Promoting students’ learning achievement and self-efficacy: a mobile chatbot approach for nursing training
Abstract
Abstract The aims of nursing training include not only mastering skills but also fostering the competence to make decisions for problem solving. In prenatal education, cultivating nurses' knowledge and competence of vaccine administration is a crucial issue for protecting pregnant women and newborns from infection. Therefore, obstetric vaccination knowledge has become a basic and essential training program for nursing students. However, most of these training programs are given via the lecture‐based teaching approach with skills practice, providing students with few opportunities to think deeply about the relevant issues owing to the lack of interaction and context. This could have a negative impact on their learning effectiveness and clinical judgment. To address this problem, a mobile chatbot‐based learning approach is proposed in this study to enable students to learn and think deeply in the contexts of handling obstetric vaccine cases via interacting with the chatbot. In order to verify the effectiveness of the proposed approach, an experiment was implemented. Two classes of 36 students from a university in northern Taiwan were recruited as participants. One class was the experimental group learning with the proposed approach, while the other class was the control group learning with the conventional approach (ie, giving lectures to explain the instructional content and training cases). The results indicate that applying a mobile chatbot for learning can enhance nursing students' learning achievement and self‐efficacy. In addition, based on the analysis of the interview results, students generally believed that learning through the mobile chatbot was able to promote their self‐efficacy as well as their learning engagement and performance. Practitioner notes What is already known about this topic Issues relevant to AI technology in education have been extensively discussed and explored around the world. Among the various AI systems, the potential of chatbots has been highlighted by researchers owing to the user‐friendly interface developed using the natural language processing (NLP) technology. Few studies using AI chatbots in professional training have been conducted. What this paper adds In this study, a mobile chatbot was used in a nursing training program to enhance students' learning achievement and self‐efficacy for handling vaccine cases. The mobile chatbot significantly improved the students' learning achievement and self‐efficacy in comparison with the conventional learning approach in the vaccine training program. From the interview results, it was found that the students generally believed that the mobile chatbot was able to promote their self‐efficacy as well as learning engagement and performances in the vaccine training program. Implications for practice and/or policy Mobile chatbots have great potential for professional training owing to their convenient and user‐friendly features. It would be worth applying mobile chatbots as well as other NLP‐based applications to other professional training programs in the future.
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Nursing research has been predominantly focusing on the utilization of chatbots in areas such as mental health, weight management, antenatal education, and electronic fetal monitoring.
“Nursing research has been predominantly focusing on the utilization of chatbots in areas such as mental health [18, 19], weight management [20, 21], antenatal education [22], and electronic fetal monitoring [16].”
From Development and effects of a chatbot education program for self-directed learning in nursing students (2025) · cites this paper as [22]
Positive changes in affective learning gains include learning interest, self-efficacy, satisfaction, enjoyment, and motivation.
“Positive changes in affective learning gains include learning interest (16), self-efficacy (18), satisfaction (25), enjoyment (19), and motivation (11).”
From Digital affordances of AI chatbots in nursing education: a systematic review of learning gains and gaps in the evidence (2026) · cites this paper as [18]
AI chatbots enhanced students' learning performance and self-efficacy in obstetric vaccine education by engaging with case-based scenarios.
“Another study demonstrated that AI chatbots enhanced students’ learning performance and self-efficacy in obstetric vaccine education by engaging with case-based scenarios (18).”
From Digital affordances of AI chatbots in nursing education: a systematic review of learning gains and gaps in the evidence (2026) · cites this paper as [18]
In a Taiwanese study where chatbots were applied to nursing students' learning, users reported that they could concentrate on their lessons, found chatbot learning enjoyable, and were able to explore relevant information actively.
“In a Taiwanese study, where chatbots were applied to nursing students’ learning [22], users reported that they could concentrate on their lessons, found chatbot learning enjoyable, and were able to explore relevant information actively.”
From Development and effects of a chatbot education program for self-directed learning in nursing students (2025) · cites this paper as [22]
A Taiwanese study applied chatbots to nursing students and found that it could enhance self-efficacy.
“This result is consistent with a Taiwanese study, which applied chatbots to nursing students and found that it could enhance self-efficacy [22].”
From Development and effects of a chatbot education program for self-directed learning in nursing students (2025) · cites this paper as [22]
Similar results on self-efficacy have been found in previous studies such as Chen et al. (2020), Pérez et al. (2020), and Chang et al. (2022).
“Similar results have been found in previous studies such as Chen et al. (2020), Pérez et al. (2020), and Chang et al. (2022).”
From Implementing the bashayer chatbot in Saudi higher education: measuring the influence on students' motivation and learning strategies (2023) · cites this paper as Chang et al. (2022)
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“Another study demonstrated that AI chat-bots enhanced students’ learning performance and self-efficacy in obstetric vaccine education by engaging with case-based scenarios (18).”
- Authors
- Chang, C., Hwang, G., & Gau, M.
- Affiliations
- Taipei Medical University (TW)
- National Taiwan University of Science and Technology (TW)
- National Taipei University of Nursing and Health Science (TW)
- Corresponding author
- Hwang, Gwo‐Jen
- Venue
- British Journal of Educational Technology
- Publisher
- Wiley
- Published
- 2021-08-22
- Volume
- 53
- Issue
- 1
- Pages
- 171-188
- ISSN
- 0007-1013 (ISSN-L)
- 1467-8535
- OpenAlex
- W3193767085
- Cited by
- 294
- References
- 56
- Citations by year
- 2026: 56 · 2025: 91 · 2024: 70 · 2023: 59 · 2022: 16 · 2021: 2
- FWCI
- 12.99
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- British Journal of Educational Technology (publishedVersion)
- Funders
- Ministry of Science and Technology, Taiwan (MOST‐109‐2511‐H‐011‐002‐MY3, MOST 109‐2635‐H‐227‐001, MOST 110‐2511‐H‐038‐008)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Information Systems › Mobile Learning in Education
- Keywords
- nursing education, self-efficacy, academic performance, clinical decision-making, artificial intelligence in education, natural language processing, prenatal education, clinical judgment, nursing students, interactive learning, student engagement, professional training, clinical case-based learning, lecture method comparison
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