Exploring the Relationships Between Academic Buoyancy,Engagement,and Achievement in English Reading Among EFL Learners

Abstract

Academic buoyancy has been a hot topic in positive psychology and foreign language learning. Previous research has shown a strong connection between academic buoyancy and academic achievement. However, little is known about how academic buoyancy affects EFL (English as a Foreign Language) reading through academic engagement. Adopting a cross-sectional design with two questionnaires and a reading test, the study used a convenient sampling technique that balanced economic efficiency with power analysis to recruit participants. This research examined the associations between academic buoyancy, academic engagement (including its three dimensions: behavioral, emotional, and cognitive engagement), and EFL reading performance among 660 English learners from Chinese colleges. The results indicated that academic buoyancy, academic engagement, and EFL reading outcomes were positively correlated. Academic buoyancy indirectly affected EFL reading achievement through academic engagement, particularly emotional engagement. This study extends the everyday motivational resilience and vulnerability framework as well as self-determination theory from general academic fields into the EFL reading domain. These findings highlight the importance of promoting academic buoyancy and engagement in EFL reading, particularly emotional engagement, among learners to enhance their EFL reading achievement.

Plain Language Summary

Investigating how staying positive in school, being engaged, and doing well in English reading relate to each other for students learning English as a foreign language

People have been really interested in how well students can handle school challenges, especially in positive psychology and learning foreign languages. Studies have already shown that being good at dealing with school challenges helps students do better in school. However, we do not know much about how this ability affects English reading skills for students who are learning English as a foreign language. To find out, this study used two surveys and a reading test, and picked a group of participants in a way that was both cost-effective and reliable. They looked at 660 college students in China who are learning English to see if there is a link between their ability to handle school challenges, how engaged they are in their studies (including their behavior, emotions, and thinking), and their English reading skills. This study found that these factors are all connected. The ability to handle school challenges indirectly helps with English reading by affecting how engaged students are, especially their emotional engagement. This research shows that the ideas about motivation and vulnerability in overall school subjects can also apply to English reading. The findings suggest that it is important to help students get better at dealing with school challenges and to be more engaged, especially emotionally, to improve their English reading performance.

Keywords

academic buoyancy academic engagement academic achievement EFL reading emotional engagement

Introduction

Academic buoyancy (AB) has been a focus in positive psychology and foreign language learning. This construct refers to the ability of students to effectively manage their daily non-severe challenges and obstacles they face in the academic environment, such as dealing with poor grades, competing deadlines, high-pressure exams, and demanding schoolwork (Martin & Marsh, 2008). In recent years, an increasing number of researchers have explored the role of AB in academic learning and how this construct can be utilized to develop strategies to enhance academic performance (Putwain et al., 2019). Prior studies have shown that AB is correlated with academic performance (e.g., Collie et al., 2024; Colmar et al., 2019; Gao et al., 2025; Guo et al., 2024; Malmberg et al., 2013; Putwain et al., 2016, 2024; Saalh & Kadhim, 2020) across various school subjects and skills.

Academic engagement (AE) is a multifaceted construct with distinct emotional, behavioral, and cognitive components (Fredricks et al., 2004). Cognitive engagement refers to allocating mental resources and using effective learning strategies (e.g., skimming while reading) to deeply understand complex concepts. Emotional engagement encompasses experiencing both positive and negative affective states (i.e., enjoyment during reading), which can either facilitate or hinder academic performance. Emotional engagement highlights the role of positive emotions in shaping learners’ motivation and attitudes. Behavioral engagement pertains to the level of effort invested in completing academic tasks (i.e., looking up unknown words in reading materials) and the persistence displayed in response to daily challenges. This dimension emphasizes the active participation and dedication necessary for successful learning outcomes. Previous studies have shown that AB is correlated with AE (e.g., Datu & Yang, 2018; Heydari et al., 2024; Liu et al., 2025; Putwain & Wood, 2023; Thomas & Allen, 2021; Wang & Liu, 2022) across various school subjects and skills.

In EFL learning, which is important for English acquisition, reading requires AB and AE. Learners often have limited opportunities to speak or write in EFL settings, so reading becomes an essential source for them to acquire English (Yapp et al., 2023). Through reading, learners can acquire vocabulary and grammar. Understanding the factors that contribute to reading is crucial for both learners and teachers, such as the role of AB and AE in predicting EFL reading performance. Higher AB and greater AE can enhance reading outcomes. Reading may not be inherently difficult, but learners should devote considerable time, energy, and resources (AE) to acquiring this skill (Barber & Klauda, 2020). During the reading process, learners may encounter various daily challenges that test their AB, such as reluctance to look up unknown words within reading passages (Kimberley & Thursby, 2020). Consequently, learners would benefit from greater AB and increased AE in EFL reading.

However, little research has addressed the role of AB in EFL reading performance and the mediating role of AE between AB and EFL reading achievement. Prior studies have focused on AB across various school subjects, for example, in mathematics (e.g., Malmberg et al., 2013; Putwain et al., 2016; Putwain & Wood, 2023), English (e.g., Malmberg et al., 2013; Putwain et al., 2016; Yun et al., 2018), and overall school subjects (mean scores of subjects; e.g., Guo et al., 2024; Putwain et al., 2024). The reason may be that researchers find it easier to obtain scores for these subjects from final examinations, but these tests do not report grades for some skills (e.g., EFL reading). To the best of the author’s knowledge, few studies have illustrated the relationship between AB and EFL reading (e.g., Collie et al., 2024; Colmar et al., 2019; Saalh & Kadhim, 2020). Only Lee (2014) showed that behavioral and emotional engagement significantly predicted reading outcomes. This study aims to fill this gap by investigating the relationships among AB, AE, and EFL reading, as well as the indirect influence of AB on EFL reading via AE. Understanding these relationships might enhance EFL reading instruction and extend the everyday motivational resilience and vulnerability framework, as well as self-determination theory, from school subjects into the EFL reading field.

Literature Review

AB, proposed by Martin and Marsh (2008), might be confused with academic resilience. This construct, academic resilience, pays attention to less privileged groups suffering from severe academic setbacks due to disabilities or extreme poverty (Kim et al., 2018). Conversely, AB focuses on all groups facing non-severe academic challenges (e.g., competing deadlines, complex assignments, or poor grades). That is, academic resilience explores catastrophic setbacks faced by less privileged groups, hindering academic achievement, whereas AB researches the daily challenges faced by all groups, facilitating academic performance.

