Research in education involves the systematic investigation of teaching methods, learning behaviors, and educational systems. Its goal is to improve educational outcomes by identifying what works in the classroom and informing policies and practices. By using methods like surveys, experiments, and case studies, researchers can gather data to support better decision-making in education.
Traditional research is primarily focused on generating new knowledge or testing a hypothesis. One key aspect is that the researcher is an outsider who doesn't directly involve themselves with the participants to ensure that they do not influence the results.
Systematic with experiments, surveys and conducted in controlled environments
Aims to be able to produce the results in other environments.
Example: A university study on the psychological effects of social media across diverse populations.
Defining the Research Question
Conducting a literature review
Designing the research study
Collecting, analyzing, and interpreting data
Action research is more about problem-solving, specifically in the real-world setting. In this type of research, the researcher is not an outsider but an active participant. Collaboration is a key feature since the research and participants are working together to get immediate feedback and immediately implement changes to address specific issues. This research is typically done in real-world settings like teachers.
Example: A teacher working with students to improve classroom engagement through collaborative interventions.
Plan - Develop an action to guide the research process.
Acting - Collect and organize research data
Developing - Develop an action plan
Reflecting - Could the problem be solved by the research done?
Gather and analyze information using number and data. This type of research focuses on measuring things.
Example from my Research: This would be when I asked the students to rate their math skills from 1-5 and average math grade. This helped me measure the relationship between self-efficacy and academic performance.
Instead of focusing on numbers, this focuses more on understanding people's thoughts, feelings, and experiences.
Example from my Research: This would be the open-ended questions I asked in the survey to help me gather more detailed information about their learning behaviors. This helped me see how they handle challenges and difficult scenarios.
This type of research combines both quantitative and qualitative. This allows the researcher to have a complete understanding of their study not only does this allow for measurable data but it also provides a deeper understanding of those results. Researchers here aren't only focused on "how many" but also "why"
Example from my Research: By combining both quantitative and qualitative data, I used a mixed-methods approach to get a comprehensive view. The scaled questions provided measurable data, while the open-ended responses helped me explore personal experiences with math confidence and anxiety.
This research investigates the relationship between self-efficacy and student performance in mathematics courses, examining factors like math anxiety, pattern recognition, and past experiences that influence self-efficacy.
Key Findings:
•Self-efficacy, defined as belief in one’s ability to succeed in specific tasks (Bandura, 1977), is a critical factor in motivation and achievement.
•Lower self-efficacy correlates with poorer performance in mathematics (Núñez-Peña et al., 2013).
Methodology:
A Google Form survey collected quantitative data from 11 participants, including current and graduate CSUSB students. Questions focused on attitudes toward math, self-assessment of skills, and past performance.
Future Research:
Need for larger, more diverse samples and explore how self-efficacy changes during a course and its connection to final grades.
Through conducting this research on self-efficacy in math, I gained valuable insight into how both quantitative and qualitative methods work and can help provide a fuller picture of student experiences. The survey data gave me clear, measurable results on how confidence impacts math performance, while the open-ended responses revealed deeper insights into students’ struggles with math anxiety. Using a mixed-methods approach strengthened my findings, showing me the importance of combining data types to understand learning challenges more comprehensively.
This experience has enhanced my ability to apply research methods effectively in future projects.