Order	Time	ID	Full information
1	15:30-15:45	IT1008	Research on LLMs-Based Multimodal Demand Perception and Flexible Adaptation of University Talent Development—An Intelligent Decision-Making Framework for Addressing the "Employment-Education Lag" Author(s): Jingru Cui, Hua Wen, Jun Liu, Jie Yang Presenter: Jingru Cui, Xi'an Jiaotong University, China Abstract: The acceleration of digital transformation and the shortening of technological iteration cycles have exacerbated the structural misalignment between the dynamic demands of the labor market and the talent cultivation systems in higher education institutions. Traditional matching models based on static job competency lists are increasingly inadequate in addressing the challenge of "employment-education lag". This study proposes an intelligent decision-making framework for dynamic adaptation. Through natural language processing driven by Large Language Models (LLMs) and Prompt Engineering, the accurate extraction and description of required skills and cultivated skills are realized. On this basis, the adaptation between the two is calculated using LLMs to achieve dynamic two-way calibration of supply and demand. This framework provides quantifiable decision support for industry-academia collaborative talent cultivation and facilitates the precise alignment of educational supply-side reform with industrial talent strategies.
2	15:45-16:00	IT1084	Exploration and Practice of a Training Model for Top Innovative Talents in Compiler Systems in the Context of Artificial Intelligence Author(s): Min Dong, Sheng Bi Presenter: Min Dong, South China University of Technology, China Abstract: The rapid advancement of artificial intelligence technology is driving profound transformations in the field of compiler systems. Based on years of teaching practice, this paper proposes and implements a novel training model for top innovative talents in compiler systems, characterized by "AI Empowerment + Multi-dimensional Integration". The model’s implmentation involves building an intelligent teaching system with a dynamic knowledge graph at its core, implementing a multi-dimensional integration strategy, a reformed curriculum, innovative teaching methods, and strengthened practical modules. The model has effectively boosted students' innovative capacities and engineering practice skills. Practice has shown its significant effectiveness in fostering student development and elevating teaching quality, providing a valuable reference for talent cultivation in China's foundational software industry.
3	16:00-16:15	IT3323	Construction of Dynamic Pathway for Graduation Project Topics Selection Under the “Industry-Science Education” Author(s): Jin-Gang Jiang, Rui Zhang, Tao Shen, Yu-Dong Bao, Jiang-Long Xiong, Jian-Peng Sun Presenter: Jiang Jingang, Harbin University of Science and Technology, China Abstract: As a crucial component of undergraduate education, the graduation project plays a key role in cultivating students' comprehensive abilities. The quality of its topic selection directly impacts the development of students' holistic competencies and their future professional adaptability. To address issues such as delayed updates to topics databases, insufficient personalized recommendations, and subjective evaluation criteria in the process of selecting graduation project topics, this study proposes the construction of a dynamic pathway and evaluation system for graduation project topics selection. This system is driven by a dual mechanism integrating "industry-education collaboration" and "scientific research-education synergy." By integrating enterprise demands, scientific research projects, and competition outcomes, a multi-dimensional topics sourcing mechanism is established. Furthermore, a multi-layer intelligent framework based on a knowledge graph—incorporating BiLSTM-CRF, TransE, and GAT—is introduced to achieve dynamic and personalized topic recommendations. Meanwhile, an evaluation index system encompassing four dimensions—innovativeness, practical value, feasibility, and comprehensive educational effectiveness—was developed. The analytic hierarchy process (AHP) was employed to determine the weights of each indicator, forming a scientific and quantifiable quality evaluation model. Empirical results demonstrate that this system significantly enhances topic-matching satisfaction, industry relevance, and students’ comprehensive capabilities, thereby providing an effective pathway for optimizing graduation project topic selection in higher education institutions.
4	16:15-16:30	IT2150	Construction and Practice of an AI-Empowered "Four-Dimensional Integration and Five-Stage Progressive" Experimental Teaching System for Mechanical Engineering Programs Author(s): Xiangfu Fu, Guochao Yu, Xuebing Li, Yaping Wang, Yuqi Fan Presenter: Xiangfu Fu, Harbin University of Science and Technology, China Abstract: In response to the demand for interdisciplinary and innovative mechanical engineering talent in the new era of engineering education, and to address persistent issues in traditional experimental teaching such as disciplinary barriers, theory-practice disconnection, and unidimensional assessment, this paper proposes and implements a novel AI-empowered "four-dimensional integration and five-stage progressive" experimental teaching system. Driven by artificial intelligence technology, this system constructs a new pedagogical framework based on knowledge graphs, digital twins, and intelligent agents, deeply integrating four dimensions: "discipline, theory-practice, university-industry, and ideological-political education," while systematically designing five progressive stages: "cognition, foundation, specialization, innovation, and advanced application." Practice demonstrates that this system effectively enhances the intelligence, personalization, and engineering orientation of experimental teaching. Students' comprehensive practical abilities, innovative spirit, and complex engineering problem-solving capabilities have been significantly strengthened, providing a replicable pathway for experimental teaching reform in mechanical engineering programs.