Theoretical Foundations

From the perspective of the everyday motivational resilience and vulnerability framework (Pitzer & Skinner, 2017; Skinner et al., 2016), AB is positively correlated with cognitive, emotional, and behavioral engagement to promote academic outcomes. In the present study, academic achievement refers to the scores in school subjects or skills. This model takes students’ AB in confronting daily academic difficulties and challenges as the starting point, their AE in facing these problems as the essential path, and academic achievement after experiencing these issues (manifested as persistence) as the endpoint. This process forms an integrated system of AB-AE-achievement. Students with higher AB adopt adaptive coping strategies and engage more. Learners with lower AB are more likely to adopt non-adaptive coping strategies and engage less. Therefore, AB may influence academic achievement through AE. Finally, AB is positively related to academic performance. Coping strategies refer to the three subdivisions of AE. Learners with higher AB may persist in promoting academic outcomes. As a result, they tend to manage their learning strategies (cognitive engagement), devote more time and energy (behavioral engagement), and experience greater happiness (emotional engagement) when encountering daily setbacks in learning, ultimately improving their academic performance. For instance, Putwain and Wood (2023) examined the reciprocal relations between AB, behavioral engagement, and math achievement in 1,242 primary school students. The results showed that AB predicted math achievement indirectly, mediated through behavioral engagement. EFL reading, one of the academic skills, may be influenced by AB through AE. Conversely, little research has examined the relationship of how AB influences EFL reading through AE.

Empirical Studies

The Relationship Among AB, AE, and Academic Achievement

Existing empirical studies have investigated the correlation between AB, AE, and academic achievement across various school subjects or skills.

Studies have revealed that AB predicts academic achievement in math (e.g., Malmberg et al., 2013; Putwain et al., 2016; Putwain & Wood, 2023), English (e.g., Malmberg et al., 2013; Putwain et al., 2016; Yun et al., 2018), overall school subjects (i.e., Guo et al., 2024; Putwain et al., 2024), and reading (i.e., Collie et al., 2024; Colmar et al., 2019; Saalh & Kadhim, 2020). For example, Colmar et al. (2019) investigated the relationship among AB, academic self-concept, and academic achievement in reading and math among 191 high school students. Structural equation modeling confirmed a significant relationship between AB and academic achievement, mediated by academic self-concept.

Some studies have found that AB predicts AE in English (e.g., Liu et al., 2025; Wang & Liu, 2022), math (i.e., Putwain & Wood, 2023), and overall school subjects (e.g., Datu & Yang, 2018; Heydari et al., 2024; Thomas & Allen, 2021). For instance, Wang and Liu (2022) investigated the relationships among autonomous motivation, AB, boredom, and AE in 561 Chinese high school students. A chain mediation analysis showed that AB affected AE in English.

Several prior studies have demonstrated that AE positively predicts academic achievement across overall school subjects (e.g., Laranjeira & Teixeira, 2025; Zilvinskis et al., 2017), computer literacy (e.g., Avcı & Ergün, 2022), math (i.e., Putwain & Wood, 2023), and reading (i.e., Lee, 2014). For example, Putwain and Wood (2023) examined the reciprocal relations between AB, behavioral engagement, and math achievement among 1,242 primary school students, revealing that behavioral engagement positively predicted math achievement. Recent meta-analyses (e.g., Patall et al., 2024; Wong et al., 2024) have demonstrated a correlation between AE and academic achievement.

However, little is known about the relationship between AB, AE, and EFL reading, especially the three dimensions of AE. To the best of the author’s knowledge, few studies have involved reading (e.g., Collie et al., 2024; Colmar et al., 2019; Saalh & Kadhim, 2020), demonstrating that AB is positively related to reading performance. For instance, Collie et al. (2024) noted that AB was correlated with performance in reading, math, and science. Only Lee (2014) showed that behavioral and emotional engagement significantly predicted reading outcomes.

It is imperative to research AB and AE in EFL reading settings. In EFL settings, learners have few opportunities to use English, so reading is essential for them to acquire English (Yapp et al., 2023). Reading equips learners with vocabulary, grammar, and reading skills (Lawrence et al., 2022). Learners may encounter daily challenges, such as a reluctance to look up unknown words encountered in reading passages (Kimberley & Thursby, 2020), so they need higher levels of AB. EFL reading is crucial for EFL learners but differs from other subjects. Reading may not be difficult, but learners should devote considerable time, energy, and resources to learning it (Barber & Klauda, 2020). In EFL reading, learners are often unfamiliar with English words and the knowledge within reading materials (Toti & Hamid, 2022), so they should devote more AE to addressing these issues. Therefore, learners may need greater AB and more AE in reading. However, few studies focus on the relationship between AB and AE in reading.

In conclusion, learners have few opportunities to read English in EFL settings because many of the materials they encounter are not in English. Learners primarily take the initiative to read English in classroom settings, where they more easily encounter daily setbacks such as unfamiliarity with English vocabulary and cultural backgrounds. AB and AE play essential roles in EFL reading performance. Specifically, AB, AE, and EFL reading performance may be correlated. However, scant research focuses on the relationship between AB, AE, and EFL reading achievement within a single framework.

The Mechanism of AB Predicting Academic Achievement

On the mechanism through which AB predicts academic achievement, AB may influence academic achievement through various psychological factors. For example, intrinsic motivation, which refers to students’ drive to learn effectively in academic settings (Datu & Yang, 2021), is proposed to mediate the relationship between AB and academic achievement (Yun et al., 2018). AB may enhance students’ perception of external support and enable them to use it more effectively (Middleton et al., 2023) to foster a sense of belonging in school. This mechanism may enhance their intrinsic motivation to meet daily academic challenges and thereby improve academic achievement (Hirvonen et al., 2019; Miller et al., 2013). For instance, Datu and Yang (2021) explored the mediating role of intrinsic motivation between AB and academic achievement in a sample of 393 Filipino high school students. The results indicated that AB indirectly affected academic performance through intrinsic motivation. In addition, academic self-control and academic self-concept may also mediate the relationship between AB and academic performance. Academic self-control is related to students’ belief in their ability to control and influence their academic outcomes (Collie et al., 2015). Academic self-concept pertains to an individual’s perceived competence or adequacy within academic contexts (Colmar et al., 2019). For example, Colmar et al. (2019) investigated the relationship between AB and academic self-concept in academic achievement domains such as reading and math in a sample of 191 high school students by examining the mediating role of academic self-concept. Structural equation modeling confirmed this relationship. Moreover, AB influenced math achievement through academic self-efficacy, which is a personal belief in one’s competence to achieve academic goals (Weißenfels et al., 2023).

Based on the everyday motivational resilience and vulnerability framework, AE may mediate the relationship between AB and academic achievement (Pitzer & Skinner, 2017; Skinner et al., 2016). However, to the best of the author’s knowledge, only Putwain and Wood (2023) examined the reciprocal relations among 1,242 primary school students’ AB, behavioral engagement, and math achievement. The results showed that AB predicted math achievement through behavioral engagement. It is essential to understand the mechanism by which AB predicts EFL reading achievement. Reading proficiency in EFL is a crucial aspect of English learning, as it enables learners to enhance their vocabulary and develop their grammar skills. However, students inevitably encounter challenges in reading, including difficulties in understanding grammatical structures and vocabulary. These challenges are common for learners. Consequently, AB may be particularly relevant during reading. These setbacks may lead to varying levels of AE among EFL learners, which, in turn, may affect their reading performance (Selim & Islam, 2022). Therefore, AB might positively predict EFL reading achievement, mediated by AE. However, no existing studies have attended to this mediating role.

