Basic psychological needs satisfaction at school, behavioral school engagement, and academic achievement: Longitudinal reciprocal relations among elementary school students

Contemporary Educational Psychology 56 (2019) 130–139

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Contemporary Educational Psychology journal homepage: www.elsevier.com/locate/cedpsych

Basic psychological needs satisfaction at school, behavioral school engagement, and academic achievement: Longitudinal reciprocal relations among elementary school students

T

Yanhui Wanga,b,c, Lili Tiana,b,c, , E. Scott Huebnerd ⁎

a

School of Psychology, South China Normal University, Guangzhou 510631, People’s Republic of China Center for Studies of Psychological Application, South China Normal University, Guangzhou 510631, People’s Republic of China c Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, People’s Republic of China d Department of Psychology, University of South Carolina, Columbia, SC, USA b

ARTICLE INFO

ABSTRACT

Keywords: Basic psychological needs satisfaction at school Behavioral school engagement Academic achievement Reciprocal relations Elementary school students

Based on self-system processes theory and transactional theory, a longitudinal design was employed to test the reciprocal relations among basic psychological needs satisfaction at school (BPNSS), behavioral engagement, and academic achievement. A total of 627 elementary school students from Grades 3-4 in China (Mage = 9.01, 45.8% female) completed measures of BPNSS and behavioral engagement in the middle of four consecutive semesters. Teachers also assessed students’ academic achievement at the end of the first three consecutive semesters. After controlling for gender, age, and fathers’ and mothers’ education, the results indicated that: (a) BPNSS, behavioral engagement, and academic achievement reciprocally facilitated each other directly; (b) BPNSS indirectly enhanced academic achievement via behavioral engagement, and academic achievement also indirectly enhanced BPNSS via behavioral engagement. Findings suggested that BPNSS, behavioral engagement, and academic achievement formed a complex, dynamic system. Limitations and practical applications of the study were discussed.

1. Introduction Children’s academic achievement plays a fundamental role in their subsequent educational experiences (Hughes, Luo, Kwok, & Loyd, 2008); it is also related to their mental health outcomes (i.e., subjective well-being) throughout their school years (Bücker, Nuraydin, Simonsmeier, Schneider, & Luhmann, 2018; Tian, Zhang, Huebner, Zheng, & Liu, 2016). Given the importance of academic achievement in the early school period (Badri, Amani-Saribaglou, Ahrari, Jahadi, & Mahmoudi, 2014), psychologists and educational researchers have considered the discovery of its determining factors as one of the main issues in education (Chamorro-Premuzic & Furnham, 2003). The major determinants can be divided into two aspects: environmental factors (e.g., socioeconomic status) and individual factors (e.g., self-beliefs; Chen, 2005; Sirin, 2005; Valentine, DuBois, & Cooper, 2004). However, little attention has been paid to basic psychological needs satisfaction at school (BPNSS) in particular, which is a critical factor connecting environmental factors and individual factors (Tian, Han, & Huebner, 2014). BPNSS reflects students’ assessment of how well the school (an

⁎

external context) is fulfilling their basic needs. Furthermore, according to self-system processes theory (Connell & Wellborn, 1991), BPNSS should be associated with an important individual factor (i.e., behavioral engagement), which in turn should be associated with subsequent academic achievement. Some studies have supported associations among basic psychological needs satisfaction, behavioral engagement, and academic achievement (e.g., Jang, Kim, & Reeve, 2012; Skinner, Furrer, Marchand, & Kindermann, 2008). Although such previous studies have enriched the literature, there have been some limitations. First, extant studies have paid attention to the role of general psychological needs satisfaction on academic achievement, but not to the role of domain-specific (i.e., school-based) needs satisfaction. Given that students spend a substantial amount of time in school (i.e., a minimum of six hours per day for students even as early as elementary school), and complete most of their academic activities in the school setting (Xu & Minca, 2008), studies of their needs satisfaction in school seem especially instructive for improving students’ academic achievement (Tian, Han et al., 2014). Second, most of the extant studies have

Corresponding author at: School of Psychology, South China Normal University, Guangzhou 510631, People’s Republic of China. E-mail addresses: [email protected], [email protected] (L. Tian).

https://doi.org/10.1016/j.cedpsych.2019.01.003

Available online 06 January 2019 0361-476X/ © 2019 Elsevier Inc. All rights reserved.

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involved adolescents. Only a handful of studies have involved elementary school students (e.g., Marshik, 2010; Milyavskaya & Koestner, 2011; Stratton, 2012), which is an important omission because academic achievement during the elementary school period is crucial to students’ success in their subsequent educational experiences (Deci & Ryan, 2000; Tian, Zhang et al., 2016). Third, most of the previous research has been cross-sectional (e.g., Marshik, 2010; Milyavskaya & Koestner, 2011; Stratton, 2012). This methodological limitation reduces confidence in the ability to derive reliable inferences due to the failure to incorporate statistical controls for prior levels of the dependent valuables. Fourth, most studies have failed to test for the reciprocal effects of behavioral engagement and academic achievement on basic needs satisfaction. Consistent with transactional theory (Sameroff, 1975), children’s development results from the dynamic interactions between individuals and their contexts. Children’s actions are influenced by context, and their actions also influence context. Thus, unidirectional models might not be adequate representations of developmental processes. Therefore, by combining self-system processes theory and transactional theory, we aimed to further understand the reciprocal relations among BPNSS, behavioral engagement, and academic achievement employing a longitudinal design with elementary school students.

