As has been described, both qualitative and quantitative data was collected using focus groups as well as survey methodology. All student participants who formed part of the focus groups also participated in completing the questionnaire. The intent of using both of these methods was not to seek confirmation and alignment but rather to expand and present complementary findings and more in-depth insights.
Qualitative focus group data—thematic analysis
Five focus group sessions were held during the 8-month period of this study. The number of participants at each session ranged from 2 to 9 women, for a total of 25 participants. Of the focus group participants (N = 25), 56% identified themselves as White, non-Hispanic, and the rest (44%) as a minority or multi-racial, including 36% Hispanic and 12% African-American students (one student selected both Hispanic and African American).
The eight groups of focus questions from the guide are shown in Table 1. The first three sets of questions of the focus group were developed to explore the constructs of interest and motivation. These questions sought to explore interest development, intrinsic process sources of motivation, external process sources of motivation, and internal self-concept sources of motivation. For this analysis, a deductive thematic analysis (Daly et al. 1997) was used to search for emerging themes judged as being important to the description of the constructs of interest and motivation. Such an analysis is a form of pattern recognition within the interview data towards the identification of overarching themes that relate back to the constructs.
Intrinsic process sources of motivation
The following table (Table 2) presents a summary of the coded subthemes within the intrinsic process source of motivation:
One of the underlying motives for this set of questions was to understand how women in this study described their personality and whether they made any connections between their intrinsic sources of motivation and their choice and interest in STEM fields of study. The following selected quotes from a longer transcript (using speaker pseudonyms) reveal some of the variety in personality descriptions and intrinsic motivation sources:
Response highlights from question set #1
I am independent and like to stand out. As a girl in engineering, I stand out / it’s easier to stand out. I like to be better than the guys. I like to know (that) I’m better than guys. I’m a girl and the best, so I stand out.
Anisa expresses a strong drive to be the best and attributes her gender as an identity element that lets her and others know she is the best.
Ellie: I’m joking and sarcastic. I’m curious; I want to know how things work. I want to learn why things happen. I would be a professional student if I could and not be in debt the rest of my life. But can also be very lazy at times. Like, I could get A’s if I applied myself more.
Ellie identifies with the characteristic of curiosity and her love of learning as part of her personality and her interest in STEM. She states that her curiosity makes her want to learn how and why things work. This curiosity is an intrinsic process motivator.
I’m basically… I’m very bubbly, and very outspoken in a way. I’ve been told I am resilient, and I didn’t know what that was, so I had to look it up. I found a lot of meanings about it, one of them is actually like a, an example is pulling a spring and having it bounce back. I go oh, there goes engineering right there, that’s science. Cool, I’m relating to both I guess.
Carina shares her discovery of the word “resilience” and presents it now with pride as not only an identifying word about her but also as an interesting science phenomena. By describing herself this way, she reveals an intrinsic satisfaction with being a resilient and outspoken learner.
I'm a people person. I really like making things run efficiently, for things to work effectively. I don't like things to be broken, and so I wanted to apply that to people and to companies and organizations.
Ana discusses how she does not like things to be broken. She describes her personality as one that wants to improve things for people and larger organizations. She reveals her intrinsic motivation for wanting to help.
I’m very outgoing and I love meeting new people. I love art, I love building things out of nothing, I love math- I get a math test and I get excited!
Stacey describes her outgoing personality and love for building out of nothing as a good match for STEM learning. She also shares her love for mathematics and the intrinsic fun and joy she gets in doing this kind of work.
I like everything neat and all in its place – code is neat and perfect and all in its place so that fits well with my personality.
Gabriela likens her preference for order and neatness and a close link to her engineering field of study. Her intrinsic motivation is to satisfy her desire for order.
Overall analysis revealed that even those women who described themselves as introverts, revealed an inner independence and curiosity intrinsic to their personality that aligned to their particular personal skills (organization, problem solving, technology, etc.) and saw this as a good fit to their chosen field of study. They are motivated to pursue a STEM field because they recognize an inner satisfaction or intrinsic motivation that drives them to persist.
