Navigating Schools through the Pandemic Crisis: A Study on the Determinants Influencing the Well-Being of Secondary Students in Northeast Thailand

Abstract

The COVID-19 pandemic has disrupted education systems worldwide, with students facing challenges related to online learning, social isolation, and mental well-being. This study explores the determinants of well-being in education among secondary school students in northeast Thailand during the post-pandemic recovery phase. Employing a multistage sampling approach and Cochran’s formula for sample size determination, the research engaged 400 students from 30 schools. Data were collected using an interview schedule based on the OECD’s framework for well-being in education, assessing psychological, social, cognitive, and physical dimensions. Multiple regression analysis revealed that students’ perceptions of the pandemic’s social impact, family relationships, school personnel, and the school’s physical environment significantly influenced their well-being in education, collectively explaining 45.30% of the variance. The findings underscore the importance of fostering supportive family environments, ensuring adequate school staffing, and improving educational infrastructure to enhance students’ well-being in the post-pandemic context. This study offers valuable insights for educators and policymakers in developing targeted interventions and policies that prioritize the holistic well-being of students, ensuring a resilient and inclusive educational environment in the face of global crises.

1. Introduction

The COVID-19 pandemic has posed unparalleled disruptions to several aspects of human society, including impacts on the entire educational sphere [1,2]. During the 2020–2021 academic year, a substantial number of students, totaling over 147 million and representing more than half of the global student population, encountered the denial of access to their schools as a part of lockdowns to ensure that the pandemic is curbed. The mandatory closure of schools resulted in a rapid shift towards online learning methods [3,4]. The unanticipated change in the mode of educational provision presented significant challenges for both students and educators, with wide-ranging effects on not just physical health but also the mental health and psychological well-being of children [4,5]. However, the shift to online learning was not uniform across the globe. Developed countries, with robust digital infrastructures, could more readily adapt to online education, mitigating some educational disruptions. In contrast, many developing countries struggled with this transition due to limited access to technology and internet connectivity, which exacerbated educational inequalities [6]. In addition, the emotional and psychological impact on students’ well-being was further intensified by the deployment of lockdown measures, adherence to social distancing procedures, and heightened dependence on virtual contact [7].

Amidst the backdrop of the worldwide pandemic, 24 million students across various educational levels, from early childhood to higher education, face the possibility of being unable to resume their studies at their respective institutions, and nearly half of these students are located in South and West Asia and sub-Saharan Africa [4]. The education system in Thailand witnessed significant changes with far-reaching effects, including lifestyle, economics, culture, and education management. Similar to many countries, the swift spread of COVID-19 in Thailand prompted the implementation of school closures and an urgent transition to remote learning platforms. Thai educational institutions have implemented virtual learning environments, conducted training for instructors to proficiently utilize these platforms, and built support mechanisms to tackle the difficulties of distance education. Nevertheless, there were practical constraints when it came to applying novel methods of teaching and learning. As a result, the availability of educational opportunities was hampered, leading to difficulties for students in adjusting to new online learning formats [8,9].

The emergence of the “new normal” necessitated a shift for both students and educators towards the virtual learning environment, resulting in complex challenges related to the quality of education and the digital divide. The challenges are particularly acute for secondary students in Thailand, who face significant obstacles in their academic progress due to sudden shifts in exam preparation and the critical nature of their coursework [10], such as obstacles to their academic progress [8] and the uncertainty of support from family [11,12]. This financial strain not only hindered students’ access to essential educational resources but also heightened their vulnerability to the adverse effects of the pandemic. Concurrently, the pandemic’s toll on mental health cannot be overstated, as secondary students navigated isolation, anxiety, and the stress of adapting to new learning modalities [13]. Furthermore, the interruption of traditional classroom instruction results in pervasive gaps in students’ knowledge and skills [14]. In addition, factors exacerbating the challenges posed by the pandemic include assessment practices that place a greater emphasis on testing rather than fostering a comprehensive understanding, increased workloads for teachers, and the limited involvement of parents and the community in the educational process [9,15].

Although the negative consequence of COVID-19 is evident, the pandemic also presents opportunities. In particular, the lockdown measures motivate the transition from conventional modes of education to distance and online modes of learning [16]. In Thailand, the conventional mode of education prior to COVID-19, although it has undergone reforms, is argued to be responsible for the low performance of education that is reflected in the PISA scores. In addition, educators have recently recognized the links between students’ well-being and educational performance. Given the complex nature of constraints posed by COVID-19 and the response to the crisis, there is a notable deficiency in research about students’ well-being within the Thai school system during the period after COVID-19. Therefore, it is crucial to analyze how the Thai education system responded to the crisis and how this affected the well-being of students, which could further influence educational outcomes.

