A Closer Look into Recent Video-based Learning Research: A Comprehensive Review of Video Characteristics, Tools, Technologies, and Learning Effectiveness

People increasingly use videos on the Web as a source for learning. To support this way of learning, researchers and developers are continuously developing tools, proposing guidelines, analyzing data, and conducting experiments. However, it is still not clear what characteristics a video should have to be an effective learning medium. In this paper, we present a comprehensive review of 257 articles on video-based learning for the period from 2016 to 2021. One of the aims of the review is to identify the video characteristics that have been explored by previous work. Based on our analysis, we suggest a taxonomy which organizes the video characteristics and contextual aspects into eight categories: (1) audio features, (2) visual features, (3) textual features, (4) instructor behavior, (5) learners activities, (6) interactive features (quizzes, etc.), (7) production style, and (8) instructional design. Also, we identify four representative research directions: (1) proposals of tools to support video-based learning, (2) studies with controlled experiments, (3) data analysis studies, and (4) proposals of design guidelines for learning videos. We find that the most explored characteristics are textual features followed by visual features, learner activities, and interactive features. Text of transcripts, video frames, and images (figures and illustrations) are most frequently used by tools that support learning through videos. The learner activity is heavily explored through log files in data analysis studies, and interactive features have been frequently scrutinized in controlled experiments. We complement our review by contrasting research findings that investigate the impact of video characteristics on the learning effectiveness, report on tasks and technologies used to develop tools that support learning, and summarize trends of design guidelines to produce learning video

A Tool for the Semantic Analysis and Recommendation of Videos in e-Learning

Video lessons are increasingly adopted in education, especially in universities and lifelong learning projects. Their popularity is due to the people's familiarity with video and to other intrinsic characteristics of this medium, such as the message rapidity and its reproducibility. Accordingly, Massive Open Online Courses are gaining a prominent role in both formal and informal education and many universities provide video courses for their students through suited platforms or even freely accessible to everyone. To improve the effectiveness of video lessons and to make them part of a wider learning environment, we decided to investigate the possibility of making a system that, starting from a video, can suggest further \u201creadings\u201d. Such a system is thought for independent lifelong learners, for regular students, for teachers and instructional designers as well