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The Evolution of Short Answer Grading Systems: From Manual Methods to AI-Driven Solutions with GPT-4

by Augustine O. Ugbari, Chidiebere Ugwu, Laeticia N. Onyejegbu
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 186 - Number 30
Year of Publication: 2024
Authors: Augustine O. Ugbari, Chidiebere Ugwu, Laeticia N. Onyejegbu
10.5120/ijca2024923846

Augustine O. Ugbari, Chidiebere Ugwu, Laeticia N. Onyejegbu . The Evolution of Short Answer Grading Systems: From Manual Methods to AI-Driven Solutions with GPT-4. International Journal of Computer Applications. 186, 30 ( Jul 2024), 33-39. DOI=10.5120/ijca2024923846

@article{ 10.5120/ijca2024923846,
author = { Augustine O. Ugbari, Chidiebere Ugwu, Laeticia N. Onyejegbu },
title = { The Evolution of Short Answer Grading Systems: From Manual Methods to AI-Driven Solutions with GPT-4 },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2024 },
volume = { 186 },
number = { 30 },
month = { Jul },
year = { 2024 },
issn = { 0975-8887 },
pages = { 33-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume186/number30/the-evolution-of-short-answer-grading-systems-from-manual-methods-to-ai-driven-solutions-with-gpt-4/ },
doi = { 10.5120/ijca2024923846 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-07-26T23:00:35.484335+05:30
%A Augustine O. Ugbari
%A Chidiebere Ugwu
%A Laeticia N. Onyejegbu
%T The Evolution of Short Answer Grading Systems: From Manual Methods to AI-Driven Solutions with GPT-4
%J International Journal of Computer Applications
%@ 0975-8887
%V 186
%N 30
%P 33-39
%D 2024
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The evaluation of short answer responses has long been a critical component of educational assessments, providing insights into student comprehension and analytical skills. This paper traces the evolution of short answer grading systems from their inception in manual grading practices to the advent of AI-driven solutions, focusing particularly on the advancements brought by models like GPT-4. Through a comprehensive review of historical developments, technological advancements, and pedagogical impacts, this research provides a detailed understanding of the progression and future prospects of short answer grading systems.

References
  1. M. A. Hearst, "The debate on automated essay grading," IEEE Intelligent Systems and their Applications, vol. 15, no. 5, pp. 22-37, 2000.
  2. E. B. Page, "The use of the computer in analyzing student essays," International Review of Education, vol. 14, no. 2, pp. 210-225, 1968.
  3. S. Valenti, F. Neri and A. Cucchiarelli, "An overview of current research on automated essay grading.," Journal of Information Technology Education: Research,, vol. 2, pp. 319-332, 2003.
  4. M. D. Shermis and J. Burstein, "Automated essay scoring: A cross-disciplinary perspective," Lawrence Erlbaum Associates, 2003.
  5. L. M. Rudner, V. Garcia and C. Welch, "An evaluation of IBM's SPSS Modeler automated essay scoring system.," The Journal of Technology, Learning, and Assessment, vol. 4, no. 7, 2006.
  6. Y. Attali and J. Burstein, "Automated essay scoring with e-rater," The Journal of Technology, Learning and Assessment, vol. 4, no. 3, 2006.
  7. L. Anderson and D. Krathwohl, A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom's Taxonomy of Educational Objectives, Longman, 2001.
  8. D. Sadler, "Formative assessment and the design of instructional systems," Instructional Science, vol. 18, no. 2, pp. 119-144, 1989.
  9. N. Gronlund, Assessment of Student Achievement, Allyn & Bacon, 2006.
  10. J. Wang and M. S. Brown, "Automated essay scoring versus human scoring: A comparative study," Journal of Educational Computing Research, vol. 35, no. 3, pp. 325-348, 2007.
  11. M. D. Shermis and J. Burstein, Automated Essay Scoring: A Cross-disciplinary Perspective, Lawrence Erlbaum Associates, 2003.
  12. S. Burrows, I. Gurevych and B. Stein, "The Eras and Trends of Automatic Short Answer Grading," *International Journal of Artificial Intelligence in Education, vol. 25, no. 1, pp. 60-117, 2015.
  13. S. Jordan and T. Mitchell, "e-Assessment for learning? The potential of short-answer free-text questions with tailored feedback," British Journal of Educational Technology, vol. 40, no. 2, pp. 371-385, 2009.
  14. A. e. a. Radford, "Language Models are Unsupervised Multitask Learners," OpenAI, 2019.
  15. T. e. a. Brown, Language Models are Few-Shot Learners, arXiv preprint arXiv:2005.14165, 2020.
  16. OpenAI, "GPT-4 Technical Report," OpenAI, 2023.
  17. R. Bennett and M. Zhang, "Validity and Reliability in Automated Essay Scoring.," Educational Measurement: Issues and Practice, vol. 35, no. 1, pp. 2-12, 2016.
  18. E. e. a. Higgins, "The future of AI in Education: Insights from the NMC Horizon Report," International Journal of Artificial Intelligence in Education, vol. 29, no. 2, pp. 123-142, 2019.
Index Terms

Computer Science
Information Sciences

Keywords

Short Answer Grading System GPT-4 Machine Learning.

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