Not all research, even scholarly and peer-reviewed, research is created equal. Making it especially important to know what to look for when reading through an abstract or a full scholarly article to determine the credibility of the resource. This is where the acronym CRAA(M)P comes in handy as a helpful tool in evaluating the credibility of a resource. CRAA(M)P stands for:
Currency - How recent is the article? While this question does not always mean that you shouldn't use a resource, it's especially important in scientific literature to make sure the resources you are using haven't been superseded by further studies.
Relevance - As you read through the research article, ask yourself if the research being presented is relevant to the question presented.
Authority - It's important to be aware of author affiliations with universities and institutes. Usually, with a quick Google search you'll be able to identify where the author works and some of their background information like what degrees they hold and whether they have a history of publishing on this topic. Using a web resource can be trickier, there is not always an author clearly presented. Use clues like the group publishing the information and look for an "About" page that might give some context as to why they are publishing content on the topic.
Accuracy - Does the information presented align with other information on the topic. Verify that the information presented does not conflict with information gathered in your background research. Go through the bibliography (citations to sources used in the resource) section and make sure that the research you use cites other credible sources. Identify what types of sources the author uses.
Methodology - Understanding the methodology used and the reasons behind it are integral to understanding research articles.
Purpose - The purpose of reliable resources should be to teach the public or to add valid information to the scientific community. Be cautious of the goals of web material.
Evaluating the credibility of data is an important part of scientific scholarship. If data is not correctly collected or analyzed appropriately it can lead to misinterpretations of findings. You may have heard the phrase before, science is self-correcting. Scientific findings should be reproducible by other scientists looking to confirm results. A movement that has become increasingly common is the push for publishing raw data. Raw data and data associated with publications can be found in data repositories associated with institutions like the Texas Data Repository, field-specific repositories like Dryad, and repositories based out of tools like Mendeley Data.
The challenge of evaluating data is no easy task. Faculty level researchers sometimes produce data or analysis errors that may not be caught initially. Looking into data and understanding the methods that went into that research is an important part of science literacy. The following resource from Mozilla Science Lab contains a checklist outlining parameters to consider when assessing a data resource and a dataset behind a publication.
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