Order	Time	ID	Full information
1	15:30-15:45	IT1027	AI-enabled Design and Practice of Blended Teaching of "Fundamentals of Circuit Analysis" Author(s): Chen Feng, Xinmin Ren, Mai Yan, Haoyi Ji, Lijian Zhou Presenter: Chen Feng, Ocean University of China, China Abstract: To address the issue of insufficient internalization of knowledge into ability in the online and offline blended teaching of the "Fundamentals of Circuit Analy-sis" course, AI technologies such as knowledge graphs and Deepseek are inte-grated to assist teachers in designing a new blended teaching plan that com-bines "classroom chain thinking" with "online transfer learning", and to achieve personalized learning and critical thinking cultivation for students through the Rain Classroom platform. The score data of classroom teaching and offline learning were collected for analysis. The results show that com-pared with the traditional blended teaching scheme, in the practice of the AI-enabled blended teaching scheme, classroom teaching and online learning have a stronger correlation. The results show that the AI-enabled blended teaching plan can enhance students' online learning efficiency and improve their mastery of knowledge points.
2	15:45-16:00	IT2112	Bridging the Gap Between Construction and Application: A Policy-Driven Model for Enhancing MOOC Effectiveness in Universities Author(s): Chen Gu, Haiyan Wang Presenter: Chen Gu, Nanjing University of Posts and Telecommunications, China Abstract: A significant gap persists between the scale of Massive Open Online Course (MOOC) construction and its practical integration into teaching, limiting the realization of its educational potential. To explore systematic strategies for enhancing MOOC effectiveness, this study proposes and examines a “Policy-Driven MOOC Ecosystem Model.” Based on an in-depth, longitudinal case study of a Chinese research university, the research employs a mixed-methods approach combining policy text analysis, quantitative performance data, and qualitative interviews.  The findings indicate that bridging the “construction-application” gap requires synergistic institutional design at the university level. The validated model comprises four core, interacting mechanisms: An Incentive and Recognition Mechanism formally links MOOC outcomes to faculty evaluation and reward systems; a Quality and Standard Mechanism regulates the course development lifecycle with clear technical and pedagogical specifications; a Support and Service Mechanism provides comprehensive, proactive assistance from training to technical implementation; and an Assessment and Feedback Mechanism utilizes learning analytics to drive evidence-based, continuous improvement of both courses and policies. Empirical evidence demonstrates that under this integrated framework, the case university’s MOOCs achieved not only scaled construction (over 200 courses launched) but also deep, impactful application. Its courses have been adopted by nearly 200 universities nationwide, with student enrollment ranking among the highest in the country. This has effectively facilitated the cross-institutional flow of high-quality resources and made technology-enhanced blended learning a pedagogical norm. The study concludes that the successful transition of MOOCs from isolated digital resources to deeply integrated teaching practices necessitates robust, top-down policy architecture. The proposed model offers a practical, systemic framework to guide higher education institutions globally in using strategic policy interventions to transform digital course investments into tangible educational impact, with implications for promoting educational quality and equity.
3	16:00-16:15	IT2139	A Review of Research, Hot Topics and Emerging Trends in Massive Open Online Course for Undergraduate Education: A Bibliometric Analysis Author(s): Xinru Zhao, Zhixiong Tang, Wanru Zhao, Ruixin Chen, Peng Jiao Presenter: Wanru Zhao, Guangxi University of Finance and Economics, China Abstract: To elucidate the research evolution, hot topics, and future development trends of Massive Open Online Course (MOOC) in undergraduate education, a bibliometric analysis was conducted on relevant literature from 2014 to 2024. The analysis utilized publications sourced from the Web of Science core database and employed bibliometric analysis tools CiteSpace and VOSviewer. The findings clarify the annual publication trends, disciplinary distribution, the most influential and productive authors, institutions, and country/region distribution of research on MOOC in undergraduate teaching, thereby revealing the research development over the past decade and future research trends in this field. After an initial nascent phase, research on MOOC in undergraduate teaching entered a phase of rapid growth post-2019 and transitioned into a stable development phase around 2022. Research disciplines are concentrated primarily in the fields of Education Educational Research and Computer Science, indicating a relatively focused disciplinary development. The United States of America, People's Republic of China and Spain are the three countries with the most prominent research contributions. The University of Tasmania, Massachusetts Institute of Technology, and Central China Normal University are the institutions with notable contributions. Keyword cluster analysis reveals seven main research hot topics, including mooc learner, scoping review, systematic mapping study, continuance intention, massive open online courses, deep learning model and using machine. Keyword burst detection and timeline analysis indicate that future research on MOOC in undergraduate education will center on learners, deepen the integration of technologies such as artificial intelligence and deep learning with teaching, and thereby enhance teaching effectiveness.
