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Designing experiential learning activities with generative artificial intelligence tools for authentic assessment
(Emerald, 2024)
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Vilalta-Perdomo, Eliseo
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Michel-Villarreal, Rosario
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Montesinos, Luis
Purpose: This article investigates the application of generative artificial intelligence (GenAI) in experiential learning for authentic assessment in higher education. Recognized for its human-like content generation, GenAI has garnered widespread interest, raising concerns regarding its reliability, ethical considerations and overall impact. The purpose of this study is to explore the transformative capabilities and limitations of GenAI for experiential learning. Design/methodology/approach: The study uses “thing ethnography” and “incremental prompting” to delve into the perspectives of ChatGPT 3.5, a prominent GenAI model. Through semi-structured interviews, the research prompts ChatGPT 3.5 on critical aspects such as conceptual clarity, integration of GenAI in educational settings and practical applications within the context of authentic assessment. The design examines GenAI’s potential contributions to reflective thinking, hands-on learning and genuine assessments, emphasizing the importance of responsible use. Findings: The findings underscore GenAI’s potential to enhance experiential learning in higher education. Specifically, the research highlights GenAI’s capacity to contribute to reflective thinking, hands-on learning experiences and the facilitation of genuine assessments. Notably, the study emphasizes the significance of responsible use in harnessing the capabilities of GenAI for educational purposes. Originality/value: This research showcases the application of GenAI in operations management education, specifically within lean health care. The study offers insights into its capabilities by exploring the practical implications of GenAI in a specific educational domain through thing ethnography and incremental prompting. Additionally, the article proposes future research directions, contributing to the originality of the work and opening avenues for further exploration in the integration of GenAI in education. ©The authors, Emerald Group Publishing.
Scopus© Citations 7 21
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Transdisciplinary experiential learning in biomedical engineering education for healthcare systems improvement
(BMC, 2023)
Montesinos, Luis
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Santos-Diaz, Alejandro
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Background: The growing demand for more efficient, timely, and safer health services, together with insufficient resources, put unprecedented pressure on health systems worldwide. This challenge has motivated the application of principles and tools of operations management and lean systems to healthcare processes to maximize value while reducing waste. Consequently, there is an increasing need for professionals with the appropriate clinical experience and skills in systems and process engineering. Given their multidisciplinary education and training, biomedical engineering professionals are likely among the most suitable to assume this role. In this context, biomedical engineering education must prepare students for a transdisciplinary professional role by including concepts, methods, and tools that commonly belong to industrial engineering. This work aims to create relevant learning experiences for biomedical engineering education to expand transdisciplinary knowledge and skills in students to improve and optimize hospital and healthcare care processes. Methods: Healthcare processes were translated into specific learning experiences using the Analysis, Design, Development, Implementation, and Evaluation (ADDIE) model. This model allowed us to systematically identify the context where learning experiences were expected to occur, the new concepts and skills to be developed through these experiences, the stages of the student’s learning journey, the resources required to implement the learning experiences, and the assessment and evaluation methods. The learning journey was structured around Kolb’s experiential learning cycle, which considers four stages: concrete experience, reflective observation, abstract conceptualization, and active experimentation. Data on the student’s learning and experience were collected through formative and summative assessments and a student opinion survey. Results: The proposed learning experiences were implemented in a 16-week elective course on hospital management for last-year biomedical engineering undergraduate students. Students engaged in analyzing and redesigning healthcare operations for improvement and optimization. Namely, students observed a relevant healthcare process, identified a problem, and defined an improvement and deployment plan. These activities were carried out using tools drawn from industrial engineering, which expanded their traditional professional role. The fieldwork occurred in two large hospitals and a university medical service in Mexico. A transdisciplinary teaching team designed and implemented these learning experiences. Conclusions : This teaching-learning experience benefited students and faculty concerning public participation, transdisciplinarity, and situated learning. However, the time devoted to the proposed learning experience represented a challenge. ©The authors, BMC Medical Education.
Scopus© Citations 14 22
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Experiential Learning in Biomedical Engineering Education Using Wearable Devices: A Case Study in a Biomedical Signals and Systems Analysis Course
(MDPI, 2022)
Montesinos, Luis
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Santos-Diaz, Alejandro
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Cendejas-Zaragoza, Leopoldo
Biomedical engineering (BME) is one of the fastest-growing engineering fields worldwide. BME professionals are extensively employed in the health technology and healthcare industries. Hence, their education must prepare them to face the challenge of a rapidly evolving technological environment. Biomedical signals and systems analysis is essential to BME undergraduate education. Unfortunately, students often underestimate the importance of their courses as they do not perceive these courses’ practical applications in their future professional practice. In this study, we propose using blended learning spaces to develop new learning experiences in the context of a biomedical signals and systems analysis course to enhance students’ motivation and interest and the relevance of the materials learned. We created a learning experience based on wearable devices and cloud-based collaborative development environments such that the students turned daily-life scenarios into experiential learning spaces. Overall, our results suggest a positive impact on the students’ perceptions of their learning experience concerning relevance, motivation, and interest. Namely, the evidence shows a reduction in the variability of such perceptions. However, further research must confirm this potential impact. This confirmation is required given the monetary and time investment this pedagogical approach would require if it were to be implemented at a larger scale. ©MDPI, The authors.
Scopus© Citations 7 2

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