It is necessary to differentiate among the three aspects of AE when studying the relationship between AB and EFL reading achievement. AE is a multifaceted construct with distinct emotional, behavioral, and cognitive components (Fredricks et al., 2004). Different aspects of AE in reading may individually predict reading performance, and AB in reading may predict AE differently. EFL learners may manage their AE in reading in various ways. For example, they may skim and scan texts or use schema to help them understand the reading passages (cognitive engagement). When learners encounter a new text, they look for background information about it. They are confident in their ability to learn English reading and feel interested in attending English reading classes each time, demonstrating emotional engagement. They concentrate on English reading during class and discuss the material with their classmates afterward, showing behavioral engagement. These three aspects of AE in reading vary in behavior, cognition, and emotion. Therefore, AB would positively predict EFL reading academic achievement, mediated by the different dimensions of AE.

Moreover, previous studies have focused on overall AE rather than its three subdivisions (e.g., Laranjeira & Teixeira, 2025; Zilvinskis et al., 2017). Different subdivisions may correlate with AB or academic achievement. For example, a path analysis of 253 undergraduate and graduate students conducted by Thomas and Allen (2021) indicated that students with higher levels of AB experienced more positive emotional and behavioral engagement across school subjects. In a recent meta-analysis, Patall et al. (2024) concluded that the three subdivisions of AE positively correlated with academic performance. However, regarding the mediating role of these subdivisions of AE, to the best of the author’s knowledge, only Putwain and Wood (2023) investigated the reciprocal relations between AB, behavioral engagement, and math achievement among 1,242 primary school students. The results showed that AB positively predicted behavioral engagement while learning math. Research on the mediating role of the three subdivisions of AE between AB and academic achievement is scarce. Therefore, it is imperative to focus on the mediating role of the three subdivisions of AE between AB and EFL reading, given the importance of AB and AE during EFL reading.

The Present Study

This study aims to explore how AB influences EFL reading through AE. Despite abundant empirical research on the relationship among AB, AE, and academic achievement, several gaps remain unaddressed. Firstly, limited studies have explored the relationship between AB, AE, and EFL reading. Secondly, few studies have examined the mediating role of AE between AB and EFL reading. These gaps raise two questions:

What is the relationship between AB, AE, and EFL reading?

Can AE, with its three sub-dimensions, mediate the relationship between AB and EFL reading?

Two hypotheses were formulated based on the literature review and the everyday motivational resilience and vulnerability framework (Pitzer & Skinner, 2017; Skinner et al., 2016).

H1: AB, AE, and EFL reading are positively related.

H2: AE, with its three sub-dimensions, mediates the relationship between AB (independent variable) and EFL reading (dependent variable).

Methods

This study investigated the relationship between AB, AE, and EFL reading achievement, considering the mediating role of AE between AB and EFL reading.

Participants

A convenient sampling technique was used to balance economic efficiency and power analysis for recruiting participants in this study. A required English course emphasizing reading comprehension is a standard part of the curriculum for all Chinese college students. Therefore, potential participants for this study were freshmen taught by the researcher and his colleagues who offered this course. The sample size was determined using Monte Carlo power analysis for indirect effects (MacKinnon et al., 2007; power = 0.90, a = 0.05). The results indicated that 252 participants were needed to detect the mediation effect of AE between AB and academic achievement. Although only 252 participants were required, 688 individuals from the classes taught by the researcher and his colleagues volunteered to participate. After removing participants with incomplete or uniform responses to the questionnaire items, a valid sample of 660 participants was obtained, with a response rate of 96%.

Covariates

Covariates included gender, age, major, English achievement, and socioeconomic status (SES). There were 495 females and 165 males. Participants ranged in age from 17 to 22 years (M = 18.69, SD = 0.876). They were freshmen majoring in various subjects: Packaging (N = 58), Food Science (N = 50), Biology (N = 62), Chemistry (N = 58), Accounting (N = 48), Finance (N = 60), Economics (N = 60), Marketing (N = 58), Law (N = 58), Tourism Management (N = 45), Computer Science (N = 52), and Information Technology (N = 51). Prior to participating in the current study, they had learned English for 9 years. Their English achievement was assessed using the National Matriculation English Test (NMET), a widely recognized English test in China. At the beginning of the survey, participants reported their NMET scores. SES was measured using a five-point Likert scale, ranging from very low to very high.

Measures

The present study adapted questionnaires on AB (Martin & Marsh, 2008) and AE (Fredricks et al., 2004). The current study utilized Reading Test One from Cambridge IELTS 17 without adaptations, given its well-known reputation as a reliable and valid measure of EFL reading achievement.

AB Scale

This study adapted Martin and Marsh’s (2008) questionnaire to measure participants’ AB in EFL reading. The original scale comprised four items that captured various daily academic obstacles, such as competing homework, negative feedback, and academic pressure. To adapt this questionnaire to EFL reading, the phrase “English reading” was integrated into each item (see Supplemental Appendix I for details). Using a 5-point Likert response format (1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree), a revised questionnaire was used to measure participants’ AB during EFL reading. The revised questionnaire consisted of four items. For example, “I think that I am good at dealing with pressures related to English reading.” The confirmatory factor analysis (CFA) of AB was satisfactory: χ²/df = 2.87, p < .001, CFI (Comparative Fit Index) = 0.91, RMSEA (Root Mean Square Error of Approximation) = 0.05, and RMR (Root Mean Square Residual) = 0.09. Reliability analyses indicated that AB demonstrated acceptable internal consistency in the current examination (Cronbach’s α = .830, McDonald’s ω = 0.834).

AE Scale

Fredricks et al.’s (2004) school engagement scale, which includes behavioral, emotional, and cognitive engagement, was adapted to evaluate participants’ AE during EFL reading. The questionnaire was modified for this study by incorporating the phrase “English reading” into each item. This instrument assessed the three sub-dimensions of AE: behavioral, emotional, and cognitive. Specifically, the scale contained items that measured emotional engagement (e.g., “I always look forward to English reading class and find it very interesting.”), behavioral engagement (e.g., “I actively answer questions raised by the teacher during English reading class.”), and cognitive engagement (e.g., “After finishing English reading homework or tests, I check again for any mistakes.”). The questionnaire consisted of 29 items (see Supplemental Appendix II for details). Participants rated each item on a 5-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree), with higher scores indicating higher levels of AE. The CFA of AE was satisfactory: χ²/df = 2.96, p < .001, CFI = 0.92, RMSEA = 0.05, and RMR = 0.09. Reliability analyses indicated acceptable internal consistency in this investigation with overall AE (Cronbach’s α = .945, McDonald’s ω = .945), behavioral engagement (Cronbach’s α = .866, McDonald’s ω = .868), emotional engagement (Cronbach’s α = .845, McDonald’s ω = .849), and cognitive engagement (Cronbach’s α = .905, McDonald’s ω = .906).

