Abayneh Lemma,
Keila Muller,
Zamira Torres,
Camila Senespleda and
Tamra Legron-Rodriguez
*
Department of Chemistry, University of Central Florida Physical Sciences, Bld, 4111 Libra Dr, Orlando, FL 32816, USA. E-mail: Tamra.legron-rodriguez@ucf.edu
First published on 11th April 2025
Understanding students' sense of belonging across different demographics is crucial for supporting their learning and attracting and retaining students in STEM education. Studies show that sense of belonging in foundational courses like general chemistry is associated with academic achievement and success, highlighting the need to monitor and support early belonging variations. It was, therefore, aimed in this mixed-methods study to investigate how race and gender affect undergraduate students’ belonging and belonging uncertainty in a large-enrollment general chemistry course. The data were collected using a sense of belonging survey, which was administered to 141 students at the beginning and end of the 2023 spring semester. The end-of-semester survey comprised one more open-ended question where students reflect on their sense of relatability and underlying reasons. The Wilcoxon test was used to compare the beginning and end of the semester, while the Multivariate Kruskal–Wallis (MKW) test was employed to assess differences across gender and ethnic categories. Free responses from the end-of-semester survey were analyzed thematically to understand underlying concerns and reasons. The sense of belonging remained unchanged throughout the semester, but there was an increase in belonging uncertainty. While no significant difference was found across gender categories, the largest difference in belonging uncertainty was observed between the Hispanic/Latinx and Asian American/Asian ethnic categories. Course nature and students’ struggles, majors, career goals and interests, self-belief, classroom dynamics and settings were found to be associated with the overall sense of belonging as well as the increase in belonging uncertainty among the Asian American/Asian ethnic category.
Recent literature acknowledges improvements in these disparities in some STEM fields, such as biology and mathematics. For example, Master and Meltzoff (2020) noted that certain STEM fields have reached near-equal gender representation. According to their comparison, in 2016, women in the United States received 60% of bachelor's degrees in biological sciences and 43% in mathematics and statistics. Others, such as Cimpian and King (2024), have also reported that gender gaps in STEM fields have narrowed at math-selective schools.
On the other hand, women's representation was reported in Master and Meltzoff (2020) to be much lower in fields like computer science and engineering. Others have also documented similar evidence of the persistence of such disparities (Beroíza-Valenzuela and Salas-Guzmán, 2024; Cimpian and King, 2024). Besides, Dost (2024) indicated that only 31% of students enrolled in STEM A-level qualifications between 2010 and 2019 were female. Dost (2024) also highlighted that, in 2021/22, women constitute only 20.5% of engineers and 16% of engineering graduates in the UK, underscoring the persistent gender gap in these disciplines. Similarly, the National Science Foundation (NSF, 2023) reported that although there has been an increase in the participation of women and ethnic minorities in STEM careers and educational programs, significant disparities persist. The report emphasizes that Black, Hispanic, American Indian, and Alaska Native individuals are still underrepresented in numerous STEM fields. This demonstrates the ongoing underrepresentation of ethnic minorities in STEM disciplines, despite some advancements.
Let alone the persisting disparities, the history by itself significantly affects students' sense of belonging. This history makes students from historically marginalized groups sensitive and feel uncertain about their acceptance (Steele, 1997). Research indicates that this historical context, which includes systemic exclusion and underrepresentation, contributes to uncertainty in and/or diminished sense of belonging among these students (Walton and Cohen, 2007; Reohr et al., 2023). Belonging uncertainty refers to students' doubts about their sense of belonging, which indicates how much students see themselves as fitting in with those around them, and their concerns about others' acceptance of their academic fit or ability (Edwards et al., 2022; Fink et al., 2023).
The resulting uncertainty among students from these marginalized groups regarding their social acceptance and academic fit in higher education poses significant challenges (Walton and Cohen, 2007). This uncertainty makes students sensitive to their daily academic interactions, including the reactions of others (Cohen and Garcia, 2005; Walton and Cohen, 2007). For example, a question about course content from the instructor, directed toward a student from an underrepresented group, could be interpreted as testing their ability (Walton and Cohen, 2007; Master and Meltzoff, 2020). While the question is part of classroom instruction with no such intention, students with belonging uncertainty could misinterpret it and become unsure of their acceptance. According to Walton and Cohen (2007, p. 83), this may lead some to generalize that “people like me do not belong here,” potentially resulting in dropping out of school or courses. In general, such a diminished sense of academic fit and belonging is associated with increased stress, dissatisfaction, and lower academic performance (Zumbrunn et al., 2014; Wilson et al., 2015; Rodriguez and Blaney, 2021; Edwards et al., 2022; Fink et al., 2023). Notably, these impacts may be more severe in large class settings, particularly for the first-time college students transitioning from high school to college.
A variety of interventions have been developed, tried, and reported to be significantly effective in addressing the impacts of low sense of belonging and belonging uncertainty in STEM departments. For example, Walton and Cohen (2007) have focused on psychological interventions that target students' internal mindsets. These approaches are promising as they equip students to handle real-world challenges both within and outside academic institutions. They also provide valuable insights into how students from marginalized groups perceive their academic and social fit, influenced by their interpretations of others' reactions and everyday adversities. However, such psychological approaches may not address course-specific concerns.