4	16:15-16:30	IT2144	Construction and Practice of Blended Online and Offline Teaching Mode in Engineering Drawing Author(s): Yanjiang Zhao, Jingshu Hu, Yue Meng, Xin Tong Presenter: Yanjiang ZHAO School of Mechanical and Power Engineering, Harbin University of Science and Technology, China Abstract: Based on the characteristics and objectives of the  engineering drawing course, this study has developed a blended  learning model that combines online and offline teaching methods.  Through systematic resource construction, data-driven classroom  interaction, and continuous project practice, a closed-loop  mechanism of teaching, evaluation, feedback and optimization has  been formed. Teaching practice has shown that this model  effectively improves students’ academic performance, learning  engagement, and achievement of drawing competencies.
5	16:30-16:45	IT2151	Project-Based Flipped Classroom Reform with Interactive and Collaborative Approaches Author(s): Ning Ye, Xiaoshi Song, Rong Geng, Ce Ji Presenter: Ning Ye, Northeastern University, China Abstract: This paper presents a novel project-based flipped classroom model that synthesizes two core innovations: Guided Learning-Mutual Growth and Symbiotic Co-Creation. The three-stage, four-dimensional teaching architecture integrates teacher demonstration, collaborative research, and student-led practice with competency development in critical thinking, engineering implementation, innovation breakthroughs, and collaborative leadership. By embedding authentic industrial case studies and implementing AI-assisted scaffolding, the framework enables dynamic optimization of instruction and competency cultivation. The model demonstrates significant empirical outcomes: students achieve an autonomous task completion rate of 85% or higher, which notably exceeds the 51% observed in traditional classrooms. Furthermore, team innovation proposal acceptance shows a 60% increase from a baseline of 34%, while enterprise evaluation of job-role alignment improves by 40% from a baseline of 27%. These results validate the effectiveness of applying the gradual release of responsibility teaching theory to engineering education.
6	16:45-17:00	IT2163	AI-Enabled Blended Teaching Practices in Design Courses: A Study Using the National Exhibition Resource Repository Author(s): Zhen Liu, Meng Zhou, Muzi Wang, Zheng Tan Presenter: Zhen Liu, Hubei Light Industry Technology Institute, China Abstract: This study addresses persistent challenges in higher education design curricula, including the misalignment between disciplinary knowledge and industry needs, limited integration of artificial intelligence (AI), and low student engagement. It proposes an AI-enabled blended teaching model supported by the National Exhibition Resource Repository. Built upon industry-standard management software and integrated national-level resource platforms, the model constructs a closed-loop instructional process encompassing digital resource retrieval, intelligent design, project presentation, immersive experience, and enterprise evaluation.Empirical results indicate that the model increased enterprise adoption of student projects by 27.3%, reduced the design revision cycle by 41.2%, and significantly enhanced both teaching efficiency and the practical applicability of learning outcomes. The study further develops a tripartite instructional architecture integrating technical tools, resource repositories, and industry demands. By employing AI to reorganize the knowledge structure of exhibition design, a three-dimensional network linking courses, modules, and knowledge points is established to support systematic learning.Through the reconstruction of authentic learning scenarios, students engage in offline project design via online collaborative platforms, enabling cross-regional and asynchronous collaboration. Enterprises and social learners can access repository resources via mobile devices, overcoming traditional spatial and temporal constraints. The research additionally constructs an AI-enhanced dynamic case library comprising 12 enterprise projects and an industry-oriented intelligent assessment system with an evaluation accuracy of 89.6%. Overall, the model offers a replicable paradigm for advancing blended teaching practices and promoting the digital transformation of design education.
7	17:00-17:15	IT3203	Enhancing Student Learning Engagement for the Islamic Finance Course: A Case Study of an Interactive Learning Author(s): Syeliya Md Zaini, Noor Azlin Mohd Kasim, Kania Nurcholisah Presenter: Syeliya Md Zaini, Faculty of Accountancy, Universiti Teknologi MARA, Malaysia Abstract: Interactive learning, characterised by active participation, collaborative engagement, and the integration of dynamic instructional tools, offers a vital pathway toward fostering educational sustainability. Nevertheless, learners frequently encounter significant challenges in theoretical courses, which affect their engagement, comprehension, and overall academic performance. The abstract and complex nature of theoretical concepts often creates cognitive difficulty. Additionally, limited perceived relevance and challenges in applying theory to practical scenarios can reduce motivation and hinder deep learning. These challenges underscore the need for more interactive, supportive, and contextually grounded teaching approaches to enhance the accessibility and sustainability of theoretical learning at the undergraduate level. This paper provides empirical evidence on interactive learning implemented in the Islamic Finance education course for accounting undergraduates in Malaysia. Interactive learning is assessed through students’ final assessment performance and feedback collected through surveys, interviews, and testimonials. The study demonstrates a significant average improvement of 13.63% in the experimental student group's performance. Further, positive student feedback underscores its effectiveness in utilising an interactive teaching and learning approach, promoting in-depth understanding, collaborative teaching, and interest in theoretical courses. The findings of this paper indicate that interactive learning is a cost-effective intervention that supports students in Islamic finance courses and enhances their cognitive, critical-thinking, creativity, teamwork, and interpersonal skills.
8	17:15-17:30	IT3257	The Integration of Artificial Intelligence into A Blended Course in an Elementary School Teacher Education Program: A Quasi-Experimental Study Author(s): Binbin Wu Presenter: Binbin Wu, Shanghai Normal University Tianhua College, China Abstract: Artificial Intelligence (AI) reshapes teaching methodologies, learning experiences, and the role of educators. The purpose of this study is to explore the integration of AI in a blended course in an elementary school teacher education program and examine the impact of the AI-empowered intervention on teacher candidates’ learning. This quantitative research design is quasi-experimental. “Educational Research Methods” is a required 16-week course for teacher candidates. The course in the intervention group adopted an AI-empowered blended teaching model combining online and offline learning. The AI-empowered online component is supported by the AI Workbench of Tianhua AI-course and the AI teaching assistant embedded within the Chaoxing Fanya Network Course Platform. The findings show that though the intervention did not significantly impact teacher candidates’ learning, an increment of their academic self-efficacy in the intervention group was evidenced. For future studies, the design of practical AI-empowered blended courses is needed. More training is needed for participants to master integrating AI tools in education. The intervention duration should also be sufficient.
9	17:30-17:45	IT3381	The Effects of Blended Learning in University Science Courses: A Meta-Analytic Review Author(s): Lingna Li, Nan Yao, Xinyue Hu, Lili Wang, Junhong Xie, Guopeng Zeng Presenter: Lingna Li, Southwest Petroleum University, China Abstract: As digital transformation in education advances, blended learning is evolving from an innovative approach into a mainstream format in higher education, signif-icantly reshaping traditional teaching ecosystems. Current research presents in-consistent findings on how blended learning affects student outcomes in under-graduate science courses. To address this, a meta-analysis was conducted, syn-thesizing 28 empirical studies from China and abroad. The results indicate that: (1) Blended learning has a moderately positive overall effect on learning out-comes in university science courses; (2) Regarding instructional design, full-semester duration, small class sizes, and a moderate proportion of online learning show stronger effectiveness; (3) In terms of instructional support, videos and reading materials play the most essential foundational role, while learning man-agement systems prove more effective than online meeting tools; (4) Regarding assessment, formative evaluation and data-driven comprehensive evaluation out-perform summative evaluation. Based on these findings, this study proposes building a blended learning system centered on “scientific cognitive principles”, aimed at systematically enhancing students disciplinary literacy and higher-order thinking skills through optimized course structure, deeper technology integration, and diversified assessment practices.
10	17:45-18:00	IT1010	Exploring and Cultivating Competency Structures for Cold Chain Logistics Personnel Using the LDA Topic Model under the OBE Framework Author(s): Fanfan Jia, Huichuan Dai Presenter: Fanfan Jia, Guangdong University Of Science &Technology Abstract: Cold chain logistics constitutes a critical industry safeguarding public welfare, with its high-quality development requiring support from highly skilled, multidisciplinary professionals. Addressing current issues such as the disconnect between talent cultivation and industry demands in cold chain logistics, this paper first employs the LDA topic model to mine textual data from online recruitment platforms concerning cold chain job descriptions. Through text prepossessing, tokenisation and vectorisation, model training, and topic consistency assessment, core job themes are extracted. Subsequently, these themes are interpreted and synthesized into a competency matrix for positions. Finally, guided by the Outcome-Based Education (OBE) philosophy, the competency matrix serves as the output target to reverse-engineer a talent development pathway for cold chain logistics. This research validates the LDA model's efficacy in educational needs analysis, while the proposed pathway offers a solution for overcoming industry-education integration challenges and transitioning talent cultivation from disciplinary logic to competency-based logic.