@misc{MalchowBauerMeinel2018, author = {Malchow, Martin and Bauer, Matthias and Meinel, Christoph}, title = {Enhance Learning in a Video Lecture Archive with Annotations}, series = {Proceedings of OF 2018 IEEE Global Engineering Education Conference (EDUCON)}, journal = {Proceedings of OF 2018 IEEE Global Engineering Education Conference (EDUCON)}, publisher = {IEEE}, address = {New York}, isbn = {978-1-5386-2957-4}, issn = {2165-9567}, pages = {849 -- 856}, year = {2018}, abstract = {When students watch learning videos online, they usually need to watch several hours of video content. In the end, not every minute of a video is relevant for the exam. Additionally, students need to add notes to clarify issues of a lecture. There are several possibilities to enhance the metadata of a video, e.g. a typical way to add user-specific information to an online video is a comment functionality, which allows users to share their thoughts and questions with the public. In contrast to common video material which can be found online, lecture videos are used for exam preparation. Due to this difference, the idea comes up to annotate lecture videos with markers and personal notes for a better understanding of the taught content. Especially, students learning for an exam use their notes to refresh their memories. To ease this learning method with lecture videos, we introduce the annotation feature in our video lecture archive. This functionality supports the students with keeping track of their thoughts by providing an intuitive interface to easily add, modify or remove their ideas. This annotation function is integrated in the video player. Hence, scrolling to a separate annotation area on the website is not necessary. Furthermore, the annotated notes can be exported together with the slide content to a PDF file, which can then be printed easily. Lecture video annotations support and motivate students to learn and watch videos from an E-Learning video archive.}, language = {en} } @misc{BauerMalchowMeinel2018, author = {Bauer, Matthias and Malchow, Martin and Meinel, Christoph}, title = {Improving access to online lecture videos}, series = {Proceedings of 2018 IEEE Global Engineering Education Conference (EDUCON)}, journal = {Proceedings of 2018 IEEE Global Engineering Education Conference (EDUCON)}, publisher = {IEEE}, address = {New York}, isbn = {978-1-5386-2957-4}, issn = {2165-9567}, doi = {10.1109/EDUCON.2018.8363361}, pages = {1161 -- 1168}, year = {2018}, abstract = {In university teaching today, it is common practice to record regular lectures and special events such as conferences and speeches. With these recordings, a large fundus of video teaching material can be created quickly and easily. Typically, lectures have a length of about one and a half hours and usually take place once or twice a week based on the credit hours. Depending on the number of lectures and other events recorded, the number of recordings available is increasing rapidly, which means that an appropriate form of provisioning is essential for the students. This is usually done in the form of lecture video platforms. In this work, we have investigated how lecture video platforms and the contained knowledge can be improved and accessed more easily by an increasing number of students. We came up with a multistep process we have applied to our own lecture video web portal that can be applied to other solutions as well.}, language = {en} } @misc{GawronChengMeinel2018, author = {Gawron, Marian and Cheng, Feng and Meinel, Christoph}, title = {Automatic vulnerability classification using machine learning}, series = {Risks and Security of Internet and Systems}, journal = {Risks and Security of Internet and Systems}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-76687-4}, issn = {0302-9743}, doi = {10.1007/978-3-319-76687-4_1}, pages = {3 -- 17}, year = {2018}, abstract = {The classification of vulnerabilities is a fundamental step to derive formal attributes that allow a deeper analysis. Therefore, it is required that this classification has to be performed timely and accurate. Since the current situation demands a manual interaction in the classification process, the timely processing becomes a serious issue. Thus, we propose an automated alternative to the manual classification, because the amount of identified vulnerabilities per day cannot be processed manually anymore. We implemented two different approaches that are able to automatically classify vulnerabilities based on the vulnerability description. We evaluated our approaches, which use Neural Networks and the Naive Bayes methods respectively, on the base of publicly known vulnerabilities.}, language = {en} } @article{ThienenClanceyCorazzaetal.2018, author = {Thienen, Julia von and Clancey, William J. and Corazza, Giovanni Emanuele and Meinel, Christoph}, title = {Theoretical foundations of design thinking creative thinking theories}, series = {Design Thinking Research: Making Distinctions: Collaboration versus Cooperation}, journal = {Design Thinking Research: Making Distinctions: Collaboration versus Cooperation}, publisher = {Springer}, address = {New York}, isbn = {978-3-319-60967-6}, doi = {10.1007/978-3-319-60967-6_2}, pages = {13 -- 40}, year = {2018}, abstract = {Design thinking is acknowledged as a thriving innovation practice plus something more, something in the line of a deep understanding of innovation processes. At the same time, quite how and why design thinking works-in scientific terms-appeared an open question at first. Over recent years, empirical research has achieved great progress in illuminating the principles that make design thinking successful. Lately, the community began to explore an additional approach. Rather than setting up novel studies, investigations into the history of design thinking hold the promise of adding systematically to our comprehension of basic principles. This chapter makes a start in revisiting design thinking history with the aim of explicating scientific understandings that inform design thinking practices today. It offers a summary of creative thinking theories that were brought to Stanford Engineering in the 1950s by John E. Arnold.