Exploring Latent Class Profiles of Mathematics Performance among Filipino Students: Insights from PISA 2022 Using Growth Mindset Indicators and Group Comparison Analysis

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Exploring Latent Class Profiles of Mathematics Performance among Filipino Students: Insights from PISA 2022 Using Growth Mindset Indicators and Group Comparison Analysis

https://doi.org/10.21203/rs.3.rs-4617174/v1

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This study explored the growth mindset among Filipino students and its impact on mathematics performance. It utilized the data from the PISA 2022 assessment. Growth mindset has been illustrated as the belief that abilities can be developed through effort. It is identified as a critical factor that influences educational outcomes. The primary aim of this study is to identify distinct latent class profiles based on growth mindset indicators among Filipino students. Also, it examined the relationship between these profiles and mathematics performance. The study is grounded in the growth mindset theory. This theory posits that students' beliefs about their intelligence and abilities can significantly influence their academic performance. Growth mindset is classified as a concept of multidimensional because it encompasses mental, physical, emotional, and spiritual aspects. Thus, this is also explored. Data from 6,791 Filipino students who participated in PISA 2022 were analyzed. The study employed Latent Class Analysis (LCA) to identify distinct growth mindset profiles based on student responses to mindset-related questions. Following the identification of profiles, ANOVA was used to determine differences in mathematics performance among the identified groups. Based on the results, there were three latent classes were identified: Limitation Acceptors, Optimistic Learners, and Mindset Explorers. Limitation Acceptors (50% of the students) predominantly believed in fixed intelligence and performed lower in mathematics. Optimistic Learners (17%) exhibited a strong growth mindset and achieved significantly higher mathematics scores. Mindset Explorers (33%) displayed ambivalence towards fixed and growth mindset statements, with mathematics performance similar to Limitation Acceptors. ANOVA results indicated a significant difference in mathematics performance among the three groups, with Optimistic Learners outperforming the other two.

Latent Class Analysis

mathematics performance

growth mindset

PISA

Results from international assessments like the Programme for International Student Assessment (PISA) and Trends in International Mathematics and Science Study flaunted the real face of our education system in the Philippines^[16][15][5]. Data reported by these international assessments tell that mathematics education is still a major concern that needs attention among experts and policymakers. Mathematics proficiency among Filipino students is still at lower levels meaning they lack critical thinking skills which is an important skill among 21st-century learners^[16][5]. It is also reported that there is a descending interest in mathematics learning which was further worsened by the COVID-19 pandemic because of the adoption of modular and asynchronous teaching methods, which both the learners and the teachers were not well-equipped to handle, especially in teaching and learning mathematics^[16][5][21].

According to the OECD (2023), there is still rampant usage of traditional teaching methods which fails to prepare most Filipino learners to solve real-world problems. This very reason stems from the challenges and gaps in understanding the students’ performances in mathematics. Their reports also include the disparity among the country’s regions and between public and private schools which persists and intensifies all the challenges the country is facing. Playing an important role in future opportunities and global development, mathematics proficiency among Filipino learners continues to decline due to various factors, including insufficient teaching and learning practices^[15][21].

Developing effective instructional strategies will greatly help only if educators acknowledge students' varying levels of mathematics proficiency^[15]. There is a need to address the infrastructure gaps, reduce teacher-student ratios, and invest in teacher training^[31]. These interventions and support strategies will understand the diversity in mathematics performance among students. Since students come from heterogeneous populations, Latent Class Analysis (LCA) can be used as a powerful statistical tool to reveal latent patterns or profiles with a particular focus on analyzing mathematics performance data^[20]. One of LCA’s advantages as compared to traditional methods in grouping students such as cluster analysis or factor analysis is that it is model-based. Another advantage is it estimates of probabilities of class membership for each individual analyzing the observed variables. In the study of Nacion & Balila (2020), LCA was able to uncover unobservable characteristics among students. These characteristics showed a significant impact on the mathematics performance of the students, thus giving a clearer understanding of students' profiles. As a result, they were able to provide valuable insights for educational interventions.

