I basically got to a point where I knew how I … I-I-saw like light at the end of the tunnel in a way, that if I spent enough time I could figure out a way to explain it. And uh, but basically this sorta got me used to—like that was just shocking. But then I got sorta immune to—er numb to the fact that things will probably be presented in a way that doesn't make any sense {smiles} so I should just sorta … Like I—you see it, you know it, you take—you write it down, but then you say “when I have time I'll get back to that.” And so that's, yeah, basically what I did. (Interview 6)

Michael's use of “grief” and his mid-speech correction of “immune” to “numb” suggest his experience in the course was troubling and deeply felt.

Yet, as bothered as Michael was by the course, none of his engineering friends seemed upset that the ideal conductor and other concepts did not make sense. Upon hearing Michael's concerns, they'd say, “don't worry about it.” Michael thought of this as a “standard engineering student response” (Interview 6). Even when he talked to engineers who had already taken E&M and found it difficult, Michael sensed they were not interested in why the class was hard.

Michael: And so one of them said how much they, you know, how they thought it was, how they struggled in the class, er, you know, like. I was like, “there's a very good reason you struggled in the class.” And they were like, “what?” I was like, “because it doesn't make any sense!” {laughs} “and so, you shouldn't …”

Interviewer: Did they agree?

Michael: Yeah, but I don't think they … {drops head} So then I started explaining this, they like did their thing where they nod their head, but I don't really know if they actually wanted the conversation to go very far, was the feeling I got. (Interview 6)

Admittedly, there might be many reasons Michael's peers were uninterested in his ideas at that moment. It might have been a bad time, or they might have been busy. For our purposes, what is important is how Michael interpreted what he saw as their indifference.

He spoke of his engineering peers' reaction to him with a tone of weary acceptance. His demeanor was similar when he described finally reaching a conclusion to the original current-through-an-ideal-conductor paradox.

Interviewer: So you're experiencing this tension, you're talking to people about it, you're talking to your professor about it, you're talking to people who may or may not be interested about it, and you're, you're hunting it down on your own time.

Michael: Yeah …

Interviewer: Um.

Michael: Which, miraculously, didn't end up hurting, you know, my grades.

Interviewer: Why do you say miraculously?

Michael: Because there was one weekend where I did nothing except think about those sort of things. And I tried a couple of different theories of explaining it, but I always ended up getting like, hitting something that didn't make much sense. And so that put me significantly behind {laughs} in my other classes. So, so, the uh, education system did its job by punishing me [for] doing any sort of independent research or studying. (Interview 6)

In sum, Michael's story of the E&M paradox and his efforts to reconcile it illustrate the continuation of two patterns we observed in previous years. First, even though the course was a terrible experience in some ways, Michael did not blame his instructor. In this and earlier interviews, Michael emphasized that he liked many of his professors and fellow students, but that he disliked the overall intellectual climate they helped to constitute. In short, his disidentification was epistemological, not social or personal. Second, Michael continued to find deep, conceptually engaging issues like the conductor paradox as he took upper-division courses, but he found that an instructional focus on resolving difficult conceptual issues was rare or absent from both class and textbooks.

Michael felt punished for sense-making

The E&M episode illustrates another pattern we observed, that Michael often felt “punish[ed]” (Interview 6) for devoting time and energy to sense-making, that is, for being himself. In Interview 3, for example, Michael spontaneously graphed the relationship of a student's grades (y-axis) to the student's effort spent understanding (x-axis) for his Signals and System Theory course. Figure 1 is a faithful representation of the graph he drew, choosing discrete Fourier transforms as an example.


Figure 1. A representation of Michael's graph of students' grades versus their level of understanding particular course material. Note how Michael draws a tiny marginal increase on students' grades for understanding why Fourier transforms work.

Download figure to PowerPoint

As Michael explained, solving problems requires understanding how to use discrete Fourier transforms, thus achieving understanding that leads to higher grades. But that increase in grades tapers sharply for large x values. In other words, Michael argued, deep understanding in his engineering courses had very low marginal utility. The added payoff in grades for understanding why Fourier transforms work and make sense was negligible. Meanwhile, the marginal cost – hours and hours of independent studying and talking with professors – was enormous. In Michael's view, being an engineer, as illustrated in Figure 1 by what his courses held him accountable for knowing and doing (Stevens et al., 2008, pp. 356–357), did not capture what was important to him. And, as time wore on, it became more and more costly for Michael to pursue what was important to him.

Michael considered changing his major to mathematics

In January 2011, Michael, who at the time was double-majoring in mathematics, said he had often thought of leaving engineering so he could spend more time on math. In an earlier interview, he reflected that his attraction to becoming a math major was based mainly on his “romanticized” view that he would be in intellectually-compatible company; he thought students “become math majors because they like math” (Interview 5). We discuss this romantization more below. But in the January 2011 interview, the idea of switching entirely to math arose immediately after he explained that taking a high-level linear algebra course gave him a ready insight and intuition into what unified concepts across classes in systems theory, control systems, communications, and digital signal processing. Those classes, he said, were ones other students saw as disconnected:

Michael: People take these sort of different classes and they're like, “OK, I have to memorize these procedures for this problem and these procedures for that problem” {firmly taps hands to create two different imaginary groups on the table} and they're missing this fundamental connection that everything has. And, you know what though? I, I uh. I've oftentimes sort of thought like to drop engineering and just do math. And then, there'd be less classes and there'd be more time to think about things in my own way. (Interview 6)

This excerpt exemplifies the link between Michael's identity and his epistemology. Here, Michael positioned himself epistemologically apart from others who do not see the connection he sees. With strong gestures, Michael painted others as trying to memorize separate rote algorithms: “people” who miss what Michael saw as the “fundamental connection” that linear algebra provides for many engineering subdisciplines. In those same few minutes, Michael went on to explain that results in control systems, for example, “are not random things you have to remember, they're very natural sort of consequences,” and while “a lot of other people [not in the advanced linear algebra class] just, they can't make the connection,” Michael felt the connection was “really important” (Interview 6). In other words, part of what drew Michael to mathematics was his view of its foundational importance for understanding and thinking about engineering concepts.

