## 3 Review Results
### Note on the Methodologies Applied in the Studies
#### 3.9.1 Research Design  
**Cross-sectional Research Design:**Many studies have adopted a cross-sectional research design, which involves collecting data at a single time point from a sample representing the population. This design enables researchers to analyze the relationships between variables and understand the factors influencing the adoption of ChatGPT among students and educators. By examining the data collected in this manner, researchers can identify trends, correlations, and potential causal links between various factors, such as perceived usefulness, ease of use, trust, and cost, and their impact on the adoption of ChatGPT [2, 19, 22, 24]. One of the key benefits of a cross-sectional research design is its efficiency and simplicity. Cross-sectional studies are typically quicker and more straightforward than longitudinal studies. Since the data are collected at a single point in time, it reduces the time and resources required for data collection. Additionally, this design provides a snapshot of the current state of adoption and usage patterns of ChatGPT among students and educators. It helps in terms of understanding the prevailing attitudes, behaviors, and factors influencing adoption at a specific time. Furthermore, cross-sectional studies effectively identify and analyze the relationships between different variables. Researchers can explore how various factors like perceived usefulness, enjoyment, and cost interact and influence the adoption of ChatGPT. The design's versatility enables it to be applied to diverse populations and settings, making it suitable for studying different user groups and contexts. However, there are also notable disadvantages associated with cross-sectional research designs. One significant limitation is the inability to establish causality. While cross-sectional studies can identify correlations between variables, they cannot determine whether one variable directly influences another or if underlying factors are at play. Additionally, since the data are collected at a single point in time, cross-sectional studies do not account for changes over time. They cannot track how attitudes, behaviors, or external factors influencing adoption may evolve, limiting the understanding of long-term trends and impacts. In summary, while a cross-sectional research design offers efficiency, simplicity, and valuable insights into the current trends and relationships between variables, it also has limitations in establishing causality and understanding the changes over time. These benefits and disadvantages highlight the importance of carefully considering the research design when studying the adoption of ChatGPT among students and educators. **Quantitative Research Approach:**  
Many studies have utilized a quantitative research approach, employing structured surveys to collect numerical data that can be statistically analyzed [4, 5, 27]. This approach is effective in identifying patterns, testing hypotheses, and making generalizations regarding the adoption of ChatGPT in higher education. Using quantitative methods, researchers can systematically measure variables and quantify the relationships between them, providing robust and objective insights into the factors influencing the adoption of ChatGPT. One of the primary benefits of a quantitative research approach is its ability to identify patterns and trends across large samples. By collecting data from a wide range of participants, researchers can discern commonalities and variations in how different groups perceive and use ChatGPT. This method is also highly effective for testing hypotheses. Researchers can formulate specific testable predictions pertaining to the factors influencing ChatGPT adoption and use statistical techniques to determine whether the data support these hypotheses. Furthermore, the quantitative approach enables generalizations about the broader population.