Assessing the validity

• Validity

  • Checks if what's being measured matches what's happening.

  
  

  Validity of a study depends on whether it accurately measures the actual improvements in student learning.

  
  

  Example: A thermometer showing different temperatures for the same thing is not valid. A questionnaire leading to the same diagnosis is likely valid, indicating accurate measurement of symptoms.

  
  

  Not just about consistency; it's about ensuring we're measuring what we intend to measure. Careful planning and validation are necessary for designing test
• Internal Validity


  Internal validity means how much we can trust the results of a study when it says one thing causes another. Simply put, it's about being sure that the results come from what we changed in the experiment, not from something outside the experiment.
• Strong internal validity


  To find out if something you did (a treatment) caused a change, you need to compare it to a group that didn’t get the treatment (a control group). If both groups are the same in every other way, then any differences in results must be because of the treatment.

  
  

  Randomization: Putting people into groups randomly to make sure each group is similar and to avoid picking biased groups.

  
  

  Blinding: Keeping people in the dark about who's getting what treatment to prevent bias in how data is collected and understood.
• Weak internal validity 


  Confounding variables: Hidden factors that affect both the thing we're changing and the thing we're watching, making it seem like one causes the other.

  
  

  Selection bias: Not picking participants randomly, so the groups are already different in ways that matter for the result.
• External validity


  External validity in research is about whether the findings of a study can apply to other places or groups of people.
• Strong external validity


  Representative samples: The people in the study should be similar to the group you want to apply the findings to. For example, if you're studying how a new fertilizer works on corn, you'd want to use a sample that represents typical corn-growing conditions.

  
  

  Realistic settings: Doing research in places that are like real life helps make sure the results will work in those real situations. For instance, if a new teaching method is only tested in a lab with short lessons, it might not work the same way in full-day classrooms.
• Ecological validity


  Ecological validity is about how much a research study matches real life. Basically, it's about if what the study finds can be used in everyday situations.
• Strong ecological validity


  Good for understanding how things work in real life.

  
  

  Helps researchers say more confidently how people act in everyday situations.

  
  

  Example: Instead of testing a new anxiety pill in a boring lab, they test it in a situation where someone has to speak in public, like a real-life scenario.
• Reliability 


  Reliability in research refers to the trustworthiness of measurements or findings over time, ensuring accuracy, consistency, and reproducibility of results.

  
  

  • It's important to plan research carefully to avoid mistakes or differences in results.

  
  

  • Making clear decisions during interviews or observations is vital to get reliable answers every time.

  
  

  • Keeping research conditions the same is really important to make sure the results are dependable and to control outside influences.