1975, 2009), environments affect children, and children also affect their environments (Skinner & Belmont, 1993). Thus, children’s academic achievement should also likely influence their school environment. In school, teachers and classmates comprise the most important parts of the school social environment. Usually, teachers prefer students who display higher achievement (Davis, 2006). Teachers may engage in different interactions with preferred students, even though they may not be aware of the differential treatment (Košir & Tement, 2014). Furthermore, teachers’ preferences may affect classmates’ preferences (Hendrickx, Mainhard, Boor-Klip, & Brekelmans, 2017). Therefore, students with different academic achievement levels might be treated differently by their teachers and classmates, resulting in varying levels of basic psychological needs satisfaction at school. Although no study has directly tested the impact of academic achievement on children’s BPNSS, Košir and Tement (2014) revealed that academic achievement affects teacher acceptance using a two-wave longitudinal design with a sample of students from Slovenian elementary and secondary schools. Similarly, Hajovsky, Mason, and McCune (2017) found that American elementary school students’ math achievement levels exerted positive effects on subsequent teacher-student closeness, and negative effects on teacher-student conflict. In addition, Véronneau, Vitaro, Brendgen, Dishion, and Tremblay (2010) demonstrated that higher academic achievement predicted increases in peer acceptance and decreases in peer rejection using a longitudinal model in a sample of students in Canada ranging from middle childhood to early adolescence. The influence of students’ academic achievement on their BPNSS would be expected to be stronger among Chinese students than students in Western countries. In China, there is a deeply rooted tradition to emphasize and demand academic achievement (Wang & Ollendick, 2001). Therefore, Chinese students’ academic achievement would likely have more impact on their environment (i.e., BPNSS), compared to students in other cultures. Specifically, Chinese students with high academic achievement would be more likely to be appreciated by their teachers and respected by their classmates than students in Western countries (Li, 2012). Overall, according to the previous literature, we expected that children’s BPNSS and academic achievement would enhance each other reciprocally among Chinese elementary school students.

1.1. Basic psychological needs satisfaction at school and academic achievement Grounded in Deci and Ryan’s basic psychological needs theory (BPNT), which is a sub-theory of Self-Determination Theory (Deci & Ryan, 2000), one of the most widely accepted theories of individuals’ motivation and behaviors, Tian, Han et al. (2014) applied BPNT to the studies of students’ school lives. Given that needs satisfaction is largely contextually determined (Deci & Ryan, 2008), and that school is a crucial context for students, adapting general basic needs theory to a specific domain (i.e., school) is important in theory and practice. Tian, Han et al. proposed that there were three basic psychological needs for students at school: autonomy, relatedness, and competence. These school-specific basic needs are generally the same three as in BPNT and SDT. The school-specific need for autonomy refers to “students’ desires to experience a sense of volition and self-endorsement of their behavior at school”; the school-specific need for relatedness refers to “students’ desires to experience a sense of school belonging, including a sense of connection with teachers and classmates”; and the school-specific need for competence refers to “students’ desires to interact effectively with the school environment and to experience opportunities for developing and expressing their individual capabilities” (Tian, Han et al., 2014, p. 258). The satisfaction of basic psychological needs at school is thought to be beneficial for students’ development in their lives (Tian, Chen, & Huebner, 2014; Tian, Pi, Huebner, & Du, 2016). In turn, it has been suggested that BPNSS would improve students’ academic achievement, as individuals’ needs satisfaction in a particular domain (e.g., school domain) might especially influence their performance in that particular domain (Tian, Tian, & Huebner, 2016). Although no research has directly examined the relations between basic psychological needs satisfaction in school and academic achievement in particular, there has been some evidence that the general satisfaction of basic needs is positively associated with students’ academic achievement (e.g., Badri et al., 2014; Maralani, Lavasani, & Hejazi, 2016). For example, Marshik (2010) found that students’ psychological need satisfaction (general, but not school specific) was a positive predictor of academic achievement in elementary school students. Such associations have also been demonstrated in secondary school students and high school students (Badri et al., 2014; Diseth, Danielsen, & Samdal, 2012; Duchesne, Ratelle, & Feng, 2016). Therefore, it seems plausible that BPNSS would be positively associated with children’s academic achievement. As noted previously, according to transactional theory (Sameroff,

1.2. Behavioral school engagement and academic achievement Student’s engagement behaviors have been linked to a range of positive outcomes, such as greater academic achievement and superior psychological adjustment (Van Ryzin, 2011). In addition, low school engagement itself has been characterized as one of the most immediate and persistent problems exhibited by students (Wang, 2010). Compared to other types of school engagement, such as cognitive engagement and emotional engagement, behavioral engagement has tended to be the focus of research with elementary school students (Hughes et al., 2008; Miles & Stipek, 2006). Behavioral school engagement refers to attendance, participation, and positive conduct in school (Fredricks, Blumenfeld, & Paris, 2004). Behavioral engagement has been demonstrated to be an important antecedent variable for academic achievement (Archambault, Janosz, Morizot, & Pagani, 2009; Maralani et al., 2016; Wang & Eccles, 2012). Students with higher levels of behavioral engagement participate more in class discussions and exert more overall effort in school activities (Reyes, Brackett, Rivers, White, & Salovey, 2012). These behaviors should enhance students’ achievement outcomes. Several studies have revealed the predictive role of behavioral engagement in students’ academic achievement (e.g., Guo, Connor, Tompkins, & Morrison, 2011; Ladd & Dinella, 2009; Reyes et al., 2012). The above studies examined the path from behavioral engagement to academic achievement. Yet academic achievement may also affect behavioral engagement. Children with low academic achievement are likely to experience more academic stressors (Hughes et al., 2008), and 131

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Fig. 1. The hypothesized full longitudinal cross-lagged model. Note. T = Time. BPNSS = Basic Psychological Needs Satisfaction at School, BE = Behavioral Engagement, AA = Academic Achievement.

fulfillment of their basic needs within a particular context. In other words, when a student (i.e., a self) feels that the school fulfills her/his basic psychological needs well, she/he will be more likely to engage in school activities, in turn resulting in higher academic achievement. Using a sample of American secondary school students, Van Ryzin (2011) demonstrated that students’ perceptions of the school environment (i.e., feelings of autonomy, belongingness, and competence) were linked to self-reported engagement (i.e., behavioral and emotional) in learning, which, in turn was linked to changes in academic achievement. In a sample of eighth grade students in Korea, Jang et al. (2012) found that autonomy need satisfaction affected self-reported classroom engagement (i.e., behavioral, emotional, cognitive, and agentic), which in turn was related to academic achievement in a 3-wave longitudinal research design. On the other hand, it is also possible that academic achievement has indirect effects on BPNSS via behavioral engagement. Students’ high academic achievement serves as a positive feedback for children, which encourages them to engage more in school activities; in turn, the students with higher levels of engagement eliciting more positive feedback from teachers and classmates, which might means higher levels of BPNSS. Specifically, as mentioned before, students with higher academic achievement may be more likely to engage in school activities, because they have more positive emotions and higher self-efficacy toward learning due to previous success (Poorthuis et al., 2015). Furthermore, by engaging persistently, these students can demonstrate higher levels of interest in learning and academic self-regulation, which in turn may elicit more supportive behavior from teachers and more respect from classmates (Skinner & Belmont, 1993; Van Ryzin, 2011). In the Chinese culture, schools emphasize cultural values and norms that foster academic excellence, self-discipline, and social harmony (Bear et al., 2018). Students’ behavioral engagement likely reflects these cultural values and characteristics. Therefore, the influence of students’ behavioral engagement on their BPNSS would be stronger among Chinese students. Overall, given the reciprocal association of behavioral engagement with both BNPSS and academic achievement, it is plausible that behavioral engagement would work as a factor transferring the reciprocal process between BPNSS and academic achievement.

