Predictors of Licensure Examination Performance of Bachelor’s in Education Graduates of a Community College in Bukidnon, Philippines

Predictors of Licensure Examination Performance of Bachelor’s in Education Graduates of a Community College in Bukidnon, Philippines

Ryan T. Camañero^1*, Ariel M. Berico², Denis A. Tan³

¹Research Director, Don Carlos Polytechnic College, Don Carlos, Bukidnon, Philippines

²Vice President for Academic Affairs, Don Carlos Polytechnic College, Don Carlos, Bukidnon, Philippines

³Dean, College of Education, Central Mindanao University, Maramag, Bukidnon, Philippines

^*Correspondence Author

DOI: https://dx.doi.org/10.47772/IJRISS.2024.8100067

Received: 04 October 2024; Accepted: 07 October 2024; Published: 04 November 2024

ABSTRACT

This study investigated the factors affecting the licensure examination performance of graduates from the College of Teacher Education at Don Carlos Polytechnic College. The alarming decline in takers’ performance across various licensure examinations has compelled researchers to investigate a range of potential factors that may influence their success or failure in these critical assessments. This study aimed to determine the level of perceptions on the following factors: student factors, Home and family factors, School factors, Review center factors, and Personal factors; ascertain the relationship between respondents’ perceptions of factors affecting the licensure examination performance and the LET rating of respondents; and identify the factor/s singly or in combination best predict/s the LET rating of the respondents. The study utilized a descriptive-correlational ex post facto research design and employed purposive sampling to get the 175 College of Teacher Education graduates who undertook the licensure examination during the academic years 2021-2022. The study used a questionnaire adapted from the study of Herrero (2015). The study employed statistical methods, including correlation analysis and regression modeling, to identify the factors influencing LET performance The results of the study showed that the student factor has a low influence, the home and family factor have a moderate influence, the school factor has a moderate influence, the review center factor has also a moderate influence, and the personal factor has a moderate influence. There is a statistically significant positive relationship between respondents’ perceptions of the student factor, home and family factor, review center factor, personal factor, and their LET rating. The student, review center, and personal factors collectively contribute significantly to predicting LET performance. Overall, the study provides valuable insights into the factors that influence academic success and the efficacy of the educational programs at Don Carlos Polytechnic College.

Keywords: student factors, family support, school environment, review centers, personal attributes.

INTRODUCTION

The pursuit of higher education is a transformative journey that culminates in the successful attainment of a degree, symbolizing the acquisition of knowledge and skills. For many students, the ultimate test of their educational journey is passing a licensure examination, a critical step that opens doors to professional opportunities and career advancement. License is a standard mark of a professional recognized by the government and public to introduce excellence, behavior, guidelines of recruitment and measures of member protection, assuring a high sense of dedication, responsibility, skills and quality towards one’s profession, (Merced et al 2015). This study delves into the multifaceted landscape of licensure examination performance at Don Carlos Polytechnic College, examining it through a quantitative lens to decipher the underlying factors that influence students’ success in this pivotal endeavor.

Passing the licensure examination is often regarded by graduates as a tedious deliberation. Aquino and Balilla (2015) explained that it is primarily due to the differences in the ability of the graduates to learn and acquire knowledge that crucially affects their chances of passing the licensure examination. This is confirmed by an apparent dismal performance in the licensure examination of teacher education graduates in DCPC. In September 2021, DCPC achieved a passing rate of 53.85%, with 14 out of 26 graduates successfully passing the exam, slightly below the national passing rate of 57.17%. However, in January 2022, DCPC surpassed the national passing rate with a success rate of 56.75% (21 out of 37), while the national passing rate was 54.55%. The trend continued in March 2022, with DCPC achieving a passing rate of 67.86% (19 out of 28), significantly higher than the national passing rate of 45.43%. The performance in October 2022 demonstrated consistent success, with a passing rate of 61.48% (166 out of 270), far exceeding the national passing rate of 26.32%.  Their passing rate is erratic for there are times that it is higher than the national passing rate and there is a time that it is below, and a large number of non-passers is noticeable.

