How can we help?

Home > User Guides > Authorship Investigate > Investigator > The Authorship Report > Interpreting the Authorship Report

Interpreting the Authorship Report

Authorship Investigate does not detect contract cheating. Instead, as the name suggests, it investigates the authorship of a file and then presents the evidence in the form of the Authorship Report.

 

None of the results in the report are empirical evidence that contract cheating has taken place, but together they indicate if the investigation file warrants further scrutiny by the appropriate body within your institution. This tool should be used as one step in a larger process to combat contract cheating.


This guide will break down each section of the report, help you interpret the results, but also offer some potential false flag scenarios. For a more in depth look at the content of the report, read the Authorship Report breakdown.

 


Report section

What is this section of the report telling you? How does the report calculate the results?

Causes for concern

What are the causes for concern in the results? What should the investigator look for?

Valid explanations

Could these results be explained in a way that doesn’t point to contract cheating?

 



MagnifyingGlassPaper_OrangeCircle.png

Readability

 

Readability uses the Flesch-Kincaid Grade Level Formula. Assuming the text is grammatically correct, this scale estimates the years of education needed to understand the text.

 

The scale will show the estimated years of education needed to understand each file and gives you an indication of what grade level each file falls into.

 

The Flesch-Kincaid Grade Level Formula is one of two test that comprise the Flesch-Kincaid readability tests. This article will help you learn more about the Flesch-Kincaid readability tests.

Causes for concern

 

If the result of the investigation file falls outside the 90th percentile (highlighted in orange) of the results of the comparison files then further investigation is recommended.  

 

WarningTrainagle_Orange_OrangeCircle.png

ThumbsUp_Orange_OrangeCircle.png

Valid explanations

 

An author’s readability score should improve over time. This should be taken into consideration if any of the comparison file(s) are older examples of an author’s work.

 

Variation in subject matter and/or assignment length can also lead to a swing in ‘Readability’ results.

 


 


MagnifyingGlassPaper_OrangeCircle.png

Document Information

 

If any of the files submitted to Authorship Investigation are a .docx or .pdf file types, the report will pull the file’s metadata. We can find four different types of metadata; Author Name, Dates, Editing Time, and Revisions. Using .docx will provide the most complete data.


‘Author Name’ is the name that the word processor will give to the creator of the file. The results will be displayed in a table that will allow you to see the author of each file, and who each file was last modified by.

 

‘Dates’ will show you all the dates pertinent to the investigation file and comparison files. The results will be displayed in a table that will allow you to see the date that each file was created, and the date each file was last modified.

 

‘Editing Time’ is the total time spent editing the file. This is the amount of time spent with the document open and in front of other windows, whether you are typing or not. This time is saved and added up each time you save your changes.

 

‘Revisions’ will show how many times the file has been revised (opened and changes made).

Causes for concern

 

The metadata pulled from .docx files can sometimes be the biggest indicator that there may have been possible academic misconduct in a submission.

 

If a name belonging to anyone other than the supposed author is shown in these results, further investigation is recommended.

 

Short editing times and/or few revisions on lengthier documents should be noted as they indicated the copying and pasting of content.

 

WarningTrainagle_Orange_OrangeCircle.png

ThumbsUp_Orange_OrangeCircle.png

Valid explanations

 

An author may use a blank file created by an instructor or peer as the basis for their document. Or they may have worked on the essay using the computer belonging to a friend, peer, or library. Another possibility is they may have asked a peer to proofread and spell check a document. All these scenarios would lead to modifications by someone other than the author and a variance in the ‘Author Name’ section.

 

If the author has copied content from a document into a new document, or the author has used the ‘Save as…’ functionality to create a fresh copy of a document, the editing time would be reset to '0' in the new document, along with the dates. This could explain short results in ‘Editing Time’ and ‘Dates’.

 


 


MagnifyingGlassPaper_OrangeCircle.png

Sentences

 

How an individual uses sentences and phrases is often a stylistic feature that is common in all their writing.

 

The ‘Sentence Type’ visualization shows how each of the document have utilized the four main sentence structures. These are sentence structure types are simple, compound, complex, and compound-complex. If a sentence does not fall into one of these types, the report will list it as “other”.

 

The ‘Phrases per Sentence’ score is the average number of phrases per sentence in a document. Phrases are sets of words that form a single grammatical piece of a sentence. The score conveys the sentence complexity within a document and an author’s grammatical understanding of English.

 

Average sentence length is the average number of words per sentence in a document.

Causes for concern

 

How we structure sentences in our writing is habitual. A change in sentence usage or average sentence length between documents can often signify a change in authorship. Look for large variances in the different sentence types between documents.

 

WarningTrainagle_Orange_OrangeCircle.png

ThumbsUp_Orange_OrangeCircle.png

Valid explanations

 

Variation in subject matter and/or assignment length can lead to a swing in all of the data gathered in the Sentences section. It is good practise to attempt to compare files of similar length and subject matter to achieve the most accurate results.

 


 


MagnifyingGlassPaper_OrangeCircle.png

Vocabulary

 

The features in the vocabulary section of the report offer insight into the stylistic preferences of an author. The results for each of the lexical features will differ from file to file, but files by the same author should have relatively similar results.

 

‘Unique Word Usage’ (type-token ratio) calculates the total number of unique words as a percentage of the total number of words used in a document.

 

‘Vocabulary Richness’ (Hapax Legomena ratio) calculates the percentage of words in a document that only occur once.

Causes for concern

 

We all have certain words and phrases that we tend to use without realising. Further to that, everyone's vocabulary has limits. This section can be a good indicator about whether the essay in question should be further examined for interesting or unusual word usage.

 

If the percentages in this section are high, think about whether the student speaks as eloquently in class discussions. If the student seldom speaks, this section will be useful in an interview with the student to compare their spoken vocabulary to their supposed written one.

 

WarningTrainagle_Orange_OrangeCircle.png

ThumbsUp_Orange_OrangeCircle.png

Valid explanations

 

An author’s vocabulary should improve over time. This should be taken into consideration if any of the comparison file(s) are older examples of an author’s work.

 

Variation in subject matter and/or assignment length can also lead to a swing in the ‘Vocabulary’ results.


 

Last modified

Tags

This page has no custom tags.

Classifications

(not set)