External self-concept source of motivation
The following section and table (Table 3) present a summary of the coded subthemes within the strand of external self-concept motivation. One of the underlying motives for this set of questions was to understand how women in this study described experiences that hinted at connections between external influences and people and their interest and motivation to pursue a STEM field of study. The following selected quotes from a longer transcript (using speaker pseudonyms) reveal the variety in responses regarding external self-concept sources of motivation.
Response highlights from question set #7
In what ways has your family been a support (or not) to you regarding pursuing your career choice? Do you think there are barriers to women with careers in STEM? Why? Do you think this is changing? Why?
My uncles are in construction and have built house for people in oil and gas and want me to meet all these people. They are very supportive and call me their ‘retirement plan!’ I’m definitely not letting them down.
Carina reveals that she is motivated to make her uncles proud and as they joke about her being their future security, she is interested in their external affirmation and understands that she has a responsibility to succeed and earn a good living.
My mom went back to school when we were younger and became an educator. My dad is in computer technology. He didn’t go to school but is like naturally intelligent. They always wanted me to do something lucrative. ‘If you are going to get your fashion merchandising degree, you can find someone else to pay for it.’
Ellie discusses the role expectations of her parents that promote her behavior of pursuing a career that is in a lucrative field. She values her parents and their educational and intellectual abilities and seeks to be accepted.
They are very supportive. Mom started me in the camps early and Dad is in computer science. Grades are important to the family, but there was a push to pursue a lucrative career. I can be like my brother too. He is at Ohio State and majoring in Mechanical Engineering.
Anisa reveals the push by her family to seek good grades and a lucrative career. She is determined to achieve the expectations of her family and is externally motivated to be like her brother.
I am the oldest child and only girl. In Hispanic culture, I should have been a boy as the eldest. But I’m doing what my dad is doing. And as it turned out, my brother was in culinary school – so, I’m like, see, I’m way more awesome.
In this particular comment, Jasmine reveals an expectation that she attributes to her Hispanic culture. This expectation was that the eldest should be a son, and a son should follow in the footsteps of his father. In her family’s case, she is the oldest, but she is a girl. Yet she is externally motivated to step into her brother’s expected role and make her family proud.
I think my parents are very proud of me, not because of specifically what I’m going to be doing, but just the fact that I’m pursuing something that I enjoy. And I have stressed to them that my brother is one of the biggest influences in my life, just because he’s been the person who said take this, what can you use with this plate and silverware…he’d come up with something I wouldn’t even think about.
Gabriela mentions a similar, external motivation to receive the affirmation of her family. Yet, in her statement, she also reveals a more complex motivation source leading to internal self-concept-based motivation.
In this section, we can see how some students are guided in their behavior and motivation in ways that satisfy external reference groups. Although students had the opportunity to discuss external motivating forces such as peers and faculty, they did not respond to being influenced by others as much as they did by their families. Families proved to be a noteworthy external reference group from which students sought affirmation and felt a responsibility to fulfill expectations.
Internal self-concept source of motivation
The following table (Table 4) presents a summary of the coded subthemes within the theme of internal self-concept of motivation.
Response highlights from question set #3
Describe yourself as a student. What was your original declared major? What is your major now? What are your best subjects? Why? What are your least favorite subjects? Why?
Question set three probed students’ internal self-concept and explored the challenges and successes of their academic pursuits. The following comments are self-explanatory and are not individually analyzed. Students discussed some of their insecurities as women in a male dominated environment, the perception that men would or should know more than women in STEM classes. Some suggested that large classes and the inattention of their lecturer or the intimidation of such an environment were not conducive to their academic success. Some suggested that smaller class size helps to engage students and relieves feelings of being lost or insignificant. Finally, several discussed the importance and need for supplemental academic support or dedicated learning peers and caring professors.