are more likely to show lower academic self-efficacy and higher learned helplessness in school (Diener & Dweck, 1978). These feeling are associated with lower persistence and effort. On the contrary, children with high academic achievement would likely be encouraged from the positively feedback of their performance, and thus be more likely to engage and persist in academic activities. Some longitudinal studies have demonstrated a positive association between academic achievement and subsequent teacher-reported behavioral engagement in an American sample of students assessed from first grade through third grade (Hughes et al., 2008), as well as a positive association between academic achievement and self-reported behavioral engagement in a sample of Dutch secondary school students (Poorthuis et al., 2015). According to the previous literature, we also expected that children’s academic achievement and behavioral engagement would facilitate each other reciprocally. Using cross-lagged designs, a few studies have directly investigated the possibility of reciprocal relations between behavioral engagement and academic achievement (e.g., Guo, Sun, Breit-Smith, Morrison, & Connor, 2015; Hughes et al., 2008); however, the results have been mixed. Hughes et al. (2008) found reciprocal relations between teacherreported behavioral engagement and academic achievement in an American sample of elementary school students. However, in a different sample of American elementary school students, Guo et al. (2015) found that academic achievement predicted later observed behavioral engagement, whereas observed behavioral engagement did not predict subsequent academic achievement. Thus, our study was intended to examine further the nature of the relations between behavioral engagement and academic achievement among elementary school students. 1.3. The indirect paths between BPNSS and academic achievement By combining the reciprocal relations among context (i.e., BPNSS), individuals’ actions (i.e., behavioral engagement), and outcomes (i.e., academic achievement) together, we could find some indirect paths in the model. For instance, students’ behavioral engagement might work as a factor transferring the reciprocal process between BPNSS and academic achievement. On the one hand, students’ BPNSS might have indirect effect on academic achievement via their behavioral engagement. According to self-system processes theory (Connell & Wellborn, 1991), the developing self is seen as an “active partner” in assessing how well the school is in fulfilling students’ basic needs; furthermore, it also posits that engagement (action) occurs when individuals obtain

1.4. The current study In order to more thoroughly understand the relations among BNPSS, behavioral engagement, and academic achievement, we employed a 132

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reciprocal effects model (see Fig. 1) to test the reciprocal relations and possible indirect paths among the three study variables in a sample of Chinese elementary school students. Based on the extant literature, we formulated two hypotheses: (1) BNPSS, behavioral engagement, and academic achievement will positively predict each other. Specifically, there will be positive reciprocal relations between BPNSS and academic achievement, behavioral engagement and academic achievement, and BPNSS and behavioral engagement. (2) BPNSS will have an indirect effect on academic achievement via behavioral engagement, and academic achievement will have an indirect effect on BPNSS via behavioral engagement. Specifically, there will be indirect paths of “BPNSS → behavioral engagement → academic achievement” and “academic achievement → behavioral engagement → BPNSS”.

2.2. Procedure The study was approved by the relevant school boards, principals, teachers, as well as the Human Research Committee of University. Consistent with institutional review board procedures in China, parental consent and student assent were both obtained before participation. The student-reported data (i.e., BPNSS, behavioral engagement, and demographic variables) were collected in the regular classroom environment by trained graduate assistants. Students were informed of the general nature of the study, told that they could refuse to participate at any time, and promised that their responses would be treated confidentially. The assistants provided additional explanations to the participants when necessary. No evidence was found to suggest that children in the samples had difficulties in understanding the measures or procedures. The teacher-reported data (i.e., academic achievement) were obtained from schools at the end of the semesters. A unique ID number for each student was created for data-matching purposes.

2. Method 2.1. Participants

2.3. Measures

Participants were recruited from two public elementary schools from a city in southern China. According to the information provided by the local education authorities, these two schools were similar in school characteristics, including the quality of students, school size, class size, and teachers’ teaching ability. Each school included eight classes for each grade. We randomly selected and invited five classes from Grade 3 and Grade 4 of each school. Four classes from Grade 3 and five classes from Grade 4 from each school agreed to participate. The initial student response rate was about 90%. The participants were surveyed semiannually on four occasions, completing self-report measures of BPNSS, behavioral engagement, and selected demographic questions. The assessments were conducted in the middle of four consecutive semesters to minimize students’ academic stress levels relative to the final examinations at the end of semesters. The academic achievement data were provided by the teachers at the end of the first three semesters and subsequently obtained from the schools. Therefore, there were seven occasions of data collection across four semesters. During Time 1 (T1), Time 3 (T3), Time 5 (T5), and Time 7 (T7), the BPNSS and behavioral engagement measures were administered to the students. During Time 2 (T2), Time 4 (T4), and Time 6 (T6), the academic achievement data were provided by the teachers and obtained from schools. At the baseline assessment (T1), 627 students (287 girls, 340 boys) from Grades 3–4 participated (Mage = 9.01, SD = 0.76, range from 8 to 11 years). Almost all of the participants were from middle-income families with parents who had earned at least a middle school degree. The percentages of participants providing date from T2 to T7 were 99.8%, 86.8%, 86.8%, 89.5%, 75%, 90.4%, respectively. Two possible reasons for attrition were: The students transferred to other schools, which accounted for about 15% of the missing data; the students were absent from school on the day of the assessment, which accounted for about 85% of the missing data. Differences in demographic variables and study variables were examined among students who provided data at all seven time points (Group 1), and students with missing data (Group 2). Compared to Group 2 students, Group 1 students showed significantly higher age levels, and higher scores on the measures of T1 behavioral engagement, T2 academic achievement, and T6 academic achievement. However, the effect sizes were low (η2s less than 0.02). Furthermore, no statistically significant differences between the groups emerged for gender or father’s and mother’s education or on any of the other major study variables. Little (1988) Missing Completely at Random test produced a normed chi-square (χ2/df) of 1.38, which indicated that the data were likely missing at random and that it was safe to impute missing values (Bollen, 1989). Therefore, full information maximum likelihood (FIML) estimation, which could make full use of available data and could generate unbiased parameter estimates (Peng, Harwell, Liou, & Ehman, 2006), was used to deal with the missing data.

