Transforming Industrial Engineering Education: Introducing the CWILE Model for Work-Integrated Learning in the Digital Age

,; Jewpanya, Parida; Nuangpirom, Pinit; ,; Pitjamit, Siwasit; ,; Jaichomphu, Pakpoom; ,; Chaithanul, Kitchar; ,; Sriyab, Suwannee; ,

doi:10.30880/jtet.2023.15.04.012

Cited by 3 publications

(1 citation statement)

References 7 publications

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“…Hybrid learning, blending traditional face-to-face instruction with online components, and distance learning, characterized by the delivery of education remotely, have gained prominence as viable alternatives to traditional classroom settings [10]. This shift has been accelerated by advancements in technology, the proliferation of online resources, and the increasing demand for lifelong learning opportunities [11]- [15].…”

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confidence: 99%

Bibliometric Analysis of Hybrid and Distance Learning Literature in the Digital Age

Mardiani,

Riniati,

Mokodenseho

et al. 2024

Learn. Educ.

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This bibliometric analysis delves into the literature on hybrid and distance learning within the digital age, examining its evolution, trends, and impact. Through systematic retrieval and analysis of scholarly outputs from 1980 to 2024, key bibliometric metrics, network visualizations, and citation analyses were conducted. The findings reveal a significant transition from traditional to technical research themes over time, reflecting broader societal shifts towards data-driven decision-making. Highly cited works underscore the enduring relevance of foundational concepts and the timely exploration of emergent topics, particularly in response to the COVID-19 pandemic. Moreover, future study directions identified through network visualization offer promising avenues for advancing research agendas in education. This analysis provides valuable insights for educators, policymakers, and researchers, informing evidence-based decision-making and fostering interdisciplinary collaborations in educational innovation.

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Section: Introductionmentioning

confidence: 99%

Bibliometric Analysis of Hybrid and Distance Learning Literature in the Digital Age

Mardiani,

Riniati,

Mokodenseho

et al. 2024

Learn. Educ.

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Impact of Demographic Backgrounds by Humanities and Social Sciences Students on Their Psychological of Emotional Intelligence Skill: Structural Equation Multiple Cause and Multiple Indicator (SEM-MIMIC) Model

Kunchai

2024

IJSASR

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Background and Aims: Although the educational framework aims to develop employability skills, there is concern among establishments regarding educational policies and accredited bodies. However, it is not widely known that students in humanities and social sciences perceive general emotional intelligence skills. Part of the motivation to learn such skills stems from Work-Integrated Learning (WIL) programs and students' backgrounds. The development of these skills in higher education institutions often occurs through specific initiatives only, without a well-structured curriculum design framework. The conflict over the differences and interpretation of general skills across disciplines makes designing a framework more challenging. This study aims to 1) perform exploratory factor analysis and confirmatory factor analysis of emotional intelligence skills for students in Work-Integrated Learning (WIL) programs within the humanities and social sciences, and 2) To examine a structural equation of multiple causes and multiple indicator (SEM-MIMIC) model of emotional intelligence skills for students in WIL programs within the same fields using techniques that test the congruence between variables and confirm the relationship between individual variables and their respective components. Methodology: This cross-sectional research and stratified random sampling and online questionnaire were conducted among 780 third and fourth-year humanities and social sciences WIL program students from eight universities in Thailand. The online survey consisted mainly of items that asked students to rate their level of self-efficacy in 28 general emotional intelligence skills. Exploratory and Confirmatory Factor analyses and SEM-MIMIC models were performed to examine the psychometric properties of the instrument to its evidence of reliability and validity. Results: Structural validity checks of the tool through exploratory and confirmatory factor analysis revealed that humanities and social sciences students returning from WIL programs of more than 16 weeks or one academic semester of the workplace have components of emotional intelligence skills, namely 1) emotional awareness, 2) emotional management, and 3) effective relationship management. Analysis using the Structural Equation Multiple Cause and Multiple Indicator (SEM-MIMIC) model showed that demographic variables such as gender, year level, cumulative grade point average, and major affect the development of emotional intelligence skills in humanities and social sciences students. The model's consistency with empirical data is demonstrated by the following values: ( = 832.892, df = 353, p = 0.000, / df = 2.360, CFI = 0.945, TLI = 0.924, RMSEA = 0.058, SRMR = 0.040). Conclusion: The analysis by the SEM-MIMIC model allows researchers to precisely understand how demographic backgrounds can impact emotional intelligence skills and that the measurement of these skills in humanities and social sciences students who have completed more than 16 weeks or one academic semester of workplace experience is beneficial for promoting WIL programs in these faculties. These programs can foster engagement with establishments, and career development advisors, and assist students in developing emotional intelligence skills for future livelihood and career advancement.

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Las nuevas demandas educativas en ingeniería industrial impulsadas por la automatización en la era digital

Enciso Huaman,

Fuchs Angeles

2024

SER

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En el mundo actual presidido por tecnologías emergentes como la automatización, la inteligencia artificial (IA), la robótica, el internet de las cosas (IOT), el big data y la realidad aumentada; la educación superior está atravesando un periodo de inminente transformación. Por ello, el presente artículo brinda una revisión bibliográfica detallada sobre las nuevas demandas educativas para la carrera de ingeniería industrial. Mediante la aplicación de un enfoque metodológico cualitativo, de carácter bibliográfico y documental, se realizó la selección y evaluación de 36 fuentes académicas contemporáneas, identificando los enfoques educativos, retos curriculares, las innovaciones pedagógicas y las competencias técnicas y blandas relevantes para la Industria 4.0. Como resultado del estudio, se destaca el dominio de programación, análisis de datos, robótica colaborativa, sistemas ciberfísicos, el trabajo en equipo, la adaptabilidad y el pensamiento crítico. En ese contexto, los planes de estudio de ingeniería industrial se están adaptando para incluir la enseñanza de estos nuevos conocimientos, con metodologías innovadoras como el aprendizaje basado en proyectos, simulaciones y el uso de realidad aumentada. También, se hace notar el papel protagónico que deben tener las universidades, primero superando los retos preexistentes, como la resistencia al cambio, las brechas de infraestructura, la actualización curricular y la de su plana docente. Además, potenciando sus capacidades de formación con el uso de la IA para la enseñanza. Por último, creando una red colaborativa entre universidades y con la industria, de manera que se pueda asegurar la calidad y vanguardia de los programas educativos.

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Transforming Industrial Engineering Education: Introducing the CWILE Model for Work-Integrated Learning in the Digital Age

Cited by 3 publications

References 7 publications

Bibliometric Analysis of Hybrid and Distance Learning Literature in the Digital Age

Bibliometric Analysis of Hybrid and Distance Learning Literature in the Digital Age

Impact of Demographic Backgrounds by Humanities and Social Sciences Students on Their Psychological of Emotional Intelligence Skill: Structural Equation Multiple Cause and Multiple Indicator (SEM-MIMIC) Model

Las nuevas demandas educativas en ingeniería industrial impulsadas por la automatización en la era digital

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