Investigating the Relationships between Problem-Solving Ability, Resilience and Academic Burnout in Virtual Medical Education Students Using Structural Equation Modeling

IF 0.7 Q3 EDUCATION & EDUCATIONAL RESEARCH Psikhologicheskaya Nauka i Obrazovanie-Psychological Science and Education Pub Date : 2023-11-03 DOI:10.17759/pse.2023280408
Z. Khoshgoftar, F. Karamali, M.Z. Nasrabadi, M.H. Nejad
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Abstract

the purpose of the present study is to investigate the relationship between academic resilience and academic burnout through the mediation of problem-solving ability.Research questionnaires (demographics, academic burnout, academic resilience and problem-solving ability) were sent online through Press Online software in 2021 for a sample size of 260 students of virtual medical education. Descriptive statistics, Pearson correlation and Structural equation modeling were used to examine the characteristics of the participants, correlation between main variable and test the study hypothesis. Based on the results the model fit indices CFI (comparative fit index), NFI (normed fit index), TLI (Tuckere Lewis index), X2/DF (the ratio of X2 to degrees of freedom) and RMSEA (Root mean of square error approximation) were appropriate. it was found that the academic burnout with problem solving skill (&beta; = -0.77), academic resilience (&beta; = 0.26) and problem-solving skill with academic Resilience (&beta; = 0.96) has a statistically significant relationship. Also, it was found that most of the relationship between academic burnout and academic resilience is indirect and through the mediator variable of problem-solving skills (-0.871).The results of this research determined that there is a certain group of students suffering from burnout and weak problem-solving skills, who are at risk. Screen such students and provide them with short courses aimed at developing adaptive coping skills, such as problem solving, which can prevent their academic burnout.

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运用结构方程模型研究虚拟医学教育学生解决问题能力、心理弹性与学业倦怠的关系
本研究旨在通过问题解决能力的中介,探讨学业弹性与学业倦怠之间的关系。研究问卷(人口统计、学业倦怠、学业弹性和问题解决能力)于2021年通过Press online软件在线发送,样本量为260名虚拟医学教育学生。采用描述性统计、Pearson相关和结构方程模型对研究对象的特征、主要变量之间的相关性和研究假设进行检验。结果表明,模型拟合指标CFI(比较拟合指数)、NFI(归一化拟合指数)、TLI (Tuckere Lewis指数)、X2/DF (X2与自由度之比)和RMSEA(均方根误差近似)是合适的。研究发现,学业倦怠与问题解决能力(β= -0.77),学业韧性(β= 0.26)、问题解决能力与学业弹性(β= 0.96)有统计学意义。此外,我们还发现学业倦怠与学业弹性之间的关系大部分是间接的,并通过问题解决能力这一中介变量(-0.871)。这项研究的结果表明,有一群学生患有倦怠和解决问题的能力较弱,他们处于危险之中。筛选这样的学生,并为他们提供旨在培养适应性应对技能的短期课程,例如解决问题的能力,这可以防止他们的学业倦怠。
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来源期刊
CiteScore
1.80
自引率
37.50%
发文量
31
审稿时长
12 weeks
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