EFL Reading Test

This study used Reading Test One from Cambridge IELTS 17 to assess the reading achievement of the participants. The IELTS is a widely recognized and respected assessment tool for evaluating English language proficiency among learners. However, college students in China typically do not have access to this examination. Furthermore, post-test surveys revealed that none of the participants had previous experience with this IELTS reading test. The selected reading test comprised 40 questions (see Supplemental Appendix III for details). Table 1 shows that all 40 questions were objective, so strict binary grading criteria were applied (0 or 1 score for one question). A correct response was awarded one score. The scores were graded and recorded automatically through Wenjuanxing, a reputable testing and survey platform in China, known for its standardized and automated scoring system. The participants (M = 15.81, SD = 5.809) scored an average of five out of nine possible scores on the IELTS, indicating an intermediate level of reading proficiency.

Table 1.

Questions and Types of Reading Test One From IELTS 17.

Questions	Types	Questions	Types
1–6	Gap fillings	18–22	Gap fillings
7–13	True, false, not given	23–31, 36–40	Multiple choices
14–17	Matching	32–35	Yes, no, not given

Data Collection

Two questionnaires (AB and AE) were translated into Chinese and guaranteed their reliability. Initially, possessing expertise in questionnaire development, the author translated English versions of the questionnaires into Chinese. The translator back-translated these questionnaires to verify their linguistic and conceptual equivalence. Next, the questionnaires were pilot-tested with a sample of 51 participants (28 females and 23 males), similar to this study. The pilot study yielded high-reliability estimates for all variables, with respondents completing the two questionnaires within approximately 5 min. After the pilot study, the questionnaires underwent additional evaluation and refinement. Two educators specialized in teaching EFL reading to participants. Two experienced researchers focused on English reading. These four people reviewed and provided feedback on the questionnaires.

Two questionnaires and a reading test were administered in Wenjuanxing, accessible on mobile devices, tablets, and laptops. The participants had access to the questionnaires and tests online with a password-protected link. They completed the surveys independently in the following order. First, they completed the AB and AE questionnaires (completed within 5 min, as per the pilot study). The current research divided all participants from 12 majors into Set A (Packaging, Food Science, Biology, Chemistry, Accounting, and Financing) and Set B (Economics, Marketing, Law, Tourism Management, Computer, and Information Technology). The participants of Set A filled the AB scale first and then the AE scale, but those of Set B took the reverse order. After a 10-min break, they finished the reading test within 60 min, preset by IELTS. It would alleviate common method bias using a counterbalance design and a time delay to increase the physical separation between the two questionnaires and the reading test. To ensure the integrity of the data collection process, a teacher was present in the classroom to monitor the participants and prevent any instances of academic dishonesty. Each item in the two questionnaires employed a 5-point Likert scale, offering response options ranging from one to five. The English reading test comprised 40 questions, with each item one score. The data were exported from Wenjuanxing in excel format after completing the survey.

The data collection process complied with the ethical principles of the American Psychological Association (APA). First, before participating in the survey, participants knew well about the nature of the study, including its objectives, anticipated duration, and guarantees of anonymity throughout the survey and data analysis processes. Second, they signed an informed consent form. Participants voluntarily participated and could decline the invitation to respond to the questionnaires or withdraw during the survey without penalty. Third, the researcher and his collaborators administered the survey in each class, providing the participants with thorough information regarding the purpose and scope of the study, as well as assurances of confidentiality and anonymity. Fourth, the present study did not collect personal identifying information to protect participants’ privacy. Only the researchers involved in the study had access to the data. The present study destroyed the data upon completion of the research. Finally, the researchers demonstrated respect for participants’ time by offering grades for their involvement in the current study.

Data Analyses

SPSS 26.0 analyzed the data with five steps. First, the Harman single-factor test diagnosed the common method bias of AB and AE scales in the present study. The principal component factor analysis without rotation showed that the eigenvalues of six factors were more than one. The variance explained by the first factor was 36.45%, below the threshold of 40%. Therefore, common method bias did not affect the outcomes of this study. Second, the present study detected normal distributions. The data revealed that all study variables, including EFL reading, AB, and AE with its three sub-dimensions, exhibited normality, as evidenced by Skewness and Kurtosis values falling within the acceptable range of nearly −1 to +1 (see Table 2 for details). Therefore, the data were appropriate for further statistical analyses, including Pearson correlation analysis, linear regression analysis, and mediation effect analysis with covariates of gender, major, age, SES, and English achievement. Third, Pearson correlation analyses investigated the association among AB, AE (behavioral, emotional, and cognitive aspects), and EFL reading. Fourth, to address H1, linear regression analyses examined whether AB predicts EFL reading, AB predicts AE (including its three sub-dimensions), and AE with its three dimensions predicts EFL reading, respectively. Finally, to address H2, Process 3.5 for SPSS analyzed the data to perform the mediation model (Hayes, 2013). This analysis used the maximum-likelihood estimation and bootstrapping with 5,000 re-sampling times. Model 4 in Process 3.5 investigated the mediating role of AE and its three sub-dimensions as mediators in the relationship between AB (independent variable) and EFL reading (dependent variable). Covariates included gender, major, English achievement, SES, and age.

Table 2.

Pearson Correlation Analysis for Variables in the Present Study.

Variables	Sex	Major	SES	Age	English	Reading	AB	AE	Behavioral	Emotional	Cognitive
Sex	1
Major	0.179**	1
SES	0.079*	0.004	1
Age	−0.002	0.136**	−0.054	1
English	0.258**	0.100**	0.179**	−0.169**	1
Reading	0.261**	0.127**	0.142**	−0.150**	0.438**	1
AB	−0.058	−0.004	0.201**	−0.037	0.079*	0.112**	1
AE	0.130**	0.024	0.487**	−0.045	0.238**	0.143**	0.405**	1
Behavioral	0.146**	0.045	0.359**	−0.031	0.226**	0.124**	0.377**	0.899**	1
Emotional	0.093*	0.021	0.382**	−0.071	0.191**	0.136**	0.374**	0.869**	0.717**	1
Cognitive	0.105**	0.002	0.538**	−0.032	0.216**	0.128**	0.347**	0.917**	0.692**	0.719**	1
Mean	1.75	6.39	3.56	18.69	108.37	15.81	3.34	3.28	3.19	3.30	3.36
SD	0.433	3.409	0.795	0.876	16.148	5.809	0.722	0.508	0.525	0.566	0.602
Kurtosis	−0.663	−1.171	0.322	0.957	1.223	−0.424	0.268	0.998	1.078	0.761	0.773
Kurewness	−1.157	0.035	−0.419	0.977	−0.840	−0.078	−0.176	0.141	0.165	0.025	0.047

p < .05. **p < .01.

Results

What is the Relationship Between AB, AE, and EFL Reading?

