Pixel International Conferences

Digital Library Directory > The Future of Education 14th Edition 2024
The Future of Education 14th Edition 2024

AI-simplification of Mark Twain’s "The Adventures of Tom Sawyer": Assessment and Considerations

Adela Chindriș; Mădălina Chitez

Abstract

Text simplification, a linguistic concept dedicated to enhancing the understanding of written texts, is very important within educational contexts. The improvement of text understanding can be achieved through various strategies, such as grammatical, lexical or topical simplification. Presently, digital platforms, like ChatGPT, offer automatic text simplification, yet the efficacy of these simplifications remains untested. This paper aims to investigate the effectiveness of AI-generated text simplifications of some excerpts taken from Mark Twain’s “The Adventures of Tom Sawyer” across multiple criteria, including readability scores and vocabulary complexity. The study uses widely accepted readability scores, such as Flesch-Kincaid and Coleman-Liau, and the online tool Coh-Metrix to assess the impact of simplification on text comprehension. Simplifications will be analyzed from the angles of syntactic complexity and lexical complexity. The study also includes an applied section featuring a questionnaire addressed to primary and middle schoolers, with the intent to assess the effectiveness of the simplifications.

 

Keywords: ChatGPT, Mark Twain, natural language processing (NLP), readability, text simplification

REFERENCES

  1. Siddharthan A., “Syntactic simplification and text cohesion”, University of Cambridge Computer Laboratory, Cambridge, 2004.
  2. Araújo S., Aguiar M., “Simplifying Specialized Texts with AI: A ChatGPT-Based Learning Scenario”, Perspectives and Trends in Education and Technology, Singapore, Springer, 2023, pages 599–609. https://doi.org/10.1007/978-981-99-5414-8_55
  3. Ayre J., Mac O., McCaffery K., et al., “New Frontiers in Health Literacy: Using ChatGPT to Simplify Health Information for People in the Community”, J GEN INTERN MED, 2024, pages 573–577. https://doi.org/10.1007/s11606-023-08469-w
  4. Liu Y. J., Han T., Ma S., Zhang J., Yang Y., Tian J., He H., Li A., He M., Liu Z., Wu Z., Zhang L., Zhu D., Li X., Niu Q., Shen D., Liu T., & Ge B., “Summary of ChatGPT-Related research and perspective towards the future of large language models”, Meta-radiology, 2023. https://doi.org/10.1016/j.metrad.2023.100017
  5. Rutherford M., Baxter J., Johnston L., Tyagi V., & Maciver D., “Piloting a Home Visual Support Intervention with Families of Autistic Children and Children with Related Needs Aged 0–12”, International Journal of Environmental Research and Public Health, 2023. https://doi.org/10.3390/ijerph20054401
  6. Kincaid J. P., Fishburne J., P. R. R., L. C. R., & S. N. B., “Derivation of new readability formulas (Automated Readability Index, Fog Count and Flesch Reading Ease Formula) for Navy enlisted personnel”, 1975. https://doi.org/10.21236/ada006655
  7. Coleman M., & Liau T. L., “A computer readability formula designed for machine scoring”, Journal of Applied Psychology, 1975, pages 283–284. https://doi.org/10.1037/h0076540
  8. Graesser A. C., McNamara D. S., & Louwerse M. M., “What do readers need to learn in order to process coherence relations in narrative and expository text”, Rethinking reading comprehension, Guilford Publications, 2003, pages 82-98.
  9. Twain M., “The Adventures of Tom Sawyer”, Oxford University Press, USA, 2007.
  10. McNamara D. S., Graesser A. C., McCarthy P., & Cai Z., “Automated Evaluation of Text and Discourse with Coh-Metrix”, Cambridge University Press, Cambridge, 2014.
  11. OpenAI, “ChatGPT (GPT-4)”, OpenAI, 2024. https://www.openai.com/chatgpt (Accessed: April 21 - May 17 2024)

 

 

 
Publication date: 2024/06/21
ISBN:
Pixel - Via Luigi Lanzi 12 - 50134 Firenze (FI) - VAT IT 05118710481
    Copyright © 2024 - All rights reserved

Privacy Policy

Webmaster: Pinzani.it