The college is always aiming for a high rating on the board examinations. As strategies, the College of Teacher Education strongly implements the retention and promotion policy for its students. Part of it also is the conduct of board examination reviews for the takers to provide enhancement on the fundamental principles and theories of professional education, major, and general education subjects. Thus, the researchers conducted a survey on factors affecting performance of DCPC graduates in the board for professional teachers. In detail, this study aimed to identify the factors that affect the performance of test-takers concerning the assessment of the respondents to the following factors: student factor, home and family factor, school factor, review center factor, and personal factor.

METHOD

The research design employed for this study was a descriptive-correlational ex post facto design. This approach involves the analysis of existing data derived from the Teacher Education licensure examination results at the college. The research was conducted during the academic year 2023-2024. This timeframe is crucial for ensuring the relevance and timeliness of the findings, as it reflects the most current conditions and challenges faced by graduates during this specific academic period.

The participants in this study comprised 175 students who had successfully graduated from Don Carlos Polytechnic College under the College of Teacher Education and had taken the licensure examination for teachers starting from the academic year 2021-2022. Their experiences and outcomes in the licensure examinations provided valuable insights into the factors that influenced academic success and the efficacy of the educational programs at DCPC. The selection of this group allowed the researchers to capture current and real-world data, enabling a comprehensive analysis of the dynamic interplay between academic preparation and licensure examination performance. Through their participation, the researchers aimed to gain a deeper understanding of the challenges and opportunities faced by graduates of Don Carlos Polytechnic College in their pursuit of teaching licensure.

This research study used a questionnaire adapted from the study of Herrero (2015). It includes 21 statements distributed to the factors as mentioned in the study. This has a Cronbach Alpha of .87. Each category may have a different number of statements which the students were asked to rate based on the extent that they perceive how well it describes their perception. Using a five-point Likert scale, the test provides responses like 5-Very High, 4-High, 3-Moderate, 2- Low, 1-Very low, as shown below.

Rating                         Scale                           Qualitative Interpretation

4                                  3.25-4.00                     High Influence (HI)

3                                  2.50-3.24                     Moderate Influence (MI)

2                                  1.75-2.49                     Low Influence (LI)

1                                  1:00-1.74                     No Influence (NI)

The licensure examination performance of each student was taken from the office of the college registrar. With the permission of the VPAA, the names were coded for analysis.

The study employed descriptive statistics, including measures such as mean, standard deviation, frequency, and percentages, to determine the licensure examination performance of the respondents and to identify the factors influencing their performance in the licensure exam. Furthermore, the research utilized Pearson’s product-moment correlation to assess the relationships between independent and dependent variables. In addition, to identify the factor or combination of factors that most effectively predict the Licensure Examination for Teachers (LET) rating of the respondents, a stepwise linear regression analysis was applied.

RESULT AND DISCUSSION

The result and discussion are explained below.

Result

Student Factor

Table 1. Mean Distribution of Respondents’ Student Factor

Doing research in the library or through the internet has a mean of 1.94 categorizes this indicator as LI (Low Influence), suggesting that, on average, students spend relatively less time on research. Interest in the course with a mean of 2.51, is categorized as AI (Moderate Influence), indicating that students, on average, have a moderate interest in the course. The number of hours spent reading books and materials has a mean of 2.57, this indicator is categorized as AI (Moderate Influence), indicating that students, on average, spend a moderate amount of time reading books and materials, contributing positively to the Student Factor. Also, time spent on studying lessons with a mean of 2.63 categorizes this indicator as AI (Moderate Influence), suggesting that students, on average, dedicate a reasonable amount of time to studying lessons, contributing positively to the Student Factor. This may have a comparatively lower impact on the Student Factor.

The overall mean of 2.41 categorizes the Student Factor as LI (Low Influence), suggesting that, on average, the combined influence of these indicators has a comparatively lower impact on the overall Student Factor.

