| Literature DB >> 35756262 |
Cheng Zhang1, Lizhi Mao1, Nanshu Li1, Xiaoye Gu2.
Abstract
Regarding the constructive function of students' academic engagement in learning a foreign language, understanding the individuals' intrapersonal characteristics effective on engagement has gained attention. To keep up with this line of research, the present study tried to probe the contribution of grit and social-emotional competence to Chinese EFL learners' academic engagement. To do this, 493 Chinese EFL students, including both males and females, were selected conveniently to participate in the study. For collecting data, a Likert scale questionnaire entailing three items on grit, social-emotional competence, and academic engagement was administered online. Spearman Rho correlation index and multiple regression analysis along with ANOVA were employed to analyze data. The findings revealed a positive and direct relationship between Chines EFL students' grit, social-emotional competence, and academic engagement. Furthermore, the results showed that compared to social-emotional competence, EFL students' grit can predict more powerfully academic engagement. The implications of the findings are considered in the present study.Entities:
Keywords: Chinese EFL students; academic engagement; grit; psychology; social-emotional competence
Year: 2022 PMID: 35756262 PMCID: PMC9231457 DOI: 10.3389/fpsyg.2022.914759
Source DB: PubMed Journal: Front Psychol ISSN: 1664-1078
Participants’ demographic information.
| Demographic information category |
|
|
|
| ||
| Male | 229 | 46.45 |
| Female | 264 | 53.55 |
| Total | 493 | 100 |
|
| ||
| Bachelor of arts | 431 | 87.42 |
| Master of arts | 52 | 10.55 |
| Ph.D. | 10 | 2.02 |
| Total | 493 | 100 |
|
| ||
| Elementary | 117 | 23.73 |
| Intermediate | 229 | 46.45 |
| Upper-intermediate | 112 | 22.71 |
| Advanced | 35 | 7.09 |
| Total | 493 | 100 |
Questionnaires’ reliability.
| Questionnaire | Cronbach’s alpha | |
| SEC | 0.93 | 25 |
| Grit | 0.70 | 8 |
| SAE | 0.92 | 19 |
Test of normality for SEC, grit, and SAE.
| Kolmogorov-Smirnov | Shapiro-Wilk | |||||
| Statistic | df | Sig. | Statistic | df | Sig. | |
| SEC | 0.042 | 493 | 0.034 | 0.978 | 493 | 0.000 |
| Grit | 0.094 | 493 | 0.000 | 0.962 | 493 | 0.000 |
| SAE | 0.076 | 493 | 0.000 | 0.976 | 493 | 0.000 |
Correlation among SEC, grit, and SAE.
| SEC | Grit | SAE | |||
| Spearman’s | SEC | Correlation coefficient | 1.000 | 0.528 | 0.502 |
| Sig. (two-tailed) | 0.000 | 0.000 | |||
|
| 493 | 493 | 493 | ||
| Grit | Correlation coefficient | 0.528 | 1.000 | 0.504 | |
| Sig. (two-tailed) | 0.000 | 0.000 | |||
|
| 493 | 493 | 493 | ||
| SAE | Correlation coefficient | 0.502 | 0.504 | 1.000 | |
| Sig. (two-tailed) | 0.000 | 0.000 | |||
|
| 493 | 493 | 493 | ||
** Correlation is meaningful at the 0.01 level (two-tailed).
Descriptive statistics for SEC, grit, and SAE.
| Variables |
| SD |
|
| SAE | 67.52 | 9.55 | 493 |
| SEC | 101.24 | 18.28 | 493 |
| Grit | 29.47 | 5.71 | 493 |
Model summary for SEC, grit, and SAE.
| Model |
| Adjusted R square | Std. error of the estimate | |
| 1 | 0.601 | 0.362 | 0.359 | 7.65 |
ANOVA for SEC, grit, and SAE.
| Model | Sum of squares | df | Mean square |
| Sig. | |
| 1 | Regression | 16264.776 | 2 | 8132.388 | 138.85 | 0.000 |
| Residual | 28698.206 | 490 | 58.568 | |||
| Total | 44962.982 | 492 | ||||
Coefficients for SEC, grit, and SAE.
| Model | Unstandardized coefficients | Standardized coefficients |
| Sig. | ||
| B | Std. error | Beta | ||||
| 1 | (Constant) | 33.382 | 2.08 | 15.99 | 0.000 | |
| SEC | 0.167 | 0.024 | 0.320 | 6.99 | 0.000 | |
| Grit | 0.583 | 0.077 | 0.349 | 7.62 | 0.000 | |