The results of Pearson correlation analysis in Table 2 revealed several significant positive correlations among the investigated variables. Specifically, AB was positively related to AE (r = .405, p < .01), behavioral engagement (r = .377, p < .01), emotional engagement (r = .374, p < .01), cognitive engagement (r = .347, p < .01), or EFL reading (r = .112, p < .01), respectively. Similarly, EFL reading was positively related to AE (r = .143, p < .01), behavioral engagement (r = .124, p < .01), emotional engagement (r = .136, p < .01), or cognitive engagement (r = .128, p < .01), respectively. The current study showed Cronbach’s alpha of each variable in the section of Measures, so the present study did not show the information about this value here. Gender, age, English achievement, SES, and major correlated with such variables as AB, AE, and EFL reading achievement. Therefore, these were covariates in the models. These findings revealed that the data were suitable for further statistical analyses, specifically linear regression and mediation effect analysis, to explore the relationships between the variables.

The present study used linear regression analysis to answer H1. Covariates were English achievement, major, age, SES, and gender. The present study did not reveal these covariates information owing to being concise in the models.

Table 3 summarized the regression models among AB, AE, and EFL reading, addressing H1. The results indicated that AB significantly predicted AE (β = .40, p < .001, Adjusted R² = .16) and EFL reading (β = .90, p < .01, Adjusted R² = .11). Additionally, the results demonstrated that AE significantly predicted EFL reading (β = .14, p < .001, Adjusted R² = .14). Moreover, the findings revealed that AB significantly predicted behavioral engagement (β = .27, p < .001, Adjusted R² = .14), emotional engagement (β = .29, p < .001, Adjusted R² = .14), and cognitive engagement (β = .29, p < .001, Adjusted R² = .12). Finally, the results suggested that EFL reading was significantly predicted by behavioral engagement (β = .12, p < .001, Adjusted R² = .12), emotional engagement (β = .14, p < .001, Adjusted R² = .13), and cognitive engagement (β = .13, p < .001, Adjusted R² = .13), respectively. These results support the hypothesized relationships among the variables and provide insight into the complex interplay between AB, AE, and EFL reading achievement among English learners from Chinese colleges.

Table 3.

Linear Regression Analysis Models of AB, Engagement, and EFL Reading.

Models	β	SE	t	Adjusted R²	F
AB→ EFL reading	.90	0.31	2.90**	.11	8.43
AB→ AE	.40	0.03	11.35***	.40	128.88
AB→ behavioral engagement	.27	0.03	10.44***	.14	109.07
AB→ emotional engagement	.29	0.03	10.35***	.14	107.07
AB→ cognitive engagement	.29	0.03	9.49***	.12	90.06
AE→ EFL reading	.14	5.75	3.71***	.14	13.76
Behavioral engagement→ EFL reading	.12	0.43	3.20***	.12	10.23
Emotional engagement→ EFL reading	.14	0.40	3.51***	.13	12.32
Cognitive engagement→ EFL reading	.13	0.37	3.32***	.13	11.00

p < .01. ***p < .001.

Can AE, With Its Three Sub-dimensions, Mediate the Relationship Between AB and EFL Reading?

A bootstrap resampling technique was employed to generate 5,000 iterations of the data to investigate the potential mediating role of AE and its sub-dimensions in the relationship between AB and EFL reading. This technique allowed the present study to estimate a 95% bias-corrected confidence interval, with the significance threshold set at p < .05. Covariates included gender, age, socioeconomic status (SES), major, and English achievement.

Table 4 showed the mediating effect of AE between AB and EFL reading, thus addressing H2. The findings indicated that AE acted as a mediator (β = .44, 95% CI [0.182, 0.739]) between AB and EFL reading. Notably, the direct effect of AB on EFL reading was not statistically significant (95% CI [−0.203, 1.125]), suggesting that the impact of AB on EFL reading was fully mediated by AE among English learners from Chinese colleges.

Table 4.

Bootstrap Mediating Effects of AE.

Effects	β	95% CI	SE
Total effect	.90	[0.293, 1.517]	0.33
Direct effect	.46	[−0.203, 1.125]	0.34
Indirect effect	.44	[0.182, 0.739]	0.14

Table 5 presented the outcomes of a mediation analysis to investigate the potential mediating roles of the three sub-dimensions of AE (including emotional, behavioral, and cognitive engagement) in the relationship between AB and EFL reading, thereby addressing H2. The results revealed that emotional engagement acted as a mediator (β = .47, 95% CI [0.100, 0.911]) between AB and EFL reading. Specifically, the direct effect of AB on EFL reading was not statistically significant (95% CI [−0.203, 1.125]), indicating that the impact of AB on EFL reading was mediated entirely by emotional engagement. In contrast, neither behavioral (β = .06, 95% CI [−0.317, 0.470]) nor cognitive engagement (β = −.04, 95% CI [−0.394, 0.285]) demonstrated a mediating role between AB and EFL reading. These findings suggest that emotional engagement is the mediating factor in the relationship between AB and EFL reading, while behavioral and cognitive engagement do not play a mediating role in this relationship among English learners from Chinese colleges.

Table 5.

Bootstrap Mediating Effects of Three Dimensions of AE.

Statistics	Total effect	Direct effect	Indirect effect
Statistics	Total effect	Direct effect	Behavioral engagement	Emotional engagement	Cognitive engagement
β	.90	.46	.06	.47	−.04
95% CI	[0.293, 1.517]	[−0.203, 1.125]	[−0.317, 0.470]	[0.100, 0.911]	[−0.394, 0.285]
SE	0.33	0.34	0.20	0.21	0.17

Discussions

This study examined how AB in reading influences EFL reading through AE during reading. The findings imply that AB, AE, and EFL reading are mutually correlated, with AE serving as a mediator, particularly emotional engagement in reading.

The Relationship Among AB, AE, and EFL Reading Achievement

This study found a positive relationship among AB, AE, and EFL reading, supporting H1. The results indicated that higher levels of AB were associated with better EFL reading performance, higher AE associated with better EFL reading achievement, and higher AB related to AE. This finding supports that AB may determine learners’ ability to navigate daily challenges and obstacles in learning EFL reading. Everyday motivational resilience and vulnerability framework may explain this relationship. In EFL settings, the degree of AB possessed by EFL learners directly influences their reading because AB enables learners to cope with daily setbacks encountered during learning reading. These learners may manage their reading strategies (cognitive engagement). For instance, they may skim, scan, and use schema to help them understand the reading passages. When Chinese learners read a new text, they will search for some background information about this text. They are confident about learning English reading well and feel interested in having English reading classes every time, demonstrating more emotional engagement. They concentrate on English reading in classes and discuss with their classmates after classes, showing more behavioral engagement. When confronted with daily learning challenges, higher buoyant students experience more AE during reading. This experience helps learners buffer against the negative impacts of daily hassles and adversity, enabling them to maintain a high and consistent academic performance across EFL reading.

