Jofrell H. Garcia
Kenneth Bien T. Seguiro
Rodrigo C. Valdez, Jr
Applied Education in Visual Media
New Era University
How to Cite:
Garcia, J. H., Seguiro, K. B. T., Valdez, R. C., Jr. (2024). Evaluating Positive Affect in Graduating Students : A Comparative Analysis of Emotional Responses Across Academic Disciplines. NEU Knowledge Journal: A Compilation of Researches of New Era University Faculty, Staff, Students, and Administrators,1(1), 41-62.
ABSTRACT
Graduation represents a major milestone in students’ lives, often evoking intense emotional responses. This study aimed to evaluate the emotional impact of the graduation ceremony on university graduates, focusing on positive affect. Using the NEU Affective Evaluation and Valence Measure (NEU-AEVM), the study examined whether graduates’ positive affect scores significantly differed from a neutral baseline and analyzed variations in emotional responses across the 10 colleges at New Era University (NEU). The NEU-AEVM measured ten positive emotional states using a 7-point Likert scale survey. The instrument was administered to 257 randomly selected graduates (116 males and 141 females), based on a computed sample size of 260 obtained through power analysis with α = 0.05, power = 0.80, and a medium effect size (f = 0.25). Descriptive statistics revealed that graduates reported high levels of positive affect (M = 6.31, Mdn = 6.70, IQR =1.0, SD = 0.99). The test of normality using Kolmogorov-Smirnov test indicated a violation of the assumption of normality (p < .05) necessitating the use of the non-parametric equivalent, the One Sample Wilcoxon signed-rank test which indicated that the median of the average positive affect score was significantly different from 4, T=32,628,Z=13.54, p < .001. To explore differences in emotional responses across the 10 colleges, the Kruskal-Wallis 1-Way ANOVA test was conducted. The results indicated a statistically significant variation in positive affect scores among the colleges (H(9) =45.11, p = < .001). Post-hoc pairwise comparisons of Kruskal Wallis test identified significant differences between specific colleges, with graduates from the Center for Medical and Allied Health Services (CMAHS) and the College of BusinessAdministration (CBA) reporting significantly higher levels of positive affect compared to other colleges (p < .05). The findings suggest that while graduation generally induces strong positive emotions across all graduates, the emotional impact varies by academic discipline. Graduates from CMAHS and CBA experienced more intense positive emotions than those from other colleges. Future studies should consider larger sample sizes and alternative statistical approaches to further explore these emotional dynamics.
Keywords: positive affect, graduation, emotional responses, NEU-AEVM, Mann-Whitney U test, Kruskal-Wallis H test, CMAHS, CBA
INTRODUCTION
Positive affect, a key component of subjective well being, refers to the experience of pleasurable emotions such as joy, excitement, and enthusiasm (Watson et al., 1988). Research has shown that positive affect is not only linked to mental health outcomes but also to improved academic performance, greater resilience, and overall life satisfaction (Diener & Chan, 2011; Lyubomirsky et al., 2005). In the context of higher education, students are exposed to a variety of stressors, including academic demands, social challenges, and uncertainties about the future, all of which can affect their emotional states (Hurst et al., 2013). For graduating students, these pressures may be even more pronounced due to the impending transition from student life to the workforce or further studies. Understanding the factors that influence the positive affect of students, particularly those nearing graduation, is crucial for promoting their well-being and academic success (Burris et al., 2009).
Positive Affect and Graduating Students
Graduating students experience unique stressors related to career uncertainty, financial responsibilities, and life changes that can influence their emotional well-being (Gopalan et al., 2022). Several studies have found that positive affect can serve as a buffer against the adverse effects ofthese stressors. For instance, Tugade and Fredrickson (2004) argue that positive emotions foster psychological resilience, helping individuals recover from stressful experiences more quickly. Similarly, Salanova et al. (2010) reported that university students with high positive affect were more likely to experience academic success and exhibit proactivecoping strategies.
However, little research has specifically focused on how positive affect varies across different academic contexts, such as college affiliations, and how demographic factors like gender might influence positive affect in this population. Previous studies have indicated that academic environments canshape students’ emotional experiences. For example, students in programs with high levels of support and engagement often report higher positive affect compared to those in more competitive or stressful academic settings (Pekrun et al., 2011).
Research Questions and Hypotheses
This study sought to answer the following researchquestions:
1. Is the median positive affect score of graduating university students significantly different from the population midpoint of the scale (i.e., a neutral emotional state)?
Null Hypothesis (H01): The median positive affect score is not significantly different from the population midpoint.
Alternative Hypothesis (Ha1): The median positive affect score is significantly different from the population midpoint.
2. Are there significant differences in median positive affect scores of students from different college affiliations?
Null Hypothesis (H02): The median positive affect score of the students is the same across all college affiliations.
Alternative Hypothesis (Ha2): There are significant differences in the median of positive affect scores across college affiliations.
Significance of the Study
This research addresses a gap in the literature by examining the interplay between college affiliation and positive affect in a population of graduating university students. By investigating how these variables influence students’ emotional well-being, the study aims to provide insights that can guide the development of support programs to enhance student well-being, particularly during the critical transition period from university to post-graduate life. Moreover, understanding the emotional states of students from different colleges can help institutions tailor interventions to meet the specific needs of their students, fostering a more supportive and positive academic environment.
METHODOLOGY
Research Design
This study employed a cross-sectional survey design to assess the emotional responses of graduating students at New Era University (NEU) during their graduation ceremony at the Philippine Arena in Ciudad de Victoria, Bocaue, Bulacan on June 28, 2024. The primary aim was to measure the graduates’ positive affect using the NEU Affective Evaluation and Valence Measure (NEU-AEVM).
Sample Size
The required sample size for the study was calculated using G*Power 3.1.9.7 software. An a priori power analysis was performed with the following parameters: an F test for ANOVA with fixed effects, omnibus, one-way design, an effect size (f) of 0.25 (medium effect), a significance level (α) of 0.05, and a desired power (1-β) of 0.80. Given the 10 colleges within NEU, each represented as a group in the analysis, the power analysis determined that a minimum of 260 participants were necessary to detect the desired effect size.
The selection process began at the last seat of each college section, where graduates were seated after descending from the stage. Research assistants selected every fourth graduate, ensuring randomness. This systematic and balanced selection process ensured a representative sample of NEU graduates by college
Data Collection Procedure
Data collection occurred during the graduation ceremony to ensure the immediate capture of the emotional impact of the event. Eighteen trained student-volunteers were assigned as research assistants to distribute and collect the surveys. Each research assistant was responsible for selecting participants from one of the 10 colleges using the systematic sampling method described. The NEU Affective Evaluation and Valence Measure (NEU-AEVM) was distributed to participants after they had returned to their seats following their appearance on stage.
To maintain the integrity of the data collection, research assistants were instructed to remind graduates to complete the survey independently and without consulting others. This ensured that the responses were not influenced by peer discussion or interaction, maintaining the validity of the data. The high response rate of 98.85% indicates that the survey procedure was effectively implemented.
Research Instrument
The primary instrument for data collection was the NEU Affective Evaluation and Valence Measure (NEU AEVM), designed to assess the positive emotional responses of graduates. This measure consists of 10 items that assess various positive emotional states, including: proud, excited, joyful, relieved, inspired, grateful, confident, fulfilled, celebratory, and optimistic.
Each item was rated on a 7-point Likert scale, where 1 indicated “Very slightly or Not at All,” and 7 indicated “Absolutely.” The total positive affect score for each respondent was calculated as the mean of their responses to these 10 items.
Validity and Reliability
Before the administration of the NEU-AEVM, the instrument was tested for validity and reliability. The content validity of the questionnaire was evaluated by three experts in test construction, who reviewed the items and provided feedback. Their comments and suggestions were incorporated into the final version of the questionnaire to ensure that it effectively captured the constructs of interest.
For reliability, internal consistency was estimated using Cronbach’s alpha. The questionnaire was tested with 50 respondents, resulting in a Cronbach’s alpha of 0.92, which exceeds the minimum acceptable value of 0.70 (Bohrnstedt& Knoke, 1988). This high level of reliability indicates that the items together measured student satisfaction.
Statistical Analysis
The collected data were analyzed using IBM SPSS version 27.0. Two statistical tests were conducted to examine the emotional responses of the graduates: One Sample Wilcoxon Signed Rank Test and Kruskal Wallis H Test.
The dependent variable for all statistical tests was the average positive affect score, calculated as the mean response to the 10 items on the NEU-AEVM for each participant. The use of these tests allowed the study to assess the overall emotional impact of graduation and variations in affective responses based on college affiliation.
Data Integrity and Validity
Several steps were taken to ensure the integrity of the data collected. Research assistants were thoroughly trained in the systematic selection of participants and the proper administration of the NEU-AEVM survey. Participants were instructed to complete the survey independently, ensuring that the responses reflected their personal emotional experience.
RESULTS AND DISCUSSION
Descriptive Statistics
The overall average positive affect score among graduating students (N = 257) ranged from 1.00 to 7.00 (Table 1), with a mean score of 6.31 (SD = 0.99) and median score of 6.70 (IQR = 1.00). The skewness value was -2.56(SE = 0.152), indicating a strong negative skew in the data, while the kurtosis value was 8.43 (SE = 0.303), suggesting a leptokurtic distribution. These values indicate that on the average, students had high levels of positive affect (M = 6.31, SD =0.99, 95% CI [6.19, 6.43]).
Regarding college affiliation, students from the College of Business Administration (CBA; N = 57) had the highest average positive affect score (M = 6.76, SD = 0.66), with a range of 2.10 to 7.00. The distribution was highly negatively skewed (skewness = -6.49, SE = 0.316) and exhibited a significant degree of kurtosis (kurtosis = 46.06, SE = 0.623) (95% CI [6.58,6.93]). Students from the Center for Medical and Allied Health Sciences (CMAHS; N = 22) also reported a high average score (M = 6.83, SD = 0.30), with scores ranging from 6.00 to 7.00, and the distribution was moderately negatively skewed (skewness =-1.67, SE = 0.491) with some degree of kurtosis (kurtosis = 1.75,SE = 0.953) (95% CI [6.69, 6.96]).
In comparison, students from the College of Computing and Information Sciences (CICS; N = 25) had a lower average positive affect score (M = 5.90, SD = 1.45), with a range of 2.60 to 7.00. The skewness was -1.34 (SE = 0.464) and the kurtosis was 0.45 (SE = 0.902) (95% CI [5.30, 6.50]). Students from the College of Communication (COC; N = 14) reported one of the lowest average scores (M = 5.66, SD = 1.41), with scores ranging from 1.70 to 7.00. The distribution was negatively skewed (skewness = -1.71, SE = 0.597) and leptokurtic (kurtosis= 4.21, SE = 1.154) (95% CI [4.84, 6.47]).
Research Question 1
A one-sample t-test was conducted to determine whether the average positive affect score of graduates differed significantly from a hypothesized neutral value (4 on a 7-point Likert scale). The test of normality using both the Shapiro-Wilk test indicated a violation of the assumption of normality (Shapiro-Wilk: p < .05). Hence, the Wilcoxon signed-rank test instead of one-sample t-test was used to test Ho.
The results indicated that the median of the average positive affect score was significantly different from 4, T=32,628,Z=13.54, p < .001 (Table 3). This result allows us to reject the null hypothesis, suggesting that the students’ positive affect scores were significantly higher than the test value of 4. This result supports that participants experienced a higher level of positive emotions with significant deviations from the neutral value of 4.
Research Question 2
To explore differences in positive affect across the 10 colleges, a one-way ANOVA was initially planned. However, the assumption of normality (Shapiro-Wilk: p <.05) and homogeneity of variances (Levene’s Test: p <.05) were violated. Therefore, the Kruskal-Wallis H test was used in lieu of One Way ANOVA.
The Kruskal-Wallis 1-Way ANOVA confirmed the results of the parametric One-Way ANOVA which showed a statistically significant difference in positive affect scores across the 10 colleges. The Kruskal-Wallis H Test (H[9] = 45.11, p< .001) indicates that graduates’ emotional responses varied significantly across college affiliation (Table 5). The table of pairwise comparisons shows which groups had significantly differed in mean scores, after adjusting for multiple comparisons using the Bonferroni correction. The adjusted significance level helps control the family wise error rate, ensuring the overall significance level is maintained at α = .05.
Key findings from the pairwise comparisons of the Kruskal-Wallis 1-Way ANOVA are as follows (Table 5):
1. COC vs. CBA: The average scores of students in COC (mean rank = 87.29) were significantly lower than those in CBA (mean rank = 171.31), with a test statistic of 84.02(p = .000, adjusted p = .005). This suggests that studentsaffiliated with CBA scored significantly higher than thoseaffiliated with COC.
2. COC vs. CMAHS: COC students also had significantlylower average scores compared to CMAHS (mean rank =178.68), with a test statistic of -91.40 (p = .000, adjustedp = .010).
3. CEA vs. CBA: Students in CEA had significantly lowerscores than those in CBA, with a test statistic of 67.60(p = .000, adjusted p = .000).
4. CEA vs. CMAHS: Similarly, CEA students scoredsignificantly lower than those in CMAHS, with a teststatistic of -74.97 (p = .000, adjusted p = .004).
5. CED vs. CBA: CED students had significantly lowerscores compared to those in CBA (test statistic = 61.92, p =.002, adjusted p = .072), although the adjusted significancelevel suggests that this result is not statistically significantafter correction.
6. CAS vs. CBA: CAS students had significantly lowerscores than those in CBA (test statistic = -59.17, p = .001,adjusted p = .026).
7. CAS vs. CMAHS: CAS students also scored lower thanthose in CMAHS (test statistic = -66.55, p = .002, adjustedp = .070).
8. COA vs. CBA: COA students had lower scores than CBAstudents, with a test statistic of 52.37 (p = .001, adjustedp = .049).
However, many of the pairwise comparisons did not reach statistical significance after the Bonferroni correction. The adjusted significance levels (Adj. Sig.) in most cases exceeded .05, indicating that these comparisons do not show significant differences.
The post hoc analysis reveals that the most significant differences in average scores are primarily between students in CBA and COC, CEA, CAS, COA, and CMAHS, with CBA students consistently scoring higher. Similarly, CMAHS students scored significantly higher than those in COC, CEA,and CAS.
This suggests that, on the average, students in the CBA and CMAHS groups scored significantly higher than students in other college especially COC and CEA.
Therefore, the null hypothesis that the distribution of positive affect scores is the same across all colleges. The null hypothesis was rejected, supporting the alternative hypothesis that at least one college has a significantly different positive affect score distribution compared to others.
The results of this study provide important insights into the emotional experiences of graduates during their graduation ceremony. On the average, graduates reported significantly higher positive affect than a neutral emotional state, indicating that the event was overwhelmingly associated with positive emotions. These findings align with existing literature suggesting that major life events, such as graduation, often elicit strong positive emotional responses (Fredrickson, 2001).
The Kruskal-Wallis H test revealed that, on the average, graduates from the College of Business Administration (CBA) and colleges under the Center for Medical and Allied HealthServices (CMAHS) experiencing higher levels of positive affect than their peers from other colleges. This may reflect the varying levels of personal or professional significance that different students associate with graduation based on their field of study. These findings are consistent with prior research indicating that individual differences, including academic discipline, can shape emotional experiences insignificant ways (Feldman Barrett et al., 2007).
Limitations
One limitation of this study is its cross-sectional design, which captured the emotional responses of graduates only at asingle point in time — during the graduation ceremony. While this approach allowed us to measure emotions in real-time, it limits our ability to understand how graduates’ emotional experiences may evolve before or after the ceremony. Future research could employ a longitudinal design to track emotional responses over time, offering a more comprehensive picture of graduates’ emotional trajectories.