5	16:30-16:45	IT2166	Exploration of Practical Teaching Covers Application, Operation, Management, Research, and Development of DBMS Author(s): Deyou Tang, Ke Xu Presenter: Deyou Tang, South China University of Technolog, China Abstract: Database professionals consist of three levels: application-oriented, operation and maintenance-oriented, and kernel research & development (R&D)-oriented. Cur-rently, the curriculum in Chinese universities primarily focuses on cultivating ap-plication-level database talents, with insufficient cultivation for the latter two cate-gories, especially the shortage of talents capable of participating in kernel R&D. Kernel R&D talents need to be familiar with the architecture of database systems, possess experience in developing code for large-scale database systems, and re-quire cultivation through the integration of industry and education in real produc-tion scenarios. In response to the current state of database talent cultivation in universities, this paper designs a practical teaching system comprising 18 practi-cal modules based on openGauss. This system not only covers the cultivation of all three categories of database talents but also creates conditions for nurturing outstanding talents in the database field. The system has been executed three times, and 88.4% of students believe they benefited from the current practical teaching system. The course achievement rate has increased by 1.5%, and the teaching evaluation score has improved by 4.7%, demonstrating the effectiveness of the established practical teaching system.
6	16:45-17:00	IT3303	AI-Enabled Cultivation of Quantitative Thinking in Liberal Arts Students: An Innovative Integrated Teaching Case Based on the Tianhua Smart Learning Platform Author(s): Xiaoxia Huang Presenter: Xiaoxia Huang, Shanghai Normal University TIANHUA College, China Abstract: This case study presents an AI-enabled four-stage teaching model ("Cognitive Reshaping - Logical Foundation - Tool Application - Contextual Transfer") implemented in a mathematics course for 87 preschool education majors. Pre-course surveys revealed over 90% of students held misconceptions about mathematics. Post-intervention, average attendance reached 91.98%, mean score was 92.09 (SD=12.28), and score range was 4.8-100.0. The model effectively reduced math anxiety and enhanced quantitative thinking, providing a replicable paradigm for mathematics education in humanities disciplines.
7	17:00-17:15	IT2138	Campus Skill Mystery Box Bank: A Gamified Blockchain-Based Platform for  Knowledge Sharing Author(s): Yiping Ren, Xiaoyi Yu, Xueting Wang, Chenhe Zhang, Qiong Guo Presenter: Yiping Ren, Zhengzhou University, China Abstract: Implicit knowledge sharing among university students is often hindered by weak incentives, limited trust, and the difficulty of pricing non-standardized skills and experience. To address these issues, this paper proposes the Campus Skill Blind Box Bank, a campus-oriented knowledge-sharing platform that combines gamified interaction, consortium blockchain technology, and a token-based incentive mechanism. The platform bundles skills and experiential knowledge into digital skill mystery boxes to encourage participation, adopts Time Coins as a unified medium of exchange, and uses blockchain-based notarization to enhance transaction transparency and trust. In addition, a lightweight AI-assisted pricing mechanism is introduced to support more flexible valuation of heterogeneous knowledge resources. Based on a survey of 131 valid student responses, the feasibility of the proposed design is examined from the perspective of user acceptance and perceived risk. The results show that more than 85 percent of respondents express interest in using the platform. Precision-matching skill boxes and alumni-contributed career resources attract particularly strong attention, indicating students’ dual demand for immediate academic support and longer-term career guidance. At the same time, concerns related to time efficiency and privacy protection are identified as key design constraints. This paper presents the overall concept, system architecture, and governance logic of the platform, and discusses its limitations and directions for future validation and cross-campus deployment.
8	17:15-17:30	IT3380	Research on Intelligent Management Strategy of Graduation Project Moving Forward for "Optimizing Course Connection and Improving Topic Quality" Author(s): Jin-Gang Jiang, Jin-Xu Zhao, Tao Shen, Yu-Dong Bao, Jiang-Long Xiong, Kai-Rui Wang Presenter: Jiang Jingang, Harbin University of Science and Technology, China Abstract: To address common challenges in undergraduate thesis management—including inadequate course system support, inconsistent topic quality, and lax process oversight—this study proposes an intelligent pre-thesis management strategy focused on "optimizing course alignment and enhancing topic quality." By establishing a systematic implementation framework centered on course integration, supported by topic repository development and interdisciplinary resource integration, and implementing a comprehensive evaluation system based on AHP (Analytic Hierarchy Process), the strategy achieves quality monitoring and continuous improvement throughout the pre-thesis phase. The research innovatively introduces Knowledge Graph technology to construct a "course-competency-thesis" relationship graph, enabling precise course system support and personalized topic recommendations. Pilot implementation in related majors at Harbin Institute of Technology demonstrates that this strategy effectively improves the alignment between course content and thesis requirements, enhances topic relevance and cutting-edge relevance, and provides a systematic solution for reforming undergraduate thesis quality management.
9	17:30-17:45	IT4458	Digital Era Insights into Online Technical Readiness and Teaching Effectiveness: The Mediating Role of Teaching Presence Author(s): Yuxin Jiang, Yuxia Du, Yuli Li, Xuemin Gao, Daoming Fu, Mei Zhang Presenter: Yuxin Jiang, Guangdong University of Education, China Abstract: Under the dual imperatives of "digital transformation in education" and the "normalization of blended learning," online teaching has developed into an integral component of elementary education. However, effectively organiz-ing online classrooms, sustaining student attention, and ensuring the quali-ty of instructional interaction have emerged as pressing practical challenges for frontline teachers. To identify factors affecting the effectiveness of online teaching for primary school teachers and improve teaching quality, we developed a model that reveals the relationship between online teaching technical readiness, teaching presence, and teaching efficacy based on litera-ture and survey research. We analyzed data collected from 1,647 primary school teachers in China using SPSS. The data showed that online teaching technical readiness positively predicts online instructional efficacy and presence, with the latter partially mediating the effect of the former on online teaching efficacy. These findings have practical implications for im-proving teacher professional development and enhancing the abilities nec-essary for successful online teaching among primary school teachers, train-ers, principals, and researchers.