I took three math classes and dropped one. It was college algebra and a huge freshman lecture class. You could tell the lecturer was an older lecturer. I enjoyed my statistics class, as it was smaller. I feel like it would be good if supplemental instruction went along with math classes. I know people who have classes where all they do is take tests but I thinking having to practice is good. Forced practice is good.
So far, classes are challenging. I don’t struggle but I have to work hard to understand. Like I just learned the universal [coefficient] theorem and how it connects to my research project. Once I understand and can apply it, then I get it. I work twice as hard [as others] to understand, but once I get it then I really see the connection and it’s much easier for me. I have to see how it’s applied in a conceptual way for me to get it.
Carina: Honestly, I'm a little lazy, to be honest, especially when it doesn't really interest me. If it's something I have to do and I know I'm not going to like it. I guess I come to the point where, if it's too much material to where is overwhelming just to learn one simple thing, its just too much, and I get lazy about it and I don't even want to pursue reading it.
I prefer to work by myself, but I’ve noticed that the girls have started to gravitate to working together on group projects, but a lot of the guys are always asking for help whereas the girls try to figure it out on your own.
When you’re one of like three girls, I feel like I have to be smarter because you are being looked down upon and judged.
I was weeded out of Aerospace engineering at (other University name) because I wasn’t getting the grades I got in high school. I got a 74 on my 1
test and so I fled. I didn’t know about curves or that your grade on first test may not be your final grade. I didn’t know to go talk to my teacher-or about rounding!
I’m independent and faster than the guys – they would ask me for help sometimes, but I would be surprised because I thought they were supposed to be better than me.
Emergent themes—interest development
The following selected quotes from a longer transcript (using speaker pseudonyms) reveal the variety in responses regarding interest development. The following table (Table 5) presents a summary of the coded subthemes within the theme of interest development.
Response highlights from question set #2
How long have you been interested in STEM? Was there a particular experience that you can remember that sparked that interest as a child, middle and high school student, and now college? If yes, can you please explain?
One of the underlying motives for this set of questions was to explore if students credited particular experiences with motivating or sustaining their interest in a STEM field of study. The following quotes reveal some of these memories:
The first thing I wanted to be when I was younger was an astronaut. I’m from Galveston and they opened a new planetarium and my friends and I got to meet all these astronauts. I always really enjoyed my science classes. I don’t feel like sociology or philosophy would spark my interest. It’s like “hey here memorize Aristotle.” I like hands on and doing things. Science does take memorization but it’s more hands on.”
Olivia describes her visit to a new planetarium when she was a student as influential.
I have an older brother who was in a science fair and created an amusement park out of K’NEX and I thought it was so cool! The Ferris wheel moved. Also, I really loved Rollercoaster Tycoon. I spent hours designing. I knew I was an engineer right there. Playing that I knew that I was going to be an engineer.
Alicia describes the influence of her brother’s participation in a science fair as an early interest trigger.
We did a lot of residential work growing up. At first I only watched and then I was allowed to wield tools. My parents remodeled the home and I was finally allowed to wield tools. It was like, “Look, I can make something out of this!”
Sarah credits her family’s building construction business and access to early experiences with tools as empowering.
When I was little…we had a Synertek, the 3
Apple computer [and it was] always crashing – so I had to troubleshoot to fix it so could play the computer games (internet didn’t work on it). Both my parents worked at Apple so I always had a computer…Dad would take apart a computer to show me the inside and teach me how to fix it. I was really young when I saw the inside of a computer – it looked like a little city!
Gabriela describes her early exposure to computers, problem solving, and her father’s involvement with her as early influences to identify with STEM as well as her parents serving as role models.
“[STEM] sparked my interest at a young age. My high school was in a great school district. They offered AP Bio, Anatomy, regular Bio, Chem. It confirmed that this is something that I wanted to be doing.”
Ellie discusses her experiences in a STEM-focused high school as confirming of her field of study choice.