The main objective of this study is to examine the factors that influence the well-being of secondary students in the aftermath of COVID-19. This research endeavors to provide significant insights to policymakers, educators, and stakeholders in the Thai education system, not only given the possible recurrence of the pandemic but also because of the importance of transitional education management in response to other types of global crises. This paper delves into the consequences of COVID-19 on education and its impact on the well-being of students in Thai schools. Additionally, this research will suggest strategies that are supported by evidence and prioritize the well-being of students, while also promoting a resilient and inclusive educational setting. The study endeavors to provide an enabling educational setting that facilitates the adaptation and growth of students in distant northeast schools by addressing their distinct requirements and confronting the obstacles they encounter.

2. Theoretical Framework

Well-being is a broad concept and is sometimes variously defined. It is generally agreed that well-being encompasses both subjective and objective aspects. Often, the concept of well-being is interchangeable with the concept of quality of life [17]. In an objective or material aspect, well-being covers “need satisfiers” [18], including nutritional food and clean water, protective housing, a non-hazardous work environment, appropriate healthcare, security in childhood, significant primary relationships, physical security, economic security, safe birth-control and childbearing, appropriate education, and a safe environment. Objective well-being is identical to the social services or welfare provided to the population who fail to maintain an acceptable level of well-being from the labor market [19].

On the other side, subjective well-being is concerned with intangible aspects, primarily the cognitive conditions of human beings. Subjective well-being is considerably fueled by positive psychology [20]. Deiner (2000), a prominent positive psychologist widely known as Dr. Happiness, defines subjective well-being as a broad category of phenomena that involves people’s emotional responses, domain satisfactions, and global judgment of life satisfaction. Subjective well-being is composed of three domains, life satisfaction (cognitive evaluation of one’s life), the presence of positive moods, and the absence of negative moods. Deiner argued that governments should consider the population’s happiness and life satisfaction similarly to how they treat economic indicators such as GDP [21]. Research in positive psychology suggests that high levels of subjective well-being are associated with numerous benefits, such as increased longevity, better health outcomes, and greater life effectiveness, particularly relevant in educational environments where such outcomes can influence both learning and teaching experiences [22].

To examine the well-being of individuals, several models have been introduced. There are various models of student well-being, such as those proposed by Seligman (2011) [23], Keyes (2002) [24], and Csikszentmihalyi (1990) [25]. Seligman’s PERMA model focuses on five essential elements of well-being: Positive emotions, Engagement, Relationships, Meaning, and Accomplishment. Keyes’ model of mental health includes three components: emotional, psychological, and social well-being. Csikszentmihalyi introduces the Flow theory, which delineates the state of concentration and engagement that an individual can attain when completing a task that tests their abilities. Moreover, well-being has been defined in the field of education, such as the OECD [26]. The OECD’s framework of well-being in education encompasses four dimensions: psychological, social, cognitive, and physical well-being. This model emphasizes the importance of considering multiple aspects of students’ lives in understanding their overall well-being and educational outcomes. These previous models share some commonalities with the OECD framework, such as an emphasis on positive relationships and a sense of meaning. However, they differ in their specific focus and conceptualization of well-being. In this study, the OECD framework has been adopted as it specifically addresses well-being in the educational context and provides a comprehensive set of dimensions that align with our research objectives.

There has been growing recognition of the positive impacts of subjective well-being on schooling. Research indicates that students who experience positive emotions tend to have better attention, more creativity, and greater problem-solving abilities, all of which contribute to improved academic performance [27]. The government of the UK, for instance, adopted eight principles for promoting students’ and young people’s mental health and well-being. These include; (1) leadership and management that supports and champions efforts to promote emotional health and wellbeing, (2) an ethos and environment that promotes respect and values diversity, (3) curriculum, teaching, and learning to promote resilience and support social and emotional learning, (4) enabling student voices to influence decisions, (5) staff development to support their own well-being and that of students, (6) identifying need and monitoring the impact of interventions, (7) working with parents and careers, and (8) targeting support and appropriate referral [28]. Similar principles are also promoted by the Department of Education in Australia [29]. Enhancing students’ mental health not only benefits the students but also significantly aids in the personal and professional growth of educators. A less stressful and more engaging classroom environment reduces educator burnout and enhances job satisfaction [30].

Additionally, educators benefit from professional development opportunities related to mental health, which enrich their teaching toolkit and broaden their skill set. This proactive environment encourages positive interactions and engagement, stimulating intellectual growth and motivation [31]. Ultimately, a focus on student well-being helps foster a supportive school culture, enhancing overall job satisfaction and contributing to educators’ personal and professional development [30,31].

Thailand has enacted a series of reforms to modernize the education system. About a decade prior to COVID-19 (between 2001 and 2008), there was a significant shift in the school curriculum from an information retention approach to a learner-centered approach. The implementation of these reforms has been impeded by the centralization of government management, particularly the centralized standard-based approach. The reforms are generally crippled by insufficient and inappropriate support [32] from centralized government. Public spending by the central government on education is relatively low, at about 2.62 percent of GDP in 2022, compared with 3.5 percent in Malaysia, 2.9 percent in Vietnam, and 3.7 percent in upper-middle-income countries [33]. Teachers are not sufficiently well-prepared to support these series of reforms. The outcomes of education, shown in PISSA scores, are relatively low, behind those of students from Vietnam and Turkey [34]. According to the OECD PISA 2022 Results, Thailand’s performance in reading, mathematics, and science has remained relatively stable since 2018. However, the country’s scores are still below the OECD average. The report also highlights that students in Thailand reported a lower sense of belonging at school compared to the OECD average, with a higher percentage of students feeling lonely and out of place in their schools [28].

