@article{HagedornSerthMeinel2023,
  author    = {Hagedorn, Christiane and Serth, Sebastian and Meinel, Christoph},
  title     = {The mysterious adventures of Detective Duke},
  series = {Frontiers in education},
  volume    = {7},
  journal   = {Frontiers in education},
  publisher = {Frontiers Media},
  address   = {Lausanne},
  issn      = {2504-284X},
  doi       = {10.3389/feduc.2022.1016401},
  pages     = {22},
  year      = {2023},
  abstract  = {About 15 years ago, the first Massive Open Online Courses (MOOCs) appeared and revolutionized online education with more interactive and engaging course designs. Yet, keeping learners motivated and ensuring high satisfaction is one of the challenges today's course designers face. Therefore, many MOOC providers employed gamification elements that only boost extrinsic motivation briefly and are limited to platform support. In this article, we introduce and evaluate a gameful learning design we used in several iterations on computer science education courses. For each of the courses on the fundamentals of the Java programming language, we developed a self-contained, continuous story that accompanies learners through their learning journey and helps visualize key concepts. Furthermore, we share our approach to creating the surrounding story in our MOOCs and provide a guideline for educators to develop their own stories. Our data and the long-term evaluation spanning over four Java courses between 2017 and 2021 indicates the openness of learners toward storified programming courses in general and highlights those elements that had the highest impact. While only a few learners did not like the story at all, most learners consumed the additional story elements we provided. However, learners' interest in influencing the story through majority voting was negligible and did not show a considerable positive impact, so we continued with a fixed story instead. We did not find evidence that learners just participated in the narrative because they worked on all materials. Instead, for 10-16\% of learners, the story was their main course motivation. We also investigated differences in the presentation format and concluded that several longer audio-book style videos were most preferred by learners in comparison to animated videos or different textual formats. Surprisingly, the availability of a coherent story embedding examples and providing a context for the practical programming exercises also led to a slightly higher ranking in the perceived quality of the learning material (by 4\%). With our research in the context of storified MOOCs, we advance gameful learning designs, foster learner engagement and satisfaction in online courses, and help educators ease knowledge transfer for their learners.},
  language  = {en}
}
@book{MeinelWillems2014,
  author    = {Meinel, Christoph and Willems, Christian},
  title     = {openHPI : 哈索•普拉特纳研究院的 MOOC（大规模公开在线课）计划},
  number    = {89},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-291-9},
  issn      = {1613-5652},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-70380},
  publisher      = {Universit{\"a}t Potsdam},
  pages     = {22},
  year      = {2014},
  abstract  = {摘要。哈索•普拉特纳研究院 (HPI) 的新型互动在线教育平台 openHPI (https://openHPI.de) 可以为从事信息技术和信息学领域内容的工作和感兴趣的学员提供可自由访问的、免费的在线课程。与斯坦福大学于 2011 年首推，之后也在美国其他精英大学提供的"网络公开群众课"（简称 MOOC）一样，openHPI 同样在互联网中提供学习视频和阅读材料，其中综合了支持学习的自我测试、家庭作业和社交讨论论坛，并刺激对促进学习的虚拟学习团队的培训。与"传统的"讲座平台，比如 tele-TASK 平台 (http://www.tele-task.de) 不同（在该平台中，可调用以多媒体方式记录的和已准备好的讲座），openHPI 提供的是按教学法准备的在线课程。这些课程的开始时间固定，之后在连续六个课程周稳定的提供以多媒体方式准备的、尽可能可以互动的学习材料。每周讲解课程主题的一章。为此在该周开始前会准备一系列学习视频、文字、自我测试和家庭作业材料，课程学员在该周将精力用于处理这些内容。这些计划与一个社交讨论平台相结合，学员在该平台上可以与课程导师和其他学员交换意见、解答问题和讨论更多主题。当然，学员可以自己决定学习活动的类型和范围。他们可以为课程作出自己的贡献，比如在论坛中引用博文或推文。之后其他学员可以评论、讨论或自己扩展这些博文或推文。这样学员、教师和提供的学习内容就在一个虚拟的团体中与社交学习网络相互结合起来。},
  language  = {de}
}
@book{MeinelWillems2013,
  author    = {Meinel, Christoph and Willems, Christian},
  title     = {openHPI : the MOOC offer at Hasso Plattner Institute},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-264-3},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-67176},
