TY - GEN A1 - Renz, Jan A1 - Shams, Ahmed A1 - Meinel, Christoph T1 - Offline-Enabled Web-based E-Learning for Improved User Experience in Africa T2 - 2017 IEEE Africon N2 - 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. KW - Educational Technology KW - E-Learning KW - Internet KW - Bandwidth KW - Mobile Learning KW - Mobiles KW - MOOC KW - Offline-Enabled KW - Ubiquitous Y1 - 2017 SN - 978-1-5386-2775-4 U6 - https://doi.org/10.1109/AFRCON.2017.8095574 SN - 2153-0025 SP - 736 EP - 742 PB - IEEE CY - New York ER - TY - GEN A1 - Staubitz, Thomas A1 - Wilkins, Christian A1 - Hagedorn, Christiane A1 - Meinel, Christoph T1 - The Gamification of a MOOC Platform T2 - Proceedings of 2017 IEEE Global Engineering Education Conference (EDUCON) N2 - Massive Open Online Courses (MOOCs) have left their mark on the face of education during the recent years. At the Hasso Plattner Institute (HPI) in Potsdam, Germany, we are actively developing a MOOC platform, which provides our research with a plethora of e-learning topics, such as learning analytics, automated assessment, peer assessment, team-work, online proctoring, and gamification. We run several instances of this platform. On openHPI, we provide our own courses from within the HPI context. Further instances are openSAP, openWHO, and mooc.HOUSE, which is the smallest of these platforms, targeting customers with a less extensive course portfolio. In 2013, we started to work on the gamification of our platform. By now, we have implemented about two thirds of the features that we initially have evaluated as useful for our purposes. About a year ago we activated the implemented gamification features on mooc.HOUSE. Before activating the features on openHPI as well, we examined, and re-evaluated our initial considerations based on the data we collected so far and the changes in other contexts of our platforms. KW - MOOC KW - Gamification KW - e-learning KW - Massive Open Online Courses Y1 - 2017 SN - 978-1-5090-5467-1 U6 - https://doi.org/10.1109/EDUCON.2017.7942952 SN - 2165-9567 SP - 883 EP - 892 PB - IEEE CY - New York ER - TY - GEN A1 - Staubitz, Thomas A1 - Meinel, Christoph T1 - Collaborative Learning in MOOCs - Approaches and Experiments T2 - 2018 IEEE Frontiers in Education (FIE) Conference N2 - This Research-to-Practice paper examines the practical application of various forms of collaborative learning in MOOCs. Since 2012, about 60 MOOCs in the wider context of Information Technology and Computer Science have been conducted on our self-developed MOOC platform. The platform is also used by several customers, who either run their own platform instances or use our white label platform. We, as well as some of our partners, have experimented with different approaches in collaborative learning in these courses. Based on the results of early experiments, surveys amongst our participants, and requests by our business partners we have integrated several options to offer forms of collaborative learning to the system. The results of our experiments are directly fed back to the platform development, allowing to fine tune existing and to add new tools where necessary. In the paper at hand, we discuss the benefits and disadvantages of decisions in the design of a MOOC with regard to the various forms of collaborative learning. While the focus of the paper at hand is on forms of large group collaboration, two types of small group collaboration on our platforms are briefly introduced. KW - MOOC KW - Collaborative learning KW - Peer assessment KW - Team based assignment KW - Teamwork Y1 - 2018 SN - 978-1-5386-1174-6 SN - 0190-5848 PB - IEEE CY - New York ER - TY - GEN A1 - Staubitz, Thomas A1 - Teusner, Ralf A1 - Meinel, Christoph T1 - MOOCs in Secondary Education BT - Experiments and Observations from German Classrooms T2 - 2019 IEEE Global Engineering Education Conference (EDUCON) N2 - Computer science education in German schools is often less than optimal. It is only mandatory in a few of the federal states and there is a lack of qualified teachers. As a MOOC (Massive Open Online Course) provider with a German background, we developed the idea to implement a MOOC addressing pupils in secondary schools to fill this gap. The course targeted high school pupils and enabled them to learn the Python programming language. In 2014, we successfully conducted the first iteration of this MOOC with more than 7000 participants. However, the share of pupils in the course was not quite satisfactory. So we conducted several workshops with teachers to find out why they had not used the course to the extent that we had imagined. The paper at hand explores and discusses the steps we have taken in the following years as a result of these workshops. KW - MOOC KW - Secondary Education KW - School KW - Teamwork KW - K-12 KW - Programming course KW - Java KW - Python Y1 - 2019 SN - 978-1-5386-9506-7 U6 - https://doi.org/10.1109/EDUCON.2019.8725138 SN - 2165-9567 SP - 173 EP - 182 PB - IEEE CY - New York ER - TY - THES A1 - Staubitz, Thomas T1 - Gradable team assignments in large scale learning environments BT - collaborative learning, teamwork, and peer assessment in MOOCs BT - Kollaboratives Lernen, Teamarbeit und Peer Assessment in MOOCs N2 - Lifelong learning plays an increasingly important role in many societies. Technology