The impact of COVID-19 was evident across the region and Thailand was not an exception. Van Eekert et al., explored how the pandemic impacted the mental health of university students, focusing on those who are potentially vulnerable [35]. This study revealed that the nature of the pandemic, accompanied by the lack of social interactions, is a significant stressor. The lack of in-person social interactions and support networks severely impacted students’ mental well-being. Donald and Jackson investigated how the COVID-19 pandemic impacted the subjective well-being of students in higher education and recent graduates in the UK [36]. They found that students’ well-being generally declined. However, the study also notes some positive aspects, including more time for personal health, hobbies, and strengthening relationships. Apostol et al., similarly found that COVID-19 had both negative and positive impacts on students’ well-being [37]. The shift to online learning significantly affected SW students, particularly because their education heavily relies on practical, hands-on experiences. Students reported both positive and negative impacts of online learning. On the positive side, they discovered new online tools and resources. These studies, however, focus on university students, while reports on the impacts of COVID-19 on pre-university age groups are underrepresented.

This study examines the determinants of students’ well-being during the COVID-19 pandemic, recognizing the potential for both negative and positive effects on students’ experiences and the importance of well-being for educational performance. This research employs the OECD’s comprehensive framework of well-being in education [26], which encompasses four key dimensions: psychological, social, cognitive, and physical well-being. By adopting this multidimensional approach, this study aims to provide a holistic understanding of the factors influencing students’ well-being in the context of the pandemic, ultimately informing strategies to support and promote well-being in educational settings during and beyond the COVID-19 crisis.

3. Materials and Methods

3.1. Population and Sample Size

This quantitative research employs a cross-sectional design to examine the well-being of secondary students in northeastern Thailand, as well as to explore the variables that influence their educational well-being. The target population consisted of secondary school students in grades 7 through 12, aged between 13 and 18 years old, attending schools in the northeastern region of Thailand. The northeastern region was chosen due to its unique socio-economic and cultural landscapes, which may influence students’ well-being and educational experiences.

The sample size for this study was determined using Cochran’s formula [38], which is commonly used to calculate the required sample size for a population with unknown characteristics. The formula is as follows:

$$\mathrm{n}=\frac{Z^{2}p(1-p)}{e^2}$$

where:

$\mathrm{n}$ = sample size

$Z$ = value from the standard normal distribution corresponding to the desired confidence level (e.g., 1.96 for 95% confidence)

$p$ = estimated proportion of the population with the characteristic of interest (0.5 is used to provide the maximum sample size)

$e$ = desired level of precision (margin of error)

Using a confidence level of 95%, a margin of error of 5%, and an estimated proportion of 0.5, the calculated sample size was 384. To account for potential non-responses and incomplete data, we rounded up the sample size to 400.

3.2. Sampling Methods

The sampling procedure employed a multistage sampling technique designed to enhance the representativeness of the sample and account for geographical and school-level variations across the northeastern region of Thailand. The schools involved in this study include a mix of public, private, and religiously affiliated institutions, reflecting the broad spectrum of educational settings in Thailand.

In the first stage, the northeastern region was divided into three sub-regions: upper, central, and lower. This stratification was based on the geographic location of the provinces within the region. The upper area was represented by the provinces of Udon Thani and Sakon Nakhon, the central area by the provinces of Khon Kaen and Roi Et, and the lower area by the provinces of Ubon Ratchathani and Buriram. From each sub-region, schools were further stratified by area settlement (urban and non-urban) and school size (small, medium, large, and extra-large). The categorization of school size was based on the number of students enrolled in each school, following the standard classification used in the Thai education system. Small schools had fewer than 500 students, medium schools had 500–1499 students, large schools had 1500–2499 students, and extra-large schools had 2500 or more students.

Within each sub-region, a total of 10 schools were randomly selected using a proportional allocation based on the distribution of schools across the different strata (area settlement and school size). This approach ensured that the selected schools were representative of the diverse characteristics within each sub-region. In total, 30 schools were selected across the three sub-regions, with 10 schools from each sub-region.

In the second stage, within each selected school, students were further stratified by grade level (grades 7 through 12). A simple random sampling technique was then employed to select students from each grade level to participate in the study. The number of students selected from each school was proportional to the total number of students in that school to ensure a representative sample.

