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Detecting Plagiarism in Microsoft Excel Assignments

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Laurence Hellyer and Lawrence Beadle. Detecting Plagiarism in Microsoft Excel Assignments. Typical Excel Assignments. Loan Repayment Pension Calculator Annuity Calculator. A Familiar Problem. Plagiarising an Excel Assignment. Plagiarism: The action of taking someone else's work.

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Presentation Transcript
typical excel assignments
HEA ICS 10th Annual Conference 2009Typical Excel Assignments
  • Loan Repayment
  • Pension Calculator
  • Annuity Calculator
a familiar problem
A Familiar Problem

HEA ICS 10th Annual Conference 2009

plagiarising an excel assignment
HEA ICS 10th Annual Conference 2009Plagiarising an Excel Assignment
  • Plagiarism: The action of taking someone else's work
  • Text Cells
  • Formula Cells
  • Charts
  • Numeric Cells – these are often specified by the assignment (i.e. assume an interest rate of 18%)
objective
HEA ICS 10th Annual Conference 2009Objective
  • Develop and use an automated tool to assist markers in detecting intra and inter group plagiarism within Microsoft Excel assignments.
case study
Case Study

Suspected Plagiarism Detected by Human Markers

existing solutions
HEA ICS 10th Annual Conference 2009Existing Solutions?
  • Similar tools exist for different contexts
    • TurnItIn
    • Moss
human markers detecting plagiarism
HEA ICS 10th Annual Conference 2009Human Markers Detecting Plagiarism
  • Microsoft Excel files can save meta-data about the file:
    • Author
    • Last saved by
    • Creation time
    • Last modification time
    • Registered Company
human markers detecting plagiarism sometimes
HEA ICS 10th Annual Conference 2009Human Markers Detecting Plagiarism (Sometimes)
  • Microsoft Excel files can save meta-data about the file:
    • Author
    • Last saved by
    • Creation time
    • Last modification time
    • Registered Company
presenting excelsmash
HEA ICS 10th Annual Conference 2009Presenting ExcelSmash…
  • ExcelSmash is our software tool to highlight submissions requiring further scrutiny
    • It conducts the almost all the tests human markers can conduct
usage
HEA ICS 10th Annual Conference 2009Usage
  • Analyses 400 students in < 2 minutes
  • Output rapidly identifies submissions with similar content
data used by excelsmash
HEA ICS 10th Annual Conference 2009Data Used by ExcelSmash…

Submission server

Student username

Author, Last saved by,

Creation and modification time,

Company Name

Strings found in Text cells

Strings representing formulas found in Formula cells

Excel 97-2003, 2007

analysing submissions
HEA ICS 10th Annual Conference 2009Analysing Submissions
    • Pair wise comparisons of submissions
      • 80,000 comparisons for 400 submissions
    • Individual tests on each submissions
  • If a submission fails a test we add a “red flag” to the submission
  • Each test has an associated severity score
  • Only report submissions that exceed a run-time specified threshold
example output
HEA ICS 10th Annual Conference 2009Example Output

Login: aaaa --- Severity: 7

Author match “Andrew” with: bbbb --- Severity: 5

Author “Andrew” and last saved by “aaaa” mis-match --- Severity: 2

Login: cccc --- Severity: 23 Similar creation time to dddd --- Severity: 1  

Similar creation time to eeee --- Severity: 1

Similar creation time to ffff --- Severity: 1

100% similar text to ffff --- Severity: 10

100% similar formula to ffff --- Severity: 10

text matching
HEA ICS 10th Annual Conference 2009Text Matching
  • Case insensitive string equality

Please Enter Your Annual Salary

Annual Salary

Please Enter Your Annual Salary

Please enter your annual salary

formula matching
HEA ICS 10th Annual Conference 2009Formula Matching
  • Case insensitive string equality

=AVERAGE(H1:H10)*100

=100*AVERAGE(H1:H10)

=SUM(A1:D4)

=SUM(A2:D5)

case study2
HEA ICS 10th Annual Conference 2009Case Study

Suspected Plagiarism Detected in 2007-08 Cohort

(382 students)

excelsmash conclusions
HEA ICS 10th Annual Conference 2009ExcelSmash Conclusions
  • New class of tool aimed at detecting possible plagiarism within Microsoft Excel assignments
  • Quickly identifies submissions requiring further scrutiny
  • Improved detection of intra group and especially intergroupplagiarism compared to human markers
further work
HEA ICS 10th Annual Conference 2009Further Work
  • Make code available to academics
  • Current formula comparison algorithm is easy to circumvent
    • Tokenise formulas before comparisons to remove dependence on absolute cell references
  • Avoid warnings for common author names
  • Add warning if metadata is stripped
thank you
HEA ICS 10th Annual Conference 2009Thank you

Questions?

www.cs.kent.ac.uk/~lh243

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