Others, such as Casey et al. (2023) and Clements et al. (2023), have adopted pedagogical approaches aimed at creating a conducive and engaging classroom environment. Methods like Peer-Led Team Learning (PLTL) and Learning Assistant (LA) models foster interaction and camaraderie among students, enhancing their sense of belonging. There have also been significant efforts in diagnosing and assessing the sense of belonging at the course level, examining its association with test scores, exam performance, and overall grades (Wilton et al., 2019; Edwards et al., 2022; Fink et al., 2023; Maghsoodi et al., 2023).
Despite various interventions aimed at enhancing students' sense of belonging and mitigating belonging uncertainty in STEM fields, we lack a comprehensive understanding of the dynamics in students' sense of belonging and belonging uncertainty throughout a semester under regular instructional settings. Understanding these dynamics is crucial for evaluating how pedagogical strategies and classroom environments impact students' sense of belonging, academic performance, and overall well-being. This knowledge is also essential for informing the design of effective interventions. Furthermore, it is important to explore how students from diverse academic backgrounds perceive their course experiences in terms of social acceptance, connectedness, similarities, comfort, and academic fit. Most importantly, given the large enrollment in such courses, it is necessary to understand how the regular instructional practices and learning environments at our university influence or correlate with sense of belonging and belonging uncertainty across different gender and ethnicity groups.
Therefore, it is essential to investigate the dynamics of students' sense of belonging and belonging uncertainty in large enrollment courses, such as General Chemistry 2 (GC2), over the course of a semester. It is also crucial to identify any differences across gender and ethnic groups, and to explore students' perceptions and associated concerns.
(1) Do students' sense of belonging and belonging uncertainty in a General Chemistry 2 (GC2) course differ between the beginning and end of the semester?
(2) Are there statistically significant differences in students’ sense of belonging and belonging uncertainty across different gender and ethnic groups in a General Chemistry 2 (GC2) course?
(3) How do students in a General Chemistry 2 (GC2) course perceive their sense of belonging in terms of relatability (similarities and differences with others in the course), and what factors influence this perception?
General Chemistry 2 covers topics such as intermolecular forces, properties of solutions, chemical kinetics, chemical equilibria, acids and bases, thermodynamics, electron transfer reactions, and nuclear chemistry. Multiple sections of GC2 are offered each semester and the course is coordinated to ensure all instructors follow a common curriculum, which includes use of the standardized American Chemical Society (ACS) exam. There is also a separate lab component. Not all majors are required to take the lab component. Those who are required to take it can choose to take it either concurrently with the GC2 lecture or in a subsequent semester, depending on their academic plan and the total number of credits they are taking.
While sense of belonging is multifaceted with multiple intertwined aspects, we focused on relatability as it offers significant insights into students' feelings of belonging. The phrase “people are a lot like me” reflects a crucial aspect of sense of belonging, as it raises the question of how students relate to their classmates through similar experiences, backgrounds, or struggles (Walton and Cohen 2007; Pardede et al., 2021). This question evaluates the social relationships within the classroom and provides students with the opportunity to share their perspectives on how they feel they do or don't belong in the class.
As already indicated, we adopted the instrument from Fink et al. (2020, 2023), who validated it under a similar context of population, course, and learning setting. They conducted exploratory factor analyses (EFAs) and confirmatory factor analyses (CFAs) to establish the validity of the instrument. In the EFAs, they tested one-, two-, and three-factor structures for the original seven-item belonging survey. The three-factor model did not converge correctly, producing a Heywood case error. The one- and two-factor structures did converge, accounting for 39% and 49% of the total variance, respectively. The two-factor model, which aligned with the literature, was chosen for further analysis. This model included a belonging factor (four items) and a belonging uncertainty factor (two items), accounting for 53% of the variance.
The CFAs used three model fit indices: the comparative fit index (CFI), the standardized root-mean-square residual (SRMR), and the root-mean-square error of approximation (RMSEA). The two-factor structure for the belonging survey from GC1 yielded satisfactory fit indices: CFI = 0.962, SRMR = 0.031, and RMSEA = 0.098. A subsequent CFA on pre-survey data from GC2 produced similar results, with CFI = 0.984, SRMR = 0.023, and RMSEA = 0.066, indicating acceptable relative and absolute fit (Fink et al., 2020, p. 1056).
Regarding reliability, they reported Cronbach's alpha values ranging from 0.78 to 0.84 for the four belonging items and from 0.72 to 0.84 for the two belonging uncertainty items, depending on the survey time-point. These values imply a good range of internal consistency for both the sense of belonging and belonging uncertainty items (Fink et al., 2023, p. 332).
The students came from a wide range of major areas, including health, biological, physical, and social sciences. Most students were majoring in Biology (22.2%) and Health Sciences (18.3%). Other majors included Biomedical Sciences (13.9%), Psychology (3.9%), Chemistry (3.3%), and Forensic Science (3.2%). There were also majors with only one student, such as Music Performance, Aerospace Engineering, and Sociology.