2.3.1. Basic psychological needs satisfaction at school (BPNSS) Basic psychological needs satisfaction at school was measured on four occasions in the middle of the respective semester across 6-month time intervals at T1, T3, T5, and T7, with the Adolescent Students’ Basic Psychological Needs at School Scale (ASBPNSS; Tian, Han et al., 2014). The ASBPNSS has been shown to be suitable for elementary school students (Tian, Zhang, & Huebner, 2018). There are three subscales: The Autonomy subscale (e.g., “I can decide for myself how to do things at school.”) consisted of five items assessing students’ autonomy need satisfaction at school. The Relatedness subscale (e.g., “Teachers and classmates care about me at school.”) consisted of five items assessing students’ relatedness need satisfaction at school. The Competence subscale (e.g., “I am capable of learning new knowledge at school.”) consisted of five items assessing students’ competence need satisfaction at school. Response options reflected a six-point Likert scale ranging from 1 (strongly disagree) to 6 (strongly agree). The mean score was calculated, and higher scores reflected higher satisfaction of basic psychological needs in school. In this study, the Cronbach’s α coefficients were 0.85, 0.90, 0.94, 0.93 at T1, T3, T5, and T7, respectively. We also tested the longitudinal invariance of the BPNSS, and the model of the BPNSS showed scalar measurement equivalence over time, meeting the requirements for longitudinal analysis. More detailed information about longitudinal invariance is provided in the supplementary material. 2.3.2. Behavioral engagement Behavioral engagement was measured on four occasions in the middle of the respective semester across 6-month intervals at T1, T3, T5, and T7 using the Behavioral Engagement subscale of the School Engagement Questionnaire. The questionnaire was developed by Fredricks, Blumenfeld, Friedel, and Paris (2005) for middle childhood and revised among Chinese elementary school students by Liang (2011). Procedures of translation and back-translation were performed in Liang’s study to make sure that the items of Chinese version corresponded exactly to the items of original version. The Behavioral Engagement subscale (e.g., “I follow the rules at school.” “I pay attention in class.” “I complete my work on time.”) consisted of five items assessing students’ participation or involvement in school activities. Responses involved a four-point Likert scale ranging from 1 (strongly disagree) to 4 (strongly agree). The mean score was calculated, and higher scores reflected higher levels of behavioral engagement. In this study, the Cronbach’s α coefficients were 0.68, 0.68, 0.73, 0.74 at T1, T3, T5, and T7, respectively. In the longitudinal invariance analysis, the model of behavioral engagement showed metric measurement equivalence over time, thus meeting the requirements for longitudinal analysis. More detailed information about longitudinal invariance is provided in 133

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the supplementary material.

Kline, 2005).

2.3.3. Academic achievement Academic achievement was reported on three occasions across 6month intervals at T2, T4, and T6 by teachers at the end of the respective semester. Chinese, Math, and English are three major academic subjects taught in Chinese schools, and students’ performance on these three subjects are usually used to evaluate Chinese students’ academic achievement (Liu et al., 2017). Students’ performance in these three subjects were separately reported by their teachers of the corresponding subjects. Teachers were asked “how did the students perform in your subject this term?”. Responses involved 5 levels, ranging from 1 to 5 (1 = needs more effort, 2 = qualified, 3 = moderate, 4 = good, and 5 = excellent). In this context in the Chinese culture, “needs more effort” was a euphemistic expression for “not qualified”. The mean scores for students’ performances in the three subject areas were calculated, and higher score represented higher levels of academic achievement. In this study, the Cronbach’s α coefficients were 0.79, 0.79, 0.74 at T2, T4, and T6, respectively.

3. Results 3.1. Descriptive statistics and correlations for observed factors The means, standard deviations, and bivariate correlations for the observed factors are presented in Table 1. Both within and across waves, BPNSS, behavioral engagement, and academic achievement were significantly and positively associated with each other. The pattern of correlations was consistent with our expectations, providing initial support for the hypothesized cross-lagged model. 3.2. The longitudinal model The full model with all cross-lagged paths, auto-regressive paths, second-order auto-regressive paths, and concurrent covariances demonstrated an acceptable fit to the data, χ2 (28, N = 627) = 46.701, CFI = 0.991, TLI = 0.970, SRMR = 0.029, RMSEA = 0.033, a 90% RMSEA confidence interval [0.015, 0.049]. The standardized path coefficients are presented in Fig. 2. The paths from BPNSS at T1, T3, and T5 to behavioral engagement at T3, T5, and T7 were all statistically significant (β = 0.12, p < .01; β = 0.14, p < .001; β = 0.11, p < .05). The paths from behavioral engagement at T1, T3, and T5 to BPNSS at T3, T5, and T7 were all also statistically significant (β = 0.09, p < .05; β = 0.17, p < .001; β = 0.22, p < .001). Therefore, BPNSS and behavioral engagement promoted each other reciprocally. The paths from BPNSS at T1, T3, and T5 to academic achievement at T2, T4, and T 6 were all significant (β = 0.14, p < .001; β = 0.07, p < .01; β = 0.07, p < .05). The paths from academic achievement at T2 and T6 to BPNSS at T3 and T7 were significant (β = 0.14, p < .05; β = 0.15, p < .001). Overall, BPNSS and academic achievement enhanced each other reciprocally. The paths from behavioral engagement at T1 and T3 to academic achievement at T2 and T4 were statistically significant (β = 0.29, p < .001; β = 0.07, p < .05). The paths from academic achievement at T2, T4, and T6 to behavioral engagement at T3, T5, and T7 were all statistically significant (β = 0.24, p < .001; β = 0.10, p < .01; β = 0.10, p < .01). Overall, behavioral engagement and academic achievement related to each other reciprocally. Therefore, hypothesis 1 was supported. With regard to control variables, age was significantly, positively related to T6 academic achievement (β = 0.11, p < .01). Other paths were not statistically significant.

