Dataset of Vietnamese students' intention in respect of study abroad before and during COVID-19 pandemic Authors Hiep-Hung Pham1, Quang-Anh Phan2, Anh-Duc Hoang3, Yen-Chi Nguyen3, Ngoc-Thuy Ta3, Viet-Hung Dinh4 Affiliations 1. Phu Xuan University, Hue 49000, Vietnam 2. PostDoc at Department of Social Anthropology and Cultural Studies, University of Zurich 3. EdLab Asia Educational Research and Development Centre, Hanoi 100000, Vietnam 4. University of Labour and Social Affairs, Hanoi 100000, Vietnam Corresponding author(s) Hiep-Hung Pham (phamhunghiep@pxu.edu.vn) Abstract The Covid-19 Pandemic had completely disrupted the worldwide educational system. Many schools chose the online delivery mode for students in case learning losses incurred during social distance decree. However, as to these students who are currently in the study abroad planning stages, reached an intention crossroads, whether standing for certain unchanging decisions in study abroad destinations or changing swiftly due to the unexpected policies in quarantine. This case opened to interpretation, which was based on our e-survey since 3 May to 13 May 2020 with 397 responses covering a range of Vietnamese students. In this dataset, we focused on (i) Students' Demographics; (ii) The previous intention of students to study abroad before and during the Covid19 ravaged and (iii) Their intention afterwards. Keywords Education; Education system; Study abroad; COVID-19; Vietnam Specifications Table Subject Education, Education Management Specific subject area Study abroad Type of data Raw data in excel file, and analysed data How data were acquired Data was gathered using an online survey and converted into the .xlsx format for formal analysis in SPSS v.20. Data format Raw Analyzed Parameters for data collection This research focuses on Vietnamese students (high school level and tertiary level) who are going to plan for study abroad. Description of data collection An online survey has been delivered to random students throughout some groups related to study abroad on Facebook. From the connection within group members, the survey drew 410 responses. Data source location Information is collected from student in Vietnam (Latitude 16°0'N, Longitude 106°0'E) Data accessibility Repository name: Mendeley Data Data identification number: Direct URL to data: https://data.mendeley.com/datasets/7gpkx5p3z9/1 Value of the Data  The data acquisition makes a special contribution towards research in the field of study abroad in the worldwide pandemic context.  The dataset can be used for additional analysis of students' intention to choose study abroad destinations due to the policy responses within the Covid-19.  The dataset can be applied to build models related to investigate the situational factors behind students' intention to study abroad.  The dataset conveys a message to policymakers in the education sector in respect of exporting and importing study abroad.  The significant change in the study abroad decision of students before and during Covid19 partly contributes to overall educational models from the pandemic's damage. 1. Data Description For years, study abroad brings about many benefits for students, such as personal growth, intercultural development, education and career attainment, and so on [1]. In addition, it is also a crucial source of income for the host colleges, universities and the host government [2, 3]. In Vietnam, education is considered more of an imported service than an exported one [4], and this trend of study abroad has become more popular recently. From the year 2010 to 2019, Vietnam climbed from the ninth to the sixth place among countries with most students studying in the United States [5]. Moreover, the number of Vietnamese students studying in other countries also increased sharply, reached top 5 in Canada, top 4 in Australia, and top 2 in Japan in 2018 [6]. Since the expansion