تقرير
A Deep Learning Approach for Automatic Detection of Qualitative Features of Lecturing
العنوان: | A Deep Learning Approach for Automatic Detection of Qualitative Features of Lecturing |
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المؤلفون: | Wroblewska, Anna, Jasek, Jozef, Jastrzebski, Bogdan, Pawlak, Stanislaw, Grzywacz, Anna, Ann, Cheong Siew, Chee, Tan Seng, Trzcinski, Tomasz, Holyst, Janusz |
المصدر: | International Conference on Artificial Intelligence in Education, AIED 2022 |
سنة النشر: | 2022 |
المجموعة: | Computer Science |
مصطلحات موضوعية: | Computer Science - Artificial Intelligence, Computer Science - Computers and Society, Computer Science - Machine Learning, Computer Science - Multimedia |
الوصف: | Artificial Intelligence in higher education opens new possibilities for improving the lecturing process, such as enriching didactic materials, helping in assessing students' works or even providing directions to the teachers on how to enhance the lectures. We follow this research path, and in this work, we explore how an academic lecture can be assessed automatically by quantitative features. First, we prepare a set of qualitative features based on teaching practices and then annotate the dataset of academic lecture videos collected for this purpose. We then show how these features could be detected automatically using machine learning and computer vision techniques. Our results show the potential usefulness of our work. Comment: 10 pages, 9 figures |
نوع الوثيقة: | Working Paper |
DOI: | 10.1007/978-3-031-11644-5_70 |
URL الوصول: | http://arxiv.org/abs/2205.14919 |
رقم الأكسشن: | edsarx.2205.14919 |
قاعدة البيانات: | arXiv |
DOI: | 10.1007/978-3-031-11644-5_70 |
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