@phdthesis{Rohloff2021, author = {Rohloff, Tobias}, title = {Learning analytics at scale}, doi = {10.25932/publishup-52623}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-526235}, school = {Universit{\"a}t Potsdam}, pages = {xvii, 138, lxvii}, year = {2021}, abstract = {Digital technologies are paving the way for innovative educational approaches. The learning format of Massive Open Online Courses (MOOCs) provides a highly accessible path to lifelong learning while being more affordable and flexible than face-to-face courses. Thereby, thousands of learners can enroll in courses mostly without admission restrictions, but this also raises challenges. Individual supervision by teachers is barely feasible, and learning persistence and success depend on students' self-regulatory skills. Here, technology provides the means for support. The use of data for decision-making is already transforming many fields, whereas in education, it is still a young research discipline. Learning Analytics (LA) is defined as the measurement, collection, analysis, and reporting of data about learners and their learning contexts with the purpose of understanding and improving learning and learning environments. The vast amount of data that MOOCs produce on the learning behavior and success of thousands of students provides the opportunity to study human learning and develop approaches addressing the demands of learners and teachers. The overall purpose of this dissertation is to investigate the implementation of LA at the scale of MOOCs and to explore how data-driven technology can support learning and teaching in this context. To this end, several research prototypes have been iteratively developed for the HPI MOOC Platform. Hence, they were tested and evaluated in an authentic real-world learning environment. Most of the results can be applied on a conceptual level to other MOOC platforms as well. The research contribution of this thesis thus provides practical insights beyond what is theoretically possible. In total, four system components were developed and extended: (1) The Learning Analytics Architecture: A technical infrastructure to collect, process, and analyze event-driven learning data based on schema-agnostic pipelining in a service-oriented MOOC platform. (2) The Learning Analytics Dashboard for Learners: A tool for data-driven support of self-regulated learning, in particular to enable learners to evaluate and plan their learning activities, progress, and success by themselves. (3) Personalized Learning Objectives: A set of features to better connect learners' success to their personal intentions based on selected learning objectives to offer guidance and align the provided data-driven insights about their learning progress. (4) The Learning Analytics Dashboard for Teachers: A tool supporting teachers with data-driven insights to enable the monitoring of their courses with thousands of learners, identify potential issues, and take informed action. For all aspects examined in this dissertation, related research is presented, development processes and implementation concepts are explained, and evaluations are conducted in case studies. Among other findings, the usage of the learner dashboard in combination with personalized learning objectives demonstrated improved certification rates of 11.62\% to 12.63\%. Furthermore, it was observed that the teacher dashboard is a key tool and an integral part for teaching in MOOCs. In addition to the results and contributions, general limitations of the work are discussed—which altogether provide a solid foundation for practical implications and future research.}, language = {en} } @phdthesis{Che2017, author = {Che, Xiaoyin}, title = {E-lecture material enhancement based on automatic multimedia analysis}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-408224}, school = {Universit{\"a}t Potsdam}, pages = {xviii, 148}, year = {2017}, abstract = {In this era of high-speed informatization and globalization, online education is no longer an exquisite concept in the ivory tower, but a rapidly developing industry closely relevant to people's daily lives. Numerous lectures are recorded in form of multimedia data, uploaded to the Internet and made publicly accessible from anywhere in this world. These lectures are generally addressed as e-lectures. In recent year, a new popular form of e-lectures, the Massive Open Online Courses (MOOCs), boosts the growth of online education industry and somehow turns "learning online" into a fashion. As an e-learning