  publisher      = {Universit{\"a}t Potsdam},
  pages     = {21},
  year      = {2013},
  abstract  = {The new interactive online educational platform openHPI, (https://openHPI.de) from Hasso Plattner Institute (HPI), offers freely accessible courses at no charge for all who are interested in subjects in the field of information technology and computer science. Since 2011, "Massive Open Online Courses," called MOOCs for short, have been offered, first at Stanford University and then later at other U.S. elite universities. Following suit, openHPI provides instructional videos on the Internet and further reading material, combined with learning-supportive self-tests, homework and a social discussion forum. Education is further stimulated by the support of a virtual learning community. In contrast to "traditional" lecture platforms, such as the tele-TASK portal (http://www.tele-task.de) where multimedia recorded lectures are available on demand, openHPI offers didactic online courses. The courses have a fixed start date and offer a balanced schedule of six consecutive weeks presented in multimedia and, whenever possible, interactive learning material. Each week, one chapter of the course subject is treated. In addition, a series of learning videos, texts, self-tests and homework exercises are provided to course participants at the beginning of the week. The course offering is combined with a social discussion platform where participants have the opportunity to enter into an exchange with course instructors and fellow participants. Here, for example, they can get answers to questions and discuss the topics in depth. The participants naturally decide themselves about the type and range of their learning activities. They can make personal contributions to the course, for example, in blog posts or tweets, which they can refer to in the forum. In turn, other participants have the chance to comment on, discuss or expand on what has been said. In this way, the learners become the teachers and the subject matter offered to a virtual community is linked to a social learning network.},
  language  = {en}
}
@book{MeinelWillems2013,
  author    = {Meinel, Christoph and Willems, Christian},
  title     = {openHPI : das MOOC-Angebot des Hasso-Plattner-Instituts},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-259-9},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-66802},
  publisher      = {Universit{\"a}t Potsdam},
  pages     = {22},
  year      = {2013},
  abstract  = {Die neue interaktive Online-Bildungsplattform openHPI (https://openHPI.de) des Hasso-Plattner-Instituts (HPI) bietet frei zug{\"a}ngliche und kostenlose Onlinekurse f{\"u}r interessierte Teilnehmer an, die sich mit Inhalten aus dem Bereich der Informationstechnologien und Informatik besch{\"a}ftige¬n. Wie die seit 2011 zun{\"a}chst von der Stanford University, sp{\"a}ter aber auch von anderen Elite-Universit{\"a}ten der USA angeboten „Massive Open Online Courses", kurz MOOCs genannt, bietet openHPI im Internet Lernvideos und weiterf{\"u}hrenden Lesestoff in einer Kombination mit lernunterst{\"u}tzenden Selbsttests, Hausaufgaben und einem sozialen Diskussionsforum an und stimuliert die Ausbildung einer das Lernen f{\"o}rdernden virtuellen Lerngemeinschaft. Im Unterschied zu „traditionellen" Vorlesungsportalen, wie z.B. dem tele-TASK Portal (http://www.tele-task.de), bei dem multimedial aufgezeichnete Vorlesungen zum Abruf bereit gestellt werden, bietet openHPI didaktisch aufbereitete Onlinekurse an. Diese haben einen festen Starttermin und bieten dann in einem austarierten Zeitplan von sechs aufeinanderfolgenden Kurswochen multimedial aufbereitete und wann immer m{\"o}glich interaktive Lehrmaterialien. In jeder Woche wird ein Kapitel des Kursthemas behandelt. Dazu werden zu Wochenbeginn eine Reihe von Lehrvideos, Texten, Selbsttests und ein Hausaufgabenblatt bereitgestellt, mit denen sich die Kursteilnehmer in dieser Woche