of the Coronavirus, countries around the world have taken many measures to avoid outsiders, in particular imposing travel restrictions, locking down airports, and closing borders [7]. Many teachers, including local as well as expat teachers, met so many problems. Students were suddenly acquainted with online learning. In this particular dataset we portrayed the decisions and factors related to Vietnamese students' study abroad before and after the COVID19. It is an extension to our recent studies related to students' learning habit during the COVID19 [10]. The dataset includes three main parts: (i) Demographic of the partakers; (ii) Factors that influence students' decision to study abroad before COVID-19; and (iii) Factors that influence students' decision to study abroad after COVID-19. The full version of the survey, variable codes and measurements can be found on Mendeley data [11]. From this dataset, researchers can study trends among Vietnamese students as well as various factors that affect students' decision of study abroad, ranging from finance, culture, to communication related. Table 1. Descriptive statistics of participant's demographics Frequency Percent Valid Percent Cumulative Percent Gender Male 188 47.4 47.4 47.4 Female 209 52.6 52.6 100.0 Major Natural science, Engineering, Technology 85 21.4 21.4 21.4 Social science, Humanities, Art, Economics, Management, Business 214 53.9 53.9 75.3 Other 98 24.7 24.7 100.0 Cur_Location Hanoi 144 36.3 36.3 36.3 Ho Chi Minh 128 32.2 32.2 68.5 Other 125 31.5 31.5 100.0 Prior_Plan Asia 42 10.6 10.6 10.6 Europe 53 13.4 13.4 23.9 America 43 10.8 10.8 34.8 Oceania 20 5.0 5.0 39.8 Other 239 60.2 60.2 100.0 Prior_Fin Full scholarship 235 59.2 59.2 59.2 Self-finance 162 40.8 40.8 100.0 Prior_program High school 15 3.8 3.8 3.8 Bachelor 177 44.6 44.6 48.4 Master 185 46.6 46.6 95.0 Doctor 14 3.5 3.5 98.5 Other 6 1.5 1.5 100.0 Post_Plan Asia 20 5.0 5.0 5.0 Europe 15 3.8 3.8 8.8 America 9 2.3 2.3 11.1 Oceania 12 3.0 3.0 14.1 Other 57 14.4 14.4 28.5 Same country as Prior_Plan 284 71.5 71.5 100.0 Total 397 100.0 100.0 Table 2. Descriptive statistics of various factors influencing study abroad decision N Mean S.D Statistic Std. Error Prior_living 397 3.34 .028 .566 Prior_travel 397 2.46 .035 .690 Prior_language 397 3.25 .035 .695 Prior_quality 397 3.67 .027 .536 Prior_degree 397 3.41 .032 .632 Prior_IntlStu 397 2.73 .040 .804 Prior_VnStu 397 2.33 .038 .755 Prior_tuition 397 3.52 .034 .684 Prior_scholarship 397 3.68 .029 .583 Prior_livingcost 397 3.54 .031 .617 Prior_parttimejob 397 3.20 .037 .739 Prior_job 397 3.55 .033 .655 Prior_immigration 397 2.78 .044 .881 Prior_shortcut 397 2.58 .042 .845 Prior_distance 397 2.12 .041 .823 Prior_HE_repu 397 2.94 .038 .748 Prior_school_repu 397 3.19 .032 .642 Prior_diversity 397 3.03 .037 .738 Prior_facilities 397 3.29 .030 .596 Prior_stay 397 3.17 .030 .601 Prior_safe 397 3.48 .030 .601 Prior_med 397 3.19 .035 .695 Prior_climate 397 2.75 .037 .733 Prior_partner 397 1.89 .041 .817 Prior_hybrid 397 2.74 .040 .807 Cur_living 397 3.45 .030 .595 Cur_travel 397 2.33 .041 .817 Cur_language 397 3.19 .037 .729 Cur_quality 397 3.55 .030 .607 Cur_degree 397 3.36 .034 .685 Cur_IntlStu 397 2.73 .042 .830 Cur_VnStu 397 2.44 .043 .853 Cur_tuition 397 3.53 .032 .645 Cur_scholarship 397 3.66 .030 .602 Cur_livingcost 397 3.54 .032 .629 Cur_parttimejob 397 3.20 .039 .783 Cur_job 397 3.46 .036 .712 Cur_immigration 397 2.77 .047 .931 Cur_shortcut 397 2.68 .044 .869 Cur_distance 397 2.31 .046 .912 Cur_HE_repu 397 3.04 .038 .754 Cur_school_repu 397 3.23 .033 .667 Cur_diversity 397 3.08 .036 .712 Cur_facilities 397 3.31 .030 .606 Cur_stay 397 3.27 .031 .619 Cur_safe 397 3.52 .031 .626 Cur_med 397 3.39 .034 .671 Cur_climate 397 2.88 .041 .824 Cur_partner 397 1.84 .041 .823 Cur_hybrid 397 3.01 .040 .799 Table 3. Paired samples statistics Mean N Std. Deviation Std. Error Mean Pair 1 Prior_living 3.34 397 .566 .028 Cur_living 3.45 397 .595 .030 Pair 2 Prior_travel 2.46 397 .690 .035 Cur_travel 2.33 397 .817 .041 Pair 3 Prior_language 3.25 397 .695 .035 Cur_language 3.19 397 .729 .037 Pair 4 Prior_quality 3.67 397 .536 .027 Cur_quality 3.55 397 .607 .030 Pair 5 Prior_degree 3.41 397 .632 .032 Cur_degree 3.36 397 .685 .034 Pair 6 Prior_IntlStu 2.73 397 .804 .040 Cur_IntlStu 2.73 397 .830 .042 Pair 7 Prior_VnStu 2.33 397 .755 .038 Cur_VnStu 2.44 397 .853 .043 Pair 8 Prior_tuition 3.52 397 .684 .034 Cur_tuition 3.53 397 .645 .032 Pair 9 Prior_scholarship 3.68 397 .583 .029 Cur_scholarship 3.66 397 .602 .030 Pair 10 Prior_livingcost 3.54 397 .617 .031 Cur_livingcost 3.54 397 .629 .032 Pair 11 Prior_parttimejob 3.20 397 .739 .037 Cur_parttimejob 3.20 397 .783 .039 Pair 12 Prior_job 3.55 397 .655 .033 Cur_job 3.46 397 .712 .036 Pair 13 Prior_immigration 2.78 397 .881 .044 Cur_immigration 2.77 397 .931 .047 Pair 14 Prior_shortcut 2.58 397 .845 .042 Cur_shortcut 2.68 397 .869 .044 Pair 15 Prior_distance 2.12 397 .823 .041 Cur_distance 2.31 397 .912 .046 Pair 16 Prior_HE_repu 2.94 397 .748 .038 Cur_HE_repu 3.04 397 .754 .038 Pair 17 Prior_school_repu 3.19 397 .642 .032 Cur_school_repu 3.23 397 .667 .033 Pair 18 Prior_diversity 3.03 397 .738 .037 Cur_diversity 3.08 397 .712 .036 Pair 19 Prior_facilities 3.29 397 .596 .030 Cur_facilities 3.31 397 .606 .030 Pair 20 Prior_stay 3.17 397 .601 .030 Cur_stay 3.27 397 .619 .031 Pair 21 Prior_safe 3.48 397 .601 .030 Cur_safe 3.52 397 .626 .031 Pair 22 Prior_med 3.19 397 .695 .035 Cur_med 3.39 397 .671 .034 Pair 23 Prior_climate 2.75 397 .733 .037 Cur_climate 2.88 397 .824 .041 Pair 24 Prior_partner 1.89 397 .817 .041 Cur_partner 1.84 397 .823 .041 Pair 25 Prior_hybrid 2.74 397 .807 .040 Cur_hybrid 3.01 397 .799 .040 Table 4. Paired samples correlations N Correlation Sig. Pair 1 Prior_living & Cur_living 397 .557 .000 Pair 2 Prior_travel & Cur_travel 397 .667 .000 Pair 3 Prior_language & Cur_language 397 .734 .000 Pair 4 Prior_quality & Cur_quality 397 .586 .000 Pair 5 Prior_degree & Cur_degree 397 .665 .000 Pair 6 Prior_IntlStu & Cur_IntlStu 397 .634 .000 Pair 7 Prior_VnStu & Cur_VnStu 397 .596 .000 Pair 8 Prior_tuition & Cur_tuition 397 .636 .000 Pair 9 Prior_scholarship & Cur_scholarship 397 .681 .000 Pair 10 Prior_livingcost & Cur_livingcost 397 .649 .000 Pair 11 Prior_parttimejob & Cur_parttimejob 397 .716 .000 Pair 12 Prior_job & Cur_job 397 .648 .000 Pair 13 Prior_immigration & Cur_immigration 397 .726 .000 Pair 14 Prior_shortcut & Cur_shortcut 397 .648 .000 Pair 15 Prior_distance & Cur_distance 397 .606 .000 Pair 16 Prior_HE_repu & Cur_HE_repu 397 .640 .000 Pair 17 Prior_school_repu & Cur_school_repu 397 .640 .000 Pair 18 Prior_diversity & Cur_diversity 397 .664 .000 Pair 19 Prior_facilities & Cur_facilities 397 .588 .000 Pair 20 Prior_stay & Cur_stay 397 .552 .000 Pair 21 Prior_safe & Cur_safe 397 .563 .000 Pair 22 Prior_med & Cur_med 397 .522 .000 Pair 23 Prior_climate & Cur_climate 397 .654 .000 Pair 24 Prior_partner & Cur_partner 397 .722 .000 Pair 25 Prior_hybrid & Cur_hybrid 397 .543 .000 Table 5. Paired samples test Paired Differences t df Sig. (2tailed) Mean S.D S.E Mean 95% Confidence Interval of the Difference Lower Upper Pair 1 Prior_living Cur_living

-.015 .568 .029 -.071 .041 -.530 396 .597 Pair 9 Prior_scholarship Cur_scholarship

.023 .474 .024 -.024 .069 .954 396 .341 Pair 10 Prior_livingcost Cur_livingcost

.000 .522 .026 -.052 .052 .000 396 1.000 Pair 11 Prior_parttimejob Cur_parttimejob

