Enhance learning in a video lecture archive with annotations

Author(s):  
Martin Malchow ◽  
Matthias Bauer ◽  
Christoph Meinel
Keyword(s):  
Author(s):  
Мей Фан

The article analyzes the content of the concept of «multimedia», the content of multimedia technologies in higher education. The types of multimedia courses in the training of specialists in musical art are shown: video lecture, multimedia lecture, analogue educational publications. It has been proven that the introduction of multimedia technologies in the educational process improves the quality of training specialists in musical art.


Author(s):  
Elizaveta V. Variyasova ◽  
Elena A. Ivanova ◽  
Vera V. Karnyushina

The active development of digital technologies has had a significant impact on the educational process. Higher education institutions en masse switch to distance learning courses, vlogs, video hosting, popular science educational platforms. All of these platforms provide lectures in various branches of knowledge, regardless the curriculum, level of education, or even professional orientation. The development of modern media formats implies the possibility of active interaction with content. Can the format of video lecture meet these requirements? Or does the content consumer remain passive and cant influence anything? How long will such training format exist, and what are its prospects? In such rapidly changing conditions of life, the skills of flexibility and adaptation are applied to the educational process and teaching formats likewise. To improve the efficiency of work, everyone, including teachers, lecturers and students, needs to quickly adjust and adapt. The authors of the article attempted to explore the popularity and effectiveness of video lectures, identify the problems related to this form of teaching, and offer some possible solutions to create an educational model of online interaction that would promote the development of communication and learning skills.


Author(s):  
Oryina Kingsley Akputu ◽  
Kah Phooi Seng ◽  
Yun Li Lee

This chapter describes how a machine vision approach could be utilized for tracking learning feedback information on emotions for enhanced teaching and learning with Intelligent Tutoring Systems (ITS). The chapter focuses on analyzing learners’ emotions to show how affective states account for personalization or traceability for learning feedback. The chapter achieves this goal in three ways: (1) by presenting a comprehensive review of adaptive educational learning systems, particularly inspired by machine vision approaches; (2) by proposing an affective model for monitoring learners’ emotions and engagement with educational learning systems; (3) by presenting a case-based technique as an experimental prototype for the proposed affective model, where students’ facial expressions are tracked in the course of studying a composite video lecture. Results of the experiments indicate the superiority of such emotion-aware systems over emotion-unaware ones, achieving a significant performance increment of 71.4%.


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