Education Research and Development is an international, peer-reviewed open access journal dedicated to advancing research the field of education. The journal provides a rapid publication process to ensure wide dissemination of high-quality articles to scientists, professionals, and interested individuals worldwide. Our goal is to serve as an efficient, reliable, and trusted platform for scholars and readers, publishing cutting-edge research in the field.
Abstract: This study explores the role of educational large language models in the digital transformation of engineering courses. A four-in-one transformation framework is constructed, covering teaching content, teaching modes, practical components, and teaching evaluation. The core course, Facility Planning in the Industrial Engineering program, is selected for instructional experimentation. In terms of teaching content, a knowledge graph is generated through a large language model, and industry-oriented frontier cases are dynamically produced. In teaching modes, the instructional workflow before, during, and after class is reshaped through an AI-supported dual-teacher collaboration mechanism. In the practical component, a facility-planning system integrating the DeepSeek model and the Systematic Layout Planning (SLP) method is developed. Natural-language interaction enables the full workflow from data analysis to solution optimization, supporting intelligent design training that follows the sequence of input, analysis, generation, and optimization. In teaching evaluation, a comprehensive system is adopted by combining process-based data with multi-dimensional capability assessment. Empirical results from one semester indicate significant improvements in students’ engagement, abilities to solve complex engineering problems, and systems thinking. Meanwhile, the teacher’s role gradually shifts from knowledge transmitter to learning facilitator and context designer. The proposed framework and its implementation path may serve as a reference for digital reform in other engineering courses. Future work extends to domain-specific model development, cross-course application, and the construction of shared resource ecosystems.Abstract: This study explores the role of educational large language models in the digital transformation of engineering courses. A four-in-one transformation framework is constructed, covering teaching content, teaching modes, practical components, and teaching evaluation. The core course, Facility Planning in the Industrial Engineering program, is selected...Learn More
Abstract: Private higher vocational colleges constitute a vital component of Chongqing’s higher vocational education system, making significant contributions to the its economic and social development. As modern vocational education enters a new phase, accelerating the development of private higher vocational colleges in Chongqing is a crucial measure for achieving high-quality development. However, numerous practical challenges persist in areas such as funding sources, faculty development, and industry-education integration mechanisms, hindering the accelerated advancement of these institutions’ connotation construction. In light of this, the paper analyzes the specific challenges faced by Chongqing’s private higher vocational colleges in their connotation construction from the perspectives of funding sources, faculty development, and industry-education integration mechanisms, based on in-depth research and multi-dimensional data analysis and verification. Then, to address the challenge of funding constraints, practical pathways to overcome these challenges are proposed through broadening resource channels, optimizing resource allocation, and deepening industry-education integration. To address the challenge of faculty development, practical pathways are proposed through implementing targeted talent recruitment initiatives, innovating growth-empowering models, and refining diversified incentive mechanisms. To tackle the challenge of industry-education integration mechanisms, practical pathways are proposed through innovating benefit-sharing models, improving corporate governance structures, and clarifying property rights and the capitalization of innovation factors. The paper aims to provide insights for overcoming the practical difficulties encountered by Chongqing’s private higher vocational colleges in advancing their connotation construction, thereby contributing to the high-quality development of modern vocational education in Chongqing.Abstract: Private higher vocational colleges constitute a vital component of Chongqing’s higher vocational education system, making significant contributions to the its economic and social development. As modern vocational education enters a new phase, accelerating the development of private higher vocational colleges in Chongqing is a crucial measure for ac...Learn More
Abstract: Grounded in the Interaction Hypothesis, this study investigates the mechanisms underlying digital human-driven collaborative English speaking learning. Addressing the persistent problem of interaction fossilization in computer-supported collaborative learning, the study argues that learners’ low willingness to communicate and insufficient collaborative scaffolding often prevent peer interaction from developing into meaningful negotiation of meaning. Against this backdrop, digital human companions—characterized by multimodal interaction and enhanced social presence—are examined as potential mediators of interactional conditions conducive to second language acquisition. Drawing on interactionist theory, the study proposes a three-dimensional closed-loop interaction mechanism consisting of Pre-adaptation, Process Synergy, and Feedback Iteration. The pre-adaptation dimension calibrates learner profiles, task design, and affective readiness to establish optimal conditions for interaction. The process synergy dimension focuses on sustaining negotiation of meaning through scaffolded interaction, clarification requests, and prompts that encourage pushed output. The feedback iteration dimension embeds non-intrusive, data-driven corrective feedback and affective regulation into ongoing interaction, enabling continuous adjustment of task difficulty and interaction strategies. Theoretically, the proposed mechanism extends interactionist explanations of language learning to multimodal, human–AI collaborative environments. Practically, it offers a structured and implementable framework for designing intelligent speaking tasks that enhance interaction depth, feedback quality, and learner engagement. The study concludes that digital human companions can function as interactional facilitators rather than mere tools, supporting the transition from superficial participation to sustained, meaning-focused collaborative speaking.Abstract: Grounded in the Interaction Hypothesis, this study investigates the mechanisms underlying digital human-driven collaborative English speaking learning. Addressing the persistent problem of interaction fossilization in computer-supported collaborative learning, the study argues that learners’ low willingness to communicate and insufficient collabora...Learn More