The population demographics included 68.3% female students, 31.5% male students, and 0.1% students identified as ‘other’. Ethnically, there were 39.8% White students, 31.0% Hispanic/Latinx students, 11.7% Asian students, 9.2% Black students, 5.8% Multiracial students, 0.4% American Indian students, 0.3% Pacific Islander, and 1.1% described as ‘not specified’. The ethnicity of the remaining 5 students was left blank. These demographics were gathered from institutional data and may not represent how students self-identify.
All the 726 students were invited to participate in both rounds of the survey. After obtaining permission from the course professors, we went to the classrooms with the link to the survey in Qualtrics to recruit students and asked all students to participate in the survey. Paired data from 141 students who completed both the beginning and end-of-semester surveys were obtained, constituting about a 19% response rate. Although more students completed the survey at the beginning of the semester, we focused on the paired data for our analysis. The seventh (open-ended) question was included only in the end-of-semester survey to examine their course experience and reflections. Of the 141 students, 126 responded to the open-ended question.
Free responses from 126 students were thematically coded. The coding took place during the summer of 2023, with two authors taking the initiative to code separately. Both coders are undergraduate student researchers with equivalent academic backgrounds, trained and experienced in qualitative data analysis. They were trained through weekly reading and practice sessions during Fall 2022, starting with a book chapter on qualitative analysis and related articles. Then, they practiced coding using data collected that semester (from forensic science and GC2 students), guided by the team leader who initially demonstrated the coding process.
The coding for the current study was conducted step-by-step, with biweekly team meetings to discuss the resulting codebooks. Thus, the consensus coding approach was employed to ensure consistency. During these meetings, the coders revised their codebooks and the coding guidelines for the remaining responses. The differences were mainly concerned with coding segments such as “we’re all on different paths…,” which one coder interpreted as a general belonging statement and the other as an academic path. There were also differences regarding whether to include segments with neutral polarity. As the senior member and leader of the team, the last author played a mediator role in settling these differences. We ended up with two identical finalized codebooks.
Gender categories | Frequency | Percent |
---|---|---|
Woman | 101 | 71.6 |
Man | 35 | 24.8 |
Agender | 2 | 1.4 |
Nonbinary | 2 | 1.4 |
Prefer not to disclose | 1 | 0.7 |
Total | 141 | 100.0 |
Table 1 presents the gender distribution across five categories: Man, Woman, Agender, Nonbinary, and ‘Prefer not to disclose.’ Options of Trans man and Trans woman were also provided in the survey; however, they were not selected by students. The distribution of responses across categories is 71.6% for Woman, 24.8% for Man, 1.4% for both Agender and Nonbinary, and 0.7% for ‘Prefer not to disclose.’ These categories slightly differ from the categories of demographics of the population discussed under the study settings. In the population demographics, students’ genders were presented as ‘male’, ‘female’ or ‘other’ while we used relatively more specified categories. The ethnic demographics are presented in Table 2.
Ethnic categories | Frequency | Percent |
---|---|---|
White | 67 | 47.5 |
Hispanic/Latinx | 39 | 27.7 |
Asian American/Asian | 13 | 9.2 |
Hispanic/Latinx and White | 9 | 6.4 |
African American/Black | 8 | 5.7 |
Middle Eastern/North African | 5 | 3.5 |
Total | 141 | 100.0 |
The data in Table 2 represents the ethnic categories as chosen by the students. In the survey, we tried to capture the diverse ethnic identities of our students. Students could choose from categories listed in Table 2 as well as ‘Native American/Alaska Native,’ and ‘Native Hawaiian/Other Pacific Islander.’ Additionally, students had the option to select more than one category or to self-describe if they identified outside the provided options. For example, students who selected both ‘Hispanic/Latinx’ and ‘White’ were categorized under ‘Hispanic/Latinx and White,’ resulting in a new combined category.
The largest group is White (47.5%), followed by Hispanic/Latinx (27.7%), Asian American/Asian (9.2%), the combined ‘Hispanic/Latinx, White’ (6.4%), African American/Black (5.7%), and Middle Eastern/North African (3.5%). These categories differ from the demographic data of the population presented under the study settings. The registrar's data includes general categories such as ‘Multiracial’ and ‘Not Specified.’ Furthermore, we allowed students in our survey to select multiple categories.
Variables | Group | N | Mean ranks (neg/pos) | Sum of ranks (neg/pos) | Z | p | r |
---|---|---|---|---|---|---|---|
Sense of belonging | End–begin | 141 | 63.51 (62.63) | 3366.00 (4009.00) | −1.142 | 0.158 | |
Belonging uncertainty | End–begin | 141 | 58.22 (65.39) | 2111.00 (4839.00) | −2.414 | 0.016 | 0.144 |
The “Mean ranks (neg/pos)” in Table 3 represent the average ranks of the negative and positive differences between paired observations, while the “Sum of ranks (neg/pos)” indicates the total of these ranks. These metrics are associated with rank-based analysis in non-parametric tests, which do not assume multivariate normality of the data. For sense of belonging, the test statistics can be summarized as Z(140) = −1.142, p = 0.158 (Table 3). As the p-value is greater than 0.05, the difference in students’ sense of belonging between the beginning and end of the semester was not significant. However, the difference in students’ belonging uncertainty was found to be significant (Z(140) = −2.414, p = 0.016). The sum of positive ranks (4839.00) was significantly larger than the sum of negative ranks (2111.00). This indicates a significant increase in belonging uncertainty over the semester. The effect size was found to be 0.144, which corresponds to a “low” magnitude of increment.