My Mom was a biology teacher – so my whole life was a science lesson! Like when I was 7 years old – I learned about genetics from my mom because my older sister said I was adopted.
Joslyn notes that her mother, a science teacher, serves as a role model and learning support at home.
Analysis revealed that the majority of these students readily point to early experiences of hands-on learning with building kits or with real technologies such as computers. They reveal great joy when, for example, they describe their use of real building tools and how this transformed how they see and think of themselves. Many also identified an early STEM-career role model such as a family member or community hero. Some students also point to strong academic programs in their schools that welcomed girls and helped them become familiar with advanced science, technology, pre-engineering, and/or mathematics courses.
Quantitative questionnaire data
The raw questionnaire data was first reviewed to identify incomplete instruments and duplicate entries. In the case of duplicate entries, student’s most recent entry was retained for the analysis and the older entry was removed from the data set. Thus, an initial set of 54 questionnaire responses resulted in 48 usable, non-duplicated response sets that were used in this analysis. One participant did not choose to answer all of the questions, and thus, some question results are based upon 47 students. In order to examine in what ways the Latina and African-American students differed in their responses versus the White students, the questionnaire responses were sorted by self-reported ethnicity. As the population, especially when divided into minority and White student groups, was too small for meaningful results from factor analysis (Thompson 2004; Tabachnick and Fidell 2013), t tests were run for the Likert scale responses, which are presented along with their effect sizes, Cohen’s d (Grissom and Kim 2005), and N-1 two proportion tests were used for binary (yes/no, e.g.) questions to analyze the sorted data for potential differences. Binary questions were also evaluated with chi-square tests when frequency data supported this kind of test (Pett 1997). Further, groupings of questions on a common theme using Likert scale responses were evaluated for their inter-question reliability with Cronbach’s α (Cronbach 1951), which was calculated for the total sample as well as the two student groups. These question groupings were further evaluated with a correlation matrix using Spearman’s correlation (Tabachnick and Fidell 2013). Because each question group was focused on a different topic (reasons for choice, self-efficacy, etc.), it was expected that inter-item reliability across a larger group of questions and most inter-item correlations would be low. Further, multiple Likert scales had been used for different question groups (Edzie 2014). These reasons were combined for the rationale to examine the survey by common themes. The correcting significance levels for type I error using a Bonferroni correction (Myers and Well 1995) are also discussed for each question grouping. The mean responses of student groups are graphed for each question group and reported in tabular form alongside standard deviation and 95% confidence intervals.
Of the questionnaire respondents (N = 48), 54% identified themselves as White, non-Hispanic, and the rest (46%) as a minority or multi-racial; therefore, the student population in this survey study allowed for comparison between different cultural groups to examine differences and similarities (Table 6).
Interest development and choosing to major in STEM
Question: What is the PRIMARY factor that influenced you to enroll in a collegiate science, technology, engineering, or mathematics (STEM) major?
One question in the instrument asked students to identify the primary factor that influenced them to enroll in their current STEM major. The results from this study are presented in Fig. 1 broken down by student’s reported ethnicity. For simplification, data results are summarized under two group headings: White and minority students. The top two reasons provided by both the White and minority students, were “I am good at math and science” and “I wanted career options”. These two reasons relate to ideas of internal self-concept and instrumental or extrinsic process, respectively, as defined for the MSI scales (Barbuto and Scholl 1998). When compared to another study (Edzie 2014), these two reasons were also prominent. The importance of career options and being good at math and science were in the reverse order for Edzie (2014) than for students in this study. The white students, more often than the minority students, reported wanting career options as their primary factor by almost 20 percentage points (62 and 43%, respectively). Despite this large difference in percentage, the results are not statistically significant at a 95% confidence level (one tailed N-1 two proportion test, p = 0.103), likely due to the small sample size that resulted from dividing the respondents by ethnicity. Minority students still cited career options more commonly than any other choice (43%), but the response was very close to their citing being good at math and science (38%) as their primary factor for majoring in STEM. The remaining six factors were cited infrequently (by less than 10% of the respondents) as being their primary motivating factor.