But why leave engineering for a major in math? Why not engineering and math? Partly, the answer is trade-offs. Taking classes to fulfill both majors would leave Michael with less time, as he put it, for “think[ing] about things in my own way” (Interview 6). At first glance, that trade-off may seem peculiar. What Michael called his “own way” seemed to approach mathematics and engineering as deeply interconnected. Should engineering classes not also support, rather than take time away from, Michael's approach to learning? To Michael, they did not seem to. Michael's comments here indicate his disidentification with his engineering program. They highlight the same tension as his grades-versus-understanding graph (Figure 1), namely, a mismatch between his epistemological aspects of his identity and the epistemic climate he sensed in his engineering program.

In addition to that mismatch, Michael's attraction to mathematics also stemmed from his initial perceptions of the culture of the university's mathematics program – perceptions challenged by his experiences in more math classes. In a March 2010 interview, Michael told us that for a time, mathematics looked like a major more in line with his way of thinking, with an intellectual focus not on calculations but on deeper understanding. His remarks were prompted by our question, “Can you say a bit more about how you're fitting in with the larger engineering culture?” But building from our question, Michael responded that it was not simply engineering culture that was the problem.

Michael: Well, so, I used to think it was engineering culture. But, I uh—so I'm double-majoring in math. And, I had for a while sort of romanticized the image of the math department. In the sense that, I felt like, you know because engineers are known for getting pretty good starting salaries when graduating, my general perception or explanation for a lack of passion and learning in the engineering department was due to, you know, “people become engineers because they get good jobs” so fine. But, you know, my theory was that people become math majors because they like math. I felt that was a reasonable assumption; turns out I was very naive.

Interviewer: Why?

Michael: {shakes head} Because it's the same sorta thing where students, you know, wanna know {taps table for emphasis} what's gonna be on the exam and {taps table for emphasis} how to study for what's gonna be on the exam. And, I interact with math majors, and there are exceptions, so I'm not saying this is a unilateral case, but just in general. You know, people [in math] wanna know how to do well on exams, not how to think deeply or how to actually learn. You know what I mean? And I don't, I'm not blaming the—you know—the students explicitly. But I just feel like the general structure and education system we have right now just doesn't reward learning so much as it rewards regurgitating, so much as it rewards good memory. It rewards good memories and ability to reproduce stuff that you've heard before in a {presses hands together} shortened period of time. (Interview 5)

In sum, Michael was attracted to math in part because he thought math majors and undergraduate math culture would value deep learning the same way he did. To Michael, it was sensible that since people chose engineering for its comfortable career lifestyle (a result underscored in Stevens et al., 2007), engineering didn't attract many students with a passion for learning and thinking as deeply as he did. So, he reasonably assumed that math – where he felt it less likely students were just learning by rote to pursue lucrative careers – might be where he could find his place. Moreover, moving away from engineering would give Michael more time to see and think about mathematics in his own way. To Michael's disappointment, though, math majors seemed just as focused on memorizing equations and routines as were engineering majors. Crucially, in both engineering and mathematics, Michael attributed this dysfunction to programs, not students. To Michael, the system did not seem set up to reward good learning. In our next section, we explain how Michael dealt with this disillusionment and disappointment and found a way, at least for a time, to remain in engineering.

How Michael Coped

Despite his deep disidentification and dissatisfaction with the intellectual structure of his engineering program, despite feeling punished for sense-making, Michael stayed in engineering through his third year. How could one explain that? Part of the explanation is that, despite disliking his engineering program, he loved the practice of engineering. Since Michael's father and brother were engineers, Michael had the opportunity to form a vision of engineering practice that was independent of his experiences in school. Also, he particularly enjoyed a summer internship working on the control system for a robot. More generally, in multiple interviews, he expressed his excitement about solving practical problems and making things work, not just understanding theory. These experiences underscore a finding from Stevens et al. (2008) and others: when in-school experiences seem at odds with students' identities, those students might find support extramurally. That is, students form visions of what engineering is through more than just school (Jocuns et al., 2008).

Another part of the explanation for why Michael stayed is how he fashioned a coping strategy. In their extensive study of why students switch out of STEM majors, Seymour and Hewitt (1997) found that “what distinguished the survivors from those who left was the development of particular attitudes or coping strategies” (p. 30). Michael was no exception. He first coped by curtailing his sense-making when it threatened to lower his grades. Here Michael explains how he was able to achieve good grades and continue learning deeply, at least sometimes.

Michael: I think the reason [pursuing deep learning] actually hasn't affected my GPA is because I view learning as a hobby. So, as with any hobby, you shouldn't let it interfere [with] your GPA. But it is one of my hobbies, and I do enjoy learning, I just—up to the point where I get my grades done. You know what I mean? (Interview 5)

By spring 2010, in order to address the trade-off between sense-making and grades, Michael had demoted sense-making to the status of a hobby. Grades were a pressing long-term concern because “when [employers] look at resumes, one person has this grade point average, one person has this grade point average. They throw one out” (Interview 1). Since pursuing learning had come to cost him points in class, his coping strategy was to deliberately limit the time and energy he spent trying to make sense of concepts and equations. So by the end of his sophomore year, Michael not only saw his engineering program as something he was apart from, he also compromised on sense-making – a core part of his identity – in order to get by.

Our final interview in December 2011, however, showed that a year and a half later Michael returned to his old patterns: trying to make sense of concepts and endangering his high grades in the process. For instance, in a spring 2011 graduate-level math class Michael spent a lot of time searching for a proof of an under-explained result from class. He said the low grade he received on that week's homework cost him an A in the class. But Michael said he followed his curiosity anyway, knowing full well what the grade repercussions might be. Then, he revealed something that surprised us. In the fall of 2011 he took a leave of absence from school so he could co-found a Web application start-up:

Michael: I'm not trying to paint myself as a victim. I—I made a decision [to spend time searching for that proof] and I'm taking responsibility for the consequences.

Interviewer: Are you gonna keep making decisions like that?

Michael: {emphatic} Yes! {laughs} So what I'm doing right now is just like—so I'm actually taking a—I'm actually not—I haven't been taking classes this semester.