We then conducted the test for each ethnic group to determine which ones experienced significant changes in belonging uncertainty. We acknowledge that the sample sizes for the ethnic groups, particularly ‘African American/Black,’ ‘Hispanic/Latin, White,’ ‘Asian American/Asian,’ and ‘Middle Eastern/North African’ are small. Nevertheless, we proceeded with the tests for two reasons. First, rank-based non-parametric tests, such as the Wilcoxon signed-rank and Kruskal–Wallis tests, do not strictly require a minimum sample size (Harris and Hardin, 2013). Second, despite the limitations posed by small sample sizes, we believe the results can still provide valuable insights into which groups or categories warrant further focus. Table 4 presents the outputs of the Wilcoxon signed-rank tests.
Variables | Group | N | Mean ranks (neg/pos) | Sum of ranks (neg/pos) | Z | p | r |
---|---|---|---|---|---|---|---|
White | End–begin | 67 | 25.88 (33.73) | 724.50 (1045.50) | −1.216 | 0.224 | |
Hispanic Latinx | End–begin | 39 | 19.52 (15.92) | 390.50 (239.50) | −1.244 | 0.213 | |
African American/Black | End–begin | 8 | 4.00 (5.00) | 16.00 (20.00) | −0.282 | 0.778 | |
Hispanic/Latin, White | End–begin | 9 | 4.67 (5.17) | 14.00 (31.00) | −1.015 | 0.310 | |
Asian American/Asian | End–begin | 13 | 5.50 (6.05) | 5.50 (60.50) | −2.467 | 0.014 | 0.484 |
Middle Eastern/North African | End–begin | 5 | 2.50 (1.00) | 5.00 (1.00) | −1.089 | 0.276 |
The table compares the belonging uncertainty scores at the beginning and end of the semester for each group. The columns include the group name, the number of participants (N), the mean ranks and sum of ranks for negative and positive differences, the Z-value, the p-value, and the effect size (r).
The results for the White group showed an increase in belonging uncertainty, with the sum of positive ranks (1045.50) being larger than the sum of negative ranks (724.50); however, the change was not statistically significant (p = 0.224). The Hispanic Latinx group showed a decrease in belonging uncertainty, with the sum of negative ranks (390.50) larger than the sum of positive ranks (239.50); this change was also not statistically significant (p = 0.213). For the African American/Black group, the sum of positive ranks (20.00) was larger than the sum of negative ranks (16.00), suggesting an increase in belonging uncertainty, though it was not statistically significant (p = 0.778). The ‘Hispanic/Latin, White’ group also showed an increase in belonging uncertainty, with the sum of positive ranks (31.00) larger than the sum of negative ranks (14.00). This change was not statistically significant either (p = 0.310).
The Asian American/Asian group showed a significant increase in belonging uncertainty, with the sum of positive ranks (60.50) being much larger than the sum of negative ranks (5.50). This change was statistically significant (p = 0.014) with a medium effect size (r = 0.484). For the Middle Eastern/North Africa group, the sum of negative ranks (5.00) was larger than the sum of positive ranks (1.00), indicating a decrease in belonging uncertainty. Nevertheless, the change was not statistically significant (p = 0.276).
Overall, the results indicate that the Asian American/Asian group experienced a significant increase in belonging uncertainty from the beginning to the end of the semester. For other groups, the changes in belonging uncertainty were not statistically significant.
The cross ethnic groups comparison resulted χ2(5) = 8.990 with a p-value of 0.109 for sense of belonging and χ2(5) = 13.136 with a p-value of 0.022 for belonging uncertainty. This means the distribution of sense of belonging at the end of the semester does not significantly differ by ethnicity or race (p = 0.109), while it does for belonging uncertainty (p = 0.022). This implies that ethnicity may play a role in impacting the belonging uncertainty within the studied context. A further pairwise comparison of ethnic groups revealed a maximum difference between the Hispanic/Latinx and Asian American/Asian ethnic groups. Fig. 1 is a diagrammatic output of pairwise comparison adjusted by the Bonferroni correction for multiple tests.
Fig. 1 presents a comparison of the average ranks of belonging uncertainty among the ethnic groups. In the figure, red lines show non-significant differences (p > 0.05) and blue lines show significant differences (p < 0.05). This figure highlights which ethnic groups differ significantly in their belonging uncertainty. Overall, the Hispanic/Latinx category was found to have the least (lowest sample average rank, 57.38) belonging uncertainty while Asian American/Asian category have the highest belonging uncertainty (highest sample average rank, 97.92).