The Student Factor, based on the indicators, is characterized by a mix of Moderate Influence (AI) and Low Influence (LI). While students generally show an average interest in the course and dedicate a reasonable amount of time to studying lessons and reading materials, the overall influence is categorized as low. This might be due to the low influence associated with doing research, as indicated by the relatively lower mean for this specific indicator.

According to a study by Whitten, Labby, and Sullivan (2016), the number of hours spent reading books has a positive impact on academic success. The study found that pleasure reading, or reading for enjoyment, is associated with higher academic achievement. The researchers suggest that reading for pleasure can improve vocabulary, comprehension, and critical thinking skills, which are essential for academic success. Similarly, a report by the National Library of New Zealand (n.d.) highlights the importance of reading for pleasure in fostering student success. The report suggests that reading for pleasure can improve literacy skills, increase motivation, and enhance academic performance. These findings support the idea that the number of hours spent reading books can have a positive influence on student performance, contributing to the Student Factor.

Home and Family Factor

Table 2.  Frequency Distribution of Respondents’ Home and Family Factor

The indicator “Family supports all expenses in reviewing and taking the LET” has the mean of 1.85 which categorizes this indicator as LI (Low Influence), suggesting that, on average, families do not fully support all expenses related to reviewing and taking the LET. This may have a comparatively lower impact on the Home and Family Factor. Parents help a lot in preparations for the LET has the mean of 2.65 categorizes this indicator as AI (Moderate Influence), indicating that, on average, parents provide a moderate level of help in preparations for the LET, contributing positively to the Home and Family Factor. The indicator “family gives motivation and encouragement” has a mean of 2.99, and is categorized as AI (Moderate Influence), indicating that, on average, families provide a moderate level of motivation and encouragement, contributing positively to the Home and Family Factor. Also, family can be depended upon when a problem arises has a mean of 3.09, this indicator is categorized as AI (Moderate Influence), suggesting that, on average, families can be depended upon when problems arise, contributing positively to the Home and Family Factor.

The overall mean of 2.64 categorizes the Home and Family Factor as AI (Moderate Influence), suggesting that, on average, the combined influence of these indicators has a moderate impact on the overall Home and Family Factor.

The Home and Family Factor, based on the indicators, is characterized by a Moderate Influence (AI) overall. Families generally provide motivation, encouragement, and help in preparations for the LET, contributing positively to the Home and Family Factor. However, the influence is moderated by the lower impact associated with the financial support provided for reviewing and taking the LET. The qualitative interpretation provides valuable insights into the varying degrees of influence that different aspects of home and family support can have on the overall performance of students about the studied factors.

Several studies support the significant impact of home and family factors on students’ academic performance. For instance, a study by Trumbull et al. (as cited in Ilhan et al, 2019) found that the way a student lives, their sustenance, and family structure significantly impact their academic achievement. The study of Herrero (as cited by Albina et.al., 2022), pointed out that home and family factors have a high influence on CPA exam performance, alongside student factors.

School Factor

Table 3. Mean Distribution of Respondents’ School Factor

The above table shows that the adequacy of classrooms with proper ventilation has a mean of 1.29 categorizes this indicator as NI (No Influence), suggesting that, on average, the adequacy of classrooms with proper ventilation has no significant influence on the School Factor. Easy access to transportation going to school has a mean of 2.84, this indicator is categorized as MI (Moderate Influence), indicating that, on average, easy access to transportation has a moderate positive influence on the School Factor. Teaching strategies used by instructors that promote effective learning has the mean of 3.03 categorizes this indicator as MI (Moderate Influence), suggesting that, on average, teaching strategies used by instructors have a moderate positive influence on the School Factor. Adequacy of audio-visual resources has a mean of 3.09 categorizes this indicator as MI (Moderate Influence), suggesting that, on average, the adequacy of audio-visual resources has a moderate positive influence on the School Factor. Adequacy of laboratory equipment and physical facilities has a mean of 3.33, this indicator is categorized as HI (High Influence), indicating that, on average, the adequacy of laboratory equipment and physical facilities has a high positive influence on the School Factor. Availability of qualified and dedicated faculty and staff with a mean of 3.41, is categorized as HI (High Influence), indicating that, on average, the availability of qualified and dedicated faculty and staff has a high positive influence on the School Factor.