2.3.4. Covariates Several demographic covariates were reported by the students at T1, including (a) students’ gender (0 = female, 1 = male); (b) age; (c) (d) father’s and mother’s education level respectively. The education level was reported on a scale from 1 to 8 (1 = never attended school, 2 = elementary school, 3 = middle school, 4 = high school, 5 = junior college, 6 = bachelor’s degree, 7 = master’s degree, 8 = doctoral degree). Parental education was the most commonly used SES component (Sirin, 2005). Given that gender, age, and father’s and mother’s education levels have all been associated with academic achievement (Sirin, 2005; Voyer & Voyer, 2014), all of these variables were controlled in subsequent analyses. 2.4. Data analysis First, initial descriptive analyses and bivariate correlations among the observed variables were obtained in SPSS 23.0. Next, structural equation modeling (SEM), conducted in Mplus 7.4 (Muthén & Muthén, 2012), was used to analyze the reciprocal relations among BPNSS, behavioral engagement, and academic achievement. Auto-regressive paths, concurrent covariances, and cross-lagged paths were all incorporated in the model. Specifically, we constructed auto-regressive paths for BPNSS, behavioral engagement, and academic achievement, representing stability coefficients for each variable. We constructed concurrent associations between BPNSS and behavioral engagement, indicating associations within the same time point. We constructed cross-lagged paths among BPNSS, behavioral engagement, and academic achievement to examine their reciprocal relations. In addition, according to the modification indices, we added second-order auto-regressive paths (see Fig. 2). Gender, age, and father’s and mother’s education levels served as the control variables for every primary variable at every time point. To avoid confusion, the control variables are not shown in Figs. 1 and 2. Given that students were nested in classes, we corrected for the clustered data using the “cluster” option with “type = complex”, implemented in Mplus (Muthén & Muthén, 1998–2013). Third, the bias-corrected (BC) bootstrapping approach (N = 5000 bootstrap samples) was employed to examine the significance and strength of indirect paths (Asparouhov & Muthén, 2010). This approach does not require distributional assumptions (Miočević, O'Rourke, Mackinnon, & Brown, 2017), and estimates can be obtained with missing data (Yuan & Bentler, 2000). The model fit was considered acceptable when the χ2/df ratio was less than 5.0, the Comparative Fit Index (CFI) and the Tucker-Lewis Index (TLI) values were above 0.90, and when the Root Mean Square Error of Approximation (RMSEA) and the standardized root mean square residual (SRMR) values were below 0.08 (Hu & Bentler, 1999;

3.3. The indirect paths The bootstrap procedure was used to examine the indirect paths in the reciprocal relations between BPNSS and academic achievement. The results are presented in Table 2. The path from T1 BPNSS to T4 academic achievement via T3 behavioral engagement was significant (β = 0.008, BC 95% CI [0.001, 0.022]). The path from T3 BPNSS to T6 academic achievement via T5 behavioral engagement was not significant (β = 0.001, BC 95% CI [−0.006, 0.011]). The path from T2 academic achievement to T5 BPNSS via T3 behavioral engagement was significant (β = 0.042, BC 95% CI [0.022, 0.070]). The path from T4 academic achievement to T7 BPNSS via T5 behavioral engagement was significant (β = 0.022, BC 95% CI [0.006, 0.048]). Therefore, hypothesis 2 was supported. 4. Discussion Our study explored the prospective and reciprocal relations among BNPSS, behavioral engagement, and academic achievement among Chinese elementary school students. Previous studies on these variables have been mainly cross-sectional in nature, and they have focused mostly on the one-way relation from BNPSS or behavioral engagement 134

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Fig. 2. The standardized path coefficients for the cross-lagged model. Note. Only significant paths were shown. T = Time. BPNSS = Basic Psychological Needs Satisfaction at School, BE = Behavioral Engagement, AA = Academic Achievement. * p < .05, ** p < .01,*** p < .001. Table 1 Bivariate correlations and descriptive statistics among study variables. Variables 1. BPNSS (T1) 2. BE (T1) 3. AA (T2) 4. BPNSS (T3) 5. BE (T3) 6. AA (T4) 7. BPNSS (T5) 8. BE (T5) 9. AA (T6) 10. BPNSS (T7) 11. BE (T7) M SD

1

2

3

4

5

6

7

8

9

10

11

– 0.44*** 0.27*** 0.50*** 0.33*** 0.26*** 0.38*** 0.36*** 0.24*** 0.44*** 0.33*** 4.90 0.76

– 0.36*** 0.32*** 0.50*** 0.33*** 0.25*** 0.50*** 0.24*** 0.33*** 0.44*** 3.52 0.46

– 0.26*** 0.38*** 0.85*** 0.23*** 0.38*** 0.73*** 0.34*** 0.36*** 4.46 0.76

– 0.42*** 0.31*** 0.51*** 0.38*** 0.27*** 0.55*** 0.38*** 4.99 0.86

– 0.40*** 0.38*** 0.56*** 0.30*** 0.44*** 0.52*** 3.54 0.47

– 0.22*** 0.34*** 0.73*** 0.37*** 0.34*** 4.58 0.63

– 0.49*** 0.26*** 0.54*** 0.43*** 5.01 0.98

– 0.32*** 0.50*** 0.64*** 3.54 0.48

– 0.37*** 0.35*** 4.39 0.77

– 0.57*** 5.11 0.90

– 3.56 0.48

Note. T = Time. BPNSS = Basic Psychological Needs Satisfaction at School, BE = Behavioral Engagement, AA = Academic Achievement. *** p < .001.

previous research by emphasizing the direct and indirect bidirectional relations among BNPSS, behavioral engagement, and academic achievement. As predicted, our results demonstrated that BNPSS, behavioral engagement, and academic achievement reciprocally enhanced each other directly; furthermore, BPNSS displayed an indirect positive effect on academic achievement via behavioral engagement, and academic achievement also displayed an indirect positive effect on BPNSS via behavioral engagement.

