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The impact of the digital environment on the “industry-teaching integration and collaborative education” of colleges and universities is increasing day by day, and the optimization and improvement of the related working mechanisms in applied colleges and universities is urgent. The study uses the triple helix model to discuss how “industry-teaching integration and collaborative education” work in digitalized applied colleges and universities. It also builds a model of “industry-teaching integration and collaborative education” using PLS-SEM and tests it using AMOS software. AMOS software was used to empirically test the model. It was discovered that the five factors—incentive mechanism, leadership mechanism, constraint mechanism, communication mechanism, and guarantee mechanism—have various levels of positive and significant impacts on the process of “industry-teaching integration and collaborative education” in universities (P<0.05). Based on this, it is suggested that applied colleges and universities should focus on improving the four mechanisms of scientific and technological achievements sharing mechanism, digital infrastructure guarantee mechanism, practice platform operation mechanism, and digital teaching management mechanism so as to ensure the high-quality cultivation of digital applied talents.
The impact of the digital environment on the “industry-teaching integration and collaborative education” of colleges and universities is increasing day by day, and the optimization and improvement of the related working mechanisms in applied colleges and universities is urgent. The study uses the triple helix model to discuss how “industry-teaching integration and collaborative education” work in digitalized applied colleges and universities. It also builds a model of “industry-teaching integration and collaborative education” using PLS-SEM and tests it using AMOS software. AMOS software was used to empirically test the model. It was discovered that the five factors—incentive mechanism, leadership mechanism, constraint mechanism, communication mechanism, and guarantee mechanism—have various levels of positive and significant impacts on the process of “industry-teaching integration and collaborative education” in universities (P<0.05). Based on this, it is suggested that applied colleges and universities should focus on improving the four mechanisms of scientific and technological achievements sharing mechanism, digital infrastructure guarantee mechanism, practice platform operation mechanism, and digital teaching management mechanism so as to ensure the high-quality cultivation of digital applied talents.
The rapid expansion of generative artificial intelligence tools for textual production, such as ChatGPT, has been accompanied by a proliferation of similar tools used for creating images, audiovisual content, and motion graphics. These tools, valued for their creativity, are increasingly employed in the fields of art, education, and entertainment to enhance content creation, particularly on social media, while also reducing production costs. However, their use is not without controversy, as they raise significant ethical concerns, including the potential for generating fake news and disinformation. This paper presents an analysis of higher education students’ perspectives on the use of generative artificial intelligence tools within the context of a university course. The research was conducted through semi-structured interviews with 10 fourth-year students from the Department of Communication and Digital Media at the University of Western Macedonia. The study aims to provide an initial understanding of the impact of these tools in both education and communication, focusing on students who are future professionals in the communication field. The interviews explored the potential benefits of these technologies, which were valued highly, and the challenges presented such as privacy and credibility issues, which concerned the participants. Misinformation and deception were cited as the most significant risks, while these tools were evaluated positively in terms of communicative purposes, but still maintaining skepticism.
Climate change is a significant and urgent threat, gaining traction in the scientific community around the globe and requiring immediate action across many sectors. In this context, the digital economy could provide a mutually beneficial solution by utilizing innovation and technical breakthroughs to establish a sustainable future that addresses environmental deterioration, promotes economic growth, and encourages energy conservation. Against this background, this study examined the diffusion of innovation modeling-based factors affecting small and medium-sized firms’ (SMFs) adoption of the Internet of Things (IoT) technology and its impact on SMFs’ sustainability performance related to environmental, economic, innovation, and energy conservation perspectives. The key findings revealed that (i) the relative advantage, trialability, and observability drive IoT adoption. However, compatibility and complexity hinder IoT adoption. (ii) When prioritizing the adoption factors, the relative benefit is the strongest driver, and compatibility is the most significant barrier to IoT adoption. (iii) IoT technology adopter SMFs spent less on natural resources and more on renewable energy and environmental monitoring systems than non-adopter firms, boosting their environmental sustainability. (iv) IoT technology adopter firms had greater revenue, profits, and credit access than non-adopters and lower input costs, improving their economic sustainability. (v) IoT adopter firms spent more on innovative products than non-adopter enterprises, demonstrating innovation performance. (vi) Compared to non-adopter firms, IoT technology adopter SMFs had lower utility expenses and spent more on energy-efficient technologies. (vii) To realize the full potential of the IoT for a more sustainable and inventive future, authorities may pursue a variety of policy actions involving the strengthening and implementation of IoT technology standards and regulations, securing the incentivization of financial resources to SMFs, diverting the allocation of resources to research and development avenues, prioritizing the capacity development and environmental awareness, and focusing on IoT infrastructure development.
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