Interviewer: Oh, really?

Michael: I started—I signed up—and then I took a—took a leave of absence because with a friend of mine we developed an idea for a software—like a Web application, which we're hoping we can turn into a business. But, I decided I wanted to dedicate my full time, my full concentration this semester to developing it. (Interview 7)

Michael did not plan to leave school forever, though. “I'm coming back next semester full-time,” he explained. “That was the deal I made with my parents so they wouldn't kill me.”

Notably, when (if?) Michael returns to school in spring 2012, the first degree he will complete will be in mathematics. More important for our story, perhaps, were Michael's experiences during his time away from the engineering program:

Michael: The point is, um, I've enjoyed every minute of [working on this start-up]. I mean, even if this doesn't work out—you know, I know 99% of all startups fail, whatever. But it's not the point. I mean, like, you know, I've learned a lot about myself also in the process. This is just a lot of fun. It's been really enjoyable. Cuz now, it's like, any time I have an idea, I just do it, you know? I don't need to ask someone's permission. (Interview 7)

In his start-up environment, Michael felt that he had full freedom to follow his own ideas. He described it as “enjoyable” and a platform for self-discovery. That view stands in contrast to the picture Michael had painted of school. In his engineering program Michael felt he needed “permission” to pursue connections among ideas, and his independent pursuit of deep understanding had to be weighed against the cost of slipping grades.


  1. Top of page
  2. Abstract
  3. Introduction
  4. Literature Review
  5. Methods and Analytic Workflow
  6. Findings and Analysis
  7. Discussion
  8. Conclusion
  9. Acknowledgments
  10. References
  11. Appendix
  12. Biographies

In this section, after briefly summarizing our account of Michael, we argue that this study has implications for research on engineering student retention and for programs aimed at increasing retention.

Summary of Michael's Story

As part of his learning, Michael engaged in conceptual and mathematical sense-making in much the same way professional engineers do, and his devotion to sense-making was part of who he is, not just something he did. He perceived, however, that the intellectual culture of his engineering program, as manifested in particular by the rewards structure, discouraged sustained sense-making. Pursuing a deeper understanding – what Michael called “learning” – threatened to cut into the time he needed to complete homework and prepare for tests. By compartmentalizing learning as what he called a “hobby,” Michael found a way to continue sense-making under the pressures of maintaining good grades. Still, that suppression of part of his identity rankled him, and he considered leaving engineering. Ultimately, rather than continue to suppress it, he decided to take a leave of absence so he could dedicate his “full concentration” to developing his own idea for a Web application (Interview 7).

Michael, we argue, should spur discussions about what kinds of disciplinary practices we value and how our retention efforts reflect those values. If sense-making suffuses successful professional engineering – and we contend, along with others, that it does (Bucciarelli, 1994; Gainsburg, 2006; Hall & Stevens, 1995; Stevens & Hall, 1998; Stevens et al., 2005, 2008) – then we must ask why Michael feels his views are so out of place in his program. And, if an engineering program's epistemological climate can have such a strong impact on whether a student feels like leaving, retention research and retention programs should attend to such issues.

Implications for Retention Research

We argue that retention in engineering education should encompass both students and practices. In other words, improving retention should not be simply an effort to attract and retain more people; it should also be a mission to encourage and sustain engineering's core disciplinary practices through pedagogy. Sense-making is one set of such practices, yet Michael felt like an outsider for his devotion to it. In the following, we argue the implications of Michael's feelings of alienation for current and future work on retention.

In drawing our implications, we note again that Flagship State is a large, public research institution. Different classes of institution – from small engineering colleges to elite private institutions – may have different program and course structures, school cultures, and instructional philosophies. Thus, our claims pertain most directly to institutions like Flagship State. Nevertheless, we believe Michael's views capture an experience that can (and does) occur in many college engineering programs.

Why Our Case Speaks to Research on Retention

Despite our argument, one might contend that Michael's story is not relevant to retention on several grounds. First, as far as we know, he never actually switched out of his engineering major. Second, our sample consisted of one student, which makes generalizations impossible. Third, our subject was white and male, so not a member of groups historically underrepresented in engineering. We now address these three concerns.

First, the field has much to gain from studying students who consider leaving but ultimately stay. Part of the strength of studies like those of Seymour and Hewitt (1997), Stevens et al. (2005, 2008), and Foor et al. (2007) is their insights into the reasons students continue in engineering, as well as the reasons students leave. From Michael, we learn that even if a student has many predictors of persistence – family and cultural supports (Foor et al., 2007; Stevens et al., 2008), internship opportunities (Stevens et al., 2005, 2008), and meaningful one-to-one face time with professors (Walden & Foor, 2008) – disidentifying with the intellectual culture of his program can still threaten whether he stays in engineering.

This observation leads to our second point about generalizing from a single-case study. We agree that it is impossible to generalize, and particularly so in the case of Michael, who was unusually vocal about his epistemological commitments and the tensions they cause with his program. Michael's unusual articulateness, then, means that we do not want to generalize from him. Rather, we offer him as an extreme case and want to stress that it is Michael's outspokenness, rather than his capacity for sense-making, that makes him unusual among students in our data corpus.

Michael supports our plausibility argument that students devoted to sense-making can feel put off by the intellectual climate of an engineering program that does not appear to foreground sense-making, and that such students are in danger of leaving the field. If Michael – a high-achieving student with a high number of predictors of persistence – considered leaving engineering, then other students devoted to sense-making are perhaps even more likely to consider leaving. Just as a university English program has a retention problem if it drives away students who are good writers and whose identities are tied up in writing, an engineering program has a retention problem if it drives away students who are good sense-makers and whose identities are tied up in sense-making.

A third reason to think Michael might not speak to retention issues is demographic: he belongs to no traditionally underrepresented group in engineering. Our first response, as noted earlier, is to argue that engineering educators should be concerned with retaining people and productive disciplinary practices (such as sense-making). Additionally, though, efforts to prevent the alienation of students who identify as sense-makers may also increase retention of underrepresented students, as we now argue.