The eta squared was found to be 0.061. This implies that approximately 6.1% of the variance in belonging uncertainty can be attributed to differences among the ethnic groups. This represents a medium effect size, highlighting a noticeable impact of ethnicity on belonging uncertainty within the studied context.
As can be noted from the figure, the distribution of students' agreement with the overall belonging statement in the GC2 course shows a diverse range of responses. A small proportion of students (3.5%) strongly disagreed with the statement, while about (24.1%) of the students disagreed. In addition, 21.9% of students mildly disagreed. On the positive side, 19.9% of students mildly agreed, indicating a somewhat positive sense of belonging, and 21.9% agreed, reflecting a good sense of belonging among these students. Furthermore, 8.5% of students strongly agreed, showing a very high sense of belonging.
Overall, the results reveal a mix of feelings about belonging in the GC2 course. To understand these feelings better, the open responses were qualitatively analyzed. This analysis revealed six major themes. The finalized codebook is attached as an appendix. The data from 126 students resulted in approximately 183 coded segments, as some students’ responses were coded multiple times to different themes. Codes (segments) with negative polarity (−1) correspond disagreement with the overall sense of relatability, while those with a positive polarity (+1) correspond reasons for agreement. Table 5 presents the distribution of polarities of the codes within four major themes.
Theme | Polarity | Count | Percentage |
---|---|---|---|
Majors, interests, and career goals | Positive | 72 | 77.4% |
Negative | 21 | 22.6% | |
Preparation and performance | Positive | 30 | 65.2% |
Negative | 16 | 34.8% | |
Self-belief | Positive | 3 | 42.9% |
Negative | 4 | 57.1% | |
Course environment | Positive | 8 | 61.5% |
Negative | 5 | 38.5% | |
Social aspects | Positive | 4 | 40.0% |
Negative | 6 | 60.0% | |
General belonging statements | Positive | 7 | 50.0% |
Negative | 7 | 50.0% |
Table 5 highlights the polarities of the various themes of reasons to the overall sense of relatability among students in the GC2 course. Majors, interests, and career goals show a strong positive contribution, with 77.4% of segments indicating a positive sense of belonging. This suggests that students feel a sense of community when they share similar majors and career goals. Similarly, preparation and performance also have a positive influence, with 65.2% of segments reflecting a positive sense of belonging. This indicates that students who feel similarly prepared and perform at similar levels tend to feel a stronger sense of belonging. The course environment theme also shows a positive contribution, with 61.5% of segments indicating a supportive class environment and group dynamics enhance the sense of belonging among students.
On the other hand, self-belief and social aspects have a more negative impact on students' sense of belonging. In the self-belief theme, 57.1% of segments reflect a negative sense of belonging, suggesting that students who doubt their abilities or feel less capable compared to their peers are more likely to feel isolated. Social aspects also show a higher negative contribution, with 60.0% of segments with negative polarity. The segments in the last theme (general belonging statements) are evenly split, with both positive and negative contributions at 50.0%, indicating a mixed perception of belonging.
Overall, while some factors positively influence students' sense of belonging, others highlight areas that may need further attention to improve the overall sense of belonging in the course. Each theme is discussed briefly as follows, along with typical quotes and possible interpretations. Finally, the free responses from the 12 Asian American/Asian students were separately analyzed and discussed to understand the major concerns behind the rise in their belonging uncertainty.
Conversely, another student said, “I disagree. Though we are all in the same course, a lot of us have different career goals and different majors.” The student disagreed with the statement of relatability, with a concern about the differences in career goals and majors among classmates. It is crucial to interpret the subsequent explanations with the tone of this disagreement. Such a tone implies that, despite being in the same course, the varied majors and career goals were perceived to make it hard to build the desired sense of belonging.
I feel like I belong in this class and that people are like me in this class because every time we review an exam I do fairly the same as my other peers and we have a lot of things in common when it comes to weakness in the class.
This quote has a positive connotation, as it reflects a shared struggle and a sense of comfort. The student feels validated and supported by knowing that their peers face similar challenges, which can reduce anxiety and foster a collaborative learning environment. In contrast, there are segments with negative polarities where course-related challenges and struggles were used to justify disagreement with the statement of relatability. These segments are of two types.
In the first type, some students self-reflected as if the challenges, struggles, and failure to achieve well were unique to them alone, or as if they were the only ones facing these difficulties. In the second type, others were concerned about the disparities between their efforts and performance. For example, a student who strongly disagreed with the statement of relatability stated, “There are students that don’t do well and still come to class cause they like the subject, and they do get higher scores than me. This semester I tried to review and study but I was a horrible test taker.” This quote has a negative connotation, indicating feelings of inadequacy and disparity in performance. The student perceives a gap between their efforts and outcomes compared to peers, which can lead to frustration and decreased self-esteem. Such themes were also found to be associated with and coded to the self-belief theme, which is discussed next.
For example, a student mentioned, “Not great at chemistry, but I feel I’m just as capable of learning as my peers.” This reflects confidence in the student's ability to learn. Despite acknowledging their struggles with chemistry, the student believes in their overall learning capabilities, which can drive persistence and resilience. Consequently, the polarity of the quoted segment was interpreted as positive. On the other hand, another student said, “I feel as if everyone else is smarter than me and can keep up better than me.” This quote has a negative connotation, highlighting feelings of lower self-belief. It is noteworthy that the concern was raised in relation to the student's disagreement with the statement of relatability, associating the student's perception of being less capable than peers with a low sense of academic fit.