}, language = {en} } @misc{PerlichMeinel2018, author = {Perlich, Anja and Meinel, Christoph}, title = {Cooperative Note-Taking in Psychotherapy Sessions}, series = {2018 IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom)}, journal = {2018 IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom)}, publisher = {IEEE}, address = {New York}, isbn = {978-1-5386-4294-8}, pages = {6}, year = {2018}, abstract = {In the course of patient treatments, psychotherapists aim to meet the challenges of being both a trusted, knowledgeable conversation partner and a diligent documentalist. We are developing the digital whiteboard system Tele-Board MED (TBM), which allows the therapist to take digital notes during the session together with the patient. This study investigates what therapists are experiencing when they document with TBM in patient sessions for the first time and whether this documentation saves them time when writing official clinical documents. As the core of this study, we conducted four anamnesis session dialogues with behavior psychotherapists and volunteers acting in the role of patients. Following a mixed-method approach, the data collection and analysis involved self-reported emotion samples, user experience curves and questionnaires. We found that even in the very first patient session with TBM, therapists come to feel comfortable, develop a positive feeling and can concentrate on the patient. Regarding administrative documentation tasks, we found with the TBM report generation feature the therapists save 60\% of the time they normally spend on writing case reports to the health insurance.}, language = {en} } @article{RezaeiYangMeinel2020, author = {Rezaei, Mina and Yang, Haojin and Meinel, Christoph}, title = {Recurrent generative adversarial network for learning imbalanced medical image semantic segmentation}, series = {Multimedia tools and applications : an international journal}, volume = {79}, journal = {Multimedia tools and applications : an international journal}, number = {21-22}, publisher = {Springer}, address = {Dordrecht}, issn = {1380-7501}, doi = {10.1007/s11042-019-7305-1}, pages = {15329 -- 15348}, year = {2020}, abstract = {We propose a new recurrent generative adversarial architecture named RNN-GAN to mitigate imbalance data problem in medical image semantic segmentation where the number of pixels belongs to the desired object are significantly lower than those belonging to the background. A model trained with imbalanced data tends to bias towards healthy data which is not desired in clinical applications and predicted outputs by these networks have high precision and low recall. To mitigate imbalanced training data impact, we train RNN-GAN with proposed complementary segmentation mask, in addition, ordinary segmentation masks. The RNN-GAN consists of two components: a generator and a discriminator. The generator is trained on the sequence of medical images to learn corresponding segmentation label map plus proposed complementary label both at a pixel level, while the discriminator is trained to distinguish a segmentation image coming from the ground truth or from the generator network. Both generator and discriminator substituted with bidirectional LSTM units to enhance temporal consistency and get inter and intra-slice representation of the features. We show evidence that the proposed framework is applicable to different types of medical images of varied sizes. In our experiments on ACDC-2017, HVSMR-2016, and LiTS-2017 benchmarks we find consistently improved results, demonstrating the efficacy of our approach.}, language = {en} } @article{SerthStaubitzvanEltenetal.2022, author = {Serth, Sebastian and Staubitz, Thomas and van Elten, Martin and Meinel, Christoph}, title = {Measuring the effects of course modularizations in online courses for life-long learners}, series = {Frontiers in Education}, volume = {7}, journal = {Frontiers in Education}, editor = {Gamage, Dilrukshi}, publisher = {Frontiers}, address = {Lausanne, Schweiz}, issn = {2504-284X}, doi = {10.3389/feduc.2022.1008545}, pages = {15}, year = {2022}, abstract = {Many participants in Massive Open Online Courses are full-time employees seeking greater flexibility in their time commitment and the available learning paths. We recently addressed these requirements by splitting up our 6-week courses into three 2-week modules followed by a separate exam. Modularizing courses offers many advantages: Shorter modules are more sustainable and can be combined, reused, and incorporated into learning paths more easily. Time flexibility for learners is also improved as exams can now be offered multiple times per year, while the learning content is available independently. In this article, we answer the question of which impact this modularization has on key learning metrics, such as course completion rates, learning success, and no-show rates. Furthermore, we investigate the influence of longer breaks between modules on these metrics. According to our analysis, course modules facilitate more selective learning behaviors that encourage learners to focus on topics they are the most interested in. At the same time, participation in overarching exams across all modules seems to be less appealing compared to an integrated exam of a 6-week course. While breaks between the modules increase the distinctive appearance of individual modules, a break before the final exam further reduces initial interest in the exams. We further reveal that participation in self-paced courses as a preparation for the final exam is unlikely to attract new learners to the course offerings, even though learners' performance is comparable to instructor-paced courses. The results of our long-term study on course modularization provide a solid foundation for future research and enable educators to make informed decisions about the design of their courses.