It is important to acknowledge that while this sampling procedure aimed to ensure representativeness by stratifying the sample based on region, area settlement, school size, and grade level, we were unable to provide comparative data between the implemented sample and the target population due to limitations in accessing comprehensive demographic information. This lack of comparison may affect the generalizability of our findings, and future research should aim to collect and present such data to strengthen the representativeness of the sample.

The final sample consisted of 400 secondary school students from 30 schools across the upper, central, and lower sub-regions of the northeastern region of Thailand, with 10 schools from each sub-region. The sample size was determined using Cochran’s formula [38], as described in the previous section.

3.3. Data Collection

The research instrument employed in this study was an interview schedule [39] derived from the OECD’s framework on well-being in education [26]. The instrument consisted of five distinct sections, each addressing different facets of the research topic.

General characteristics of the student participants: This section included multiple-choice questions about students’ gender, age, academic standing, school location, and COVID-19 infection history. For instance, participants were asked “Have you ever been infected with COVID-19? If yes, how many times?”, with response options of “Yes” and “No” and a space to indicate the number of times infected if answering “Yes”.

Family climate: This section assessed various aspects of the family environment using 4-point Likert scale questions (1 = never, 2 = rarely, 3 = often, 4 = regularly). Family climate was defined as the overall quality of the family environment, including family relationships, financial status, parental occupation, family amenities, and learning support resources. Family relationships referred to the level of interaction and support among family members, while financial status indicated the family’s perceived economic well-being. Parental occupation referred to the main job held by the student’s parents, and family amenities and learning support resources assessed the availability of household items and educational materials, respectively. A sample item measuring family relationships was “My parents ask me to teach homework or advise me on studying”.

School climate: Participants evaluated their school climate across four dimensions: school personnel, physical environment, pedagogical practices, and parental engagement. School climate was defined as the overall quality and character of the school environment, including the relationships among students, teachers, and staff, as well as the school’s physical facilities and educational practices. School personnel referred to the adequacy and competence of teachers and staff, while physical environment assessed the availability and quality of school facilities and resources. Pedagogical practices indicated the effectiveness of teaching methods and learning activities, and parental engagement referred to the level of parental involvement in school activities and communication with teachers. Participants rated their agreement with statements on a 4-point Likert scale (1 = strongly disagree, 2 = somewhat disagree, 3 = somewhat agree, 4 = strongly agree), such as “I think the school has enough teachers for teaching and learning in the school”.

Student perception of COVID-19 impacts: This section measured students’ perceptions of the pandemic’s impact on their individual, family, schooling, and social lives. COVID-19 impacts were defined as the perceived consequences of the pandemic on various aspects of students’ lives. Individual impact referred to students’ personal experiences and well-being during the pandemic, while family impact assessed the perceived effects on family members’ health, finances, and relationships. Schooling impact indicated the perceived changes in the learning environment and educational practices due to COVID-19, and social impact referred to the perceived changes in social interactions and support systems. Participants rated their agreement with statements such as “I am well-prepared for online learning under the COVID-19 situation” on a 4-point Likert scale (1 = strongly disagree, 2 = somewhat disagree, 3 = somewhat agree, 4 = strongly agree).

Well-being in education: The final section assessed students’ well-being across psychological, social, cognitive, and physical dimensions using 4-point Likert scale questions (1 = strongly disagree/never, 2 = somewhat disagree/rarely, 3 = somewhat agree/often, 4 = strongly agree/regularly). Well-being in education was defined as a multidimensional construct encompassing students’ psychological, social, cognitive, and physical functioning within the educational context. Psychological well-being referred to students’ emotional states, life satisfaction, and self-efficacy. Social well-being indicated the quality of relationships with family, peers, and teachers, as well as experiences of bullying and belonging. Cognitive well-being assessed students’ problem-solving skills, growth mindset, creativity, and critical thinking. Physical well-being referred to students’ health status, exercise habits, and eating behaviors. A sample item measuring psychological well-being was “I feel satisfied with my current life”.

For non-dichotomous variables such as “Academic standing”, “Financial status of the family”, and “The main occupation of parents”, dummy coding was used to create dichotomous variables for each category. The reference categories were Grade 12 for academic standing, moderate level for financial status of the family, and agriculture for the main occupation of parents. Dummy variables were created for the remaining categories, and these dummy variables were included in the regression model while the reference categories were omitted.

The content validity of the questionnaire was evaluated by a panel of three experts in educational psychology and measurement. They reviewed the items for relevance, clarity, and comprehensiveness based on the OECD framework and the study’s objectives. Minor revisions were made to improve the questionnaire based on their feedback.

To assess the reliability of the instrument, a pilot study was conducted with a sample of 20 students in Khon Kaen province. The Cronbach’s alpha coefficients for the different dimensions of the questionnaire were as follows: Family Climate (0.78), School Climate (0.81), Student Perception of COVID-19 Impacts (0.83), and Well-being in Education (0.82). These values indicate a high level of internal consistency within each dimension, suggesting that the items within each dimension reliably measure the same underlying construct.