According to Williams et al (2022), educators should consider the inclusion of growth mindset indicators in constructing and developing their assessments specifically when it comes to learning mathematics. The inclusion of it will give a full understanding of the student’s attitudes and strategies in dealing with mathematics. Moreover, they have found that students with a growth mindset prioritize perseverance. Results also showed that exerting hard work in the learning process could link to resilience. Hence, analysis from these studies seconded the study of Lagon (2023) that mathematics education in the Philippines is facing obstacles. There is a need to align the targets of the country to the broader educational goals which are promoting equity and enhancing learning outcomes.

Therefore, this study will be able to give valuable information to the educational policies and practices in the Philippines. Results from this study may look deeper and determine possible reasons behind the decline in students’ interest in mathematics. It may elaborate factors inhibited in the education system showing the gaps in critical thinking skills of Filipino learners compared to their international counterparts. Hence, there should be a deeper analysis and understanding of how to promote and deliver targeted interventions to attain better mathematics performance results, especially in international assessments. Thus, this paper is aiming for valuable results that may contribute to the improvement of mathematics education in the Philippines.

This paper aimed to explore the responses of Filipino students in the PISA 2022 growth mindset questionnaires using Latent Class Analysis (LCA). Specifically, it aimed to:

Determine any latent class profiles among Filipino students based on their responses from growth mindset indicators in the Programme for International Student Assessment (PISA) 2022.

Determine whether there are significant differences in the mathematics performance among the latent class profiles to be identified through Latent Class Analysis (LCA).

Illustrate the difference regarding mathematical proficiency, as measured by the PISA 2022 mathematics score.

Obtaining results from these objectives may shed light on the varying levels of mathematics performance exhibited by Filipino students. Also, investigating the potential impact of growth mindset indicators on their academic achievement may help to advance the field’s knowledge of efficacious educational interventions and support approaches that cater to the diverse requirements of students in the Philippines.

The Current State of Mathematics Education in the Philippines

Mathematics education in the Philippines strives to teach critical thinking and problem-solving abilities that are essential for 21st-century learners^[14]. However, the COVID-19 outbreak added to the challenges and worries in this field of endeavor. There were obstacles in fulfilling K12 curriculum goals in terms of teaching techniques and instructional quality. Remote teaching has been an alternative, but most teachers have not received training in this mode^[23]. In which the topic of developing remote instructions that emphasize the need to move beyond equality of access and consider diverse features of the learners was not addressed^[6]. These challenges and concerns were also identified in the study of Atweh et al (2023). They recommended that the Philippines invest in fulfilling education's social aims, such as the impact of mathematics on society's challenges and the development of critical thinking abilities. Filipino teachers must learn to incorporate mathematics into other areas. The country must address inequities in language and access to effective mathematics education, particularly among underprivileged kids. Improvements in mathematics education assessment procedures include the development and implementation of reliable assessment tools and techniques, as well as the exploration of the use of technology in informal contexts, such as an out-of-school mathematical learning environment.

These issues and concerns were more highlighted when the Philippines joined in international assessments such as the Programme for the International Student Assessment (PISA) in the years 2018 and 2022 and also in the Trends in International Mathematics and Science Study (TIMMS) in 2019. Both international assessments performed the Filipino students showed a critical concern among educators and policymakers in the country^{[10][2][14][17]}. Among counterparts in the neighboring countries, the performance of Filipino students demonstrated lower levels of mathematical proficiency revealing deficiencies in critical thinking skills and a declining interest in the subject^{[10][2][13][14][17]}.