Table 2 The standardized magnitude and statistical significance of indirect effects (N = 627). Effects

BPNSS(T1) → BE(T3) → AA(T4) BPNSS(T3) → BE(T5) → AA(T6) AA(T2) → BE(T3) → BPNSS(T5) AA(T4) → BE(T5) → BPNSS(T7)

Product of Coefficients

Bootstrapping 95% BC Confidence Interval

Point Estimate

SE

Lower

Upper

0.008 0.001 0.042 0.022

0.005 0.004 0.012 0.010

0.001 −0.006 0.022 0.006

0.022 0.011 0.070 0.048

4.1. Basic psychological needs satisfaction at school and academic achievement As expected, BPNSS predicted later academic achievement. Higher fulfillment of basic psychological needs at school was related to higher academic achievement. Our findings were consistent with prior studies demonstrating that basic psychological needs satisfaction was positively linked with students’ academic performance (e.g., Badri et al., 2014; Marshik, 2010; Ratelle & Duchesne, 2014). The connection between needs satisfaction and academic achievement may be explained when considering the organismic approaches to motivation and selfdetermination theory together (Deci & Ryan, 2000; Niemiec & Ryan, 2009). First, the organismic approaches to motivation suggest that

Note. BC Confidence Interval: Bias corrected confidence interval. If the 95% bias corrected confidence interval did not contain zero, point estimates of effects were considered significant. T = Time. BPNSS = Basic Psychological Needs Satisfaction at School, BE = Behavioral Engagement, AA = Academic Achievement.

to academic achievement. Little research has tested the consequences of individual differences in academic achievement. By combining selfsystem processes theory and transactional theory, we expanded on 135

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human beings have innate characteristics that make them ready to involve themselves in their physical and social environments. Based on these characteristics, individuals are innately active and creative (Niemiec & Ryan, 2009). Furthermore, self-determination theory suggests that the fulfillment of the basic needs can protect and stimulate these innate characteristics. Therefore, basic psychological needs satisfaction is necessary for optimal functioning, including high academic achievement (Deci & Ryan, 2000). Our study expanded previous literature by focusing on basic needs satisfaction in the school setting and verifying the relation between BPNSS and academic achievement in the children as young as elementary school age. Meanwhile, overall, academic achievement also positively predicted later BPNSS, for two of the three paths from academic achievement to BPNSS were statistically significant. Basic psychological needs satisfaction has usually been investigated as an antecedent of academic achievement (e.g., Hughes et al., 2008; Van Ryzin, 2011), with little research attention paid to the reversed path. However, our result demonstrated that BPNSS could be affected by students’ academic achievement. Multiple possible reasons might account for this relation. First, student-teacher and student-classmates interactions might be influenced by children’s academic achievement. Low achieving students are less likely to be preferred by teachers (Heatly & Votruba-Drzal, 2017), they also have fewer chances to be assigned as assistants by their teachers in school activities. In addition, these students are also less likely to be preferred and respected by classmates (Košir & Tement, 2014; Véronneau et al., 2010). Therefore, it will be more difficult for them to obtain basic needs satisfaction under such conditions. Second, students’ perceptions of the environment are determined not only by the social context but also by their “self” (Skinner et al., 2008). Low achieving students may not be sufficiently confident; therefore, even when facing the same conditions, they will be less likely to perceive that they are loved or respected by others. Thus, they will feel less satisfied in terms of their basic psychological needs. Finally, the impact of academic achievement on BPNSS might be exaggerated in the Chinese culture. Grounded in Confucian values that emphasize self-perfection, Chinese students, teachers, and parents strongly commit to education traditionally (Bear et al., 2018). This tendency seems to be even stronger currently, given the increasing competition for high quality education resources, such as adequate infrastructures and excellent teachers. Therefore, the effect of academic achievement on BPNSS is likely to be amplified in present day China.

secondary school students (Poorthuis et al., 2015). For example, Hughes et al. found that when children successfully master academic tasks, they felt encouraged and engaged more in school activities. To the contrary, when children experienced difficulties with their academic tasks, they would feel frustrated and helpless, and they were less likely to engage in school activities (Hughes et al., 2008). Regarding the issue of reciprocal relations between behavioral engagement and academic achievement, our study contributed to the extant literature by providing additional support for a model reflecting reciprocal relations between the two variables. Specifically, using a time interval of one year, Hughes et al. (2008) found reciprocal relations between teacher-reported behavioral engagement and academic achievement among American elementary school students. Students’ levels of behavioral engagement in first grade predicted their academic achievement in second grade, which in turn predicted their behavioral engagement in third grade. Furthermore, students’ academic achievement in first grade predicted their behavioral engagement in second grade, which in turn predicted their academic achievement in third grade. However, using a time interval of two year, Guo et al. (2015) did not observe reciprocal relations between observed behavioral engagement and academic achievement among American elementary school students. They found that students’ reading achievement in preschool predicted their behavioral engagement in first grade, and reading achievement in third grade predicted their behavioral engagement in fifth grade. However, students’ behavioral engagement did not significantly predict later reading achievement. The inconsistent findings obtained from the two studies might be attributed to the differing time lags (Guo et al., 2015). To detect cross-lagged associations, the time interval should be long enough for behavioral engagement to influence academic achievement, but not so long that the effects wear off (Taris, 2000). Perhaps our findings were comparable to those of Hughes et al., albeit not those of Guo et al., because the time interval for our study was more similar to that of the former study. Such findings would support the notion of reciprocal relations between behavioral engagement and academic achievement among elementary school students, at least within certain time frames. 4.3. The indirect paths between BPNSS and academic achievement Our results revealed that the indirect paths from BPNSS to academic achievement via behavioral engagement were significant. This result was consistent with similar studies in adolescents (Jang et al., 2012; Van Ryzin, 2011). According to the self-system processes theory, fulfillment of basic psychological needs within a particular context, such as school, should facilitate corresponding levels of engagement (Elmore, 2006; Skinner et al., 2008). Specifically, students with a greater sense of autonomy satisfaction at school would show increased behavioral engagement, because they have more opportunities to practice their decision-making skills and regulate their behavior (Wang, 2010). Students with a stronger sense of relatedness would also be more likely to engage in activities in school because they feel more connected to school peers and professionals, increasing their willingness to engage in school activities (Marshik, 2010). Furthermore, students with a greater sense of competence would show more effort in school activities, because they experience greater self-efficacy, making them more likely to persist in completing school activities (Skinner et al., 2008). In general, BPNSS should work as a motivational factor that enhances individuals’ behavioral engagement in school (Talley, Kocum, Schlegel, Molix, & Bettencourt, 2012). In turn, the enhanced behavioral engagement would promote higher academic achievement. When students show higher levels of engagement behaviors, such as concentrating on learning, asking and answering questions, and being prepared for class, students can in turn perform better on academic tasks (Wang, 2010). However, it should be noted that although two indirect paths of “BPNSS → behavioral engagement → academic achievement” were tested, only one path was statistically significant,