The interview schedules were administered during the 2022 academic year, adhering to rigorous ethical standards approved by the Institutional Review Board (IRB) of Khon Kaen University. Paper formats were used to distribute the interview schedules, ensuring accessibility for all students regardless of their technological resources. Paper interview schedules were provided, which were later digitized for analysis.

To facilitate the completion of the interview schedule, trained research assistants were present during each session. They were tasked with explaining the study’s purpose and ensuring that all students understood the questions fully, thereby aiding in the accurate collection of data. Teachers and school administrators were briefed about the study’s objectives and procedures beforehand and assisted with logistical arrangements, although they did not participate in the administration of the interview schedule to maintain the impartiality of responses.

Data was collected anonymously, and confidentiality was maintained at all stages of data processing and analysis. Students were informed that participation was voluntary and that they could withdraw at any time without any consequences, ensuring ethical compliance and respect for participant autonomy.

3.4. Data Analysis

The researchers utilized IBM SPSS Statistics software for all data analyses. Descriptive statistics, including means, percentages, and standard deviations, were employed to characterize the overall attributes and contexts of the students, as well as to quantify their degrees of well-being in education.

To explore the influence of various independent variables on the composite index of well-being in education among secondary students in the northeastern area, regression analysis was conducted. Regression analysis with the OLS ENTER method was used for the regression to ensure a comprehensive evaluation of all predictors simultaneously. This method facilitates the direct assessment of the unique contribution of each variable while controlling for others.

In the regression analysis, we carefully examined all variables for multicollinearity to ensure the integrity of the statistical results. This examination included calculating the Variance Inflation Factor (VIF) for each predictor. The results showed that all VIF values were well below the commonly accepted threshold of 10, confirming that multicollinearity was not a concern in our model and that the degree of inter-correlations among the independent variables was acceptable.

This detailed approach to data analysis ensures that the findings related to the factors influencing educational well-being are both valid and reliable, providing meaningful insights into how different variables impact student well-being.

4. Results

This research engaged a cohort of 400 secondary students as participants to explore student well-being in education in northeast Thailand. The outcomes of this inquiry have been systematically categorized into three primary sections for detailed examination: (1) the demographic and general characteristics of the student population in northeast Thai schools, providing a foundational understanding of the cohort under study, (2) the assessment of family climate, school climate, and well-being in education among these students, offering insights into their perceived quality of life and satisfaction within the school environment, and (3) the analysis of the determinants that significantly impact the well-being in education of these students, aiming to identify actionable factors that could inform policy and practice. Each of these categories will be expounded upon in the subsequent sections of this document, laying the groundwork for a comprehensive understanding of the study’s findings.

4.1. The Demographic and General Characteristics of the Student Population in the Northeastern Region of Thailand

The demographic analysis of the survey sample, comprising 400 secondary students from the northeastern region of Thailand, yielded notable insights into gender distribution, age composition, academic standing, geographical distribution, and COVID-19 infection history.

Gender representation within the sample was predominantly female, accounting for 71.50% of respondents. Male participants represented 26.30%, while non-binary students comprised a smaller fraction at 2.30%. Age-wise, the bulk of the sample, 77.80%, fell within the 16 to 18 age bracket. A smaller segment, 16.40%, was under 15 years old, and 5.80% were above 18 years old, establishing a mean age of 16.68 years (SD = 1.86).

Regarding student academic standing, the sixth year of secondary education was the most common, with 41.20% of students, followed by the fourth and fifth years at 22.80% and 22.30%, respectively. Geographically, the majority of students, 76.00%, were from the central northeastern region, while 15.70% and 8.30% hailed from the upper and lower northeastern regions, respectively. Additionally, regarding COVID-19 infection history, a significant 63.50% of the surveyed students reported previous infections, with 55.30% experiencing it once. This data underscore the pandemic’s pervasiveness among the student cohort, potentially influencing their educational well-being and school experiences.

4.2. Family Climate

The investigation into the family dynamics of secondary students in northeastern Thai schools revealed notable patterns in household composition, economic conditions, and access to educational resources. The survey indicated that the predominant household size comprised three members, representing 55.00% of the sample. Families with four and five members followed, accounting for 42.00% and 3.00%, respectively. The mean number of dependent elders (aged 60 and over) per household was 0.91 (SD = 0.94), while dependents under the age of 15 averaged 0.81 per household (Mean = 0.81, SD = 0.95), with a majority reporting no dependents.

Regarding migratory work patterns, a significant 78.80% of students reported no family members migrating for employment. Financially, 88.30% of students described their family’s economic status as low, whereas 10.70% perceived it as high. The impact of COVID-19 on these economic conditions was profound, with 51.30% noting a deterioration post-pandemic. However, 39.20% observed no change, and a minority of 9.50% reported improvements.

