Effect of using artificial intelligence chatbot about electronic fetal monitoring on maternity nursing students’ performance
Amal Mohamed Talaat Abdelwahab, Marwa Ibrahim Hamdy Aboraiah, Hanan Elsayed Mohamed Elsayed · 2025
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Description
Abdelwahab, Aboraiah, and Elsayed (2025) tested whether an AI chatbot improves nursing students' skill at electronic fetal monitoring. Reading fetal traces demands knowledge and judgment, and the chatbot was meant to give focused, personal practice. In a quasi-experiment at an Egyptian university, 84 maternity nursing students were split evenly. One group learned with the chatbot, the other with traditional teaching. Both were tested before, after, and at follow-up.
The chatbot group improved significantly more in knowledge, practical interpretation, and confidence in clinical reasoning, and also in academic motivation. The gains held at follow-up. Over 90 percent of the chatbot group reported high satisfaction with its feedback. The authors conclude that chatbot education beat traditional teaching on every measure they tracked. They present it as a promising support for teaching a skill where accurate decisions matter.
Catalog record
| CREATOR | Amal Mohamed Talaat Abdelwahab, Marwa Ibrahim Hamdy Aboraiah, Hanan Elsayed Mohamed Elsayed |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 60 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |