Mixed Methods Research Questions
The key differences between mixed methods research and predictive research are as follows:
1. Approach: Mixed methods research combines both qualitative and quantitative methods to gather and analyze data, whereas predictive research primarily relies on quantitative methods to predict outcomes based on statistical analysis.
2. Purpose: Mixed methods research aims to provide a comprehensive understanding of a research problem by exploring both the depth and breadth of the topic. On the other hand, predictive research focuses on forecasting or predicting future outcomes based on existing data patterns.
3. Data collection: Mixed methods research involves collecting data through various techniques such as interviews, surveys, observations, and document analysis. In contrast, predictive research primarily relies on collecting quantitative data through surveys, experiments, or secondary data sources.
4. Analysis: Mixed methods research involves analyzing qualitative data through thematic analysis, content analysis, or discourse analysis, and quantitative data through statistical analysis. Predictive research primarily focuses on statistical analysis to identify patterns, correlations, and make predictions.
5. Integration: Mixed methods research emphasizes the integration of qualitative and quantitative data to provide a more comprehensive understanding of the research problem. In contrast, predictive research primarily focuses on quantitative data analysis and does not necessarily integrate qualitative data.
6. Timeframe: Mixed methods research often requires a longer timeframe as it involves collecting and analyzing data from multiple sources and using different methods. Predictive research can be conducted relatively quickly as it primarily relies on analyzing existing quantitative data.
Overall, mixed methods research and predictive research differ in their approach, purpose, data collection, analysis techniques, integration of data, and timeframe.