The occupational landscape of students’ parents predominantly featured agriculture (41.00%), followed by government employment (23.00%) and business (15.80%). Household amenities were widespread, including televisions (92.0%), automobiles (75.0%), motorcycles (87.3%), bicycles (58.8%), mobile phones (93.3%), refrigerators (93.0%), and fans (94.8%), with air conditioning present in roughly 50% of homes to enhance comfort.

An assessment of educational resources within these households underscored a robust provision of essential learning materials, with 66.50% having study desks, 74.80% private rooms, 81.80% internet access, 90.30% cell phones, and 87.30% textbooks. However, quieter study environments and technological tools such as dictionaries (65.30%) and encyclopedias (55.00%) were less prevalent.

Parent–student relationship levels were predominantly moderate (52.00%), with a lesser extent of high (30.70%) and low (17.30%) relationships, yielding a mean score of 2.13 (SD = 0.68). Specific supportive behaviors such as homework assistance (51.50%), encouragement in learning activities (49.80%), academic support (44.80%), and shared leisure activities (46.00%) were commonly reported, illustrating the multifaceted nature of parent–child engagement in the student’s educational journey.

4.3. School Climate

The assessment of the school climate in the sampled schools from the northeastern region revealed that a significant proportion of students held favorable views, as indicated by an overall mean score of 2.73 and a standard deviation of 0.45. A detailed examination of student perspectives on various facets of their educational environment highlighted differential evaluations across four key aspects.

Foremost, school personnel were rated the highest by students, reflected in a mean score of 3.00 and a standard deviation of 0.58, underscoring their pivotal role in shaping a positive school climate. This was closely followed by the appreciation for pedagogical practices, which garnered a mean score of 2.84 and a standard deviation of 0.67, indicating a generally positive reception of pedagogical practices.

Parental engagement, with a mean score of 2.75 and a standard deviation of 0.77, was also viewed positively, albeit to a slightly lesser extent, suggesting room for enhancing family–school collaboration. Contrarily, the physical environment of the schools was appraised the least favorably, as denoted by the lowest mean score of 2.32 and a standard deviation of 0.72, pointing to potential areas for infrastructural and environmental improvements (

Table 1. Mean score and standard deviation of students’ perceptions towards school climate.

School Climate Dimensions	Mean	SD	Interpretation
School personnel	3.00	0.58	Relatively high
School physical environment	2.32	0.72	Relatively high
Pedagogical practices	2.84	0.67	Relatively high
Parental engagement	2.75	0.77	Relatively high
overview	2.73	0.45	Relatively high

).

4.4. Student’s Perception of COVID-19 Impacts

This research examined students’ perceptions concerning the impacts of COVID-19 on their experience. The data indicated that, overall, students held a relatively high level of perception, with a mean score of 2.93 and a standard deviation of 0.38. When dissected by dimension, the analysis highlighted that the aspect most positively perceived was the individual impact on the pandemic, as evidenced by the highest mean score of 3.10 and a standard deviation of 0.64. This was closely followed by social impact, which garnered a mean score of 3.00 and a standard deviation of 0.43. The dimension of schooling impact also received a generally favorable evaluation, with a mean score of 2.91 and a standard deviation of 0.63. In contrast, the dimension of family impact was appraised the least favorably, reflected by the lowest mean score of 2.69 and a standard deviation of 0.64 (

Table 2. Mean score and standard deviation of students’ perceptions towards school climate.

Students’ Perception of COVID-19 Impacts	Mean	SD	Interpretation
Individual impact	3.10	0.58	Relatively high
Family impact	2.69	0.64	Relatively high
Schooling impact	2.91	0.63	Relatively high
Social impact	3.00	0.43	Relatively high
overview	2.93	0.38	Relatively high

).

4.5. Well-Being in the Education of Secondary Students in the Northeastern Region

The analysis illuminated that a considerable segment of the student population reported a relatively high level of well-being in education, with a mean score of 2.96 and a standard deviation of 0.28. This investigation delved into the multifaceted nature of well-being in education among secondary students, disaggregating it into four distinct dimensions for a nuanced evaluation.

Of these dimensions, social well-being emerged as the pre-eminent domain, receiving the most favorable evaluations, evidenced by a mean score of 3.21 and a standard deviation of 0.44. This was closely followed by the dimension of physical well-being, which registered a mean score of 3.03 and a standard deviation of 0.36. Psychological well-being, with a mean score of 2.81 and a standard deviation of 0.40, and cognitive well-being, with a mean score of 2.80 and a standard deviation of 0.28, were identified as areas that scored comparatively lower (

Table 3. Mean score and standard deviation of well-being in the education of secondary students in the northeastern region.

Well-Being Domains	Mean	SD	Interpretation
Psychological well-being	2.81	0.40	Relatively high
Social well-being	3.21	0.44	Relatively high
Cognitive well-being	2.80	0.28	Relatively high
Physical well-being	3.03	0.36	Relatively high
Overall	2.96	0.28	Relatively high

).

