An Analysis of Automated Essay Scoring Frameworks

Authors

  • Abeer Abdulkarem Polytechnic University (NPI) Author
  • Anastasia Krivtsun Platov South-Russian State Polytechnic University Author

DOI:

https://doi.org/10.69923/av1gt264

Keywords:

Automated Essay Scoring , Content Similarity , Hybrid Framework , Machine Learning, BERT

Abstract

Automatic essay scoring (AES) has gained significant popularity in recent years as it provides an efficient and unbiased means of evaluating student writing. Efficient and objective assessment of student writing is essential for educators, as it offers valuable feedback that can aid students in enhancing their writing abilities and achieving academic success. This study offers an extensive examination of several AES frameworks, investigating their performance indicators, underlying algorithms, and suitability for use in a range of educational contexts. The paper examined the three main frameworks of AES, which include content-based, machine learning (ML), and hybrid methods, highlighting the benefits and drawbacks of each. In the end, this analysis hopes to improve automated grading technologies and their integration into educational practices by providing educators, policymakers, and technologists with information about the strengths and weaknesses of AES frameworks through the synthesis of recent research and developments.

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Author Biographies

  • Abeer Abdulkarem, Polytechnic University (NPI)

    PhD student at Department of Information Technologies and Management, Platov South-Russian State Polytechnic University (NPI), Prosveshсhenie Str. 132, 346428 Novocherkassk, Russia. Email: abeerabdulsalam15@gmail.com

  • Anastasia Krivtsun, Platov South-Russian State Polytechnic University

    Associate professor at Department of Information Technologies and Management, Platov South-Russian State Polytechnic University (NPI), Prosveshсhenie Str. 132, 346428 Novocherkassk, Russia. Email: anastasia.srstu@gmail.com

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Published

12/30/2024

Issue

Section

Articles

How to Cite

[1]
A. Abdulkarem and A. . Krivtsun, “An Analysis of Automated Essay Scoring Frameworks”, IJApSc, vol. 1, no. 3, pp. 71–81, Dec. 2024, doi: 10.69923/av1gt264.

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