Previous STEM education research, mostly at the K–12 level, documents that STEM classes as usually taught often fail to recognize, tap into, and build upon the productive intellectual resources for sense-making that underprivileged and underrepresented students bring to the classroom. (Boaler, 2000, 2002; Rosebery, Warren, & Conant, 1992; Seiler, 2001; Warren et al., 2001). Furthermore, when students perceive a course does not value sense-making, many of them disidentify not just with the course but also with the discipline (Boaler & Greeno, 2000; Boaler, 2000). Similar dynamics may occur at the college level; some programs and courses may select for or against sense-making. If so, efforts to value, build upon, and reward all the diverse forms of sense-making of all students could help engineering programs retain students from all demographic groups who are devoted to sense-making.

The Need to Focus on Epistemological Aspects of Student Identities

We have argued that our case study has implications for research on retention. We now discuss those implications in more detail. One is the need to include epistemological aspects of students' identities as an analytical focus in retention research. Ethnographically oriented case studies could focus more attention on epistemological (mis)alignment between how strongly students identify with sense-making and the activity structures and rewards systems of their classes. For instance, Foor et al.'s (2007) subject Inez mentioned how, in her physics class, “They say, ‘Here's the equation, plug and chug.' But it wasn't like that for me” (p. 109). Was her miserable experience in physics caused by disidentification with a “plug and chug” approach to learning, by lack of skill at plugging and chugging, or by some possibly interacting combination of these factors? The answer matters for deciding what interventions (e.g., providing tutoring versus restructuring the course) would most likely help Inez. As mentioned in our literature review, Foor et al.'s (2007) excellent analysis of Inez's mismatch with her engineering program focused on social and institutional factors. We urge that such studies also tease out epistemological aspects of students' identities and how they affect students' interactions with courses and other aspects of their programs.

Building on a collection of such case studies, survey developers could use student quotations as inspiration for items probing the intersection of identity and epistemology. Note that we cannot simply redeploy items or constructs from existing epistemology work, such as Schommer's (1990) survey or Marra et al.'s (2000) work based on the Perry (1970) scheme, because these items do not specifically probe the epistemology-identity nexus.

Another implication of our work for engineering education research is the need to blur the usual distinction between research on reforming courses and research on increasing retention. To make engineering programs less alienating for Michael and other students, including perhaps Inez (Foor et al., 2007) and Bryn (Stevens et al., 2005), we need to create both the reality and the perception that their courses invite, build upon, and reward diverse practices, including the many varieties of sense-making. For this reason, research focusing on course reform could benefit from asking students the kinds of questions usually posed in retention studies; and research addressing retention issues could benefit from probing students' beliefs and attitudes (including epistemologies) in particular courses, as often happens in studies of course reform. Retention studies could also ask students those same kinds of questions about their engineering programs as a whole.


  1. Top of page
  2. Abstract
  3. Introduction
  4. Literature Review
  5. Methods and Analytic Workflow
  6. Findings and Analysis
  7. Discussion
  8. Conclusion
  9. Acknowledgments
  10. References
  11. Appendix
  12. Biographies

Despite earning excellent grades, and despite enjoying the professional practice of engineering, Michael felt like an outsider in his engineering program. That alienation arose largely because he felt his program's intellectual climate opposed a core aspect of his identity: his attachment to sense-making (pursuing a deep understanding that integrates mathematical formalism, formal concepts, and everyday or intuitive thinking). Crucially, the program's climate and alienating effect may arise despite the intentions and desires of agents in the system. For example, students like Michael may feel they want to engage in sense-making but that they cannot, lest they risk falling behind on assignments or losing points on exams. At the same time, instructors may want to incorporate more authentic sense-making into their courses, but they may believe they cannot because of departmental expectations to cover a wide swath of content. Each interacting layer of the system experiences pressures and constraints from the others. Thus, we believe it worth reiterating that many stakeholders, students and faculty alike, may desire reform. Despite that desire, current pedagogical and institutional structures make stakeholders unwitting participants in a system that can ignore, suppress, or even marginalize sense-making.

A final point concerns the limitations of our study. Since our interviews focused on Michael's university experiences, we lack sufficient evidence to explain why and how he first came to identify with sense-making. Glimmers of data tell us where we might look. For instance, Michael briefly discussed interactions with his father in grade school that may have pushed him to think more deeply about a mathematics problem than he was initially inclined to do. But these data are too thin for us to map Michael's initial trajectory toward sense-making. Nor do we have suitably rich data on how others saw Michael; we only know how Michael felt he was being perceived.

One could think that Michael might have felt less marginalized in design-focused, student-centered courses of the kind offered by some engineering-focused colleges and universities. Even if this is true, our study remains relevant for two reasons. First, Flagship State is not unique in providing limited space for design-oriented courses in the credit requirements. Second, design courses are not necessarily a panacea. They can take on a variety of epistemological perspectives to which students can react in a variety of ways, especially when students are accustomed to traditional lecture classes. Downey and Lucena (2003) and Svihla (2009), for example, have shown that design courses are complex sites of knowledge practice in which students can and do actively resist design pedagogy and sense-making. Ultimately, we believe that our data underdetermine any specific conclusions about which course reforms, design-oriented or otherwise, would feel most inviting for students like Michael.

Despite these limitations, our case study enabled us to argue for expanding retention to include retaining diverse groups of people and diverse sense-making practices, including epistemological aspects of students' identities as an analytical focus in retention studies, and increasing the integration of studies that address course improvement and studies that address retention. If we help students feel intellectually included in meaningful ways by recognizing and supporting a diversity of knowledge practices as “pathways” (Stevens et al., 2008) to engineering, we stand not just to retain students but also encourage the core practices that define engineering as a discipline.


  1. Top of page
  2. Abstract
  3. Introduction
  4. Literature Review
  5. Methods and Analytic Workflow
  6. Findings and Analysis
  7. Discussion
  8. Conclusion
  9. Acknowledgments
  10. References
  11. Appendix
  12. Biographies

We first wish to thank Michael for participating in our interviews. We also wish to thank Michael's instructor for letting us access Michael's homework, exams, and discussion section. Indispensable manuscript feedback came from the anonymous reviewers for this Journal, Michael Loui, and Tom McGeary.