4.6. Determinants of Well-Being among Secondary Students in Northeastern Thailand

This section presents the determinants influencing well-being in education among secondary students in the northeastern region. As analyzed through multiple regression, the findings revealed that variables including gender (females as the reference category), age, academic standing (with grade 12 as the reference), school location (urban area as the reference), and COVID-19 infection history had no significance on well-being in education in the cohort under study.

This study found variables that influence the well-being of secondary students. There was a positive relationship (b = 0.074) between well-being in education and family relationships. This implies a 0.074-unit augmentation in well-being for each unit increase in the quality of family relations. Additional factors that influence family climate include the number of family members, the proportion of family members aged 60 years and older, the proportion of family members aged below 15, the number of family members who migrate to different regions, the financial status of the family (moderate level as the reference), the financial status of the family after COVID-19, the main occupation of parents (agriculture as the reference), the quantity of family amenities, and the number of learning support resources. These factors were found to not affect the well-being of students in education.

Regarding the school climate, the analysis further reveals the school environment’s influence, with a particular emphasis on the presence of school personnel, which is positively related to well-being in education (b = 0.068). This suggests a corresponding enhancement in students’ well-being with an increase in school personnel numbers. In contrast, the physical demands of the school climate (b = −0.110) inversely impact well-being in education, indicating a decrease in well-being with heightened physical demands. The roles of parental involvement and pedagogical practices were found to be non-significant in affecting students’ well-being in education.

The study revealed that student perceptions regarding COVID-19’s social impact had a significant positive impact on their well-being in education (b = 0.198), indicating that a more positive perception relates to higher well-being levels. Other perceived impacts of the pandemic, encompassing family, schooling, and individual aspects, did not present a significant relationship to well-being in education.

An examination of the independent variables’ impact reveals a hierarchical significance in influencing student well-being, in descending order: perceptions towards COVID-19’s social impact (β = 0.299), school physical environment (β = −0.282), family relationships (β = 0.174), and school personnel (β = 0.140). The multiple regression model’s coefficient of determination (R² = 0.453) elucidates that the investigated independent variables collectively account for 45.3% of the variance in well-being in education among the student population in the northeastern region (

Table 4. Determinants of secondary students’ well-being in the northeastern region.

Variables	b	Beta	sig	VIF	Reference Category
(Constant)	2.016		0.000
Gender	0.022	0.035	0.380	1.12	Female
Age	−0.003	−0.017	0.753	1.05
Academic standing	0.033	0.058	0.307	1.10	Grade 12
School location	−0.017	−0.029	0.529	1.08	Urban
COVID-19 infection history	−0.018	−0.039	0.322	1.03
Number of family members	0.021	0.041	0.347	1.06
Number of family members who are over 60 years old	−0.012	−0.041	0.330	1.07
Number of family members who are under 15 years old	−0.023	−0.077	0.073	1.08
Number of family members who migrate	−0.039	−0.058	0.154	1.06
Financial status of the family	−0.032	−0.037	0.361	1.07	Moderate
Financial status of the family after the COVID-19	−0.005	−0.008	0.839	1.05
Main occupation of parents	0.007	0.012	0.771	1.09	Agriculture
Quantity of amenities.	0.008	0.053	0.303	1.04
Learning support resources.	0.001	0.009	0.866	1.05
Family relationship.	0.074	0.174	0.000 *	1.06
School personnel.	0.068	0.140	0.012 *	1.07
School’s physical environment.	−0.110	−0.282	0.000 *	1.05
Pedagogical practices	0.021	0.051	0.361	1.08
Parental engagement.	0.034	0.093	0.055	1.09
Perceptions towards COVID-19’s individual impact	0.026	0.054	0.336	1.06
Perceptions towards COVID-19’s family impact	0.020	0.047	0.330	1.04
Perceptions towards COVID-19’s schooling impact	−0.015	−0.033	0.604	1.05
Perceptions towards COVID-19’s social impact	0.198	0.299	0.000 *	1.08

* p-value < 0.05, R² = 0.453, F = 13.527, Sig of F = 0.000.

).

In summary, the factors that influence the well-being in education of secondary students in the northeastern region include students’ perceptions regarding COVID-19’s social impact, family relationships, school personnel, and the school’s physical environment.

5. Discussion

This study unveiled several determinants that significantly influence the well-being of secondary students in northeastern Thailand in the aftermath of the COVID-19 pandemic. A nuanced understanding of these determinants is crucial for developing targeted interventions and policies to enhance students’ educational experiences and outcomes. The OECD’s framework for well-being in education, which informed our study design, provides a comprehensive and multidimensional approach to understanding students’ well-being [26]. Our findings align with this framework, as we found significant associations between family relationships, school personnel, students’ perceptions of COVID-19 impacts, and their well-being in education. However, other well-being models, such as Seligman’s PERMA model [23], Keyes’ model of mental health [24], and Csikszentmihalyi’s concept of flow [25], offer complementary perspectives. Seligman’s PERMA model and Keyes’ model highlight the importance of positive relationships, meaning, and psychological and social well-being, which resonates with our findings. Csikszentmihalyi’s work on flow adds depth to our understanding of students’ well-being, suggesting that learning environments that foster engagement and challenge students appropriately may promote flow and enhance well-being [40]. Furthermore, Csikszentmihalyi’s concept of autotelic personality [41] may be relevant to our findings on students’ perceptions of COVID-19 impacts, as students with autotelic personalities may be more resilient and likely to maintain well-being during challenging times. By considering these alternative models alongside the OECD’s framework, we gain a nuanced understanding of the complex nature of well-being and its determinants in the educational context.