Traditional teaching methods have been pinpointed as the root of why challenges and gaps in understanding mathematics performance among Filipino students persist and most of the time fail to prepare the learners to solve real-world problems^{[10][2][13][14][17]}. The results also showed students from private schools outperformed students from public schools, highlighting inequities that aggravate the students' struggles, as evidenced by the 2018 PISA report ^{[10][2][13][14][17]}. The mathematical proficiency of Filipino students continues to decline despite its critical role in academic achievement, future opportunities, and nation-building due to various factors, including inadequate teaching and learning practices^{[10][2][13][14][17]}.

The examples described above highlight the urgent need to address the country's mathematics education difficulties. Improving teacher training, innovative teaching methods, and addressing access gaps aim to solve education concerns. The government and education sectors must increase mathematics competency, cultivate critical thinking in learners, and empower them to succeed in the 21st century.

Understanding Mathematics Performance among Filipino Students

The following paragraphs will enumerate the specific factors from various studies that significantly contribute to why there is still a persistent issue in achieving high-quality mathematics education in the country, as well as provide a better understanding of Filipino students' mathematics performance.

Teaching Methods and Pedagogical Approaches

Factors such as pedagogical competencies and educational resources, which are teacher-related variables, were identified by Peteros et al. (2020) as crucial factors shaping the academic achievement of students in mathematics within the context of the Philippines. These variables serve as substantial predictors, emphasizing the importance of effective teaching practices and adequate learning materials in promoting mathematics proficiency. The same study by Froilan & Cutillas (2023) found that determining instructor quality impacts the mathematics performance of Filipino students. They suggest considering the diverse learning preferences of students when formulating instructional approaches.

Socioeconomic Factors and Educational Inequality

Students' level of interest, study patterns, instructors' dispositions, school milieu, and home setting are not significant predictors of mathematics performance^{[22] [9]}, whereas socioeconomic factors and educational inequality have a significant impact on student's academic outcomes. Studies have highlighted the role of educators, families, and learners in influencing mathematics performance, with the constructive attributes and efforts of instructors playing a paramount role^[26].

Student Attitudes and Perceptions Towards Mathematics

Among student factors, their attitudes and perceptions towards mathematics play a crucial role in determining performance outcomes. While favorable study habits, attitudes, and learning methodologies among students have been associated with improved mathematics performance^[1], factors like learning preferences and drive do not necessarily correlate with academic achievement^[9].

The issues and concerns raised above were not new. The country has been dealing with these concerns for several years already, but still, mathematics education in the Philippines is at par as compared to its neighboring countries. To sum it up, several empirical investigations have explored factors influencing mathematics performance among Filipino students. A wide range of variables were examined, and these include teacher-related factors, socioeconomic backgrounds, student attitudes, and learning preferences. While some variables, such as pedagogical competencies and educational resources, emerge as significant predictors of mathematics achievement^[22], others, like learning preferences, may not have a direct impact on academic outcomes^[9].

Studies above reveal a complex relationship of factors that influence mathematics performance in the Philippines. These indicate that teacher-related variables and educational resources show a significant role in promoting academic achievement. In addition, socioeconomic factors and student attitudes are important factors that impact performance outcomes. In conclusion, multifaceted challenges faced by the country must be addressed to enhance mathematics education which consequently will improve student outcomes.

Thus, insights from the reviewed studies have important implications that may help improve educational practice and policy in the Philippines. There should be efforts from the government to enhance teacher competencies, provide adequate learning resources in all the regions of the country, and address socioeconomic disparities, which are vital steps toward improving mathematics education outcomes. Moreover, to help improve academic performance in mathematics, educators should promote interventions that focus on encouraging positive student attitudes toward the academic area hence promoting effective learning.

