The reviewed studies employed a range of sampling techniques, with non-probability methods being frequently
utilized. Convenience sampling was evident in several studies (Rao et al., 2023; Gupta, 2017; Gupta, 2017;
Sushila, 2022), where participants were selected based on their accessibility and willingness to participate.
Purposive sampling was also common (Jayaraman & Jambunathan, 2017; Little J., L., 2014; Rafee, 2019; Verma,
2021), allowing 22 researchers to select participants based on specific criteria relevant to their research
objectives. Simple random sampling was reported in at least one study (Sumetha et al., 2024), aiming for a more
representative sample. However, several studies did not explicitly detail their sampling techniques (Trivedi et
al., 2024; McKenzie, 2009; Jain, 2017; Kumar, 2019; Meghwal, 2021), making it challenging to assess the
generalizability of their findings. The primary method of data collection across the reviewed literature was the
use of questionnaires (Rao et al., 2023; Prashad et al., 2023; Gupta, 2017; McKenzie, 2009; Little J., L., 2014;
Jain, 2017; Gupta, 2017; Kumar, 2019; Rafee, 2019; Verma, 2021; Sushila, 2022). These questionnaires typically
included structured items designed to assess financial knowledge, attitudes, and behaviors. In some instances,
interviews were used as a supplementary data collection method, either alongside questionnaires (Jayaraman &
Jambunathan, 2017; May s., m., 2023) to provide richer qualitative data or as the primary method in qualitative
research (May s., m., 2023). One study utilized a structured interview schedule (Trivedi et al., 2024), suggesting
a more standardized approach to direct questioning. Additionally, some studies incorporated secondary data from
various publications (Rao et al., 2023; Gupta, 2017; Rafee, 2019; Sushila, 2022) to provide context or
supplementary information. The analysis of collected data in the reviewed studies involved a range of statistical
and qualitative techniques. Inferential statistical techniques such as t-tests and Analysis of Variance (ANOVA)
were employed to compare means across different groups (Prashad et al., 2023; McKenzie, 2009; Verma, 2021)
and to examine the statistical significance of observed differences. Correlation analysis (Jayaraman &
Jambunathan, 2017; Kumar, 2019) was used to explore the relationships between different financial literacy
variables and other factors. More advanced statistical techniques like Factor Analysis (Kumar, 2019; Rafee,
2019; Sushila, 2022) were utilized to identify underlying dimensions of financial literacy, and Structural
Equation Modelling (SEM) (Trivedi et al., 2024; Sushila, 2022) was employed to examine complex relationships
and test theoretical models. In qualitative research, data analysis involved a comprehensive assessment of
interview transcripts to identify recurring themes, perceptions, and lived experiences (May s., m., 2023).
Research gap
The existing body of literature on financial literacy in India reveals a growing interest in understanding the
financial knowledge, attitudes, and behaviors across various demographic groups. Studies have explored
financial literacy among university students (Trivedi et al., 2024; McKenzie, 2009; Jain, 2017; Gupta, 2017;
Rafee, 2019; Meghwal, 2021), working adults (Sushila, 2022), and even specific populations like agricultural
university students (Trivedi et al., 2024) and women in Vadodara (Sumetha et al., 2024). Research has also
investigated the influence of socio-demographic factors (Gupta, 2017; Kumar, 2019; Sushila, 2022) and the
potential for educational interventions (Verma, 2021). However, a noticeable gap exists in the focused
examination of financial literacy specifically among higher secondary school students within the urban context
of Vadodara city. While Prashad et al. (2023) explored financial literacy among high school students in Pune,
and Sumetha et al. (2024) studied financial awareness among women in Vadodara (which may include some
students), there is a lack of dedicated research that delves into the status of financial literacy, its influencing
factors, and potential implications for this crucial age group transitioning towards higher education and financial
independence within the specific socio-economic environment of Vadodara. Therefore, a study focusing on the
Status of Financial Literacy among Higher Secondary Students of Vadodara City would address this gap by
providing valuable insights into the financial literacy levels, attitudes, and behaviours of this specific student
population in this particular urban setting. After reviewing all the studies, researcher identifies the lack of
research of financial literacy among higher secondary students so the researcher interested to conduct this study.
Research question
Which are the major components in which higher secondary student faced difficulty of financial literacy?