Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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ACTIVE_NOT_RECRUITING
NA
84 participants
INTERVENTIONAL
2025-06-01
2025-12-01
Brief Summary
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* The aim will be achieved through the following,
1. Designing AI Chatbot about electronic fetal monitoring.
2. Exploring the effect of using AI Chatbot about electronic fetal monitoring on students' performance, interest in education, self-directed learning \& feedback satisfaction.
* The students will be divided into two groups, the intervention group will use EFM Chatbot, and the control group will receive the traditional learning
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Detailed Description
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The integration of artificial intelligence (AI) into education and research has become more prevalent in recent years. With the evolution of medical technology, content of medical and nursing education has changed; thus, continuously enhancing medical student's knowledge and capabilities is a critical educational objective.
The incorporation of AI into the education field has led to many possibilities, benefiting both educators and students. AI takes on various roles as an intelligent tutor, a learning partner, and even an adviser in influencing educational policies also, provide a focused, personalized, and result-oriented online learning environment.
The current generation of nursing students, having been raised in an era of networking \& highly familiar with internet technology. As such, it is anticipated that their learning preferences may differ from previous generations. Thus, strategies for improving students' self-directed learning, and efforts for promoting interactions between instructors and students were needed. This has led to a growing interest in using AI powered technology. Among the various forms of AI, Chatbots represent one of the most commonly encountered AI-based tools in the education field The aims of nursing training include not only mastering skills but also fostering the competence to make decisions for problem solving. Regarding essential nursing techniques in midwifery health nursing, education on installing EFM equipment and interpreting its results is required. Electronic fetal monitoring (EFM) is a method to assess fetal health, utilized to prevent fetal hypoxia and provide interventions at an early stage by observing changes in fetal heartbeat.
Since EFM-related tasks, require professional knowledge \& understanding, nursing students should be provided with sufficient learning and training in EFM prior to their training in the delivery room. With the aim of helping students to make correct decisions when dealing with real cases, it is necessary to engage them in authentic problem-solving contexts Traditional education system faces several issues, including overcrowded classrooms, high student teacher ratio, lack of personalized attention for students, varying learning paces and styles. Consequently, the lack of individualized student support leads to low satisfaction with learning and subsequent weak learning efficiency.
Based on Egypt vision 2030 one of Challenges in the Health science Sector is mismatch of skills between higher education graduates and the needs of the health sector. Given that the priority agenda of the Egyptian government is reducing the high Maternal\& neonatal Mortality Rate (MMR) \& (NMR), a specific set of KPI has been selected to be used to monitor progress until 2030 as decrease in MMR and increase in life expectancy at birth to reach 31% \& 75% respectively.
As the educational landscape continues to evolve, the rise of AI-powered chatbots emerges as a promising solution to enable students to learn and think deeply in the contexts of handling obstetrics. According to Egyptian National Council for Artificial Intelligence strategy, applying AI to areas such as education or healthcare can facilitate access, and reduce risks and costs.
In this context, it is essential to assess the effects of Chatbot, which have the potential to be used in educational institutions that have the mission of shaping society and guiding the future of all stakeholders of education. Therefore, developing \& using Chatbot as educational method and evaluating its effects in the field of nursing education are needed, so this study will be conducted.
* An approval will be obtained from the Faculty of Nursing Research Ethics Committee to carry out the study.
* An official permission will be obtained by submission of an official letter to head of woman's' health and midwifery nursing department Faculty of Nursing, Mansoura University, and the Dean of the selected setting to conduct the study after explaining the aim, importance and benefits of the research of the study to gain their cooperation and support during data collection.
* Students from level three will be recruited in the study \& divided into two groups, the intervention group will use EFM Chatbot, and the control group will receive the traditional learning.
* The researcher will measure the effectiveness of EFM Chatbot to assess how well the maternity students were remembering the material and applying the instructions compare the results with the control group.
Conditions
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Study Design
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NON_RANDOMIZED
PARALLEL
OTHER
NONE
Study Groups
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intervention group
this group will receive the designed electronic fetal monitoring AI Chatbot education
designed artificial intelligence Chatbot education about electronic fetal monitoring
effect of using designed artificial intelligence Chatbot about electronic fetal monitoring on maternity nursing students' performance
control group
this group includes students who will receive the traditional learning method (online meeting).
traditional teaching method
the traditional learning method (online meeting).
Interventions
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designed artificial intelligence Chatbot education about electronic fetal monitoring
effect of using designed artificial intelligence Chatbot about electronic fetal monitoring on maternity nursing students' performance
traditional teaching method
the traditional learning method (online meeting).
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
ALL
Yes
Sponsors
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Mansoura University
OTHER
Responsible Party
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Amal Mohamed Talaat AbdElwahab Hassan Ahmed Aboaish
assistant lecturer of woman's health and midwifery nursing department
Principal Investigators
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Amal Mohamed Talaat Abdelwahab, assistant lecturer
Role: PRINCIPAL_INVESTIGATOR
assistant lecturer at woman's health and midwifery nursing department, faculty of nursing, mansoura university
hanan alemam, professor
Role: STUDY_DIRECTOR
head of woman's health and midwifery nursing department, faculty of nursing, mansoura university
Locations
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Faculty of Nursing, Mansoura University
Al Mansurah, Dakahlia Governorate, Egypt
Countries
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References
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Han JW, Park J, Lee H. Analysis of the effect of an artificial intelligence chatbot educational program on non-face-to-face classes: a quasi-experimental study. BMC Med Educ. 2022 Dec 1;22(1):830. doi: 10.1186/s12909-022-03898-3.
Related Links
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Ministry of Planning, Monitoring and Administrative Reform Cairo
Other Identifiers
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EFM chatbot
Identifier Type: -
Identifier Source: org_study_id
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