The overall mean of 2.83 categorizes the School Factor as MI (Moderate Influence), suggesting that, on average, the combined influence of these indicators has a moderate impact on the overall School Factor.

The School Factor, based on the indicators, is characterized by a mix of High Influence (HI) and Moderate Influence (MI). The availability of qualified and dedicated faculty and staff, as well as the adequacy of laboratory equipment and physical facilities, has a high positive influence on the School Factor. Teaching strategies, easy access to transportation, and the adequacy of audio-visual resources contribute positively to the School Factor but to a lesser extent. Meanwhile, the adequacy of classrooms with proper ventilation shows no significant influence based on the overall mean. This analysis provides insights into the varying degrees of influence that different aspects of the school environment can have on the overall performance of students about the studied factors.

According to a study conducted by the Philippine Institute for Development Studies, school infrastructure has a significant impact on student performance. The same study found that low teacher qualification was a major factor in the low-quality education and poor performance of students (Navarro, 2022). Moreover, Bandele as cited by Dayaday (2018), said that the importance of physical facilities cannot be relegated. Facilities like modern laboratories, libraries, and classrooms are to be put in place in all our schools.

Review Center Factor

Table 4. Mean Distribution of Respondents’ Review Center

The table shows that active participation in the review sessions/classes conducted by the review center has a mean of 2.37 categorizes this indicator as LI (Low Influence), suggesting that, on average, active participation has a lower positive influence on the Review Center Factor. While, regular attendance to review sessions/classes conducted by the review center is categorized as MI (Moderate Influence), with a mean of 2.95, indicating that, on average, regular attendance to review sessions/classes has a moderate positive influence on the Review Center Factor.

The overall mean of 2.66 categorizes the Review Center Factor as MI (Moderate Influence), suggesting that, on average, the combined influence of these indicators has a moderate impact on the overall Review Center Factor.

The Review Center Factor, based on the indicators, is characterized by a mix of Moderate Influence (MI) and Low Influence (LI). Regular attendance to review sessions/classes conducted by the review center has a moderate positive influence, contributing to the overall effectiveness of the Review Center Factor. However, active participation in these sessions/classes shows a comparatively lower positive influence, suggesting that, on average, it may not contribute significantly to the overall impact of the Review Center Factor. This analysis provides insights into the varying degrees of influence that different aspects of review center engagement can have on the overall performance of students about the studied factors.

The study of Serrano (as cited by Albina et. al., 2015) pointed out that review school is also a factor that affects performance in the licensure examination. According to Gurung and Bord (as cited by Wang et al., 2018), students who attended review sessions scored significantly higher on exams than those who did not attend, emphasizing the potential benefits of review sessions in enhancing learning and exam preparation.

Personal Factor

Table 5. Frequency Distribution of Respondents’ Personal Factor

As shown in the table, ability to retain what has been memorized has a mean of 2.35, this indicator is categorized as LI (Low Influence), indicating that, on average, the ability to retain memorized information has a lower positive influence on the Personal Factor. Ability to manage test anxiety and other negative emotions has a mean of 2.93 categorizes this indicator as MI (Moderate Influence), suggesting that, on average, the ability to manage test anxiety and negative emotions has a moderate positive influence on the Personal Factor.  Ability to think critically and analyze every item in the exam has a mean of 2.97 categorizes this indicator as MI (Moderate Influence), suggesting that, on average, the ability to think critically and analyze items has a moderate positive influence on the Personal Factor. High motivation to pass the licensure exam has a mean of 3.27, this indicator is categorized as HI (High Influence), indicating that, on average, high motivation has a high positive influence on the Personal Factor. Lastly, emotionally stable when taking the exam has a mean of 3.55, this indicator is categorized as HI (High Influence), indicating that, on average, emotional stability has a high positive influence on the Personal Factor.

