Franka Grünewald

openHPI - A case-study on the emergence of two learning communities

Recently a new format of online education has emerged that combines video lectures, interactive quizzes and social learning into an event that aspires to attract a massive number of participants. This format, referred to as Massive Open Online Course (MOOC), has garnered considerable public attention, and has been invested with great hopes (and fears) of transforming higher education by opening up the walls of closed institutions to a world-wide audience. In this paper, we present two MOOCs that were hosted at the same platform, and have implemented the same learning design. Due to their difference in language, topic domain and difficulty, the communities that they brought into existence were very different. We start by describing the MOOC format in more detail, and the distinguishing features of openHPI. We then discuss the literature on communities of practice and cultures of participation. After some statistical data about the first openHPI course, we present our qualitative observations about both courses, and conclude by giving an outlook on an ongoing comparative analysis of the two courses.

Lecture Video Browsing Using Multimodal Information Resources

In the last decade e-lecturing has become more and more popular. The amount of lecture video data on the World Wide Web WWW is growing rapidly. Therefore, a more efficient method for video retrieval in WWW or within large lecture video archives is urgently needed. This paper presents an approach for automated video indexing and video search in large lecture video archives. First of all, we apply automatic video segmentation and key-frame detection to offer a visual guideline for the video content navigation. Subsequently, we extract textual metadata by applying video Optical Character Recognition OCR technology on key-frames and by performing Automatic Speech Recognition ASR on lecture audio tracks. The OCR and ASR transcript as well as detected slide text line types are adopted for keyword extraction, by which both video- and segment-level keywords are extracted respectively. Furthermore, we developed a content-based video search function and conducted a user study for evaluating the performance and the effectiveness of proposed indexing methods in our lecture video archive.

Next Generation Tele-Teaching: Latest Recording Technology, User Engagement and Automatic Metadata Retrieval

With the latest technological development in the last decade, new opportunities for learning environments and educational systems, such as tele-teaching, arose. Nowadays recording technology includes easy and fast workflows, high definition video recording, multiple sources and diverse output formats. With the amount of tele-teaching content growing, issues with sufficient metadata start existing. One solution is the user engagement. User engagement is based on the theory of the culture of participation and includes the usage of web 2.0 technology to activate students. This also has positive didactical side-effects. Another solution is the automatic creation of metadata. Therefore we have developed an automated framework by using video OCR (Optical Character Recognition) and ASR (Automated Speech Recognition) technologies. Indexable keywords are further extracted from those OCR and ASR transcripts.

Implementation and Evaluation of Digital E-Lecture Annotation in Learning Groups to Foster Active Learning

The use of video lectures in distance learning involves the two major problems of searchability and active user participation. In this paper, we promote the implementation and usage of a collaborative educational video annotation functionality to overcome these two challenges. Different use cases and requirements, as well as details of the implementation, are explained. Furthermore, we suggest more improvements to foster a culture of participation and an algorithm for the extraction of semantic data. Finally, evaluations in the form of user tests and questionnaires in a MOOC setting are presented. The results of the evaluation are promising, as they indicate not only that students perceive it as useful, but also that the learning effectiveness increases. The combination of personal lecture video annotations with a semantic topic map was also evaluated positively and will thus be investigated further, as will the implementation in a MOOC context.

Evaluating the Digital Manuscript Functionality --- User Testing for Lecture Video Annotation Features

In current tele-teaching platforms the main challenges for learners are searching and filtering through the content and staying focused on learning with the help of the e-lectures. Video annotation and video indexing features may provide support for learners in this situation. In this paper we will introduce one solution for a lecture video annotation feature called the digital manuscript. Digital notes can be written synchronously or asynchronously to the time of the actual lecture. Different features such as instant time markers and formatting options are available. In order to prove our hypothesis that the digital manuscript feature enables students to better concentrate on watching the video lecture and thus results in an improved learning effectiveness, we conducted a user study. The results include insights into the perceived usefulness of the annotation functionality as well as a quantitative comparison of assessment results with and without the manuscript feature and the indexing features as comparison. An outlook to group functionalities as well as a semantic extension of the video annotation feature is finally given.