Plagiarism Detection Using Edit Distance and Preprocessing
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Solution Overview
Problem
Manual detection of plagiarism in constructed responses is time-consuming and often rushed, leading to potential missed cases or false negatives, as it requires systematic human evaluation that is costly and typically conducted simultaneously with scoring.
Innovation Solution
A computerized method and system for detecting plagiarism that preprocesses constructed responses by reformatting, removing common phrases, and calculating similarity values using generalized edit distance, comparing these values to a threshold to identify potential plagiarism, with results stored for further analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual plagiarism detection is performed, then detection accuracy can be maintained through human judgment, but the process becomes time-consuming and costly
Solution Approach 1:
The plagiarism detection process is segmented into multiple independent comparison operations. Each response is compared against every other response in the set, breaking down the complex task of evaluating all responses into manageable pairwise comparisons. This segmentation enables systematic automated processing while maintaining comprehensive coverage.
Solution Approach 2:
The manual mechanical process of human readers comparing responses is replaced with an automated computer-based system. The system uses algorithmic similarity calculations (such as edit distance) to objectively compare responses, substituting human judgment with computational analysis. This replacement dramatically reduces time and cost while maintaining systematic evaluation.
2Productivity
If automated plagiarism detection is implemented, then processing speed and efficiency are improved, but complexity of the detection system increases
Solution Approach 1:
The automated system performs multiple functions within a single integrated platform: it stores responses, pre-processes text data, conducts similarity comparisons using various algorithms, and generates results. This multi-functionality reduces the need for separate systems for each task, managing complexity while maintaining high productivity.
Solution Approach 2:
The system utilizes configurable parameters such as similarity thresholds and comparison algorithms that can be adjusted without changing the fundamental system architecture. By changing parameters rather than system structure, the system adapts to different detection needs while maintaining manageable complexity.
3Reliability
If systematic plagiarism review is conducted, then detection reliability is improved, but it must be done simultaneously with scoring due to cost constraints
Solution Approach 1:
The automated plagiarism detection system performs preliminary analysis of all responses immediately after collection, before the scoring process begins. By conducting detection in advance, the system eliminates the need to schedule reviews simultaneously with scoring, providing reliable results that can inform scoring decisions without time constraints.
Data Source
AI summary
A system, method, and computer-readable medium for detecting plagiarism in a set of constructed responses by accessing and pre-processing the set of constructed responses to facilitate the pairing and comparing of the constructed responses. The similarity value generated from the comparison of a pair of constructed responses serves as an indicator of possible plagiarism.