The overall mean of 3.01 categorizes the Personal Factor as MI (Moderate Influence), suggesting that, on average, the combined influence of these indicators has a moderate impact on the overall Personal Factor.

The Personal Factor, based on the indicators, is characterized by a mix of High Influence (HI) and Moderate Influence (MI). High motivation, emotional stability, and the ability to think critically contribute significantly to the overall effectiveness of the Personal Factor. The ability to manage test anxiety and negative emotions also positively influences the Personal Factor, though to a slightly lesser extent. However, the ability to retain memorized information shows a comparatively lower positive influence on the overall Personal Factor. This analysis provides insights into the varying degrees of influence that different personal attributes can have on the overall performance of students in relation to the studied factors.

The study of Eckstein and Perels (2014) found a moderate negative correlation (r=-0.27), indicating that higher levels of anxiety tend to be associated with lower academic achievement. The study by Duckworth and Gross (2014) titled “Self-control and academic achievement” investigated the relationship between self-control and academic performance found a positive correlation between self-control and academic achievement: The study found a significant positive correlation between self-control and academic performance. Students with higher levels of self-control, defined as the ability to regulate thoughts, emotions, and behavior to achieve goals, tended to have better academic outcomes.

LET Performance Distribution

Table 6. LET Ratings

The table above shows that there are 63 respondents (36% of the total) who scored below 75, indicating a failed performance on the LET and 112 respondents (64% of the total) who scored 75 or higher, indicating a successful performance on the LET. The total number of respondents is 175, representing the entire sample has an average rating of 76.36.

The distribution of respondents’ LET ratings shows that a majority of the respondents (64%) passed the LET with a score of 75 or higher. On the other hand, 36% of the respondents failed to achieve a score of 75 or higher.

In contrast, the study found that Bachelor of Elementary Education graduates displayed an alarming result since they performed poorly both in General Education and Professional Education. In general, they have a “poor” LET performance (Llego, 2020).

Relationship between Factors and LET Ratings

Table 7. Relationship between LET Ratings

Note. * p < 0.05, ** p < 0.01, *** p < 0.001

For Student Factor, the Pearson’s correlation coefficient (r) of 0.223** with a p-value of 0.003 indicates a statistically significant positive relationship between the Student Factor and LET rating. The correlation is moderate. For Home and Family Factor, the correlation coefficient of 0.191* with a p-value of 0.012 indicates a statistically significant positive relationship between the Home and Family Factor and LET rating. The correlation is moderate. The School Factor has a correlation coefficient of 0.075 with a p-value of 0.322 indicates that the relationship between the School Factor and LET rating is not statistically significant. The correlation is weak. Also, the Review Center Factor has the correlation coefficient of 0.509*** with a p-value < 0.001 indicates a statistically significant positive relationship between the Review Center Factor and LET rating. The correlation is strong. Personal Factor has the correlation coefficient of 0.655*** with a p-value < 0.001 indicates a statistically significant strong positive relationship between the Personal Factor and LET rating.

The study of Delos Angeles (2019) shows that there is a statistically significant positive relationship between respondents’ perceptions on the Student Factor, Home and Family Factor, Review Center Factor, Personal Factor, and their LET rating. The School Factor, on the other hand, does not show a statistically significant relationship with the LET rating. The strengths of the relationships vary, with the strongest correlations observed for the Review Center Factor and Personal Factor. This information suggests that perceptions related to Review Center engagement and Personal attributes have a more substantial influence on LET rating compared to perceptions related to Student, Home and Family, and School Factors.