Segments with positive polarity acknowledge the importance of supportive group dynamics and collaborative efforts resulting from shared challenges and feelings. For example, a student noted, “Although I’d never take another chemistry course in my life, I do feel like the group dynamic in class helped. When we struggle, it's usually united and more than one of us worked together.” This quote has a positive connotation, emphasizing the supportive group dynamics. The student appreciates the collaborative efforts and shared struggles within the class, which can enhance their learning experience and sense of community.
Segments with negative polarity, on the other hand, highlight the challenge of maintaining effective interaction and engaging students in the settings of large enrollment classes. A student who disagreed with the statement of relatability, for example, highlighted, “It's difficult in a large lecture hall to interact with a lot of people, so I feel as if I didn’t really get to know that many people.” The quote has a strong negative connotation, indicating a lack of interaction and feelings of isolation in a large class setting. The student's difficulty in forming connections in a large lecture hall can lead to a sense of isolation, resulting in a lower sense of social and academic fit. This issue is particularly significant in universities, where general chemistry classes often consist of hundreds of students in a single section.
A student who agreed with the statement of relatability stated, “I have friends in my class and peers who I know from other places. They are very outgoing, and they like to help people.” This student also explained their sense of belonging positively in terms of the previously discussed shared struggles and the comfort of knowing they were not alone in facing challenges. They justified their sense of belonging through the support system from their prior friendships. The quote reflects strong social connections and support. The student benefits from having friends in the class, which enhances their sense of belonging and provides emotional and academic support.
In contrast, another student who mildly disagreed with the prior statement mentioned, “I’m not a very social person and older than most students at [name of the university].” This highlights a feeling of isolation due to a lack of social interaction. Two important aspects of social belonging are raised in this quote: age and reserved nature. The student's age and reserved nature seem to be associated with their sense of disconnection from peers.
A total of 14 segments were coded to this theme, reflecting various perspectives on social structure within the classroom. Half of the segments have a negative polarity (Table 5). One of the students who agreed to the statement of overall belonging, for example, expressed, “I feel like I belong in this class.” This statement conveys a general sense of belonging without providing specific reasons. The student's prior agreement with the statement of relatability gives positive tone to the quote. Another student who mildly disagreed with the statement of overall belonging, on the other hand, stated, “Everyone is different.” It is hard to tell the polarity of the message in this quote as negative or positive. The expression may seem to reflect a normal understanding of individual differences. However, given the student's prior disagreement with the statement of overall belonging, it casts a somewhat negative light on their sense of belonging.
It can be recalled from the statistical analysis that the Asian American/Asian ethnic group experienced a significant increase in belonging uncertainty. In our effort to understand underlying concerns, their open-ended responses were separately analyzed and coded, revealing four major themes. Table 6 summarizes the findings from this analysis.
Theme | Number of sources | Number of negative codes | Number of positive codes | Sample quotes |
---|---|---|---|---|
a Students who identified themselves as belonging to multiple ethno-racial groups, such as ‘Asian/White,’ ‘Asian American/Asian, Hispanic/Latinx, White,’ and ‘Asian American/Asian, Hispanic/Latinx,’ were categorized under the ‘Asian American/Asian’ group for simplicity in the table summarizing the findings from their open-ended responses. | ||||
Struggling with course content and performance | 7 | 6 | 1 | • […] sometimes I feel like I am the only one struggling when everyone else is doing fine. |
Major | 4 | 2 | 2 | • I am a different major [music performance] than almost everyone around me. |
Self-belief: feeling less smart than peers | 2 | 2 | — | • It feels like the content comes naturally to them. |
Class dynamic and delivery | 3 | 2 | 1 | • The content we are reading and the examples we are being taught in class do not align. |
The table provides a summary of themes related to the rise in belonging uncertainty specifically among students from the Asian American/Asian ethnic group. One prominent concern is struggling with course content and performance, which is supported by seven sources, revealing six negative and one positive reflection. A student from this ethnic group, for example, expressed, “Sometimes I feel like I am the only one struggling when everyone else is doing fine.” The quote primarily addresses the issue of the difficulty of the course content and the student's struggle with it. This sentiment highlights the student's perception of their struggle as unique, which gives a negative polarity to the quote. The quote can also be associated with the theme of self-belief, as highlighted earlier.
Another significant theme is major, derived from four sources with two positive and two negative connotations. This is exemplified by the quote from another student from the same ethnic group, who said, “I am a different major [Music Performance] than almost everyone around me.” The third theme, self-belief, is based on two sources, entirely indicating negative self-perception. Lastly, class dynamic and delivery emerge as a theme from three sources, showing two expressions of negativity. Overall, the complexity of the course, differences in majors, self-belief, class dynamic and delivery appear to be linked with the increasing uncertainty.