4.2. Behavioral engagement and academic achievement Our results showed that two of the three paths from behavioral engagement to academic achievement were statistically significant, providing partial support for our hypotheses. These connections may be explained by self-system processes theory, which has been supported in several studies of elementary school students (e.g., Guo et al., 2011; Ladd & Dinella, 2009; Reyes et al., 2012). For example, Guo et al. (2011) revealed that classroom quality positively predicted third-grade students’ teacher-reported behavioral engagement, which in turn predicted greater reading achievement. Furthermore, Ladd and Dinella (2009) investigated 383 American children who were followed from ages 5.5 to 13.5 and demonstrated changes as well as continuity in early school engagement (i.e., teacher-reported behavioral engagement and emotional engagement) were predictive of children’s long-term scholastic growth. By engaging in school activities, adhering to school rules, and concentrating on learning, students not only learn more knowledge points in classroom, but they also develop greater intellectual skills, resulting in greater academic progress (Jang et al., 2012; Janosz, 2012; Wang, 2010). Therefore, students displaying higher engagement achieve better academic outcomes. We also found that higher academic achievement predicted subsequent higher behavioral engagement. This result was consistent with some longitudinal studies of elementary (e.g., Hughes et al., 2008) and 136

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suggesting the need for further research. The indirect paths from academic achievement to BPNSS via behavioral engagement were also significant. Consistent with our expectations, students with higher academic achievement were more likely to report higher behavioral engagement, which in turn was associated with higher BPNSS. When children perform well on academic tasks, they obtain positive feedback, facilitating greater engagement in school activities (Akbari, Pilot, & Simons, 2015). Consequently, more highly engaged students elicit more supportive responses from teachers (Jang et al., 2012; Van Ryzin, 2011). They might also be provided more opportunities by their teachers to interact with teachers or classmates in the school activities because they are thought to be more likely to cooperate. In these interactions, their needs of autonomy, relatedness, and competence could be satisfied. The indirect paths from academic achievement to BPNSS via behavioral engagement are somewhat consistent with person-environment fit theory (Gilbreath, Kim, & Nichols, 2011). Person-environment fit theory posits that individual’s adjustment (e.g., well-being and performance) is a function of the interaction between people and their environments, and congruence between personal characteristics (e.g., knowledge, abilities, needs) and environmental characteristics (e.g., values) promotes adjustment (Jiang & Jiang, 2015). Our results revealed that the fit was good from another perspective because the fit between the students’ characteristics (i.e., academic achievement and behavioral engagement) and the relevant macrosystem (i.e., cultural values) could result in better support at the microsystem level (i.e., psychological needs satisfaction at school) (Bronfenbrenner, 1979). Moreover, this indirect path suggested that Chinese elementary school students can initiate actions to meet their own psychological needs, substantiating the idea that students can become the architects of their own psychological needs satisfaction. In Chinese culture, which is a collectivism culture, the “self” is regarded as malleable to some extent through personal effort and social influence if the person is willing and actually undertakes efforts to self-improve (Li, 2012). Our results suggested that such self-improving behavior (e.g., increasing behavioral engagement) is valuable in the Chinese school culture, because it appears to help students to experience a better psychological environment in school (i.e., greater needs satisfaction). However, because individualistic cultures promote more of a fixed view of the “self” and emphasize less on the need for the person to adapt to their environments (Li, 2012), the path from academic achievement to BPNSS via behavioral engagement needs to be examined and interpreted in Western countries. In addition, the indirect reciprocal relations between BPNSS and academic achievement observed in our study revealed that a complete understanding of Chinese students’ academic success and feeling in school requires equal attention to the school climate (in terms of facilitating basic need satisfaction in students) and the individual students (in terms of their behavioral engagement or academic achievement). Thus, the development and implementation of instructional practices that aim to promote student’s adjustment by disproportionately emphasizing one or the other components of the system (i.e., the individual or the environment) are less likely to be successful compared to more comprehensive practices that incorporate attention to both components. As the Chinese nation, including its schools, transitions from a more collectivistic culture toward a more individualistic one (Tamis-LeMonda et al., 2008), our results suggest that greater attention to students’ psychological needs through supportive school climates will likely enhance students’ academic success. However, our findings also suggest that Chinese students will benefit from retaining key, traditional collectivistic features of schools (e.g., focus on continuous student self-improvement, strong social norms for high levels of learning and effort) that also support students’ experience in school. We should note that there are other possible indirect paths, for example “behavioral engagement → BPNSS → academic achievement” or “academic achievement → BPNSS → behavioral engagement”.