Growth Mindset and its Relevance to Mathematics Education

According to Kolyda (2023), Xiaoyu et al. (2022), Dong et al. (2023), Ricci (2021), and Hoetmer (2022), cultivating growth mindset promotes a significant impact, particularly on mathematics performance among students. Building classrooms that practice and promote a growth mindset is encouraged among educators because it helps lessen academic achievement disparities among students, especially those who are from underprivileged backgrounds. Dong et al. (2023) showed that a growth mindset has an indirect impact on mathematics ability, that is through intrinsic motivation. In addition, they discussed the role of intrinsic drive, failure attributions, mathematical self-efficacy, and anxiety in molding academic accomplishment with a growth mindset, students who have positive thinking did better performance in mathematics. Similarly, Lou & Noels (2020) revealed that societal mindset norms influenced the relationship between growth mindsets and academic outcomes.

Accordingly, promoting a growth mindset and integrating it into the teaching approaches in the classroom that incorporate problem-based learning is indispensable in achieving a positive impact on the academic performance of Filipino students particularly in mathematics^[24]. Again, as mentioned by Xiaoyu et al. (2022), there should be voluntary actions among educators in providing interventions that unravel intrinsic motivation, failure attribution, mathematics self-efficacy, and mathematics anxiety in improving mathematics outcomes through positive thinking. Lastly, the aforementioned issues are seeking solutions that assist the formation of growth mindsets for effective learning, that is whether the learner’s mindset is growth or fixed, these have a considerable impact on their mathematical accomplishment^[33].

Educational systems in the Philippines need to start modifying classroom approaches. Offering approaches and activities that promote a growth mindset may help students achieve better outcomes and finally develop an interest in learning mathematics.

Latent Class Analysis (LCA) and its Application in Educational Research

Latent Class Analysis (LCA) has been known in the field of education because of its capability to reveal the underlying structures and patterns within a population. LCA uses an algorithm where it analyses the responses of individuals in a set of variables. After this, it produces possible homogeneous subgroups that classify the population^[29]. One of LCA’s applications is through multigroup analysis. From the exploration to the participants’ responses, specific behaviors or characteristics will be distinguished and enable the comparison of class patterns between different groups of individuals^[27][19]. LCA can also be used and fit into a structural equation model framework^[25]. He used it to examine how latent classes interact among selected variables demonstrated in the context of coping strategies and academic performance.

Unlike traditional grouping methods like Factor Analysis, LCA has several advantages in educational research. One of which is the Bayesian nonparametric LCA. Meng et al. (2023) utilized the Latent Class Analysis method in their study to determine the number of classes and handle label switching. Using this method, their study was able to provide valuable insights into clustering individuals based on different item types. Also, Weller, Bowen, & Faubert (2020) explored the power of LCA in their paper. They utilized LCA in a multivariate modeling approach. They have observed that LCA has a unique characteristic. They concluded that it allows for a more effective exploration of heterogeneous characteristics within the data. The results also showed that LCA revealed latent segments across various applications and helped extract meaningful groups from data. Likewise, Haydar (2021) applied LCA by incorporating log-linear parameterization. Using LCA, allowed them to improve the precision and accuracy of associations between variables. As a result, it enhanced the overall quality of research findings.

Studies above showed LCA’s application to a wide range of research studies. This also has shown its versatility. In education, researchers have utilized LCA to understand students' and teachers' behavior and improve academic outcomes. It is also determined that the application of LCA in a multi-group approach in the field of education can establish unique subgroups among target respondents^[27]. They were able to reveal patterns to understand the cheating behavior among students. Similarly, Haydar (2021) & Vermunt (2023) employed LCA in their exploration of the associations between variables using unobserved factors. LCA made a significant precision in modeling latent segments in their studies. It was also determined to be an effective method for improving the assessment results of learners. The results lead to a mixture of components within educational data. Among LCA’s applications in education is its power to involve clustering, scaling, and random effects modeling. Thus, these make LCA valuable in the field of education.

In conclusion, Latent Class Analysis (LCA) is an effective method used in this study. It has the power to elicit subgroups among Filipino students based on their responses to the growth mindset items of PISA 2022. Findings from this method provided unique and interesting results that helped better understand how Filipino students deal with mathematics. Therefore, the results lead educators to the necessary interventions to attain better educational outcomes in the future.

Data

This research paper will use the Philippine data set for PISA 2022 uploaded on the OECD website. PISA is a large-scale assessment triennially administered among its member countries to a randomly selected group of 15-year-old students for the academic areas of mathematics, reading, and science literacy. There is a focus on one educational place for each assessment, and for 2022, mathematics literacy is the primary domain. In this study, the area examined is the growth mindset indicators employed by the students and mathematics literacy. PISA uses different forms to other students designed to obtain a piece of broader and comprehensive information regarding the factors connected to student performance, attitudes, behaviors, and education systems (e.g., demographic variables, previous educational career choices, instruction time, and class size). Thus, students who did not respond to the questions scaling the growth mindset of the students will be deleted.

Table 1

Filipino Students Participated in PISA 2022 in Terms of Sex
Sex	Frequency	Percent
Female	3470	51.1
Male	3321	48.9
Total	6791	100.0

After a rigorous selection process conducted by the Organization for Economic Cooperation and Development (OECD) to participate in the Programme for the International Assessment (PISA), a total of 7193 Filipino students were chosen, after removing the students who did not respond to the questions under the growth mindset section of the student's questionnaire, this study was conducted with 6791 students as shown in Table 1. a. Out of these valid participants, 3470 of which are female (51.1%) and 3321 are male (48.9%).

Growth Mindset Questionnaire

One of the advantages that the PISA has as an international is it includes questions that scale the indicative of the student's mindset. Students were asked to rate statements (e.g. “Your intelligence is something about that you cannot change.”, “Some people are just not good at mathematics, no matter how hard they study.”, “Some people are just not good in the English language, no matter how hard they study.”, and “Your creativity is something about you that you cannot change very much.”). Students will choose among the four response options (“Strongly disagree”, “Disagree”, “Agree”, “Strongly agree”). Thus, with the varying mindsets among Filipino students, Latent Class Analysis (LCA) will be employed to explore latent classes that may occur based on their responses to the stated question under the growth mindset category of the PISA questionnaire and how these classes or subgroups differ in terms of mathematics performance.

Table 2

Filipino students who responded to the Growth Mindset Questions
Growth Mindset Questions	N	Mean	Std. Deviation
Agree/disagree: Your intelligence is something about you that you cannot change very much.	6791	2.64	.750
Agree/disagree: Some people are just not good at mathematics, no matter how hard they study.	6791	2.63	.786
Agree/disagree: Some people are just not good in [test language], no matter how hard they study.	6791	2.57	.783

Among the four questions, Filipino students did not answer the last question (“Your creativity is something about you that you cannot change very much.”). Thus, as shown in Table 1.2, only the three questions were used in conducting the Latent Class Analysis. In performing the Latent Class Analysis, it is important to simplify the responses of the participants (1 = Strongly disagree, 2 = Disagree, 3 = Agree, 4 = Strongly agree) into binary, thus, were recoded into (1 = Disagree, 2 = Agree). The mean and standard deviation of the participant's responses were also revealed in Table 1.2

Data Analysis:

Several steps will be conducted in analyzing the data. First, to determine the latent class profiles of Filipino students based on growth mindset indicators, Latent Class Analysis (LCA) will be conducted. After determining the latent class profiles of the respondents, Analysis of Variance (ANOVA) will be used to determine whether there are differences between the profiles. If there are significant differences in the results, a post hoc test will be conducted to analyze the results. The level of significance for all the analyses will be determined at the 0.05 level.

Latent Class Profiles Among Filipinos Using Growth Mindset Indicators

Researchers advise using a combination of criteria in determining the number of classes in Latent Class Analysis modeling^[28]. Among these criteria are the Akaike Information Criterion (AIC), the Bayesian Information Criterion (BIC), the Adjusted BIC, the Lo-Mendell-Rubin Adjusted LRT Test (LMR-LRT), and entropy are the most common and recommended statistical goodness of fit indices to be used for model selection. Smaller AIC, BIC, and adjusted BIC values show a better fit while a significant LMR-LRT value and a larger entropy value are optimal.

Table 1 shows the different models (2-class model up to 6-class model) tested to determine which one will give the best statistical fit using AIC, BIC, ABIC, LMR (LRT), and Entropy as criteria. Data used to run the Latent Class analysis were the re-coded responses of the Filipino learners who joined the PISA 2022. Examining Table 1, Model 3 or a 3-class model showed a better fit according to AIC (23659.195), BIC (23734.252), and ABIC (23699.296) values. On the other hand, Model 2 or a 2-class model is optimal if we look at the results given by the LMR (LRT) (3416.645, p < .01) and Entropy (0.777). Since theoretically, the growth mindset is multidimensional or heterogeneous, to explain further and to capture the variability in data, a 3-class model will be better^{[7][18][14][32]}. A growth mindset encompasses mental, physical, emotional, and spiritual aspects. It extends beyond intellectual abilities. This concept is referred to as a multidimensional growth mindset^[3].

In addition, a 3-class model represents a meaningful model to represent meaningful subgroups of learners possessing distinct characteristics or response patterns aligned with the theoretical expectations and practical implications. Thus, taking more than 2 classes can give room for further analyses in examining the characteristics of each class providing valuable insights into the underlying mechanisms driving differences in growth mindset among Filipino students. Analyses from a 3-class model are also beneficial in resolving practical implications for educational interventions, policy-making, or targeted support programs to promote a growth mindset and improve mathematics performance among Filipino students.

Table 3

Latent Class Analysis Models
MODEL	AIC	BIC	ABIC	LMR(LRT)	P	ENTROPY
2	23651.195	23698.958	23676.714	3416.645	0.0000	0.777
3	23659.195	23734.252	23699.296	0.000	0.8921	0.611
4	23667.195	23769.545	23721.879	0.000	0.5367	0.498
5	23675.195	23804.838	23744.461	0.000	0.2770	0.596
6	23683.195	23840.132	23767.043	0.000	0.0000	0.512

Adopting the 3-class model, there were 3 425 (50%) Filipino students who fell under class 1, 1 111 (17%) students who were classified to be under class 2, and 2 255 (33%) were classified to be under class 3. Table 2 shows the student probabilities after examining the response patterns of Filipino learners in answering the questions under the growth mindset. Taking 0.208 as an example, it means that only 20.8% of the learners under class 1 responded “disagree” to the question “Your intelligence is something about you that you cannot change very much.” This means that almost 80% of Filipino learners belonging to class 1 predominantly agree with the statements implying fixed intelligence. They believe that it is innate among them to have limitations in mathematics and language. This is quite alarming because as we can see, the total enumeration of this group is half of the total population of our respondents. Results from a 3-class model showed that the majority of Filipino learners (members in class 1) who took the PISA 2022 hold a belief that intelligence is fixed. Dong et al. (2023) explained in their paper that students in this group are likely to fail in their academic activities, which is likely attributed to fixed abilities which is an attribute of a fixed mindset person. This means that they believe that some individuals are inherently incapable of excelling in certain subjects, regardless of effort. Thus, this group of students is called “Limitation Acceptors.”

Class 2 on the other hand showed different results as compared to class 1. Students in class 2 believe that they are capable of moving out of their shells and show better results in their performances as time passes by. In short, this group of students exhibits the characteristics associated with a growth mindset because they tend to disagree with statements suggesting fixed intelligence. 91.7% of students from this group answered “disagree” to the statements “Some people are just not good at mathematics, no matter how hard they study.” and “Some people are just not good in (Test Language), no matter how hard they study.” They disagree with having inherent limitations in subjects like mathematics and language. Members of this group may believe that their intelligence and academic abilities can be developed through effort and perseverance. Xiaoyu et al. (2022) described this type of learners who are intrinsically motivated and with boosted self-efficacy. These students view failures as challenges and a learning opportunity, leading to better performance in mathematics. Thus, this group of students is termed as “Optimistic Learners.”

Table 4

Conditional and Latent Class Probabilities for Reading Strategies Using 3-Class Model.
Item		Class 1	Class 2	Class 3
To what extent do you agree or disagree with the following statements?	1. Your intelligence is something about you that you cannot change very much.	0.208	0.594	0.416
	2. Some people are just not good at mathematics, no matter how hard they study.	0.022	0.917	0.621
	3. Some people are just not good in (Test Language), no matter how hard they study.	0.000	0.917	0.806

Probabilities showed by the members in class 3, 41.6% of them disagreed in item 1, 62.1% answered a “disagree” in item 2, and 80.6% disagreed in item 3. Response patterns from this group showed an exploration in terms of a growth mindset. It is a mixed response pattern, showing that some agree with the statements suggesting fixed intelligence and limitations while also expressing some disagreement. This attitude of responding to the statements exhibits ambivalence, and uncertainty regarding their beliefs about intelligence and academics beliefs. Students of this group actively seek to understand and apply the principles of a growth mindset. They keep on exploring various strategies to improve their learning. They are also capable of adapting to various challenges which helps them enhance their learning experiences^[32]. Therefore, this group is being called “Mindset Explorers.”

Mathematics Performance of Filipino Students in PISA 2022 Using Growth Mindset Profiles

Results of the mathematics performance of 15-year-old students in the Philippines are evidence of being consistently underperformed compared to their peers in neighboring countries and on a global scale. It is also an indication that students in the Philippines have not acquired the essential competencies in mathematics, hence significantly behind international standards. On the other hand, educators and researchers believe that cultivating a growth mindset among learners can address the competency gaps that each country is experiencing^{[3][32][8][7][24][12]}. Encouraging educators to use more positive and proactive approaches to learning is one way of promoting a growth mindset among learners. Through a collaborative effort from the stakeholders, giving value and learning from mistakes, the Philippines may achieve significantly enhanced quality of education, contributing to stronger economic growth and global competitiveness.

Table 3 shows the mean performance of the classified growth mindset profiles of Filipino students who participated in the recently released results from PISA. The mathematics performance of the learners was identified using one of the Plausible Values in Mathematics (PV1MATH). These plausible values likely represent the proficiency of the learners based on their obtained scores in mathematics.

Limitation Acceptors has 3425 Filipino students with a mathematics performance mean of 352.49. Optimistic Learners has 1111 test takers with a mathematics performance mean of 374. 44. Lastly, Mindset Explorers has 2255 students with a mean performance in mathematics of 352. 65. To determine if there is a difference in the mathematics mean performance among profiles, one-way ANOVA was used.

Table 5

Performance Growth Mindset Profiles of Filipino Students in Mathematics in PISA 2022
Growth mindset profiles	Number of respondents	Mean performance
Limitation Acceptors	3425	352.49 b
Optimistic Learners	1111	374.44 a
Mindset Explorers	2255	352.65 b
The mean difference is significant at the 0.05 level.

ANOVA results (F_{(2, 6788)} = 55.734, p < 9.81E-25) showed that there is a statistically significant difference in mathematics performance among growth mindset profiles. In addition, the Tukey post hoc test revealed that Optimistic Learners performed significantly better in mathematics in PISA 2022 compared to Limitation Acceptors (352.49 ± 56.80, p < .01) and (352.65 ± 64.18, p < .01) Mindset Explorers . On the other hand, the mathematics performances of Limitation Acceptors and Mindset Explorers showed no difference (p = 1.71).