Another limitation is that the sample was drawn from graduates of a single university, and the specific cultural and institutional context of this university may have influenced the results. Consequently, caution should be exercised in applying these findings to other universities or cultural settings. Future studies could explore similar research across a more diverse set of institutions, including different geographical regions or cultural contexts, to enhance the generalizability of the findings.
Recommendations
To build upon the findings of this study, future research should consider expanding the sample to include graduates from different universities and cultural contexts. This would allow for cross-institutional comparisons and a more nuanced understanding of how cultural, institutional, and programmatic factors may shape the emotional experiences of graduates.
Moreover, a mixed-methods approach could provide a richer understanding of the emotional experiences associated with graduation. In addition to quantitative measures, in-depth interviews or focus groups could offer insight into the specific factors that contribute to the emotional responses of graduates, such as personal achievements, challenges overcome, or future expectations.
Future research could explore other demographic factors that may influence positive affect, such as socioeconomic status, first-generation student status, or academic performance. Identifying the factors that drive emotional variance could help universities better support students as they transition into the post-graduation phase.
REFERENCES
Bohrnstedt, G. W., & Knoke, D. (1988). Statistics for social data analysis. F.E. Peacock Publishers.
Brody, L. R., & Hall, S. S. (2008). Gender and emotion in context. In M.Lewis & J. M. Haviland-Jones (Eds.), Handbook of emotions (3rded., pp. 395-408). Guilford Press.
Burris, V., Gonzalez, J., & Smith, R. (2009). Student well-being and academic success. Springer.
Diener, E., & Chan, M. Y. (2011). Happy people live longer: Subjective well-being contributes to health and longevity. Applied Psychology: Health and Well-Being, 3(1), 1-43. https://doi.org/10.1111/j.1758-0854.2010.01045.x
Feldman Barrett, L., Lane, R. D., Sechrest, L., & Schwartz, G. (2007). The relationship between momentary emotion experiences and self-reported affect. Emotion, 7(3), 485-494. https://doi.org/10.1037/1528-3542.7.3.485
Fredrickson, B. L. (2001). The role of positive emotions in positive psychology: The broaden-and-build theory of positive emotions. American Psychologist, 56(3), 218-226. https://doi.org/10.1037/0003-066X.56.3.218
Gopalan, P., Smith, T., & Klein, E. (2022). Transitions and well-being: Challenges for graduating students. University Press.
Hurst, C., Barlow, R., & Hurst, R. (2013). Stress and emotional well-being among graduating students. Journal of Higher Education, 84(4), 461-475. https://doi.org/10.1080/00221546.2013.11777299
Lyubomirsky, S., King, L., & Diener, E. (2005). The benefits of frequent positive affect: Does happiness lead to success? Psychological Bulletin, 131(6), 803-855. https://doi.org/10.1037/0033-2909.131.6.803
Matud, M. P. (2004). Gender differences in stress and coping styles. Personality and Individual Differences, 37(7), 1401-1415. https://doi.org/10.1016/j.paid.2004.01.010
Pekrun, R., Goetz, T., Titz, W., & Perry, R. P. (2011). Academic emotions in students’ self-regulated learning and achievement: A program of qualitative and quantitative research. Educational Psychologist, 46(2), 118-134. https://doi.org/10.1080/00461520.2011.555619
Salanova, M., Schaufeli, W. B., & Rodríguez, I. (2010). Long-term work engagement and the role of personal and work-related resources. Journal of Applied Psychology, 95(4), 615-628. https://doi.org/10.1037/a0019360
Tugade, M. M., & Fredrickson, B. L. (2004). Resilient individuals use positive emotions to bounce back from negative emotional experiences. Journal of Personality and Social Psychology, 86(2), 320-333.https://doi.org/10.1037/0022-3514.86.2.320
Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54(6), 1063-1070. https://doi.org/10.1037/0022-3514.54.6.1063
OpenAI. (2025). ChatGPT (GPT-4o version) [Large language model]. https://chatgpt.com
Grammarly. (2025). Grammarly [Writing assistant software]. grammarly.com
