Experiential Learning Spaces for Industrial Engineering Education

Salinas-Navarro, David Ernesto; Garay-Rondero, Claudia Lizette; Calvo, Ericka Zulema Rodríguez

doi:10.1109/fie43999.2019.9028580

Cited by 23 publications

(6 citation statements)

References 9 publications

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“…HE demands pedagogical approaches that consider real-world situations to gain relevant learning and build new capabilities in students for their future professional careers [24]. Moreover, these approaches should allow for long-lasting learning in diverse environments and from multiple perspectives [25].…”

Section: Experiential Learningmentioning

confidence: 99%

Using Generative Artificial Intelligence Tools to Explain and Enhance Experiential Learning for Authentic Assessment

Salinas-Navarro,

Vilalta-Perdomo,

Michel-Villarreal

et al. 2024

Education Sciences

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The emergence of generative artificial intelligence (GenAI) requires innovative educational environments to leverage this technology effectively to address concerns like academic integrity, plagiarism, and others. Additionally, higher education needs effective pedagogies to achieve intended learning outcomes. This emphasizes the need to redesign active learning experiences in the GenAI era. Authentic assessment and experiential learning are two possible meaningful alternatives in this context. Accordingly, this article investigates how GenAI can enhance teaching and learning by constructively addressing study situations beyond conventional learning approaches and cultivating high-order skills and knowledge acquisition. This study employs thing ethnography to examine GenAI tools’ integration with authentic assessment and experiential learning and explore implementation alternatives. The results reveal insights into creating human-centered and GenAI-enhanced learning experiences within a constructive alignment. Specific examples are also provided to guide their implementation. Our contributions extend beyond the traditional use of GenAI tools as mere agents-to-write or agents-to-answer questions to become agents-to-support experiential learning for authentic assessment. These findings underscore the transformative role of GenAI tools in enhancing teaching and learning efficacy and effectiveness. The limitations in treating GenAI tools as subjects in thing ethnography are acknowledged, with potential for future implementation evaluation.

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Section: Experiential Learningmentioning

confidence: 99%

Using Generative Artificial Intelligence Tools to Explain and Enhance Experiential Learning for Authentic Assessment

Salinas-Navarro,

Vilalta-Perdomo,

Michel-Villarreal

et al. 2024

Education Sciences

Self Cite

View full text Add to dashboard Cite

show abstract

“…Según Romero y Robinson (2017) y Hassan (2014), los social labs son ideados para solucionar problemas sociales de manera colectiva, experimentar y crear continuamente y resolver retos de manera sistémica. Desde este enfoque, las personas son los sujetos que experimentan, aprenden, observan, entienden y solucionan problemas (Lake et al, 2016;Salinas et al, 2019).…”

Section: Tipos De Social Labsunclassified

Laboratorio Social. Innovación y experimentación para la economía formal e inclusiva

Liñeiro¹,

Barrera²,

Ramírez³

2023

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El libro tuvo como objeto definir el diseño y la estructura del modelo de negocio de un Laboratorio Social (esto es, un laboratorio centrado en la creación de prototipos y gestión de soluciones prometedoras, formado por personas de diversos sectores y con distintas experiencias para atacar la raíz y el núcleo de los problemas sociales) para una economía formal e inclusiva. A partir de tres fases (recopilación de datos, análisis de la información y cocreación del modelo de negocio), se obtuvo la estructura del modelo de negocio del Laboratorio Social, que cuenta con características que lo diferencian de institu-ciones similares: es sostenible y está en capacidad de brindar servicios a las entidades del ecosistema, opera en red para ser flexible y eficiente, aborda el fenómeno de la informalidad desde una perspectiva multienfoque o interdisciplinar y tiene un mayor enfoque en los territorios, profundidad de análisis y capacidad de monitoreo sobre el conocimiento que genera. Además, resultado de una investigación de casi dos años, este libro también plantea las etapas para el desarrollo del Laboratorio Social (planeación, consolidación y sostenibilidad), de tal forma que pueda ajustarse a las necesidades de investigación y de la población objetivo, escalar y consolidarse.

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“…In this work, we propose the use of blended learning spaces that combine direct instruction, experiential learning in daily-life scenarios, and cloud-based collaborative development environments in a "biomedical signals and systems analysis" course from the perspective of a teaching practice. Our proposal is grounded in an innovative concept of the "experiential learning space" previously presented [12,13]. Notably, we incorporate wearable devices as the enabling technology for experiential learning activities to record physiological and behavioural signals in everyday scenarios.…”

Section: Introductionmentioning

confidence: 99%

Experiential Learning in Biomedical Engineering Education Using Wearable Devices: A Case Study in a Biomedical Signals and Systems Analysis Course

et al. 2022

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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.

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Experiential Learning Spaces for Industrial Engineering Education

Cited by 23 publications

References 9 publications

Using Generative Artificial Intelligence Tools to Explain and Enhance Experiential Learning for Authentic Assessment

Using Generative Artificial Intelligence Tools to Explain and Enhance Experiential Learning for Authentic Assessment

Laboratorio Social. Innovación y experimentación para la economía formal e inclusiva

Experiential Learning in Biomedical Engineering Education Using Wearable Devices: A Case Study in a Biomedical Signals and Systems Analysis Course

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