Independent, Dependent, Control and Confounding Variables

• A variable is any characteristic, number, or quantity that can be measured or quantified and can change or vary across different conditions or participants in a study.

Independent vs Dependent Variables

• Independent variables are manipulated or controlled by the researcher to observe their effect on other variables
• The type of fertilizer used on plants is an example of an independent variable
• Dependent variables are the outcomes or effects that are measured in an experiment
• The growth of plants measured in height or biomass is an example of a dependent variable

Control Variables

• Control variables are essential because they ensure that the results of an experiment are due to the manipulation of the independent variable only
• When researchers keep control variables constant, they can isolate the effect of the independent variable on the dependent variable, thereby establishing a clear cause-and-effect relationship

Confounding Variables

• Controlling confounding variables prevents them from influencing the dependent variable, which can lead to incorrect conclusions
• Uncontrolled variables can introduce bias and variability in the data
• When bias and variability are introduced, it becomes difficult to determine whether the observed effects are due to the independent variable or some other factor

Plant Growth Experiment: Control Variables

• Light exposure: Ensures all plants receive the same amount of light, which affects growth.
• Watering schedule: Ensures all plants receive the same amount of water, preventing discrepancies in growth due to hydration differences.
• Soil type: Ensures all plants grow in the same soil conditions, eliminating soil quality as a variable affecting growth outcomes.

Evaluation vs Conclusion

• Evaluation: The process of systematically assessing the design, implementation, and outcomes of an activity or program to determine its effectiveness and impact.
• Conclusion: A judgment or decision reached by reasoning, summarizing the findings of an evaluation or research study based on the analyzed data.
• Evaluation involves assessing and analyzing data to determine the effectiveness or impact of an activity or program
• Conclusion is the final judgment or decision based on the results of the evaluation
• Evaluation provides the evidence and rationale
• Conclusion provides the final interpretative summary
• Evaluation involves setting criteria, collecting and analyzing data, and assessing outcomes to determine the value or success of a program or activity
• The purpose of evaluation is to inform decision-making by providing evidence of what works and what doesn't
• Examples of evaluation include evaluating the effectiveness of a new educational curriculum, assessing the impact of a public health intervention, or determining the success of a business strategy
• Distinguishing between evaluation and conclusion ensures clarity in communication, allowing stakeholders to understand both the detailed findings and the overarching implications

Formative Evaluation Plan Steps

• Define objectives by identifying the goals of the educational program
• Develop evaluation criteria by establishing what success looks like in terms of student performance
• Collect baseline data by gathering initial data on student performance before the program starts
• Implement the program by beginning the educational intervention
• Monitor progress by collecting data on student performance regularly during the program
• Analyze data by comparing ongoing data to baseline data to assess progress
• Provide feedback by offering continuous feedback to educators and students for improvement
• Data collected includes student test scores, attendance records, classroom observations, student and teacher feedback

Formative vs Summative Evaluation

• Formative Evaluation:
  • Objective: Improve and refine a program or activity while it is being developed or implemented
  • Methodology: Ongoing data collection, continuous feedback, qualitative and quantitative data, often informal and flexible
• Summative Evaluation:
  • Objective: Assess the overall effectiveness and impact of a program or activity after it has been completed
  • Methodology: Final data collection, comprehensive analysis, primarily quantitative data, structured and formal
• Key Differences:
  • Timing: Formative evaluation occurs during the program; summative evaluation occurs after completion
  • Purpose: Formative aims to improve ongoing processes; summative aims to judge final outcomes
  • Data Use: Formative uses data for immediate feedback; summative uses data for final decision-making and reporting