Abstract
The rapid growth of Massive Open Online Courses (MOOCs) has revolutionized the education landscape by providing accessible and flexible learning opportunities. However, with the emergence of hybrid learning models, how to integrate MOOC into traditional classroom environments and effectively utilize MOOC video content in face-to-face teaching has become a current challenge. To solve this problem, we propose an instructive video locating system for MOOC hybrid teaching. The system analyzes teacher instructions and leverages technologies such as speech recognition, text segmentation, and natural language processing to easily locate relevant video clips in MOOC courses, enhancing the blended teaching experience. We conducted experiments using educational videos in MOOC online courses. The results show that the system can accurately locate video clips based on text queries. Compared with manual searches, the accuracy rate exceeds 85%, which significantly improves the efficiency of merging and supplementing multimedia content. The video locating system proposed in this article seamlessly integrates MOOC resources into the physical classroom through intelligent information retrieval, which not only enhances teaching flexibility and enriches hybrid teaching, but also lowers the technical threshold for teachers to use video assistance. This innovative application has great potential to promote the development and application of hybrid learning models in the education field.
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Acknowledgement
This work was supported by the grants of the following program: National Natural Science Foundation of China (NSFC, No. 62077004, 62177005)
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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Song, T., Li, M., Zhao, W. (2024). An Instructive Video Locating System for Hybrid Teaching with MOOC. In: Hong, W., Kanaparan, G. (eds) Computer Science and Education. Teaching and Curriculum. ICCSE 2023. Communications in Computer and Information Science, vol 2024. Springer, Singapore. https://doi.org/10.1007/978-981-97-0791-1_29
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DOI: https://doi.org/10.1007/978-981-97-0791-1_29
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