-.264 .767 .039 -.340 -.189 6.867 396 .000 2. Experimental Design, Materials, and Methods The research group collected data with snowball and convenience sampling methods. The survey was published on the biggest Facebook groups of current and potential Vietnamese overseas students (Scholarship hunter) and then was spread wider by those group members. From 03 May 2020 to 13 May May 2020, a total of 410 responses was collected. After cleaning the dataset, 13 invalid observations were cleared, we finally analyzed the dataset of 397 observations. Since shorter scales are "quick to use" [12], the research group used a four-point Linkert scale to reach a specific respondent opinion and avoid "neutral" responses as well. Table 1 shows descriptive statistics about participants' demographics including gender, major, current location, financial source, and study program. Table 2 shows descriptive information regarding influence factors of study abroad decision before the COVID-19 (Prior-) and during the pandemic (Cur-). Those 25 factors are classified into six categories according to Lee's model of decision-making process of studying abroad [13]. This model is the integration of three-phase synthesis model [14] and push-pull model [15]. Lee's model [11] originally includes seven dimensions: (i) Personal improvement (Prior_personal, Cur_personal), (ii) Knowledge and awareness of the host country (Prior_knowledge, Cur_knowledge), (iii) Recommendation from others, (iv) Physical and learning environment (Prior_learning, Cur_learning), (v) Cost issues (Prior_cost, Cur_cost), (vi) Social links and geographic proximity (Prior_social, Cur_social), and (vii) Institution image (Prior_institution, Cur_institution). However, in order to adapt better to Vietnam context, researchers dropped dimension (iii) as well as omitted and modified some factors within other dimensions. Table 3, 4 and 5 illustrates results of t-test between influence factors before and during the COVID-19. Moreover, the dataset includes destination countries where students plan to go to, which can be divided into five categories: Asia, Europe, America, Oceania and Other [16]. As a consequence, future researchers can study on the crucial factors that determine destination choice of overseas students, and whether those factors play different roles before and during the pandemic: Prior_Plan ~ β0 + β1* (Prior_personal) + β2*(Prior_knowledge) + β3*(Prior_learning) + β4*(Prior_cost) + β5*(Prior_social) + β6*(Prior_institution) + u Cur_Plan ~ β0 + β1* (Cur_personal) + β2*(Cur_knowledge) + β3*(Cur_learning) + β4*(Cur_cost) + β5*(Cur_social) + β6*(Cur_institution) + u In addition, the change in decision to study abroad (AFFECT) was showed by question number 8 (from 8.1 to 8.5), thus future study can use multinomial logistic regression to find the relationship between various factors (before and during the COVID-19) and change in the decision to study abroad as the following model: AFFECT ~ β0 + β1* (Prior_personal) + β2*(Prior_knowledge) + β3*(Prior_learning) + β4*(Prior_cost) + β5*(Prior_social) + β6*(Prior_institution) + u Acknowledgments We would like to thank all students who helped us to finish this study, as well as admins of various Facebook communities, teachers and school leaders, who contributed to elevating the data collection process. This research is funded by Vietnam's National Foundation for Science and Technology Development (NAFOSTED) under the project 502.02-2019.22 Competing Interests The authors declare that they have no known competing financial interests or personal relationships which have, or could be perceived to have, influenced the work reported in this article. References [1] Dwyer, M. M., & Peters, C. K. (2004). The benefits of study abroad. Transitions abroad, 37(5), 56-58. [2] Altbach, P. G., & Knight, J. (2007). The internationalization of higher education: Motivations and realities. Journal of studies in international education, 11(3-4), 290-305. [3] Healey, N. M. (2008). Is higher education in really 'internationalising'? Higher Education, 55, 333-355. [4] Pham, H. H., Lai, S. L., & Vuong, Q. H. (2019). The Role of Subjective Task Value in Forming Satisfaction and Loyalty Among Vietnamese International Students: A Structural Equation Model. 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