}, language = {en} } @article{SteinbeckMeinel2023, author = {Steinbeck, Hendrik and Meinel, Christoph}, title = {What makes an educational video?}, series = {EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash?}, journal = {EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash?}, editor = {Meinel, Christoph and Schweiger, Stefanie and Staubitz, Thomas and Conrad, Robert and Alario Hoyos, Carlos and Ebner, Martin and Sancassani, Susanna and Żur, Agnieszka and Friedl, Christian and Halawa, Sherif and Gamage, Dilrukshi and Scott, Jeffrey and Kristine Jonson Carlon, May and Deville, Yves and Gaebel, Michael and Delgado Kloos, Carlos and von Schmieden, Karen}, publisher = {Universit{\"a}tsverlag Potsdam}, address = {Potsdam}, doi = {10.25932/publishup-62208}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-622086}, pages = {47 -- 58}, year = {2023}, abstract = {In an effort to describe and produce different formats for video instruction, the research community in technology-enhanced learning, and MOOC scholars in particular, have focused on the general style of video production: whether it is a digitally scripted "talk-and-chalk" or a "talking head" version of a learning unit. Since these production styles include various sub-elements, this paper deconstructs the inherited elements of video production in the context of educational live-streams. Using over 700 videos - both from synchronous and asynchronous modalities of large video-based platforms (YouTube and Twitch), 92 features were found in eight categories of video production. These include commonly analyzed features such as the use of green screen and a visible instructor, but also less studied features such as social media connections and changing camera perspective depending on the topic being covered. Overall, the research results enable an analysis of common video production styles and a toolbox for categorizing new formats - independent of their final (a)synchronous use in MOOCs. Keywords: video production, MOOC video styles, live-streaming.}, language = {en} } @misc{RenzShamsMeinel2017, author = {Renz, Jan and Shams, Ahmed and Meinel, Christoph}, title = {Offline-Enabled Web-based E-Learning for Improved User Experience in Africa}, series = {2017 IEEE Africon}, journal = {2017 IEEE Africon}, publisher = {IEEE}, address = {New York}, isbn = {978-1-5386-2775-4}, issn = {2153-0025}, doi = {10.1109/AFRCON.2017.8095574}, pages = {736 -- 742}, year = {2017}, abstract = {Web-based E-Learning uses Internet technologies and digital media to deliver education content to learners. Many universities in recent years apply their capacity in producing Massive Open Online Courses (MOOCs). They have been offering MOOCs with an expectation of rendering a comprehensive online apprenticeship. Typically, an online content delivery process requires an Internet connection. However, access to the broadband has never been a readily available resource in many regions. In Africa, poor and no networks are yet predominantly experienced by Internet users, frequently causing offline each moment a digital device disconnect from a network. As a result, a learning process is always disrupted, delayed and terminated in such regions. This paper raises the concern of E-Learning in poor and low bandwidths, in fact, it highlights the needs for an Offline-Enabled mode. The paper also explores technical approaches beamed to enhance the user experience inWeb-based E-Learning, particular in Africa.}, language = {en} } @article{BinTareafBergerHennigetal.2020, author = {Bin Tareaf, Raad and Berger, Philipp and Hennig, Patrick and Meinel, Christoph}, title = {Cross-platform personality exploration system for online social networks}, series = {Web intelligence}, volume = {18}, journal = {Web intelligence}, number = {1}, publisher = {IOS Press}, address = {Amsterdam}, issn = {2405-6456}, doi = {10.3233/WEB-200427}, pages = {35 -- 51}, year = {2020}, abstract = {Social networking sites (SNS) are a rich source of latent information about individual characteristics. Crawling and analyzing this content provides a new approach for enterprises to personalize services and put forward product recommendations. In the past few years, commercial brands made a gradual appearance on social media platforms for advertisement, customers support and public relation purposes and by now it became a necessity throughout all branches. This online identity can be represented as a brand personality that reflects how a brand is perceived by its customers. We exploited recent research in text analysis and personality detection to build an automatic brand personality prediction model on top of the (Five-Factor Model) and (Linguistic Inquiry and Word Count) features extracted from publicly available benchmarks. Predictive evaluation on brands' accounts reveals that Facebook platform provides a slight advantage over Twitter platform in offering more self-disclosure for users' to express their emotions especially their demographic and psychological traits. Results also confirm the wider perspective that the same social media account carry a quite similar and comparable personality scores over different social media platforms. For evaluating our prediction results on actual brands' accounts, we crawled the Facebook API and Twitter API respectively for 100k posts from the most valuable brands' pages in the USA and we visualize exemplars of comparison results and present suggestions for future directions.}, language = {en} }