Original Research
Integrating Reading Bots with Guided Reading Strategies to Enhance EFL Nursing Students’ Comprehension of Medical Texts
- Abstract
- Full text
- Metrics
This mixed-methods study examined the role of chatbot-supported guided reading in EFL reading comprehension among undergraduate nursing students. Using a quasi-experimental design, 84 participants in experimental and control groups completed pre- and post-tests assessing overall comprehension and sub-skills. The experimental group used chatbot-guided reading, while the control group received traditional instruction. Semi-structured interviews with 27 participants explored learners’ perceptions. Quantitative results showed significant improvement in overall comprehension and lower-level skills (e.g., skimming), but not critical reading. Qualitative findings indicated that chatbot-guided reading enhanced motivation and reduced anxiety through instant feedback, simplified explanations, and a non-judgmental environment. However, concerns emerged regarding response reliability and limited cognitive engagement. Overall, chatbot-guided reading supports basic skill development and affective engagement but is insufficient for fostering higher-order critical reading skills. The research suggests that a mixed teaching method that combines reading tasks based on AI support with training on critical thinking conducted by an instructor is recommended.
Page 1 of
Download Count : 10
Visit Count : 309
Keywords
Reading Bots; Guided Reading; EFL Nursing Students; Medical Comprehension; AI-Assisted Learning
Author(s) Information
Acknowledgements
The authors would like to express their sincere appreciation to the nursing students for their time and cooperation.
Funding Statement
This work was supported and funded by the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University (IMSIU) (grant number IMSIU-DDRSP2602).
CRediT Authorship Contribution Statement
Nada S. Al Ruwaili: Conceptualization, Methodology, Investigation, Data Curation, Writing – Original Draft, Project Administration
Abdul Aziz Mohamed Mohamed Ali El Deen: Writing – Review & Editing, Validation, Formal Analysis, Visualization, Revision Management
Shahad Z. Aldandan: Investigation, Resources, Data Curation, Writing – Review & Editing
Noura A. Alhudaib: Investigation, Resources, Data Curation
Mohammed A. Alrashed: Methodology, Formal Analysis, Supervision, Writing – Review & Editing
Amr M. Mohamed: Conceptualization, Methodology, Supervision, Formal Analysis, Writing – Original Draft, Writing – Review & Editing, Project Administration
Generative AI Use Disclosure Statement
The authors confirm that no Gen-AI applications were used in the conception, design, analysis, or writing of this manuscript. However, Grammarly was employed solely for language editing and readability.
Ethics Declarations
World Medical Association (WMA) Declaration of Helsinki–Ethical Principles for Medical Research Involving Human Participants
Ethical approval was granted by North Private College of Nursing, in line with the Declaration of Helsinki. All participants gave written informed consent and were assured they could withdraw at any time without penalty.
Competing Interests
The authors declare that they have no competing interests.
Data Availability
The datasets are available from the corresponding author upon reasonable request.