This study’s findings were inconsistent with previous research about the relationship between AB, AE, and academic achievement. Former studies found that AB predicted academic achievement in math (e.g., Malmberg et al., 2013; Putwain et al., 2016; Putwain & Wood, 2023), English (e.g., Malmberg et al., 2013; Putwain et al., 2016; Yun et al., 2018), and overall school subjects (Guo et al., 2024; Putwain et al., 2024). Prior studies demonstrated a positive relationship between AB and AE in English (e.g., Liu et al., 2025; Wang & Liu, 2022), math (e.g., Putwain & Wood, 2023), and overall school subjects (e.g., Datu & Yang, 2018; Heydari et al., 2024; Thomas & Allen, 2021). Existed research revealed a positive correlation between AE and academic achievement in overall school subjects (e.g., Laranjeira & Teixeira, 2025; Zilvinskis et al., 2017), computer literacy(e.g., Avcı & Ergün, 2022), and math (e.g., Putwain and Wood (2023). The possible reason is that former studies did not research AB, AE, and EFL reading in one framework. The results suggest that AB, AE, and academic achievement correlated in school subjects, though EFL reading differs from English, math, and overall school subjects.

The results were partly consistent with some previous studies demonstrating a positive correlation between AB and EFL reading (Collie et al., 2024; Colmar et al., 2019; Saalh & Kadhim, 2020), as well as studies finding that behavioral and emotional engagement during reading were associated with reading achievement (Lee, 2014). The possible reason is that previous studies only researched AB and reading achievement (Collie et al., 2024; Colmar et al., 2019; Saalh & Kadhim, 2020) or behavioral and emotional engagement with reading (Lee, 2014). In diverse research settings, AB is positively related to reading achievement, and behavioral and emotional engagement in reading are associated with reading achievement. These studies imply a relationship between AB, AE, and EFL reading. This finding is proved by Pearson correlation analysis and linear regression analysis in the section of Results (see Tables 2 and 3 for details).

The results suggest that the relationship between AB, AE, and academic achievement may be domain-general. In academic disciplines, learners encounter daily hassles, experiencing AB. More academically buoyant learners exhibit more time (behavioral engagement), positive emotions (emotional engagement), and strategies (cognitive engagement) to conquer these challenges, showing better academic outcomes. Conversely, less academically buoyant learners exhibit less time, negative emotions, and ineffective strategies to overcome these hassles, exhibiting less academic performance. Consequently, the relationship among these three variables is correlated, irrespective of school subjects or skills.

The Mediating Role of AE in EFL Reading

The findings of this study demonstrated the mediating effect of AE in the relationship between AB and EFL reading outcomes, partially confirming H2. This result indicates that AE is a mechanism by which AB influences EFL reading achievement. The everyday motivational resilience and vulnerability framework may explain this relationship. In EFL settings, the degree of AB among EFL learners indirectly impacts their reading achievement via AE. AB enhances the satisfaction of basic positive psychological needs for competence, equipping students with tools to tackle daily academic-related challenges in reading effectively. For example, EFL learners are confident about learning English reading (cognitive engagement), interested in English reading classes (emotional engagement), and committed to completing English reading homework (behavioral engagement). AB fosters the development of various cognitive, behavioral, and emotional resources by fulfilling these competence needs. This system explains why AB indirectly affects EFL reading performance via AE.

The current study’s findings differed from previous research (e.g., Collie et al., 2015; Colmar et al., 2019; Datu & Yang, 2021; Weißenfels et al., 2023; Yun et al., 2018) that identified alternative factors as mediators between AB and academic achievement. For instance, AB during math influenced math achievement through academic self-efficacy (Weißenfels et al., 2023). In contrast, AE emerged as the mediator between AB and EFL reading in the present study. Two plausible explanations can account for this disparity. Firstly, unlike this study, previous investigations did not consider AE as a potential mediator. Secondly, the school subjects examined in those studies differed from the EFL reading focus of the current study. It is conceivable that different mechanisms may contribute to the mediating effect between AB and diverse school subjects or skills. These fields may reveal distinct levels of AB, requiring various psychological factors as mediators. The findings suggest that multiple pathways might exist in the relationship between AB and academic achievement.

However, when analyzing the separate mediating roles of the three subdivisions within AE, the findings demonstrated the mediating effect of emotional engagement, rather than behavioral or cognitive engagement, in the relationship between AB and EFL reading outcomes, partially confirming H2. This result indicates that emotional engagement is a mechanism by which AB influences EFL reading performance. In the everyday motivational resilience and vulnerability framework, by devoting emotional engagement resources, learners can sustain their motivation and interest in reading, ultimately leading to improved academic outcomes (Putwain et al., 2019). Emotional engagement may hold greater significance due to its ability to mobilize additional behavioral and cognitive resources, thereby more likely promoting academic achievement than behavioral or cognitive engagement alone.

The findings were not congruent with Putwain and Wood’s (2023) finding that only behavioral engagement was a mediator between AB and math achievement. In contrast, this investigation revealed that emotional engagement may mediate the relationship between AB and EFL reading outcomes. One possible explanation is that Putwain and Wood (2023) assessed only behavioral engagement during math, whereas this study evaluated emotional, behavioral, and cognitive engagement in EFL reading. The results suggest that the mediating role between AB and math achievement differs from that between AB and reading outcomes. Reading may be less demanding than math but could entail more effort and perseverance. More academically buoyant students may be more adept at reading than math. Consequently, the emotional engagement of learners plays a positive role in improving their reading performance. The findings suggest that the three subdivisions of AE may separately mediate AB and various subjects or skills.

The findings support and further develop the everyday motivational resilience and vulnerability framework, explaining the process of AB on academic achievement via AE (Pitzer & Skinner, 2017; Skinner et al., 2016). This framework may apply to school subjects and EFL reading skills. Facing daily academic challenges in EFL reading, more academically buoyant learners adopt coping strategies to engage more in EFL reading. They may comply with classroom rules and finish reading tasks (behavioral engagement), shoulder difficulties (emotional engagement), and check for errors (cognitive engagement) when completing English reading assignments. Particularly, learners with more emotional engagement may exhibit more behavioral and cognitive engagement, more likely to improve EFL reading performance. Namely, the present study extends the everyday motivational resilience and vulnerability framework from general school subjects to the EFL reading field.

This study extends self-determination theory into the EFL reading realm. AB fundamentally stems from the sustained satisfaction of three basic psychological needs: autonomy, competence, and relatedness, as outlined in self-determination theory (Deci & Ryan, 2000). Educational settings during EFL reading provide autonomy support, competence reinforcement, and relatedness cultivation. Learners internalize academic challenges during EFL reading as opportunities for growth rather than threats. This need-satisfying EFL reading context fosters a “psychological immune system” that sustains AB by reframing stressors through self-determined motivation. The motivation continuum clarifies that emotional engagement reflects the internalization of extrinsic motivators into intrinsic motivation (Ryan & Deci, 2020). When AB is activated through need satisfaction, students shift from external rewards to integrated regulation during EFL reading, aligning EFL reading with self-concordant goals. Emotional engagement manifests in meaning-making while reading, such as exploring cultural narratives. Moreover, cognitive and behavioral experiences occur during EFL reading. Therefore, AE, especially emotional engagement, bridges AB and EFL reading achievement through autonomy, competence, and relatedness.