Question: What factors have influenced you to enroll in a collegiate science, technology, engineering, or mathematics (STEM) major? (Choose all that apply.)
This study also included a question requesting the students to select all of the factors that influenced their decision to enroll in a STEM major (Fig. 2). Thus, Fig. 2 shows the relative influence of the pre-collegiate experiences represented by the six low ranking factors from Fig. 1. For instance, students reported participation in math and science focused extra-curricular activities as an influence in their decision to persist for a third (33%) of the minority students and a quarter (27%) of the White students. Students were also influenced by having a parent working in a STEM field, which is often cited in literature as a factor in female STEM persistence (Gabay-Egozi, Shavit and Yaish 2015). Forty percent of the overall student response cited this factor as one of their influences. Minority students cited this factor fewer times than White students (38 and 42%, respectively), but the responses were similar. Figure 2 also closes the gap on the influence of wanting career options between the student groups with minority and White students strongly indicating this factor influenced their STEM enrollment (86 and 88%, respectively). With the exception of “My school counselor encouraged me” (one tailed N-1 two proportion test, p = 0.031 with the White students more likely to cite this factor), none of the differences between the responses of these two student groups in Fig. 2 were statistically significant. These various pre-collegiate experiences could relate to different MSI subscales depending on how these factors influenced the individual student. For instance, a parent working in the STEM field could result in an external self-concept motivation as the student seeks approval from that parent; an instrumental/extrinsic process motivation in pursuit of a career with a high salary similar to their parent’s career or internal self-concept as the student views their choice as a result of their high standards modeled upon their parent(s).
Question: Why did you choose your major? Indicate the extent to which you feel the following statements are true of your decision to major in a STEM field.
Table 7 presents the inter-item reliability statistics, Cronbach’s α, for this set of questions about why students chose to major in a STEM field. A Cronbach’s α of 0.7 or higher is considered to show some degree of inter-item agreement, and as the value increases, it indicates an increasing inter-item agreement (Tabachnick and Fidell 2013). For this question set, α is only above the 0.7 threshold for White students but very near the threshold for minority students or when all students are considered together. The moderate value of α in these responses indicates that this group of statements can reasonably be analyzed with a composite score to examine students’ overall tendency to agree with this series of statements for why they chose their major. The authors are specifically interested in which reasons the students cited for choosing their major and, therefore, also examined response differences at the individual statement level as well as the composite level. Table 8 further presents the correlations between the items in this question grouping. Correlations for the minority students are reported below the diagonal and correlations for White students are above the diagonal. For the group of questions to be expected to reasonable correlated, it would be expected that all of the reported correlations would be at 0.3 or higher. As many of the correlation values are below this threshold, it can be seen that these questions about why students chose their major typically do not measure the same item in several ways but instead are measuring different, unrelated reasons the students have identified as being true of their choices. As these questions are not highly related, the individual statements were evaluated against a significance level of 0.05, rather than a corrected significance level of 0.0045 that was used for the composite scores to account for type I error on related items. Overall, the two student groups responded to the statements about why they chose their major at a similar rate (M = 6.07 and 6.01, SD = 0.60 and 0.62, and 95% CI [4.91, 7.24] and [4.79, 7.23] for minority and White students, respectively). The difference between these composite scores is not statistically significant. The real interest in this series of questions, however, is in what, if any, differences were there in the statement-level responses. Therefore, Fig. 3 presents the average student responses by student group are presented for the individual statements alongside the composite scores for each group. A striking result from Fig. 3 is that minority students ranked their personal interest in their field of study as the lowest ranking factor (5.38) in choosing their major. This factor was ranked fairly high by the White students in the study (6.27) and is the only statistically significant difference between the two groups for this grouping of statements, t(28) = −1.77, p = 0.044, from a one-tailed t test with White students being more likely to cite their personal interest in their field of study as a factor in choosing their major. This statement also has a medium effect size (d = 0.59) whereas the other reasons for choosing a STEM major had small effect sizes, indicating that the student responses to this statement did differ a noticeable amount. While most of the minority students are not saying that they dislike their field of study, 24% of the minority students indicated some degree of that statement not true of them (less than neutral). For comparison, none of the White students indicated that the statement was not true of them to any degree. Instead, the top three factors selected by minority students were all career related (6 = True of Me): Career Opportunities (6.52), Job Security (6.30), and Salary Opportunities (6.29). These three factors were all of the instrumental motivation factors listed in this question grouping. Also tied for third place ranking by minority students is the enjoyment of science, an intrinsic process motivation, as a reason for choosing their major (6.29). This factor, along with the self-efficacy statement of being good at math and science in high school (6.05), an internal self-concept motivation factor, points to pre-collegiate preparation that encouraged these minority women to pursue STEM majors. The top three factors selected by the White students in this study showed them also to be highly motivated by career-related (instrumental motivation) factors: Career Opportunities (6.38), Job Security (6.38), and Salary Opportunities (6.31).