besch{\"a}ftigen. Kombiniert sind die Angebote mit einer sozialen Diskussionsplattform, auf der sich die Teilnehmer mit den Kursbetreuern und anderen Teilnehmern austauschen, Fragen kl{\"a}ren und weiterf{\"u}hrende Themen diskutieren k{\"o}nnen. Nat{\"u}rlich entscheiden die Teilnehmer selbst {\"u}ber Art und Umfang ihrer Lernaktivit{\"a}ten. Sie k{\"o}nnen in den Kurs eigene Beitr{\"a}ge einbringen, zum Beispiel durch Blogposts oder Tweets, auf die sie im Forum verweisen. Andere Lernende k{\"o}nnen diese dann kommentieren, diskutieren oder ihrerseits erweitern. Auf diese Weise werden die Lernenden, die Lehrenden und die angebotenen Lerninhalte in einer virtuellen Gemeinschaft, einem sozialen Lernnetzwerk miteinander verkn{\"u}pft.},
  language  = {de}
}
@article{PrestonYounie2015,
  author    = {Preston, Christina and Younie, Sarah},
  title     = {Mentoring in a Digital World},
  series = {KEYCIT 2014 - Key Competencies in Informatics and ICT},
  journal   = {KEYCIT 2014 - Key Competencies in Informatics and ICT},
  number    = {7},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  issn      = {1868-0844},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-82895},
  pages     = {343 -- 350},
  year      = {2015},
  abstract  = {This paper focuses on the results of the evaluation of the first pilot of an e-mentoring unit designed by the Hands-On ICT consortium, funded by the EU LLL programme. The overall aim of this two-year activity is to investigate the value for professional learning of Massive Online Open Courses (MOOCs) and Community Online Open Courses (COOCs) in the context of a 'community of practice'. Three units in the first pilot covered aspects of using digital technologies to develop creative thinking skills. The findings in this paper relate to the fourth unit about e-mentoring, a skill that was important to delivering the course content in the other three units. Findings about the e-mentoring unit included: the students' request for detailed profiles so that participants can get to know each other; and, the need to reconcile the different interpretations of e-mentoring held by the participants when the course begins. The evaluators concluded that the major issues were that: not all professional learners would self-organise and network; and few would wish to mentor their colleagues voluntarily. Therefore, the e-mentoring issues will need careful consideration in pilots two and three to identify how e-mentoring will be organised.},
  language  = {en}
}
@phdthesis{Renz2020,
  author    = {Renz, Jan},
  title     = {Lebensbegleitendes Lernen in einer digitalen Welt},
  doi       = {10.25932/publishup-47257},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-472573},
  school      = {Universit{\"a}t Potsdam},
  pages     = {vii, 184},
  year      = {2020},
  abstract  = {In unserer digitalisierten Welt verlagert sich das Lernen in die Cloud. Vom Unterricht in der Schule und der Tafel zum Tablet, hin zu einem lebenslangen Lernen in der Arbeitswelt und sogar dar{\"u}ber hinaus. Wie erfolgreich und attraktiv dieses zeitgem{\"a}ße Lernen erfolgt, h{\"a}ngt nicht unwesentlich von den technologischen M{\"o}glichkeiten ab, die digitale Lernplattformen rund um MOOCs und Schul-Clouds bieten. Bei deren Weiterentwicklung sollten statt {\"o}konomischen Messgr{\"o}ßen und KPIs die Lernenden und ihre Lernerfahrungen im Vordergrund stehen. Hierf{\"u}r wurde ein Optimierungsframework entwickelt, das f{\"u}r die Entwicklung von Lernplattformen anhand verschiedener qualitativer und quantitative Methoden Verbesserungen identifiziert, priorisiert und deren Beurteilung und Umsetzung steuert. Datengest{\"u}tzte Entscheidungen sollten auf einer ausreichenden Datenbasis aufbauen. Moderne Web-Anwendungen bestehen aber oft aus mehreren Microservices mit jeweils eigener Datenhaltung. Viele Daten sind daher nicht mehr einfach zug{\"a}nglich. Daher wird in dieser Arbeit ein Learning Analytics Dienst eingef{\"u}hrt, der diese Daten sammelt und verarbeitet. Darauf aufbauend werden Metriken