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III. Research methods and sampling
The study employed a comprehensive mixed-methods approach, combining quantitative
and qualitative research methodologies, to gain a holistic understanding of green finance
education within Vietnamese universities. The primary objective was to assess the
current state of green finance education, identify gaps and challenges, and explore
opportunities for enhancement.
The quantitative portion of the research was conducted through a structured survey
administered to a diverse group of university students and educators in Vietnam. The
survey aimed to gauge the level of awareness, understanding, and interest in green
finance among the respondents. The questionnaire covered various aspects, including
familiarity with green finance concepts, perceived importance of green finance
education, and the current inclusion of green finance topics in university curricula.
A stratified random sampling technique was utilized to select participants, ensuring
representation across different universities, disciplines, and levels of study. The sample
size was determined based on the total population of students and faculty members in
the targeted universities. In total, the survey garnered responses from more over 300
students and 15 educators from three different universities in Hanoi, Vietnam. A
purposive sampling method was used to select interview and focus group participants,
ensuring a comprehensive range of perspectives. Interviews were conducted with 15
educators known for their expertise or interest in green finance.
The qualitative research component consisted of semi-structured interviews and focus
group discussions with key stakeholders, including educators, students, industry experts,
and policymakers involved in green finance. These discussions aimed to delve deeper
into the qualitative aspects of green finance education, exploring participants'
experiences, perceptions, and suggestions for improvement.
Qualitative data from interviews and focus groups were transcribed and analyzed using
thematic analysis. This involved coding the data into categories and identifying recurring
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