Sources of motivation and persistence
Question: Indicate the extent to which you feel the following statements are true of your motivations to pursue your major.
Similar to the results seen in Table 7, the reliability statistics presented in Table 9 show values of Cronbach’s α that are very near the threshold of 0.7 and thus this subgroup of questions are of interest to examine additionally at the composite level. A moderate inter-item reliability indicates that there is some variance amongst the responses to the items in this group of questions about what factors motivate students to pursue their majors. The higher α for the minority students versus the White students suggests a trend that the minority students had more similar responses to all of the sources of motivation than the white students. While the composite score for each student group was examined to look for overall differences in the level of motivation to pursue a STEM major, the individual items were also explored to see if any of the factors of motivation differed between the student groups. Table 10, which presents the correlation matrix for this group of statements, further supports this analysis approach as the correlation is not consistently above 0.3. As the correlations within this grouping are only sporadically above 0.3, some of these items relating to what different factors motivated the students to pursue their major are likely independent and can therefore be evaluated with a significance level of 0.05 rather than the corrected significance level of 0.008 to control for type I error when comparing the composite scores. Figure 4 presents the composite scores of the two student groups’ responses as well as the average responses on a 7-point Likert scale to a series of statements about what factors motivate them to persist in their STEM major. For most of these questions, the minority and White students had very similar responses, and the overall level of motivation to pursue their STEM majors as measured by the composite scores for these groups were nearly identical (M = 5.58 and 5.58, SD = 1.06 and 0.81, and 95% CI [3.49, 7.66] and [3.99, 7.16] for minority and White students, respectively). Further, the small difference between these composite scores was not statistically significant. The overall top two motivating factors were students’ personal drive and desire to pursue their STEM majors with overall responses greater than 6, True of Me (6.49 and 6.11, respectively). These factors are internal self-concept motivations that have similar ratings to the instrumental motivation factors in Fig. 3. The students in this study also reported the challenging nature of their STEM fields, an internal self-concept factor, to be a motivation for persistence at a high level (5.91 overall). The family support factor in student motivation was the only individual item with a statistically significant difference between the two student groups, t(44) = 1.81, p = 0.038, with the minority students responding with higher identification with the statement than for White students. This motivation factor was the only external self-concept motivation factor that ranked highly in this grouping. The question about family influences on a students’ motivation pursue their major has a medium effect size (d = 0.52). All other effect sizes for this group of questions are small. All of the other highly ranked factors in Fig. 4 are internal self-concept motivations. The other responses did not have a statistically significant difference in response between the two groups. As the other factors were ranked in the same order of importance for the two groups excepting that family support was the third highest ranked motivating factor for the minority students versus the challenging nature of the major for the white students, the lack of statistical significance for the other responses is not surprising.