Results from the ANOVA test further added to the limited literature in the Philippines showing how a growth mindset could help learners achieve better academic performances, especially in mathematics. Also, helping students to have positive views and outlook towards achieving academic goals will enhance the achievement and realization of academic goals and objectives specifically attaining all the necessary skills and competencies in mathematics.

This study explored the latent class profiles of Filipino students who participated in PISA 2022. Based on students' responses to the growth mindset indicators, Latent Class Analyses (LCA) were administered to identify distinct classes. To determine the optimal number of classes, AIC, BIC, adjusted BIC, LMR-LRT, and entropy were used. Results showed that a 3-class model provided the best fit. These classes were identified as "Limitation Acceptors," "Optimistic Learners," and "Mindset Explorers." Fifty percent (50%) of the respondents were classified as Limitation Acceptors and labeled as students who predominantly believe that intelligence is fixed and have lower performance in mathematics. Optimistic Learners on the other hand, 17% of the total enumeration of the respondents, were characterized to exhibit a strong growth mindset, believing that intelligence can be developed through effort, and show higher performance in mathematics. Lastly, the remaining 33% of the students were classified as Mindset Explorers. Learners in this class display a mixed response, indicating ambivalence towards fixed and growth mindset statements, with mathematics performance similar to Limitation Acceptors.

ANOVA results revealed a significant difference in the mathematics performance among the three identified classes. By post hoc test, Optimistic Learners performed significantly better in mathematics compared to the other two groups.

This study highlights the significant difference in growth mindset among Filipino students and its corresponding impact on their mathematics performance. The identified three distinct classes emphasized the complexity of the growth mindset among Filipino learners. The findings of this study suggest that students with a stronger mindset (Optimistic Learners) tend to perform better academically, particularly in mathematics. Therefore, this study has the potential benefit of encouraging a growth mindset to improve educational outcomes.

Based on the findings and conclusion of this study, the following recommendations were formed:

1. Educational Interventions: It is proposed that in the program planning of school heads, they may include developing and implementing activities that promote growth mindset principles. Examples of these are workshops, curriculum integration, and teacher training. Activities mentioned may enhance students understanding that intelligence and abilities can be developed through effort and perseverance.

2. Teacher Training: To equip teachers with skills that will help them encourage and nurture a growth mindset in classrooms through professional development. These may include training that focuses on recognizing and addressing fixed mindset beliefs among students. This plays a vital role since growth mindset helps in creating a classroom environment that promotes resilience and a love for learning.

3. Policy Implications: Crafting national policies promoting growth mindset may be considered. Educational policymakers may help teachers to acquire a series of training to achieve the necessary competencies in promoting growth mindset inside their classrooms for improved student performance.

4. Further Research: Researchers may probe deeper into the impact of growth mindset beliefs on academic performance by conducting longitudinal studies. Longitudinal studies may find more interesting factors that would explain better how the development of growth mindset beliefs helps students to improve further in their academic performances in different cultural contexts.

ACKNOWLEDGMENT

I would like to express my sincere gratitude to the organizers of the International Conference on UN Sustainable Development Goals (UN SDGs) and Social Innovation (ICUNSSI) for providing the opportunity to present and publish this research. The platform offered by ICUNSSI not only facilitates the dissemination of innovative ideas but also fosters a collaborative environment for addressing global challenges. Their dedication to advancing the UN SDGs through academic and practical contributions is truly commendable. Thank you for considering this work for presentation and publication at your esteemed conference.

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The authors declare no competing interests.

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Exploring Latent Class Profiles of Mathematics Performance among Filipino Students: Insights from PISA 2022 Using Growth Mindset Indicators and Group Comparison Analysis

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Abstract

I. INTRODUCTION

II. REVIEW OF RELATED LITERATURE

III. METHODOLOGY

IV. RESULTS AND DISCUSSION

V. SUMMARY

VI. CONCLUSION

VII. RECOMMENDATIONS

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ACKNOWLEDGMENT

References

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