Indeed, the reciprocal relations among the three variables could incorporate several possible indirect paths. Furthermore, the model also demonstrated self-enhancing loops, such as “BPNSS → behavioral engagement → BPNSS” and “academic achievement → BPNSS → academic achievement”. These additional, possible indirect and self-enhancing pathways could provide a broader perspective on the interrelations among these variables, highlighting additional dynamic systems properties. Overall, our study extended the boundaries of the extant literature in four major ways. First, we addressed needs satisfaction from a context-specific perspective (i.e., needs satisfaction in school), which should yield more specific implications for improving students’ perceptions, actions, and outcomes in school. Second, we evaluated the relations between BPNSS and academic achievement among elementary school students, which could suggest interventions to enhance students’ school experience and academic performance in this foundational period. Third, we considered not only the influence of BPNSS and behavioral engagement on academic achievement, but also the reversed paths, which illuminated systemic interactions among BPNSS, behavioral engagement, and academic achievement. Finally, we examined the role of behavioral engagement in the indirect reciprocal relations between BPNSS and academic achievement, revealing a key malleable, psychological mechanism contributing to the relations between BPNSS and academic achievement, in students as young as elementary school age. 4.4. Strengths, limitations, and future research Our study displayed major strengths. One major strength was its longitudinal design. The longitudinal design enabled us to obtain data from multiple time points and to control for prior levels of the variables. This design also enabled us to examine reciprocal relations, which not only delineated the comprehensive dynamic processes but also increased the validity of the results. Finally, our study used multiple sources of information and employed a relatively large, heterogeneous sample, both of which enhanced the credibility of our results. Our study also displayed some limitations that should be addressed in future research. First, despite the fact that academic achievement was assessed and reported by teachers, which decreased common method bias, the remaining measures (i.e., BPNSS and behavioral engagement) were self-reported. Given that BPNSS refers to subjective experiences of the school environment, students seem to be the best source for this information (Skinner et al., 2008). For behavioral engagement, researchers have suggested that students were able to assess their engagement behaviors (Fredricks et al., 2005). However, future research employing multi-informant measures would still be helpful to improve confidence in the measurements, especially for behavioral engagement. Second, we focused on overall basic needs satisfaction in school in our study. Because the roles of the three basic needs satisfactions might differ in terms of the strengths of their associations with behavioral engagement and academic achievement (Zhen et al., 2017), studies which differentiate among the three needs should be considered in future research. Third, despite the autoregressive controls, it should be kept in mind that the findings were still observational results. More replications, especially experimental studies, are needed to verify the relations found in this study. Fourth, although we incorporated multiple covariates, other covariates that might influence our target variables should be considered, such as differences in intelligence and parenting practices (Wang, Deng, & Du, 2018). Fifth, we conducted our study with Chinese elementary school students. Thus, the generalizability of the results should be interpreted with caution. Future studies with other age groups and cultures should be beneficial. 4.5. Implications Although replications and extensions of our study are necessary, the elements in the theoretical framework (i.e., perceived environment, 137

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behavior/action, outcomes) and their observed reciprocal relations inform educational practices. To improve children’s academic achievement (i.e., the outcome element), instructors should not only pay substantial attention to the students’ behavior (e.g., engagement), but they should also pay attention to students’ perceptions of the school context (e.g., BPNSS). Because all of these factors are malleable, multiple points of intervention seem plausible to facilitate optimal achievement. First, the facilitating roles of BPNSS in behavioral engagement and academic achievement implied that efforts to improve children’s BPNSS would be helpful for enhancing students’ behavioral engagement and academic success. Given that teachers are the first “significant others” in students’ school lives, teachers could use multiple strategies to satisfy students’ psychological needs in the school setting. For example, for autonomy needs, teachers should consider the perspectives of the children and offer more opportunities for making choices in school. For relatedness needs, teachers should express especially frequent positive feelings toward the children and provide many opportunities for bonding with teachers and classmates. For competence needs, teachers should carefully offer different tasks to students according to their abilities and provide informal feedback and assistance as necessary to ensure success (Bear et al., 2018; Duchesne et al., 2016). Second, focusing on behavioral engagement, which demonstrated reciprocal relations with BPNSS and academic achievement and also played an important role in the reciprocal indirect associations between BPNSS and academic achievement, teachers should encourage students to engage effectively in school activities by explaining the rationale for strong engagement and making the activities interesting and suitable for children (Bear et al., 2018). Third, given that academic achievement influenced BPNSS and behavioral engagement, teachers should pay more attention to academically struggling children, for these children are most at risk for disengaging from school. Teachers should provide struggling children with more diverse and effective leaning strategies as necessary, which might increase their academic outcomes. Finally, guided by the complete, integrative model, school psychologists and other educational professionals should aim to continuously monitor and address students’ BPNSS, behavioral engagement, and academic achievement in a coordinated, comprehensive fashion to be most effective. The reciprocal processes and indirect paths suggest that the effects of such comprehensive instructional programs should amplify outcomes across time.

Philosophy and Social Science Development in Guangzhou, 2018 (No. 2018GZGJ22). This work was also supported by the Postgraduate Research and Innovation Fund from School of Psychology South China Normal University. Acknowledgements We are grateful to those who participated in data collection and data processing. Appendix A. Supplementary material Supplementary data to this article can be found online at https:// doi.org/10.1016/j.cedpsych.2019.01.003. References Akbari, E., Pilot, A., & Simons, P. R. J. (2015). Autonomy, competence, and relatedness in foreign language learning through Facebook. Computers in Human Behavior, 48, 126–134. https://doi.org/10.1016/j.chb.2015.01.036. Archambault, I., Janosz, M., Morizot, J., & Pagani, L. (2009). Adolescent behavioral, affective, and cognitive engagement in school: Relationship to dropout. Journal of School Health, 79, 408–415. https://doi.org/10.1111/j.1746-1561.2009.00428.x. Asparouhov, T., & Muthén, B. (2010). 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5. Conclusion Based on self-system processes theory and transactional theory, our study added to the extant literature related to the associations among BPNSS, behavioral engagement, and academic achievement among elementary school students. In particular, after controlling for gender, age, fathers’ and mothers’ education, concurrent covariances, and autoregression paths, we found that BPNSS, behavioral engagement, and academic achievement reciprocally enhanced each other. In addition, BPNSS indirectly facilitated academic achievement via behavioral engagement, and academic achievement indirectly facilitated academic achievement via behavioral engagement. These findings suggest that BPNSS, behavioral engagement, and academic achievement form a complex, dynamic system, which operates in students as early as elementary school. Funding This work was supported by Humanities Social Sciences Research Planning Foundation from Ministry of Education, 2015 (No. 15YJA190003), “12th Five-Year” Plan of Philosophy and Social Science Development in Guangdong Province, 2015 (No. GDCXL01), the MOE Project of Key Research Institute of Humanities and Social Sciences at Universities, 2016 (No. 16JJD190002), and “13th Five-Year” Plan of 138

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