Questions: Do you currently plan on graduating with a degree in your major? Do you intend on pursuing graduate school?
The questions of whether students intend to graduate in their current STEM major and to pursue graduate degrees had three options for their answers: yes, unsure, or no. These questions were envisioned as a gauge of students’ stated motivation to persist in their chosen STEM fields. A limitation to this question series is that the question about graduate school did not specify that the graduate degree would be in their current STEM field, another STEM field, or a non-STEM field. For instance, one student indicated that she did not intend to graduate with a degree in her current STEM major but that she did intend to pursue a graduate degree. As a result of the question structure, the authors are unable to determine if this student wishes to change fields within STEM or plans to leave STEM. Beyond this one student intending to change majors, there was one student who indicated she had been pursuing her current STEM major for less than a year and was unsure of whether she would graduate with a degree in her current major. All other students indicated they intend to graduate in their current STEM major. There was no statistically significant difference between White and minority students in their intent to graduate in their current major or in their intent to attend graduate school. As the students’ response to whether they will graduate with a degree in their major was so heavily weighted in affirmative responses, the frequency of students replying “no” or “unsure” was too low (<5) to be able to run a chi-square analysis for the question. The question asking whether students intended to pursue graduate school had one category with a low frequency, but it met the requirements to run a chi-square test (Pett 1997). The result of this test was a statistically insignificant low chi-square value, c
2 (2, N = 48) = 0.72, p = 0.70. As such, a null hypothesis of independence between ethnicity and intent to pursue graduate school cannot be rejected.
Question: Indicate how important you believe each factor to be in influencing your decision to persist in a STEM field of study at Texas State University:
Table 11 presents the inter-item reliability measures, Cronbach’s α, for this group of questions about students’ decision to persist in their STEM majors. Only the grouping of minority students had an α above the 0.7 threshold, although the other student groups are near this threshold. This result indicates that the minority students tended to respond to the questions with less variance than the White students. As the α is not especially high for either of the student groups, this result means that there is still variance amongst the answers although there is enough consistency to report the composite scores. The correlation between the different factors in this grouping are presented in Table 12. There are only sporadic correlations of 0.3 or above in this matrix; therefore, these measures fail to show correlation and consistency amongst the items in this grouping. As these questions appear to have some independence amongst a common theme, they were analyzed individually versus a standard significance of 0.05 as well as analyzed as a composite score. The t test for the minority and white student groups’ composite scores were examined with a corrected significance of 0.006 to account for type I error from analyzing related items. Regardless of significance measure used, there are no statistically significant differences between minority and White students in either the composite score or the series of statements about factors that influenced their decision to persist, as shown in Fig. 5. These groups had similar composite scores (M = 2.41 and 2.38, SD = 0.40 and 0.34, and 95% CI [1.62, 3.20] and [1.70, 3.05] for minority and White students, respectively), which suggests that the two groups has similar levels of motivation to persist in their STEM majors. By examining the individual item level as well, the authors sought to identify trends in the sources of student motivation. Both groups, for instance, had much higher responses towards the influence of their personal commitment to their goals (educational and career) than any lingering effects of their ACT/SAT scores or high school performance as shown in Fig. 5. Every student had an above neutral response to the factor of commitment to goals, an internal self-concept motivation factor, with all of the White students and all but two (91%) of the minority students indicated it was “Very Important”. Those two students ranked that factor as “Somewhat Important”, so that the average rating for this factor was 2.91 out of 3 for minority students and 3 out of 3 for White students. No other factors in this group of statements had this level of agreement amongst the participants, as all others had at least one student ranking the factor as “Not Important”. This particular factor also has a medium effect size (d = 0.67), which indicates that the response distributions are noticeably different. As all the White students gave the same response, there is no variation in that group of data for this question, which would certainly be noticeable versus the minority students’ response which did have some variation. The other factors after commitment to goals rounding out the top four factors for minority students (with 90% or more participants ranking the factor above neutral) are confidence in their quantitative skills (95% above neutral, 2.77 average rating), family support (91%, 2.73), and financial needs (91%, 2.68). While the White students have the same top four factors by average rating (commitment to goals = 3.00, confidence in quantitative skills = 2.65, financial needs = 2.58, and family support = 2.50), the top four factors by above neutral responses trade family support for study skills. These top factors represent a mixture of internal self-concept (confidence in quantitative skills and study skills), eternal self-concept (family support), and instrumental (financial needs) motivations. As in previous figures, family support is the only external self-concept motivation that ranks highly and often trends higher for the minority students even when the difference between the groups is not statistically significant.