Our colleagues, including those at the University of Maryland Physics Education Group (PERG) and Science Education group were instrumental in helping this manuscript evolve. Michael M. Hull and Eric Kuo videotaped the discussion sections and were invaluable contributors in our research meetings. Kristi Hall Berk, Laura Cathcart, Luke Conlin, Todd Cooke, William Doane, Ben Dreyfus, Julia Svoboda Gouvea, James Greeno, David Hammer, Lama Jaber, Dan Levin, Colleen Nyeggen, Gina Quan, Joe Redish, Jennifer Richards, Vashti Sawtelle, Chandra Turpen, and Jessica Watkins all shared their wisdom with us. Vanessa Svihla helped us focus on study design practices in engineering; Indigo Esmonde and Victoria Hand lent us their expertise on identity; and Connie North shaped our interpretive orientation. Allan Stein gave encouragement and support when it was needed most.

This project was supported in part by grants from the National Science Foundation: DRL 0733613 and EEC 0835880. The opinions, findings, conclusions, and recommendations expressed herein are those of the authors and do not necessarily reflect the views of the National Science Foundation.


  1. Top of page
  2. Abstract
  3. Introduction
  4. Literature Review
  5. Methods and Analytic Workflow
  6. Findings and Analysis
  7. Discussion
  8. Conclusion
  9. Acknowledgments
  10. References
  11. Appendix
  12. Biographies
  • Abu-Lughod, L. (1991). Writing against culture. In R. G. Fox (Ed.), Recapturing anthropology: Working in the present (pp. 139162). Santa Fe, NM: School of American Research Press: Distributed by the University of Washington Press.
  • Atkinson, P., & Delamont, S. (2008). Analytic perspectives. In N. K. Denzin & Y. S. Lincoln (Eds.), Collecting and interpreting qualitative materials (3rd ed., pp. 285311). Thousand Oaks, CA: Sage.
  • Ball, L. J., Onarheim, B., & Christensen, B. T. (2010). Design requirements, epistemic uncertainty and solution development strategies in software design. Design Studies, 31(6), 567589. doi:10.1016/j.destud.2010.09.003
  • Bendixen, L. D., & Rule, D. C. (2004). An integrative approach to personal epistemology: A guiding model. Educational Psychologist, 39(1), 6980. doi:10.1207/s15326985ep3901_7
  • Bernold, L. E., Spurlin, J. E., & Anson, C. M. (2007). Understanding our students: A longitudinal-study of success and failure in engineering with implications for increased retention. Journal of Engineering Education, 96(3), 263274.
  • Boaler, J. (1998). Open and closed mathematics: Student experiences and understandings. Journal for Research in Mathematics Education, 29(1), 4162.
  • Boaler, J. (2000). Mathematics from another world: Traditional communities and the alienation of learners. Journal of Mathematical Behavior, 18(4), 379397. doi:10.1016/S0732–3123(00)00026-2
  • Boaler, J. (2002). The development of disciplinary relationships: Knowledge, practice and identity in mathematics classrooms. For the Learning of Mathematics, 22(1), 4247.
  • Boaler, J., & Greeno, J. G. (2000). Identity, agency, and knowing in mathematical worlds. In J. Boaler (Ed.), Multiple perspectives on mathematics teaching and learning (pp. 171200). Westport, CT: Ablex.
  • Bucciarelli, L. L. (1994). Designing engineers. Cambridge, MA: MIT Press.
  • Buehl, M. M., & Alexander, P. A. (2001). Beliefs about academic knowledge. Educational Psychology Review, 13(4), 385418. doi:10.1023/A:1011917914756
  • Carey, S., & Smith, C. (1993). On understanding the nature of scientific knowledge. Educational Psychologist, 28(3), 235251.
  • Chi, M. T. H., Feltovich, P. J., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5(2), 121152.
  • Cohen, D. K. (1990). A revolution in one classroom: The case of Mrs. Oublier. Educational Evaluation and Policy Analysis, 12(3), 311329. doi:10.2307/1164355
  • Desimone, L. M., Porter, A. C., Garet, M. S., Yoon, K. S., & Birman, B. F. (2002). Effects of professional development on teachers' instruction: Results from a three-year longitudinal study. Educational Evaluation and Policy Analysis, 24(2), 81112. doi:10.3102/01623737024002081
  • diSessa, A. A. (2007). An interactional analysis of clinical interviewing. Cognition and Instruction, 25(4), 523565. doi:10.1080/07370000701632413
  • Downey, G. L., & Lucena, J. (2003). When students resist: Ethnography of a senior design experience in engineering education. International Journal of Engineering Education, 19(1), 168176.
  • Duranti, A., & Goodwin, C. (Eds.). (1992). Rethinking context: Language as an interactive phenomenon. Cambridge, UK: Cambridge University Press.
  • Elby, A., & Hammer, D. (2001). On the substance of a sophisticated epistemology. Science Education, 85(5), 554567. doi:10.1002/sce.1023
  • Eliot, M., & Turns, J. (2011). Constructing professional portfolios: Sense-making and professional identity development for engineering undergraduates. Journal of Engineering Education, 100(4), 630654.
  • Erickson, F. (1986). Qualitative methods in research on teaching. In M. C. Wittrock (Ed.), Handbook of research on teaching (3rd ed., pp. 119161). New York, NY; London: Macmillan; Collier Macmillan.
  • Esmonde, I., Brodie, K., Dookie, L., & Takeuchi, M. (2009). Social identities and opportunities to learn: Student perspectives on group work in an urban mathematics classroom. Journal of Urban Mathematics Education, 2(2), 1845.
  • Evans, J., Morgan, C., & Tsatsaroni, A. (2006). Discursive positioning and emotion in school mathematics practices. Educational Studies in Mathematics, 63(2), 209226. doi:10.1007/s10649-006-9029-1
  • Felder, R. M. (1995). A longitudinal study of engineering student performance and retention. IV. Instructional methods and student responses to them. Journal of Engineering Education, 84(4), 361367.
  • Felder, R. M., & Brent, R. (2004). The intellectual development of science and engineering students. Part 2: Teaching to promote growth. Journal of Engineering Education, 93(4), 279291.
  • Felder, R. M., Felder, G. N., & Dietz, E. J. (1998). A longitudinal study of engineering student performance and retention. V. Comparisons with traditionally-taught students. Journal of Engineering Education, 87(4), 469480.
  • Felder, R. M., Forrest, K. D., Baker-Ward, L., Dietz, E. J., & Mohr, P. (1993). A longitudinal study of engineering student performance and retention: I. Success and failure in the introductory course. Journal of Engineering Education, 82(1), 1521.
  • Feucht, F. C. (2010). Epistemic climate in elementary classrooms. In L. D. Bendixen & F. C. Feucht (Eds.), Personal epistemology in the classroom: Theory, research, and implications for practice (pp. 5593). Cambridge, UK; New York, NY: Cambridge University Press.
  • Fontana, A., & Frey, J. H. (2008). The interview: From neutral stance to political involvement. In N. K. Denzin & Y. S. Lincoln (Eds.), Collecting and interpreting qualitative materials (3rd ed., pp. 115159). Thousand Oaks, Calif: Sage.
  • Foor, C. E., Walden, S. E., & Trytten, D. A. (2007). “I wish that I belonged more in this whole engineering group”: Achieving individual diversity. Journal of Engineering Education, 96(2), 103115.
