Role of Internal validity in research
Role of Internal validity in research
Tiffany Bowen posted Dec 1, 2021, 2:20 PM
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The need to validate any research study comes down to what the research tries to establish in its own right (Boateng et al., 2018). Validity means that the research results end up being accurately interpreted after parameters have been confirmed.
Internal validity in research helps establish a causality relationship between a cause and its outcome (Boateng et al., 2018). This means that lacking internal validity causes outcomes deviating from the truth in research.
Having a high internal validity means that the research outcomes can be trusted since a causal link between variables can be established.
Mr. Drew taught may have experiences distractions that would have significantly reduced their ability to retrieve information from long-term memory if they had done exams when a construction event was underway just outside their classroom (Held et al., 2018).
This is because the mind gets confused as it tries to process the external events and retrieve the target information needed.
John’s students may have cheated, but there is no proof to credit or discredit that theory, but if they cheated, it could explain their higher marks than Drew’s students.
Looking closely at John’s claim, there is bias in his claims as the exam set may have been different from the one he gave out. Also, the student’s level of understanding may have been different with brighter students in John’s camp.
To establish high external validity in college, the research can apply to other students and be replicated by other researchers. The benefits of conducting lab experiments are that variables are closely monitored, relatively easier to replicate, and cheaper (Boateng et al., 2018).
If John used this information, his publications on his teaching strategies would be inaccurate as this work finds his argument a flop based on the study’s findings.
References
Boateng, G. O., Neilands, T. B., Frongillo, E. A., Melgar-Quiñonez, H. R., & Young, S. L. (2018). Best practices for developing and validating scales for health, social, and behavioral research: a primer. Frontiers in public health, 6, 149.
Held, L., Destree, M., Philipps, N., Heinemeyer, S., Bhathena, S., & Buttar, S. (2018). Effects of Divided Attention on Working and Long-Term Memory.
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