Questions: Is it important to you to have a career that positively impacts society? Do grades matter to you? Do you feel grades matter more to your male peers than they do to you?
Figure 6 presents the results from three yes/no questions in the questionnaire regarding the importance of altruism, grades, and perceptions of their male peers. The graph shows the percentage of respondents replying “yes” to each question. The first question, “Is it important to you to have a career that positively impacts society?” echoes the importance of altruism asked as a part of Fig. 3, “I chose my major because I want to help others.” For both measures of student altruism, the students in this study indicate high identification with the concept; a factor in internal self-concept motivation as well as goal internalization motivation. The students in this study found grades to be a highly influential factor, with 84% overall (including both white and minority) agreement to the question, “Do grades matter to you?” a factor related to internal self-concept motivation. Of particular note is that the minority students in this study felt far more strongly (30%) that grades mattered more to their male peers than to them versus the White students in this study (4%). This third question is the only one of this grouping with a statistically significant difference in response between the student groups (one-tailed N-1 two proportion test, p = 0.004 with the minority students more likely to agree). These three questions failed the data frequency assumptions necessary to run a chi-square test. The student response, as graphed in Fig. 6, were either predominately positive or negative. As such, the minimum data frequency of five responses was not meet 25–50% of the time for these tables and, therefore, the chi-squared test could not be calculated (Pett 1997).
Motivated strategies for learning questionnaire
Question: Indicate the extent to which you agree or disagree with each of the following:
Figure 7 presents the students’ performance motivation self-efficacy using a subsection, “self-efficacy for learning and performance motivation” of the MSLQ (Pintrich et al. 1991). This subsection includes a number of areas related to their STEM majors such as: understanding of basic concepts, mastery of skills, expectations of doing well and understanding of difficult concepts. The inter-item reliability presented in Table 13 indicates that the items within this set of questions ask similar things, with all student groups having α greater than 0.8. Table 14 shows that there are many correlations at or above the 0.3 level. As this question grouping is a subset of the MSLQ looking at students’ performance motivation self-efficacy, high Cronbach’s α results and widespread correlations are not surprising. For most of these questions, the minority and White students had very similar responses, and the composite scores for these groups were nearly the same (M = 5.84 and 5.80, SD = 0.72 and 0.77, and 95% CI [4.43, 7.25] and [4.29, 7.31] for minority and White students, respectively. This similarity in composite score suggests that the two groups of predominately juniors and seniors majoring in STEM are emerging from their courses of study with very similar levels of self-efficacy for their learning motivation. When controlling for type I error, the corrected significant level would be 0.006, and the small difference between the composite score was not statistically significant. When examining the individual items to try to explore the elements of the students’ self-efficacy, the student groups’ responses differ the most in two areas: understanding of basic concepts and expectation of an excellent GPA. For both of these instances, the minority students had lower self-efficacy than the white student; however, none of the differences in response between the two groups was statistically significant to the 95% confidence level. The student responses to understanding the basic concepts does have a medium effect size (d = 0.46). A medium effect size (Grissom and Kim 2005) indicates that these two groups have noticeable difference between the groups. The effect size between the groups for expectation of excellent GPA is only small (d = 0.23). Overall, these self-efficacy measures yielded fairly consistent results across the factors, as evidenced by the high Cronbach’s α results and relate to internal self-concept motivation factors.