The first research question focused on whether students' sense of belonging and belonging uncertainty in the GC2 course changed over the semester. The findings revealed no significant change in students' sense of belonging over time. However, belonging uncertainty increased significantly, both in the overall sample (effect size of 0.144) and particularly among the Asian American/Asian ethnic group (effect size of 0.484).
The second research question addressed whether there were statistically significant differences in students' sense of belonging and belonging uncertainty across different gender and ethnic groups. The results indicated no significant differences in sense of belonging across all gender and ethnic categories. However, belonging uncertainty varied significantly across ethnic groups, with the Hispanic/Latinx category experiencing the least uncertainty and the Asian American/Asian category experiencing the highest.
The third research question examined how students perceive their sense of belonging and underlying factors. Students' sense of belonging in the GC2 course appeared to be a mix of feelings, ranging from strongly disagreeing (3.5%) to strongly agreeing (8.5%) with the general statement of belonging. About 77.4% of the segments of the theme of ‘Majors, interests, and career goals’ have positive polarity, which are associated with a positive sense of belonging, while 27.6% have negative polarity. Similarly, 65.2% of the segments related to ‘Preparation and performance’ show positive polarity, indicating a positive sense of belonging, whereas 34.8% show negative polarity. Conversely, concerns about self-belief (57.2%) and social aspects (60%) seem to be associated with a low sense of belonging. The course environment was generally supportive (61.5% positive), though large class size was found to lead to feelings of isolation. Our discussion is organized into three topics formulated from these key findings.
The findings also highlight that Hispanic/Latinx students, categorized as People of Color (POC) in STEM, exhibited the least uncertainty or a greater sense of belonging. This is particularly interesting and warrants further exploration to understand the underlying factors contributing to this sense of belonging. As can be recalled from our overview of the study settings, the research was conducted in a large, research-intensive Hispanic-Serving Institution (HSI). The high representation of the Hispanic/Latinx ethnic group, which is the second largest group in both the target population (31.0%) and the sample (27.7%), may have contributed to this outcome. However, further investigation is needed to confirm this. If this is indeed the case, it highlights the importance of providing support for historically marginalized groups, particularly in predominantly white institutions. This approach could also be beneficial for other higher education institutions experiencing similar challenges related to a sense of belonging among different ethnic groups.
Similarly, Fink et al. (2020) identified diverse sources of belonging among first-year students, such as cognitive/affective engagement, career, preparation, content, and peers. These themes represent various categories like interest, value, student attributes, course attributes, and social factors. Both studies highlight the complexity of belonging and the importance of considering multiple factors that contribute to students' sense of belonging. Despite differences in the specific themes identified, both studies share much of the underlying concerns or issues reflected by the coded segments. This indicates a common understanding of the factors influencing belonging, even if they are described differently. Furthermore, both studies found that the same sets of sources were positively related to a higher sense of belonging for some students and negatively related to lower sense of belonging or belonging uncertainty for other students. This dual impact underscores the nuanced nature of belonging, where the same factors can have different effects depending on individual student experiences and perceptions.
What we found in association with concerns of self-belief and supportive group dynamics also overlap with the findings of Young et al. (2024). While Young et al. (2024) used a different way of analysis and organization of themes, the underlying concerns about self-belief and supportive group dynamics are consistent across these studies. This further emphasizes the critical role of students' perceptions and experiences in constructing their sense of belonging and situational value in educational settings.
Course-related challenges, struggles, and failures are often associated with students' sense of belonging and belonging uncertainty, as was also revealed in this study. They were found to positively contribute to a greater sense of belonging when perceived as shared challenges and feelings and negatively to lower sense of belonging when perceived as typical or unique to oneself (Walton and Cohen, 2007). This is also what we noted from our current study. Conversely, a strong sense of belonging can positively influence students' ability to cope with academic challenges (Zumbrunn et al., 2014; Wilson et al., 2015; Edwards et al., 2022; Fink et al., 2023).
It is acknowledged that struggling with chemistry is expected. However, this struggle should not disproportionately affect the uncertainty levels of any specific ethnic group. It is essential to continuously assess belonging uncertainty and foster a growth mindset (Walton and Cohen, 2007; Master and Meltzoff, 2020). Placing students of related majors together could be beneficial. Besides, it is important to provide examples and contexts that are relevant to students’ diverse majors. Tailoring instruction to include a wide range of disciplines ensures that all students find the material meaningful and engaging. For instance, examples designed for medical students may not resonate with music performance students. Therefore, contextualizing instruction is essential to make content more relevant and applicable to students’ majors, which can enhance their engagement and learning outcomes.
Addressing the challenge of maintaining effective interaction and engagement in large enrollment courses is crucial. The previously discussed results highlight the difficulty students face in forming connections in large lecture halls, leading to feelings of isolation. We ourselves, as course instructors, have experienced this challenge. The previously quoted reflection on such settings has strong pedagogical implications. To mitigate this, professors can leverage initiatives like Supplementary Instruction (SI) sessions, where high-achieving students from previous semesters lead tutorial support sessions. These sessions provide a more personalized learning experience and foster a sense of community. Making office hours more accessible and welcoming, both in-person and virtually, can also encourage students to seek one-on-one support and build connections with their professors. Utilizing interactive technologies and incorporating team-based learning activities can further promote student interaction and create a more engaging and interactive learning environment. By implementing these strategies, professors can enhance students' academic experience and support their overall sense of belonging.
