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Cited by 8Artificial Intelligence in EducationIntelligent Tutoring Systems and Adaptive LearningArtificial Intelligence in Healthcare and Education

Navigating the textual maze: Enhancing textual analytical skills through an innovative GAI prompt framework

Li, Xuefan, Li, Tingsong, Wang, Minjuan, Tao, Sining, Zhou, Xiaoxu, Wei, Xiaoqing, Guan, Naiqing·2025·IEEE Transactions on Learning Technologies
DOI 10.1109/tlt.2025.3539104
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Abstract

With the rapid advancement of generative artificial intelligence (GAI), its application in educational settings has increasingly become a focal point, particularly in enhancing students’ analytical capabilities. This study examines the effectiveness of the ChatGPT prompt framework in improving text analysis skills among students, specifically targeting readability, accuracy, completeness, logicality, and critical thinking. Conducted among high school students in Canada, the research assesses how GAI prompt frameworks significantly affect the quality of students’ analytical responses. Results showed significant improvements in all five aspects of readability, accuracy, completeness, logicality, and critical thinking, especially for students with no prior knowledge of the topic. However, enhancements in completeness and critical thinking were less pronounced, suggesting that while the ChatGPT framework substantially supports basic analytical skills, its effectiveness varies depending on the complexity of cognitive tasks and the extent of students’ existing knowledge. The study underscores the significant role that advanced GAI tools can play in modern educational environments, promoting deeper engagement with learning materials and enhancing students’ analytical abilities. It highlights the necessity of integrating these technologies to cater to diverse learning needs and cognitive challenges.

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Crossref · 10.1109/tlt.2025.3539104

Cites

54 of 54 references verified0 citation errors · 0 not checkable

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  • Large language models support literary writing, story crafting, and creative text generation; students iteratively revise content, adjust style, and sharpen narrative logic, often under teacher guidance.

    “Large language models support literary writing, story crafting, and creative text generation; students iteratively revise content, adjust style, and sharpen narrative logic-often under teacher guidance to rework initial plots toward intended effects [84,86,139,144,145].”

    From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [145]

  • AI provides strong scaffolds for core practices, markedly improving the quality and conventionality of learner outputs-for example, enhancing grammatical accuracy and argumentative coherence in writing, and supporting problem-solving and experimental design in science and mathematics-thereby helping learners meet baseline practice demands more efficiently.

    “First, AI provides strong scaffolds for core practices, markedly improving the quality and conventionality of learner outputs-for example, enhancing grammatical accuracy and argumentative coherence in writing [86,87,145], and supporting problem-solving and experimental design in science and mathematics [77,88,93,103,147]-thereby helping learners meet baseline practice demands more efficiently.”

    From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [145]

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Authors
Li, X., Li, T., Wang, M., Tao, S., Zhou, X., Wei, X., & Guan, N.
Affiliations
  • University of Toronto (CA)
  • Shanghai Jiao Tong University (CN)
  • Education University of Hong Kong (HK)
  • Harvard University (US)
  • Boston University (US)
ORCID
Venue
IEEE Transactions on Learning Technologies
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2025
Volume
18
Pages
206-215
ISSN
  • 1939-1382 (ISSN-L)
  • 2372-0050
DOI
10.1109/tlt.2025.3539104
OpenAlex
W4407168991
Cited by
8
References
54
Citations by year
2026: 4 · 2025: 4
FWCI
8.23
Type
journal article
Language
en
Open access
closed
Licence
Locations
IEEE Transactions on Learning Technologies (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Keywords
generative AI in education, text analysis skills, critical thinking, readability, accuracy, logicality, high school students, prior knowledge, AI-assisted learning

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