Predictors of LET Performance

Table 8. Regression Analysis of Students’ Mathematics Comprehension Test Scores with Selected Variables

R = 0.741        R² = 0.549

For Student Factor, the Pearson’s correlation coefficient (r) of 0.223** with a p-value of 0.003 indicates a statistically significant positive relationship

The intercept of 31.49 represents the expected LET rating when all predictor variables are zero. The estimate of 1.60 suggests that, holding other variables constant, a one-unit increase in the Student Factor is associated with an increase of 1.60 units in the LET rating. Also, with an estimate of 3.83, the Review Center Factor has a higher positive influence on LET rating. The estimate of 10.23 indicates that, holding other variables constant, a one-unit increase in the Personal Factor is associated with an increase of 10.23 units in the LET rating. The overall regression model, as indicated by R^2=0.549 explains 54.9% of the variability in LET rating based on the chosen predictor variables.

The regression model equation, based on the information provided in Table 9, would be:

where:  = LET Rating; x₁ = student factor; x₂ = review center factor; x₃ = person factor

This equation represents the estimated LET rating for an individual based on their scores in the Student Factor, Review Center Factor, and Personal Factor. The coefficients (1.60, 3.83, and 10.23) indicate the magnitude of the influence of each predictor variable on the LET rating. The intercept term (31.49) represents the expected LET rating when all predictor variables are zero.

This regression model suggests that, on average, an increase in the Student Factor, Review Center Factor, and Personal Factor scores is associated with an increase in the predicted LET rating. The coefficients provide the estimated change in LET rating for a one-unit increase in each predictor variable, holding other variables constant.

Numerous studies like Geary et al. (2011) demonstrate a strong positive correlation between academic ability, as measured by standardized tests and past performance, and academic achievement. However, it’s important to acknowledge that ability is not fixed and can be influenced by other factors like motivation and study habits. Effective time management, active learning techniques, and seeking help when needed are all crucial for efficient learning and knowledge retention. Dunlosky et al. (2013) provide evidence for the positive impact of various study strategies on academic performance. Students who adopt effective study habits are better equipped to manage their workload, maximize their learning potential, and prepare for exams effectively.

CONCLUSION

In conclusion, this study highlights the different factors that affect students’ performance on the licensure examination, particularly the LET rating. While students show some interest and commitment to their studies, this alone does not significantly boost their performance. This indicates a need for better strategies to help students develop stronger study habits. Family support is essential, but there is room for improvement in financial help and active involvement from parents. Additionally, while schools provide good faculty and facilities, enhancing the school environment could further benefit students. The positive link between attending review sessions and better outcomes shows that encouraging more student participation can lead to greater success.

Furthermore, the study finds that motivation, emotional stability, and critical thinking skills are important for doing well on the exam. Even though most students passed the LET, it’s crucial to understand why 36% did not succeed. The results confirm that certain factors significantly influence exam performance, rejecting the idea that these factors do not matter. The analysis shows that Student, Review Center, and Personal Factors play a big role in predicting how well students will do on the LET. By focusing on improving family support, school resources, and personal skills, we can better prepare students for success in their licensure examinations.

RECOMMENDATION

Based on the survey results and findings, educational institutions should prioritize the development and implementation of programs that foster effective research habits among students. By establishing initiatives that provide guidance and resources for research skills, schools can significantly enhance students’ overall performance in licensure examinations. Collaboration between institutions and families is also essential; providing additional financial support for review expenses and encouraging active parental involvement can create a more supportive environment for exam preparation. Schools should actively seek partnerships with

families to ensure that students receive the necessary encouragement and resources to succeed.

Additionally, school administrators should focus on continuous improvement in teaching strategies, facility conditions, and faculty qualifications to create a more conducive learning environment. Review centers could implement interactive activities and personalized support to boost student engagement during review sessions. Furthermore, students and educators should collaborate to adopt effective memory retention techniques, such as mnemonic devices or spaced repetition, to improve learning outcomes. Conducting an in-depth analysis of the challenges faced by the 36% of students who did not pass can help identify specific areas for targeted interventions. Overall, educational institutions and policymakers should prioritize support systems that address the Student, Review Center, and Personal Factors to enhance student success in licensure examinations.

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