  • Froyd, J. E., & Ohland, M. W. (2005). Integrated engineering curricula. Journal of Engineering Education, 94(1), 147164.
  • Gainsburg, J. (2006). The mathematical modeling of structural engineers. Mathematical Thinking & Learning, 8(1), 336. doi:10.1207/s15327833mtl0801_2
  • Gee, J. P. (2000). Identity as an analytic lens for research in education. Review of Research in Education, 25, 99125.
  • Guba, E. G., & Lincoln, Y. S. (2005). Paradigmatic controversies, contradictions, and emerging confluences. In N. K. Denzin & Y. S. Lincoln (Eds.), The SAGE handbook of qualitative research (3rd ed., pp. 191215). Thousand Oaks: Sage.
  • Haerle, F. C., & Bendixen, L. D. (2008). Personal epistemology in elementary classrooms: A conceptual comparison of Germany and the United States and a guide for future cross-cultural research. In M. S. Khine (Ed.), Knowing, knowledge and beliefs (pp. 151176). Dordrecht, the Netherlands: Springer. Retrieved from
  • Hall, R., & Stevens, R. (1995). Making space: A comparison of mathematical work in school and professional design practices. In S. L. Star (Ed.), The cultures of computing (pp. 118145). Oxford, UK: Blackwell.
  • Hall, R., Stevens, R., & Torralba, T. (2002). Disrupting representational infrastructure in conversations across disciplines. Mind, Culture & Activity, 9(3), 179210.
  • Hammer, D. (1989). Two approaches to learning physics. Physics Teacher, 27(9), 664670. doi:10.1119/1.2342910
  • Hammer, D. (1994a). Epistemological beliefs in introductory physics. Cognition and Instruction, 12(2), 151183. doi:10.2307/3233679
  • Hammer, D. (1994b). Students' beliefs about conceptual knowledge in introductory physics. International Journal of Science Education, 16(4), 385. doi:10.1080/0950069940160402
  • Hammer, D., & Elby, A. (2002). On the form of a personal epistemology. In B. K. Hofer & P. R. Pintrich (Eds.), Personal epistemology: The psychology of beliefs about knowledge and knowing (pp. 169190). Mahwah, NJ: Lawrence Erlbaum.
  • Hammer, D., & Elby, A. (2003). Tapping epistemological resources for learning physics. Journal of the Learning Sciences, 12(1), 5390. doi:10.2307/1466634
  • Hammer, D., Elby, A., Scherr, R. E., & Redish, E. F. (2005). Resources, framing, and transfer. In J. P. Mestre (Ed.), Transfer of learning from a modern multidisciplinary perspective. Greenwich, CT: IAP.
  • Harkema, S., Gerasimenko, Y., Hodes, J., Burdick, J., Angeli, C., Chen, Y., … Edgerton, V. R. (2011). Effect of epidural stimulation of the lumbosacral spinal cord on voluntary movement, standing, and assisted stepping after motor complete paraplegia: A case study. The Lancet, 377(9781), 19381947. doi:10.1016/S0140–6736(11)60547-3
  • Hofer, B. K., & Pintrich, P. R. (1997). The development of epistemological theories: Beliefs about knowledge and knowing and their relation to learning. Review of Educational Research, 67(1), 88140. doi:10.3102/00346543067001088
  • Holland, D. C., Lachiotte Jr., W., Skinner, D., & Cain, C. (1998). Identity and agency in cultural worlds. Cambridge, MA: Harvard University Press. Retrieved from
  • Jackson, M. (2010). Representing structure in a software system design. Design Studies, 31(6), 545566. doi:10.1016/j.destud.2010.09.002
  • Jessor, R. (1996). Ethnographic methods in contemporary perspective. In Ethnography and human development: Context and meaning in social inquiry (pp. 314). Chicago, IL: University of Chicago Press.
  • Jocuns, A., Stevens, R., Garrison, L., & Amos, D. M. (2008). Students' changing images of engineering and engineers. Paper presented at the ASEE Annual Conference & Exposition, Pittsburgh, PA.
  • Jordan, B., & Henderson, A. (1995). Interaction analysis: Foundations and practice. Journal of the Learning Sciences, 4(1), 39. doi:10.1207/s15327809jls0401_2
  • Jungebluth, P., Alici, E., Baiguera, S., Le Blanc, K., Blomberg, P., Bozóky, B., … Macchiarini, P. (2011). Tracheobronchial transplantation with a stem-cell-seeded bioartificial nanocomposite: A proof-of-concept study. The Lancet, 378(9808), 19972004. doi:10.1016/S0140–6736(11)61715-7
  • Loui, M. C. (2005). Ethics and the development of professional identities of engineering students. Journal of Engineering Education, 94(4), 383390. doi:10.1002/j.2168–9830.2005.tb00866.x
  • Lumsdaine, M., & Lumsdaine, E. (1995). Thinking preferences of engineering students: Implications for curriculum restructuring. Journal of Engineering Education, 84(2), 193204.
  • Marra, R. M., Palmer, B., & Litzinger, T. A. (2000). The effects of a first-year engineering design course on student intellectual development as measured by the Perry scheme. Journal of Engineering Education, 89(1), 3945.
  • Marra, R. M., Rodgers, K. A., Shen, D., & Bogue, B. (2012). Leaving engineering: A multi-year single institution study. Journal of Engineering Education, 101(1), 627.
  • Maxwell, J. A. (2005). Qualitative research design: An interactive approach (2nd ed.). Thousand Oaks, CA: Sage.
  • Meyers, K. L., Ohland, M. W., Pawley, A. L., Silliman, S. E., & Smith, K. A. (2012). Factors relating to engineering identity. Global Journal of Engineering Education, 14(1), 119131.
  • Miles, M. B., & Huberman, A. M. (1984). Qualitative data analysis: A sourcebook of new methods. Beverly Hills, CA: Sage.
  • Min, Y., Zhang, G., Long, R. A., Anderson, T. J., & Ohland, M. W. (2011). Nonparametric survival analysis of the loss rate of undergraduate engineering students. Journal of Engineering Education, 100(2), 349373.
  • Moller-Wong, C., & Eide, A. (1997). An engineering student retention study. Journal of Engineering Education, 86(1), 715.
  • Muis, K. R. (2004). Personal epistemology and mathematics: A critical review and synthesis of research. Review of Educational Research, 74(3), 317377. doi:10.3102/00346543074003317
  • Muis, K. R., Bendixen, L., & Haerle, F. (2006). Domain-generality and domain-specificity in personal epistemology research: Philosophical and empirical reflections in the development of a theoretical framework. Educational Psychology Review, 18(1), 354. doi:10.1007/s10648-006-9003-6
  • Murphy, T. K., Shehab, R. L., Reed-Rhoads, T., Foor, C. E., Harris, B. K., Trytten, D. A., … Moor, W. C. (2007). Achieving parity of the sexes at the undergraduate level: A study of success. Journal of Engineering Education, 96(3), 241252.
  • Nasir, N. S., & Hand, V. (2008). From the court to the classroom: Opportunities for engagement, learning, and identity in basketball and classroom mathematics. Journal of the Learning Sciences, 17(2), 143179. doi:10.1080/10508400801986108
  • O'Connor, M. C., & Michaels, S. (1993). Aligning academic task and participation status through revoicing: Analysis of a classroom discourse strategy. Anthropology & Education Quarterly, 24(4), 318335.
  • Ochs, E., Schegloff, E. A., & Thompson, S. A. (Eds.). (1996). Interaction and grammar. Cambridge, UK: Cambridge University Press.
  • Ohland, M. W., Sheppard, S. D., Lichtenstein, G., Eris, O., Chachra, D., & Layton, R. A. (2008). Persistence, engagement, and migration in engineering programs. Journal of Engineering Education, 97(3), 259278.