Conclusions, Implications, and Limitations

This study aimed to examine the relationship among AB, AE, and EFL reading achievement, as well as the mediating role of AE between AB and EFL reading performance. The results indicated that these three variables were correlated; AE, particularly emotional engagement, potentially mediated the relationship between AB and EFL reading outcomes. Compared to prior studies and theories, the relationship between AB, AE, and academic achievement may be domain-general across various subjects and skills; the three subdivisions of AE may mediate the relationship between AB and various skills or subjects differently. The findings support and further develop the everyday motivational resilience and vulnerability framework as well as self-determination theory within the realm of EFL reading. Given the complexity of mediators between AB and various subjects or skills, there is a need to explore additional mediating variables, especially subdivisions of AE. Despite the limitations, this study provides initial evidence of the role of AB and AE in EFL reading outcomes.

The findings of this study have implications for instructing reading in EFL settings. Specifically, the results underscore the importance of fostering students’ AB within existing EFL reading teaching approaches. This necessitates a collaborative effort among teachers, psychologists, and counselors to create opportunities that facilitate students’ AB in EFL reading. One effective strategy is to help students recognize the value of errors and missteps during the EFL reading process as opportunities for growth. Teachers can encourage EFL students to view challenges as integral to learning EFL reading. Teachers, psychologists, and counselors can design and implement psycho-educational programs to improve EFL students’ ability to manage minor setbacks and adversity in EFL reading. This study also emphasizes the importance of promoting AE, especially emotional engagement. Instructors can teach students strategies to manage negative emotions and cultivate positive ones when encountering new or demanding EFL reading tasks. One approach is to provide background information to familiarize students with EFL reading assignments, reducing anxiety and increasing confidence. Introducing interesting EFL reading materials may also help elicit positive emotions and motivation from students.

This investigation encountered several limitations. Initially, the study relied on self-report data to measure AB and AE in EFL reading, which may lead to common method variance. Future studies could employ alternative methods of measuring AB and AE, such as peer-report and teacher-report data, student interviews, or classroom observations. Secondly, the sample population consisted solely of Chinese EFL learners, so caution should be exercised when extending the findings to other EFL contexts. Conducting studies among learners from diverse EFL contexts is essential to establish the generalizability of these results. Thirdly, although AB is considered domain-general, its influence on distinct EFL skills may vary. For instance, Saalh and Kadhim (2020) found that learners’ AB regarding reading was substantially higher than that for listening. Hence, further exploration is required to examine the varying impacts of AB on different EFL skills. Fourthly, the indirect effect between AB and EFL reading may involve multiple pathways, such as positive psychological factors (e.g., self-concept, self-control, and intrinsic motivation). These factors may mediate the relationship between AB and EFL reading. Subsequent studies might investigate the indirect effects of these factors to understand the underlying mechanisms. Fifthly, factors such as socioeconomic status, prior academic performance, reading proficiency, teaching quality, classroom environment, or parental support could influence these relationships. Future studies should consider controlling for these variables. Finally, the cross-sectional design precludes definitive conclusions about causality. It is plausible that higher reading proficiency may enhance learners’ emotional engagement and AB, suggesting a bidirectional relationship. This limitation underscores the need for longitudinal or experimental investigations to establish temporal precedence.

Supplemental Material

sj-doc-1-sgo-10.1177_21582440251357156 – Supplemental material for Exploring the Relationships Between Academic Buoyancy, Engagement, and Achievement in English Reading Among EFL Learners

Supplemental material, sj-doc-1-sgo-10.1177_21582440251357156 for Exploring the Relationships Between Academic Buoyancy, Engagement, and Achievement in English Reading Among EFL Learners by Kang Zhai in SAGE Open

Footnotes

Acknowledgements

The author is very grateful to all the students who took part in this study. My appreciation is also extended to the reviewers and editors for their keen insights and careful attention.

ORCID iD

Kang Zhai

Ethical Considerations

This study has been approved by the Ethics Review Committee of the Foreign Languages Department at Fujian Polytechnic Normal University, with the approval number [Reference No. FPNUSFL-2024003]. Informed consent was also obtained from all individual participants included in the research. This consent elaborates on the purpose of the study, procedures, confidentiality, risks and benefits, voluntary participation, as well as contact information. This article does not contain any studies with animals performed by any of the authors.

Author Contributions

Kang Zhai completed the paper independently.

Funding

The author disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study is partially supported by the Fujian Province Social Science Planning Project in 2024 (Grant No. FJ2024B067).

Declaration of Conflicting Interests

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author, [Kang Zhai], upon reasonable request.

Supplemental Material

Supplemental material for this article is available online.

References

Avcı

Ü.

Ergün

. (2022). Online students’ LMS activities and their effect on engagement, information literacy, and academic performance. Interactive Learning Environments, 30(1), 71–84.

Barber

A. T.

Klauda

S. L.

(2020). How reading motivation and engagement enable reading achievement: Policy implications. Policy Insights from the Behavioral and Brain Sciences, 7(1), 27–34.

Collie

R. J.

Caldecott-Davis

Martin

A. J.

(2024). Academic buoyancy among female secondary school students: An examination of predictors and outcomes up to age 22. Social Psychology of Education, 27(2), 363–388.

Collie

R. J.

Martin

A. J.

Malmberg

L. E.

Hall

Ginns

(2015). Academic buoyancy, student’s achievement, and the linking role of control: A cross-lagged analysis of high school students. British Journal of Educational Psychology, 85(1), 113–130.

Colmar

Liem

G. A. D.

Connor

Martin

A. J.

(2019). Exploring the relationships between academic buoyancy, academic self-concept, and academic performance: A study of mathematics and reading among primary school students. Educational Psychologist, 39(8), 1068–1089.

Datu

J. A. D.

Yang

(2018). Psychometric validity and gender invariance of the academic buoyancy scale in the Philippines: A construct validation approach. Journal of Psychoeducational Assessment, 36(3), 278–283.

Datu

J. A. D.

Yang

(2021). Academic buoyancy, academic motivation, and academic achievement among Filipino high school students. Current Psychology, 40, 3958–3965.

Deci

E. L.

Ryan

R. M.

(2000). The “what” and “why” of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227–268.

Fredricks

J. A.

Blumenfeld

P. C.

Paris

A. H.

(2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74(1), 59–109.

10.

Gao

Chai

Shen

(2025). Linking effort-reward imbalance to academic burnout among high school students: The roles of school connectedness and academic buoyancy. Psychology in the Schools, 62(1), 202–218.

11.

Guo

Zhou

Chen

(2024). Doctoral students’ academic performance: The mediating role of academic motivation, academic buoyancy, and academic self-efficacy. Heliyon, 10, e32588. https://doi.org/10.1016/j.heliyon.2024.e32588

12.

