| Literature DB >> 36017423 |
Liu Li1, Baijun Wu2, Ataul Karim Patwary3.
Abstract
COVID-19 has affected every aspect of our life, including economic, social, and academic. Exchange and mobility students face more difficulties overseas, and Chinese students are no exception. However, e-learning has been introduced by institutions in many countries. The present study examines the psychosocial factors affecting the academic performance of Chinese outbound exchange and mobility students during the COVID-19 pandemic. The study surveys about 186 Chinese outbound exchange and mobility students. The present study performs the quantitative data analysis using Partial Least Square Structural Equation Modeling (PLS-SEM) through the Smart PLS software version 3. By confirming the measurement model and structural model assessments, the study finds that personality, social support, and language fluency are psychosocial factors that significantly influence the exchange and mobility students' academic performance. This study contributes by establishing relationships among psychosocial factors, language fluency and academic performance. Besides, practitioners can be benefitted by understanding students' psychosocial factors and its relation to academic performance during COVID-19 pandemic.Entities:
Keywords: COVID-19; exchange and mobility students; language fluency; personality; psychosocial factors; social support
Year: 2022 PMID: 36017423 PMCID: PMC9397364 DOI: 10.3389/fpsyg.2022.872516
Source DB: PubMed Journal: Front Psychol ISSN: 1664-1078
FIGURE 1Research framework.
Questionnaire items.
| Variables | Items | |
| Personality | 1 | I find it very easy to use train timetables, even if this involves several connections |
| 2 | I find myself categorizing people into types (in my own mind). | |
| 3 | I like to collect a lot of different examples about something that I like, so I can see how they differ from each other | |
| 4 | I like to know the functions of committee members and how committees are structured. | |
| 5 | If I have a collection of circular date stamp, coins, other stamps, it would be highly organized. | |
| 6 | I am curious about the precise way buildings are constructed. | |
| 7 | I give directions for someone seeking to ask the way to any part of my hometown. | |
| 8 | I enjoy looking through catalogs of products to see the details of each product in terms of similarities and differences. | |
| Language Fluency | I like to know exactly which grammar point I am studying | |
| I believe my grammar will improve quickly if I communicate using English | ||
| I find it easier to learn grammar when the instructor teaches it by himself or herself. | ||
| I prefer lessons that focus on communication and grammar | ||
| I like learning grammar through its explanations and practice exercises | ||
| Social Support | 1 | I have a special person around me whenever in need. |
| 2 | I share my joys and sorrows with a special person. | |
| 3 | My family really tries to help me | |
| 4 | I get emotional help and support from my family | |
| 5 | I have a special person who is a real source of comfort to me | |
| 6 | My friends really try to help me | |
| 7 | I have friends with whom I can share my joys and sorrows | |
| 8 | I can count on my friends when things go wrong | |
| Academic Performance | 1 | I enjoy my academic lesson |
| 2 | The way the lecturer speaks is important in understanding the lecture | |
| 3 | Lectures help me to identify my strengths and weaknesses | |
| 4 | The faculty has provided me with specific advice on how to improve my academic performance | |
| 5 | Lectures promote active reflection on the effectiveness of teaching | |
| 6 | The lectures encourage feedback that enhance learning | |
| 7 | Exam without marks prevents motivation for students cheating | |
| 8 | The time of the lectures are appropriate | |
| 9 | The pace (speed) of delivery of the teaching is reasonable. |
Demographic profile of the respondents.
| Respondents’ information | Frequency | Percentage |
|
| ||
| Male | 116 | 62.4 |
| Female | 70 | 37.6 |
| Total | 186 | 100 |
|
| ||
| Single | 158 | 84.9 |
| Married | 26 | 14.0 |
| Divorced/widowed | 2 | 1.1 |
| Total | 186 | 100 |
|
| ||
| 17–19 years old | 43 | 23.1 |
| 20–22 years old | 82 | 44.1 |
| 23–25 years old | 29 | 15.6 |
| 26–28 years old | 13 | 7.0 |
| 29 years old and above | 19 | 10.2 |
| Total | 186 | 100 |
|
| ||
| Semester 1–2 | 83 | 44.6 |
| Semester 3–4 | 9 | 4.8 |
| Semester 5–6 | 61 | 32.8 |
| Semester 7–8 | 33 | 17.7 |
|
| ||
| Undergraduate | 135 | 72.6 |
| Masters | 38 | 20.4 |
| PhD | 13 | 7 |
| Total | 186 | 100 |
Construct validity and reliability.
| Variables | Cronbach’s alpha | Composite reliability | Average variance extracted (AVE) |
| Academic performance | 0.930 | 0.942 | 0.643 |
| Language fluency | 0.836 | 0.890 | 0.627 |
| Personality | 0.933 | 0.943 | 0.675 |
| Social support | 0.886 | 0.909 | 0.564 |
FIGURE 2Measurement model.
Heterotrait-Monotrait Ratio (HTMT).
| Variables | 1 | 2 | 3 | 4 |
| 1. Academic performance | – | |||
| 2. Language fluency | 0.338 | |||
| 3. Personality | 0.196 | 0.156 | ||
| 4. Social support | 0.157 | 0.190 | 0.086 | – |
Variance inflation factor (VIF).
| Construct | Items | VIF |
| Academic performance | Academic 1 | 3.320 |
| Academic 2 | 2.829 | |
| Academic 3 | 2.242 | |
| Academic 4 | 2.753 | |
| Academic 5 | 2.607 | |
| Academic 6 | 2.245 | |
| Academic 7 | 3.088 | |
| Academic 8 | 2.620 | |
| Academic 9 | 1.950 | |
| Language fluency | Language 1 | 1.100 |
| Language 2 | 2.440 | |
| Language 3 | 3.241 | |
| Language 4 | 3.407 | |
| Language 5 | 3.490 | |
| Personality | Personality 1 | 5.112 |
| Personality 2 | 4.634 | |
| Personality 3 | 3.268 | |
| Personality 4 | 4.116 | |
| Personality 5 | 4.252 | |
| Personality 6 | 2.322 | |
| Personality 7 | 3.073 | |
| Personality 8 | 4.595 | |
| Social support | S. Support 1 | 2.806 |
| S. Support 2 | 2.916 | |
| S. Support 3 | 2.617 | |
| S. Support 4 | 2.449 | |
| S. Support 5 | 2.526 | |
| S. Support 6 | 1.893 | |
| S. Support 7 | 1.976 | |
| S. Support 8 | 1.208 |
Direct effects of the antecedent variables of students’ academic performance.
| Relationships | Path | Standard deviation | ||
| Language fluency → academic performance | 0.273 | 0.050 | 5.517 | 0.000 |
| Personality → academic performance | 0.153 | 0.053 | 2.907 | 0.004 |
| Social support → academic performance | –0.098 | 0.041 | 2.414 | 0.016 |
FIGURE 3Structural model.
Model fitness summary.
| Saturated model | Estimated model | |
| SRMR | 0.059 | 0.059 |
| d_ULS | 1.602 | 1.602 |
| d_G | 0.874 | 0.874 |
| Chi-square | 1625.213 | 1625.213 |
| NFI | 0.792 | 0.792 |