provider, besides to keep improving the quality of e-lecture content, to provide better learning environment for online learners is also a highly important task. This task can be preceded in various ways, and one of them is to enhance and upgrade the learning materials provided: e-lectures could be more than videos. Moreover, this process of enhancement or upgrading should be done automatically, without giving extra burdens to the lecturers or teaching teams, and this is the aim of this thesis. The first part of this thesis is an integrated framework of multi-lingual subtitles production, which can help online learners penetrate the language barrier. The framework consists of Automatic Speech Recognition (ASR), Sentence Boundary Detection (SBD) and Machine Translation (MT), among which the proposed SBD solution is major technical contribution, building on Deep Neural Network (DNN) and Word Vector (WV) and achieving state-of-the-art performance. Besides, a quantitative evaluation with dozens of volunteers is also introduced to measure how these auto-generated subtitles could actually help in context of e-lectures. Secondly, a technical solution "TOG" (Tree-Structure Outline Generation) is proposed to extract textual content from the displaying slides recorded in video and re-organize them into a hierarchical lecture outline, which may serve in multiple functions, such like preview, navigation and retrieval. TOG runs adaptively and can be roughly divided into intra-slide and inter-slides phases. Table detection and lecture video segmentation can be implemented as sub- or post-application in these two phases respectively. Evaluation on diverse e-lectures shows that all the outlines, tables and segments achieved are trustworthily accurate. Based on the subtitles and outlines previously created, lecture videos can be further split into sentence units and slide-based segment units. A lecture highlighting process is further applied on these units, in order to capture and mark the most important parts within the corresponding lecture, just as what people do with a pen when reading paper books. Sentence-level highlighting depends on the acoustic analysis on the audio track, while segment-level highlighting focuses on exploring clues from the statistical information of related transcripts and slide content. Both objective and subjective evaluations prove that the proposed lecture highlighting solution is with decent precision and welcomed by users. All above enhanced e-lecture materials have been already implemented in actual use or made available for implementation by convenient interfaces.}, language = {en} } @phdthesis{Hu2006, author = {Hu, Ji}, title = {A virtual machine architecture for IT-security laboratories}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-7818}, school = {Universit{\"a}t Potsdam}, year = {2006}, abstract = {This thesis discusses challenges in IT security education, points out a gap between e-learning and practical education, and presents a work to fill the gap. E-learning is a flexible and personalized alternative to traditional education. Nonetheless, existing e-learning systems for IT security education have difficulties in delivering hands-on experience because of the lack of proximity. Laboratory environments and practical exercises are indispensable instruction tools to IT security education, but security education in conventional computer laboratories poses particular problems such as immobility as well as high creation and maintenance costs. Hence, there is a need to effectively transform security laboratories and practical exercises into e-learning forms. In this thesis, we introduce the Tele-Lab IT-Security architecture that allows students not only to learn IT security principles, but also to gain hands-on security experience by exercises in an online laboratory environment. In this architecture, virtual machines are used to provide safe user work environments instead of real computers. Thus, traditional laboratory environments can be cloned onto the Internet by software, which increases accessibility to laboratory resources and greatly reduces investment and maintenance costs. Under the Tele-Lab IT-Security framework, a set of technical solutions is also proposed to provide effective functionalities, reliability, security, and performance. The virtual machines with appropriate resource allocation, software installation, and system configurations are used to build lightweight security laboratories on a hosting computer. Reliability and availability