A salient finding of this research is the positive association between family relationships and students’ well-being. Enhanced family relationships correlate with improved well-being, underscoring the pivotal role of a supportive family environment in students’ educational experiences. This aligns with the existing literature emphasizing the importance of familial support in fostering a conducive learning environment and enhancing students’ resilience and adaptation in the face of adversities such as the COVID-19 pandemic [42,43]. Moreover, the presence of school personnel emerged as a significant positive determinant of students’ well-being in education. An increase in school personnel corresponds to improved well-being in education, highlighting the essential role of adequate staffing in schools for providing necessary support and resources to students, thus facilitating a nurturing and supportive educational environment. Various studies indicate a crucial role of school staff in shaping the educational experiences and well-being of students [44,45].

Conversely, our findings regarding the school’s physical environment suggest a negative impact on students’ well-being, necessitating a careful examination of physical and infrastructural resources [46,47]. This includes aspects such as adequate heating, proper lighting, and the quality of air ventilation, which can significantly influence students’ ability to concentrate and their overall comfort in the learning environment. Additionally, considerations such as class sizes and the presence of natural elements or motivational messages within the school may also play crucial roles in shaping the learning atmosphere and thereby impacting student well-being.

Our research also highlights the importance of students’ perceptions of COVID-19’s societal impacts on their well-being, which is consistent with several studies that indicate the importance of social preparedness and resilience in students during COVID-19, helping them to learn and live effectively [48,49,50]. While we found that students who are more cognizant of the pandemic’s broader societal implications tend to report better well-being, it is essential to consider that this relationship may not be strictly causal. It is plausible that students with inherently better mental health are more likely to engage with and understand these wider implications. Therefore, the direction of this relationship should be interpreted with caution, suggesting a potential bidirectional influence.

For the Thai education system, these findings suggest the need to incorporate initiatives that promote social awareness and preparedness among students. This could involve integrating discussions about the societal consequences of events such as pandemics into the curriculum, providing resources for students to engage with these issues, and fostering community resilience. By addressing students’ perceptions of COVID-19’s social impact proactively, Thailand’s education system can better prepare students to navigate current and future challenges effectively.

To enable a better understanding of students’ well-being, it is crucial to acknowledge the non-significant findings, such as gender, age, and certain family and school climate factors. These non-significant results suggest that some traditional predictors may not hold the same relevance in the unique context of the post-COVID-19 educational landscape in northeastern Thailand.

Another observation was noted. The study highlighted a predominance of female participants, with females making up a significant majority of the study sample. This gender imbalance challenges the generalizability of the findings across the broader student population. Such a skew might suggest varying levels of engagement, accessibility, or willingness to participate in academic research among females compared to males or other gender groups. This is particularly relevant when considering mental health and educational adaptations during the pandemic, where responses could differ significantly between genders. Therefore, the predominance of females in the sample may limit the applicability of the findings, underscoring the need for future research to ensure a more balanced gender representation to enhance the relevance and applicability of the results.

Based on the study’s findings, recommendations for enhancing the well-being of secondary students in northeastern Thailand include prioritizing the improvement of family relationships and the optimization of school personnel. Academia and policy should focus on exploring and addressing the dynamics of family environments, and ensuring schools are adequately staffed to support students effectively. Efforts should also be directed towards improving the physical school environment, making it more conducive to learning. Enhancing students’ awareness of the broader societal impacts of the COVID-19 pandemic through educational programs and curriculum adjustments is also crucial. Additionally, a holistic approach incorporating various aspects of students’ lives, continuous evaluation, and the utilization of statistical insights for targeted strategy and policy development is recommended to ensure adaptability and effectiveness in improving students’ well-being in education.

6. Conclusions

In conclusion, this study underscores the multifaceted nature of educational well-being among secondary students in northeastern Thailand in the aftermath of the COVID-19 pandemic. It highlights the significant influence of family relationships, school personnel, and students’ perceptions of the pandemic’s social impact on their well-being. Notably, the adverse effect of the school’s physical environment on students’ well-being calls for urgent attention to improve educational infrastructure. These findings provide a critical foundation for policymakers and educational stakeholders to devise strategies that prioritize the holistic well-being of students, ensuring a supportive and conducive learning environment. Future research should explore longitudinal impacts and the role of digital learning environments in shaping educational well-being, offering a broader perspective in the post-pandemic educational landscape.