AI platform model on 4IR megatrend challenges: complex thinking by active and transformational learning

IF 4.7 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2024-02-06 DOI:10.1108/itse-07-2023-0145
Jorge Sanabria-Z, Pamela Geraldine Olivo
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Abstract

Purpose The objective of this study is to propose a model for the implementation of a technological platform for participants to develop solutions to problems related to the Fourth Industrial Revolution (4IR) megatrends, and taking advantage of artificial intelligence (AI) to develop their complex thinking through co-creation work. Design/methodology/approach The development of the model is based on a combination of participatory action research and user-centered design (UCD) methodologies, seeking to ensure that the platform is user-oriented and based on the experiences of the authors. The model itself is structured around the active and transformational learning (ATL) framework. Findings This study highlights the importance of addressing 4IR megatrends in education to prepare students for a technology-driven world. The proposed model, based on ATL and supported by AI, integrates essential competencies for tackling challenges and generating innovative solutions. The integration of AI into the platform fosters personalized learning, collaboration and reflection and enhances creativity by offering new insights and tools, whereas UCD ensures alignment with user needs and expectations. Originality/value This research presents an innovative educational model that combines ATL with AI to foster complex thinking and co-creation of solutions to problems related to 4IR megatrends. Integrating ATL ensures engagement with real-world problems and critical thinking while AI provides personalized content, tutoring, data analysis and creative support. The collaborative platform encourages diverse perspectives and collective intelligence, benefiting other researchers to better conceive learner-centered platforms promoting 21st-century skills and co-creation.
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应对 4IR 大趋势挑战的人工智能平台模型:通过主动学习和转型学习进行复杂思考
本研究的目的是提出一种技术平台的实施模式,供参与者开发与第四次工业革命(4IR)大趋势相关的问题的解决方案,并利用人工智能(AI)的优势,通过共同创造工作来发展他们的复杂思维。本研究强调了在教育中应对 4IR 大趋势的重要性,以便让学生为技术驱动的世界做好准备。所提出的模式以 ATL 为基础,以人工智能为支撑,整合了应对挑战和产生创新解决方案的基本能力。人工智能与平台的整合促进了个性化学习、协作和反思,并通过提供新的见解和工具提高了创造力,而用户中心设计则确保了与用户需求和期望的一致。整合 ATL 可确保参与解决现实世界中的问题并进行批判性思考,而人工智能则可提供个性化内容、辅导、数据分析和创意支持。该合作平台鼓励多元化视角和集体智慧,有利于其他研究人员更好地构思以学习者为中心的平台,促进 21 世纪技能和共同创造。
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来源期刊
CiteScore
7.20
自引率
4.30%
发文量
567
期刊介绍: ACS Applied Electronic Materials is an interdisciplinary journal publishing original research covering all aspects of electronic materials. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials science, engineering, optics, physics, and chemistry into important applications of electronic materials. Sample research topics that span the journal's scope are inorganic, organic, ionic and polymeric materials with properties that include conducting, semiconducting, superconducting, insulating, dielectric, magnetic, optoelectronic, piezoelectric, ferroelectric and thermoelectric. Indexed/​Abstracted: Web of Science SCIE Scopus CAS INSPEC Portico
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Issue Editorial Masthead Issue Publication Information Marking the 100th Issue of ACS Applied Electronic Materials Pushing down the Limit of Ammonia Detection of ZnO-Based Chemiresistive Sensors with Exposed Hexagonal Facets at Room Temperature Direct-Printed Mn–Ni–Cu–O/Poly(vinyl butyral) Composites for Sintering-Free, Flexible Thermistors with High Sensitivity
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