of laboratory platforms are covered by a virtual machine management framework. This management framework provides necessary monitoring and administration services to detect and recover critical failures of virtual machines at run time. Considering the risk that virtual machines can be misused for compromising production networks, we present a security management solution to prevent the misuse of laboratory resources by security isolation at the system and network levels. This work is an attempt to bridge the gap between e-learning/tele-teaching and practical IT security education. It is not to substitute conventional teaching in laboratories but to add practical features to e-learning. This thesis demonstrates the possibility to implement hands-on security laboratories on the Internet reliably, securely, and economically.}, subject = {Computersicherheit}, language = {en} } @phdthesis{Schwarz2005, author = {Schwarz, Jan-Arne}, title = {Kommunikation von Geoinformation}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-6018}, school = {Universit{\"a}t Potsdam}, year = {2005}, abstract = {Die effektive Erzeugung von Wissen ist eine der zentralen Herausforderungen des 21. Jahrhunderts. Informations- und Kommunikationstechnologien, wie die Neuen Medien, durchdringen alle Bereiche des t{\"a}glichen Lebens. Sie erm{\"o}glichen den Zugriff auf gigantische Datenmengen, die die Grundvoraussetzung f{\"u}r die Generierung von Wissen darstellen, aber gleichzeitig eine Datenflut bedeuten, der wir ohnm{\"a}chtig gegen{\"u}berstehen. Innerhalb der raumwissenschaftlichen Fachdisziplinen spielen die Neuen Medien f{\"u}r die Kommunikation von Sachinformation eine wichtige Rolle. Die internetbasierte Distribution von Karten, angereichert mit zus{\"a}tzlichen Informationen in Form von Audiosequenzen oder Filmausschnitten, spiegelt diese Entwicklung wieder. Vor diesem Hintergrund erfolgt die Untersuchung der Frage, ob Neue Medien dazu genutzt werden k{\"o}nnen, raumwissenschaftliche Fachinhalte zu vermitteln. Von besonderem Interesse ist dabei die Frage, ob durch den Einsatz Neuer Medien in der Lehre ein Mehrwert f{\"u}r die Benutzer entsteht. Der Ausgangspunkt dieser Forschungsfrage besteht in der herausragenden Bedeutung von Visualisierung zur leicht verst{\"a}ndlichen Darstellung komplexer Sachverhalte, sowie der entsprechenden Werkzeug- und Methodenkompetenz f{\"u}r die Nutzung Neuer Medien in den raumwissen-schaftlichen Disziplinen. Die Grundlage f{\"u}r die Entwicklung von mehrwertigen Lernangeboten ist die Betrachtung von Lernen als Kommunikationsprozess zur Konstruktion von Wissen, was bedeutet, dass der Entwickler derartiger Angebote {\"u}ber M{\"o}glichkeiten zur Optimierung dieses Kommunikationsprozesses verf{\"u}gt. Auf dieser Basis erfolgt eine Erweiterung des in den raumwissenschaftlichen Disziplinen verwendeten Kommunikationsbegriffs um den Aspekt der Lehre von Fachinhalten. Als relevante Ansatzpunkte f{\"u}r die Optimierung der Kommunikation von Fachinhalten werden die didaktische und die mediale Aufbereitung identifiziert. Diese k{\"o}nnen zum einen die Motivation der Lernenden positiv beeinflussen und zum anderen durch Wirkung auf die Wahrnehmung der Lernenden zu einem vereinfachten Verst{\"a}ndnis beitragen. Im Mittelpunkt der didaktischen Aufbereitung steht die problemorientierte Vermittlung der Inhalte, d.h. sie werden anhand konkreter Problemsituationen aus der Praxis vermittelt und gelten deshalb als besonders anschaulich und anwendungsorientiert. Bei der medialen Aufbereitung steht die Verwendung einer Kombination aus Text und Graphik/Animation im Mittelpunkt, die darauf abzielt, das Verstehen komplexer Sachverhalte zu erleichtern. Zur {\"U}berpr{\"u}fung der Forschungsfrage haben Studierende raumwissenschaftlicher Studieng{\"a}nge der Universit{\"a}t Potsdam das Lernangebot ausprobiert und anhand eines Fragebogens verschiedene Aspekte bewertet. Themenschwerpunkt dieser Evaluation waren die Akzeptanz, die Bedienbarkeit, die didak-tische und mediale Aufbereitung der Inhalte, die Auswahl und Verst{\"a}ndlichkeit der Inhalte sowie die Praxistauglichkeit. Ein Großteil der Befragten hat dem Lernangebot einen Mehrwert gegen{\"u}ber konventionellen Bildungsangeboten bescheinigt. Als Aspekte dieses Mehrwertes haben sich vor allem die Praxisn{\"a}he, die Unabh{\"a}ngigkeit von Zeit und Ort bei der Nutzung und die Vermittlung der Inhalte auf der Grundlage einer Kombination aus Text und interaktiven Animationen herauskristallisiert.}, subject = {Geoinformation}, language = {de} }