  • Olds, B. M., & Miller, R. L. (2004). The effect of a first-year integrated engineering curriculum on graduation rates and student satisfaction: A longitudinal study. Journal of Engineering Education, 93(1), 2335.
  • Palmer, B., & Marra, R. M. (2004). College student epistemological perspectives across knowledge domains: A proposed grounded theory. Higher Education, 47(3), 311335. doi:10.2307/4151547
  • Perry, W. G., & Harvard University. (1970). Forms of intellectual and ethical development in the college years; a scheme. New York, NY: Holt, Rinehart and Winston.
  • Piaget, J. (1960). The notion of thought. In J. Tomlinson & A. Tomlinson (Trans.), The child's conception of the world (pp. 3760). Paterson, NJ: Littlefield, Adams & Co.
  • Piaget, J. (1970). Piaget's theory. In P. H. Mussen (Ed.), Carmichael's manual of child psychology (3d ed., Vol. 1, pp. 703732). New York, NY: Wiley.
  • Redish, E. F., Saul, J. M., & Steinberg, R. N. (1998). Student expectations in introductory physics. American Journal of Physics, 66(3), 212224.
  • Redish, E. F., & Smith, K. A. (2008). Looking beyond content: Skill development for engineers. Journal of Engineering Education, (July 2008), 295307.
  • Reif, F. (2007). Applying cognitive science to education: Thinking and learning in scientific and other complex domains. Cambridge, MA: MIT Press.
  • Rooksby, J. (2010). “Just try to do it at the whiteboard”: Researcher-participant interaction and issues of generalisation. Proceedings of the Studying Professional Software Design (SPSD) Conference, San Diego, CA.
  • Rosebery, A. S., Warren, B., & Conant, F. R. (1992). Appropriating scientific discourse: Findings from language minority classrooms. Journal of the Learning Sciences, 2(1), 6194. doi:10.2307/1466685
  • Russ, R. S., Coffey, J. E., Hammer, D., & Hutchison, P. (2008). Making classroom assessment more accountable to scientific reasoning: A case for attending to mechanistic thinking. Science Education, 93(5), 875891. doi:10.1002/sce.20320
  • Sacks, H., Schegloff, E. A., & Jefferson, G. (1974). A simplest systematics for the organization of turn-taking for conversation. Language, 50(4), 696735. doi:10.2307/412243
  • Sandoval, W. A., & Reiser, B. J. (2004). Explanation-driven inquiry: Integrating conceptual and epistemic scaffolds for scientific inquiry. Science Education, 88(3), 345372. doi:10.1002/sce.10130
  • Schoenfeld, A. H. (1988). When good teaching leads to bad results: The disasters of “well-taught” mathematics courses. Educational Psychologist, 23(2), 145166. doi:10.1207/s15326985ep2302_5
  • Schoenfeld, A. H. (1991). On mathematics as sense-making: An informal attack on the unfortunate divorce of formal and informal mathematics. In J. F. Voss, D. N. Perkins, & J. W. Segal (Eds.), Informal reasoning and education (pp. 311343). Hillsdale, NJ: Lawrence Erlbaum.
  • Schoenfeld, A. H. (1992). Learning to think mathematically: Problem solving, metacognition, and sense-making in mathematics. In D. Grouws (Ed.), Handbook for research on mathematics teaching and learning (pp. 334370). New York, NY: MacMillan.
  • Schommer, M. (1990). Effects of beliefs about the nature of knowledge on comprehension. Journal of Educational Psychology, 82(3), 498504. doi:10.1037/0022–0663.82.3.498
  • Schommer, M., Calvert, C., Gariglietti, G., & Bajaj, A. (1997). The development of epistemological beliefs among secondary students: A longitudinal study. Journal of Educational Psychology, 89(1), 3740. doi:10.1037/0022–0663.89.1.37
  • Schommer, M., Crouse, A., & Rhodes, N. (1992). Epistemological beliefs and mathematical text comprehension: Believing it is simple does not make it so. Journal of Educational Psychology, 84(4), 43543.
  • Seiler, G. (2001). Reversing the “standard” direction: Science emerging from the lives of African American students. Journal of Research in Science Teaching, 38(9), 10001014. doi:10.1002/tea.1044
  • Seymour, E., & Hewitt, N. M. (1997). Talking about leaving: Why undergraduates leave the sciences. Boulder, CO: Westview Press.
  • Sherin, B. L. (2001). How students understand physics equations. Cognition and Instruction, 19(4), 479541.
  • Smith, C. L., Maclin, D., Houghton, C., & Hennessey, M. G. (2000). Sixth-grade students' epistemologies of science: The impact of school science experiences on epistemological development. Cognition and Instruction, 18(3), 349422. doi:10.2307/3233923
  • Stevens, R. (2010). Learning as a members' phenomenon: Toward an ethnographically adequate science of learning. Yearbook of the National Society for the Study of Education, 109(1), 8297.
  • Stevens, R., Amos, D. M., Jocuns, A., & Garrison, L. (2007). Engineering as lifestyle and a meritocracy of difficulty: Two pervasive beliefs among engineering students and their possible effects. Proceedings of the 2007 ASEE Annual Conference & Exposition, Honolulu, HI.
  • Stevens, R., & Hall, R. (1998). Disciplined perception: Learning to see in technoscience. In Talking Mathematics in School: Studies of Teaching and Learning (pp. 107150). Cambridge, UK: Cambridge University Press.
  • Stevens, R., O'Connor, K., & Garrison, L. (2005). Engineering student identities in the navigation of the undergraduate curriculum. Proceedings of the 2005 ASEE Annual Conference & Exposition, Portland, OR.
  • Stevens, R., O'Connor, K., Garrison, L., Jocuns, A., & Amos, D. M. (2008). Becoming an engineer: Toward a three dimensional view of engineering learning. Journal of Engineering Education, 97(3), 355368.
  • Svihla, V. L. (2009). How differences in interactions affect learning and development of design expertise in the context of biomedical engineering design (Unpublished doctoral dissertation). University of Texas, Austin, TX. Retrieved from ProQuest Dissertations & Theses database. (UMI No. 1033344903)
  • Tang, A., Aleti, A., Burge, J., & van Vliet, H. (2010). What makes software design effective? Design Studies, 31(6), 614640. doi:10.1016/j.destud.2010.09.004
  • Tonso, K. L. (2006a). Student engineers and engineer identity: Campus engineer identities as figured world. Cultural Studies of Science Education, 1(2), 273307. doi:10.1007/s11422-005-9009-2
  • Tonso, K. L. (2006b). Teams that work: Campus culture, engineer identity, and social interactions. Journal of Engineering Education, 95(1), 2537.
  • Walden, S. E., & Foor, C. E. (2008). “What's to keep you from dropping out?” Student Immigration into and within engineering. Journal of Engineering Education, 97(2), 191205.
  • Warren, B., Ballenger, C., Ogonowski, M., Rosebery, A. S., & Hudicourt-Barnes, J. (2001). Rethinking diversity in learning science: The logic of everyday sense-making. Journal of Research in Science Teaching, 38(5), 529552. doi:10.1002/tea.1017
  • Wilson, S. M., & Berne, J. (1999). Teacher learning and the acquisition of professional knowledge: An examination of research on contemporary professional development. Review of Research in Education, 24, 173209. doi:10.2307/1167270
  • Yin, R. K. (1984). Case study research: Design and methods. Beverly Hills, CA, Calif: Sage.


  1. Top of page
  2. Abstract
  3. Introduction
  4. Literature Review
  5. Methods and Analytic Workflow
  6. Findings and Analysis
  7. Discussion
  8. Conclusion
  9. Acknowledgments
  10. References
  11. Appendix
  12. Biographies

Transcription Conventions

To carefully document how participants speak and what they do, the following typographical conventions are used:

Speaker Names: indicate each conversational turn (Sacks et al., 1974). They always begin a line, are italicized, and are followed by colons.

Conversational turn boundaries are indicated by a change of speaker.

Interruptions, false starts, or other sudden changes in a stream of speech are set off by em-dashes—like this.

Emphasized speech is italicized.

Short pauses (lasting less than two seconds) are indicated with an ellipsis…like this.

Gestures, actions, and long pauses are {bounded by curly braces}.

  1. 1

    All names are pseudonyms to protect the identities of our participants. All italics and emphases in transcripts and quotations are in original.


  1. Top of page
  2. Abstract
  3. Introduction
  4. Literature Review
  5. Methods and Analytic Workflow
  6. Findings and Analysis
  7. Discussion
  8. Conclusion
  9. Acknowledgments
  10. References
  11. Appendix
  12. Biographies
  • Brian A. Danielak is a post-doctoral researcher in engineering education at the Wisconsin Center for Educational Research at the University of Wisconsin-Madison, 1025 West Johnson Street, Suite 785, Madison, Wisconsin 53706;

  • Ayush Gupta is a research assistant professor in the Department of Physics and Keystone instructor in the A. J. C. School of Engineering at the University of Maryland, College Park, MD, 20742;

  • Andrew Elby is an associate professor in the Department of Teaching, Learning, Policy, and Leadership at the University of Maryland, 2311 Benjamin Building, College Park, MD 20742-1115.