It is encouraging to note that none of the students raised issues of gender or ethnicity as reasons for their disagreement on the overall sense of belonging (relatability). Additionally, the discussion of the first two points revealed no significant difference in the sense of belonging across gender categories and most ethnic groups. This suggests that our focus should be on addressing the challenges identified in this study, such as contextualizing content and instruction to different majors, interests, and career goals, addressing course difficulty and low performance, self-belief, course environment, class dynamics, and delivery.
However, it is important to recognize that these results cannot be assumed to fully capture how students make sense of their social and academic fit in terms of gender, ethnicity, and related socio-economic factors. Students were not directed to reflect on these issues while responding to the open-ended question. Therefore, to gain a more comprehensive understanding, it is essential to build, validate, and use a more detailed survey instrument and conduct in-depth interviews (Fink et al., 2020; Maghsoodi et al., 2023). As Fink et al. (2020) noted, “Nonetheless, the results of these factor analyses suggest that future research would benefit from the development or usage of more elaborated belonging surveys” (p. 1056).
Our current study is also limited by its sample size and reliance on qualitative data from students' responses to only one open-ended question. We did not examine all aspects of the sense of belonging due to the constraints of the survey. To gain a more comprehensive understanding, future research should consider using a larger sample size, more detailed survey instruments, and in-depth interviews to explore the multifaceted nature of students' sense of belonging.
Theme | Description | Polarity | Example | Count |
---|---|---|---|---|
Majors, interests, and career goals | Data segments showing similarity (+1) or difference (−1) in major, major-based career goals, and general interest to succeed. | +1 | • A lot of my classmates are similar majors and have similar career interests. | 72 |
• I agree because there are a lot of STEM majors here so I can relate to them and my college experience on some level. | ||||
• They are more likely in the same major as me. | ||||
−1 | • I disagree. Though we are all in the same course, a lot of us have different career goals and different majors. | 21 | ||
• I am a different major [Music Performance] than almost everyone around me. | ||||
• I feel like a lot of people from a lot of different majors are taking Chem 2 as a pre req so as a result there are a lot of people with a lot of different interests and reasons for taking the class. | ||||
Preparation and performance | Data segments implying relatedness positively (+1) or negatively (−1) in terms of preparation (course difficulty or students struggling with the course) and performance or grades.‡ | +1 | • I agree because most people find this class difficult. | 30 |
• The people I talk to generally have the same struggles with the course as me and it helps me feel like I’m not out of place. | ||||
• I feel like I belong in this class and that people are like me in this class because every time we review an exam I do fairly the same as my other peers and we have a lot of things in common when it comes to weakness in the class. | ||||
−1 | • Most people […] struggle much more. | 16 | ||
• There are students that don’t do well and still come to class cause they like the subject and they do get higher scores than me. This semester I tried to review and study but I was a horrible test taker. | ||||
Self-belief | Data segments implying relatedness positively (+1) or negatively (−1) in terms of one's own abilities.§ | +1 | • Not great at chemistry, but I feel I’m just as capable of learning as my peers. | 3 |
−1 | • I feel as if everyone else is smarter than me and can keep up better than me. | 4 | ||
• I feel like my peers would put in the effort I did and have much better results. | ||||
Course environment | Segments implying relatedness positively (+1) or negatively (−1) in terms of class, group, team dynamics, or environment. | +1 | • Although I’d never take another chemistry course in my life, I do feel like the group dynamic in class helped. When we struggle, it's usually united and more than one of us worked together. | 8 |
• Because of communication through GroupMe I can see the feelings of other students and we discuss how well we did on exams, so it allows me to see that other students feel like how I do. | ||||
−1 | • Nobody comes to class. | 5 | ||
• It's difficult in a large lecture hall to interact with a lot of people, so I feel as if I didn’t really get to know that many people. | ||||
Social aspects | Data segments implying relatedness positively (+1) or negatively (−1) in terms social aspects not related to course environment or group dynamics | +1 | • I have friends in my class and peers who I know from other places. They are very outgoing, and they like to help people. | 4 |
−1 | • I’m not a very social person and older than most students at [name of the university]. | 6 | ||
• I don’t talk to my peers in class so I have no idea how similar I am to them. | ||||
General belonging statements | General statements implying belonging (sameness to peers, +1) or not belonging (difference from peers, −1). | +1 | • I feel like I belong in this class. | 7 |
• I think there a people in this course who are on the same boat or somewhere close to that. | ||||
−1 | • Everyone is different. | 7 | ||
Footnotes |
† This is a condensed version of the finalized codebook, including only sample codes. The original codebook is a multi-page table with all coded segments. |
‡ This also includes mention of previous knowledge being helpful. |
§ Some segments in this theme overlap with the theme “Preparation and Performance.” These segments were coded to both themes but are presented separately here, as some refer to students' general abilities, not just those specific to chemistry or the course. |
This journal is © The Royal Society of Chemistry 2025 |