Hayes

A. F.

(2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Journal of Educational Measurement, 51(3), 335–337.

13.

Heydari

Manzari

T. A.

Manzari

T. H.

Soltani

(2024). Designing a model of academic adjustment based on educational engagement, the mediatory role of academic buoyancy in students of secondary school in Yazd province. Journal of Psychological Science, 23, 1509–1526.

14.

Hirvonen

Yli-Kivistö

Putwain

D. W.

Ahonen

Kiuru

(2019). School-related stress among sixth-grade students – Associations with academic buoyancy and temperament. Learning and Individual Differences, 70, 100–108.

15.

Kimberley

Thursby

(2020). Framing the text: Understanding emotional barriers to academic reading. Journal of University Teaching and Learning Practice, 17(2), 2. https://doi.org/10.53761/1.17.2.2

16.

Kim

T. Y.

Kim

J. Y.

(2018). A qualitative inquiry on EFL learning demotivation and resilience: A study of primary and secondary EFL students in South Korea. Asia-Pacific Education Researcher, 27, 55–64.

17.

Laranjeira

Teixeira

M. O.

(2025). Relationships between engagement, achievement, and well-being: Validation of the engagement in higher education scale. Studies in Higher Education, 50, 756–770.

18.

Lawrence

J. F.

Knoph

McIlraith

Kulesz

P. A.

Francis

D. J.

(2022). Reading comprehension and academic vocabulary: Exploring relations of item features and reading proficiency. Reading Research Quarterly, 57(2), 669–690.

19.

Lee

J. S.

(2014). The relationship between student engagement and academic performance: Is it a myth or reality? Journal of Education and Research, 107(3), 177–185.

20.

Liu

Zhu

Chen

(2025). Unraveling the mediating role of buoyancy in the relationship between anxiety and EFL students’ learning engagement. Perceptual and Motor Skills, 132(1), 195–217.

21.

MacKinnon

D. P.

Fairchild

A. J.

Fritz

M. S.

(2007). Mediation analysis. Annual Review of Psychology, 58, 593–614.

22.

Malmberg

L. E.

Hall

Martin

A. J.

(2013). Academic buoyancy in secondary school: Exploring patterns of convergence in English, Mathematics, science, and physical education. Learning and Individual Differences, 23, 262–266.

23.

Martin

A. J.

Marsh

H. W.

(2008). Academic buoyancy: Towards an understanding of students’ everyday academic resilience. Journal of School Psychology, 46(1), 53–83.

24.

Middleton

Ahmed Shafi

Millican

Templeton

(2023). Developing effective assessment feedback: Academic buoyancy and the relational dimensions of feedback. Teaching in Higher Education, 28(1), 118–135.

25.

Miller

Connolly

Maguire

L. K.

(2013). Wellbeing, academic buoyancy, and educational achievement in primary school students. International Journal of Educational Research, 62, 239–248.

26.

Patall

E. A.

Yates

Lee

Chen

Bhat

B. H.

Lee

Beretvas

S. N.

Lin

Man Yang

Jacobson

N. G.

Harris

Hanson

D. J.

(2024). A meta-analysis of teachers’ provision of structure in the classroom and students’ academic competence beliefs, engagement, and achievement. Educational Psychologist, 59(1), 42–70.

27.

Pitzer

Skinner

(2017). Predictors of changes in students’ motivational resilience over the school year: The roles of teacher support, self-appraisals, and emotional reactivity. International Journal of Behavioral Development, 41(1), 15–29.

28.

Putwain

D. W.

Daly

A. L.

Chamberlain

Sadreddini

(2016). “‘Sink or swim’: Buoyancy and coping in the cognitive test anxiety – academic performance relationship”. Educational Psychologist, 36(10), 1807–1825.

29.

Putwain

D. W.

Daumiller

Hussain

Pekrun

(2024). Revisiting the relation between academic buoyancy and coping: A network analysis. Contemporary Educational Psychology, 78, 102283.

30.

Putwain

D. W.

Gallard

Beaumont

(2019). A multi-component wellbeing programme for upper secondary students: Effects on wellbeing, buoyancy, and adaptability. School Psychology International, 40(1), 49–65.

31.

Putwain

D. W.

Wood

(2023). Riding the bumps in Mathematics learning: Relations between academic buoyancy, engagement, and achievement. Learning and Instruction, 83, 101691. https://doi.org/10.1016/j.learninstruc.2022.101691

32.

Ryan

R. M.

Deci

E. L.

(2020). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. Contemporary Educational Psychology, 61, 101860.

33.

Saalh

S. M.

Kadhim

S. H.

(2020). The EFL students’ academic buoyancy in reading and listening skills. The Asian EFL Journal, 27(4), 226–253.

34.

Selim

S. M. M.

Islam

A. B. M. S

. (2022). Engaged reading: Moving from theory to implication for L2 learners. Journal of Languages and Language Teaching, 10(3), 424–433.

35.

Skinner

E. A.

Pitzer

J. R.

Steele

J. S.

(2016). Can student engagement serve as a motivational resource for academic coping, persistence, and learning during late elementary and early middle school? Developmental Psychology, 52(12), 2099–2117.

36.

Thomas

C. L.

Allen

(2021). Driving engagement: Investigating the influence of emotional intelligence and academic buoyancy on student engagement. Journal of Further and Higher Education, 45(1), 107–119.

37.

Toti

U. S.

Hamid

S. A.

(2022). An exploratory study of culturally familiar or unfamiliar texts contributing to reading comprehension in EFL context. Journal of Language Teaching and Research, 13(5), 981–989.

38.

Wang

Liu

(2022). The mediating roles of buoyancy and boredom in the relationship between autonomous motivation and engagement among Chinese senior high school EFL learners. Frontiers in Psychology, 13, 992279. https://doi.org/10.3389/fpsyg.2022.992279

39.

Weißenfels

Hoffmann

Dörrenbächer-Ulrich

Perels

(2023). Linking academic buoyancy and math achievement in secondary school students: Does academic self-efficacy play a role? Current Psychology, 42(27), 23422–23436.

40.

Wong

Z. Y.

Liem

G. A. D.

Chan

Datu

J. A. D.

(2024). Student engagement and its association with academic achievement and subjective wellbeing: A systematic review and meta-analysis. Journal of Education & Psychology, 116(1), 48–75.

41.

Yapp

de Graaff

van Den Bergh

(2023). Effects of reading strategy instruction in English as a second language on students’ academic reading comprehension. Language Teaching Research, 27(6), 1456–1479.

42.

Yun

Hiver

Al-Hoorie

A. H.

(2018). Academic buoyancy: Exploring learners’ everyday resilience in the language classroom. Studies in Second Language Acquisition, 40(4), 805–830.

43.

Zilvinskis

Masseria

A. A.

Pike

G. R.

(2017). Student engagement and student learning: Examining the convergent and discriminant validity of the revised national survey of student engagement. Research in Higher Education, 58, 880–903.

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