eingef{\"u}hrt, auf deren Grundlage die erfassten Daten nutzbar werden und die somit zu verschiedenen Zwecken verwendet werden k{\"o}nnen. Neben der Visualisierung der Daten in Dashboards werden die Daten f{\"u}r eine automatisierte Qualit{\"a}tskontrolle herangezogen. So kann festgestellt werden, wenn Tests zu schwierig oder die soziale Interaktion in einem MOOC zu gering ist. Die vorgestellte Infrastruktur l{\"a}sst sich aber auch verwenden, um verschiedene A/B/n-Tests durchzuf{\"u}hren. In solchen Tests gibt es mehrere Varianten, die an verschiedene Nutzergruppen in einem kontrollierten Experiment erprobt werden. Dank der vorgestellten Testinfrastruktur, die in der HPI MOOC Plattform eingebaut wurde, kann ermittelt werden, ob sich f{\"u}r diese Gruppen statistisch signifikante {\"A}nderungen in der Nutzung feststellen lassen. Dies wurde mit f{\"u}nf verschiedenen Verbesserungen der HPI MOOC Plattform evaluiert, auf der auch openHPI und openSAP basieren. Dabei konnte gezeigt werden, dass sich Lernende mit reaktivierenden Mails zur{\"u}ck in den Kurs holen lassen. Es ist prim{\"a}r die Kommunikation der unbearbeiteten Lerninhalte des Nutzers, die eine reaktivierende Wirkung hat. Auch {\"U}bersichtsmails, die die Forenaktivit{\"a}t zusammenfassen, haben einen positiven Effekt erzielt. Ein gezieltes On-Boarding kann dazu f{\"u}hren, dass die Nutzer die Plattform besser verstehen und hierdurch aktiver sind. Der vierte Test konnte zeigen, dass die Zuordnung von Forenfragen zu einem bestimmten Zeitpunkt im Video und die grafische Anzeige dieser Informationen zu einer erh{\"o}hten Forenaktivit{\"a}t f{\"u}hrt. Auch die experimentelle Erprobung von unterschiedlichen Lernmaterialien, wie sie im f{\"u}nften Test durchgef{\"u}hrt wurde, ist in MOOCs hilfreich, um eine Verbesserung der Kursmaterialien zu erreichen. Neben diesen funktionalen Verbesserungen wird untersucht wie MOOC Plattformen und Schul-Clouds einen Nutzen bieten k{\"o}nnen, wenn Nutzern nur eine schwache oder unzuverl{\"a}ssige Internetanbindung zur Verf{\"u}gung steht (wie dies in vielen deutschen Schulen der Fall ist). Hier wird gezeigt, dass durch ein geschicktes Vorausladen von Daten die Internetanbindungen entlastet werden k{\"o}nnen. Teile der Lernanwendungen funktionieren dank dieser Anpassungen, selbst wenn keine Verbindung zum Internet besteht. Als Letztes wird gezeigt, wie Endger{\"a}te sich in einem lokalen Peer-to-Peer CDN gegenseitig mit Daten versorgen k{\"o}nnen, ohne dass diese aus dem Internet heruntergeladen werden m{\"u}ssen.},
  language  = {de}
}
@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}
}
@misc{StaubitzMeinel2019,
  author    = {Staubitz, Thomas and Meinel, Christoph},
  title     = {Graded Team Assignments in MOOCs},
  series = {SCALE},
  journal   = {SCALE},
  publisher = {Association for Computing Machinery},
  address   = {New York},
  isbn      = {978-1-4503-6804-9},
  doi       = {10.1145/3330430.3333619},
  pages     = {10},
  year      = {2019},
  abstract  = {The ability to work in teams is an important skill in today's work environments. In MOOCs, however, team work, team tasks, and graded team-based assignments play only a marginal role. To close this gap, we have been exploring ways to integrate graded team-based assignments in MOOCs. Some goals of our work are to determine simple criteria to match teams in a volatile environment and to enable a frictionless online collaboration for the participants within our MOOC platform. The high dropout rates in MOOCs pose particular challenges for team work in this context. By now, we have conducted 15 MOOCs containing graded team-based assignments in a variety of topics. The paper at hand presents a study that aims to establish a solid understanding of the participants in the team tasks. Furthermore, we attempt to determine which team compositions are particularly successful. Finally, we examine how several modifications to our platform's collaborative toolset have affected the dropout rates and performance of the teams.},
  language  = {en}
}