is changing faster than ever and what has been important to learn today, may be obsolete tomorrow. The role of informal programs is becoming increasingly important. Particularly, Massive Open Online Courses have become popular among learners and instructors. In 2008, a group of Canadian education enthusiasts started the first Massive Open Online Courses or MOOCs to prove their cognitive theory of Connectivism. Around 2012, a variety of American start-ups redefined the concept of MOOCs. Instead of following the connectivist doctrine they returned to a more traditional approach. They focussed on video lecturing and combined this with a course forum that allowed the participants to discuss with each other and the teaching team. While this new version of the concept was enormously successful in terms of massiveness—hundreds of thousands of participants from all over the world joined the first of these courses—many educators criticized the re-lapse to the cognitivist model. In the early days, the evolving platforms often did not have more features than a video player, simple multiple-choice quizzes, and the course forum. It soon became a major interest of research to allow the scaling of more modern approaches of learning and teaching for the massiveness of these courses. Hands-on exercises, alternative forms of assessment, collaboration, and teamwork are some of the topics on the agenda. The insights provided by cognitive and pedagogical theories, however, do not necessarily always run in sync with the needs and the preferences of the majority of participants. While the former promote action-learning, hands-on-learning, competence-based-learning, project-based-learning, team-based-learning as the holy grail, many of the latter often rather prefer a more laid-back style of learning, sometimes referred to as edutainment. Obviously, given the large numbers of participants in these courses, there is not just one type of learners. Participants are not a homogeneous mass but a potpourri of individuals with a wildly heterogeneous mix of backgrounds, previous knowledge, familial and professional circumstances, countries of origin, gender, age, and so on. For the majority of participants, a full-time job and/or a family often just does not leave enough room for more time intensive tasks, such as practical exercises or teamwork. Others, however, particularly enjoy these hands-on or collaborative aspects of MOOCs. Furthermore, many subjects particularly require these possibilities and simply cannot be taught or learned in courses that lack collaborative or hands-on features. In this context, the thesis discusses how team assignments have been implemented on the HPI MOOC platform. During the recent years, several experiments have been conducted and a great amount of experience has been gained by employing team assignments in courses in areas, such as Object-Oriented Programming, Design Thinking, and Business Innovation on various instances of this platform: openHPI, openSAP, and mooc.house N2 - In einer Zeit stetigen Wandels und immer schneller wechselnder Technologien nimmt das lebenslange Lernen einen immer höheren Stellenwert ein. Massive Open Online Courses (MOOCs) sind ein hervorragendes Werkzeug, um in kurzer Zeit und mit vergleichsweise wenig Aufwand breite Teile der Bevölkerung zu erreichen. Das HPI leistet mit der eigenen Plattform openHPI und den für diverse Partner betriebenen Plattformen openSAP, OpenWHO und mooc.house sowohl im deutschsprachigen Raum als auch international einen wichtigen Beitrag zu digitalen Aufklärung. In vielen Bereichen ist die Plattform State of the Art und ist den international bekannteren Plattformen zumindest ebenbürtig. Gerade bei der Entwicklung und Anwendung von neuen Lehr- und Lernmethoden und deren technischer Unterstützung ist openHPI auch international richtungsweisend. Die vorliegende Dissertation befasst sich mit den Möglichkeiten der technischen und didaktischen Unterstützung von bewertbaren Aufgabenstellungen in MOOCs, die im Team zu bearbeiten sind. Durch die Größe der Kurse—in der Regel steht hier ein kleines Teaching Team mehreren tausend Teilnehmern gegenüber—ist eine manuelle Bewertung der Teilnehmenden durch die Lehrenden nicht möglich. Hier wird eine der alternativen Möglichkeiten zur Bewertung von Aufgaben, das sogenannte Peer Assessment, eingesetzt und für die speziellen Gegebenheiten der Bearbeitung von Aufgaben im Team angepasst. In den vergangenen fünf Jahren wurde eine iterative Langzeitstudie durchgeführt, bei der verschiedene qualitative und quantitative Methoden der Auswertung eingesetzt wurden. Das Ergebnis dieser Forschungsarbeit ist eine tiefgehende Einsicht in die Mechanismen der Teamarbeit in skalierenden digitalen Lernplattformen sowie eine Reihe von Empfehlungen zur weiteren Verbesserung der kollaborativen Eigenschaften der HPI-Plattformen, die zum Teil bereits umgesetzt wurden bzw. gerade umgesetzt werden. T2 - Benotete Teamaufgaben in skalierenden E-Learning-Systemen KW - massive open online courses KW - MOOC KW - collaborative learning KW - online learning KW - teamwork KW - peer assessment KW - digital learning KW - eLearning KW - collaborative work KW - kollaboratives Lernen KW - kollaboratives Arbeiten KW - digitales Lernen KW - MOOC KW - Massive Open Online Courses KW - Online-Lernen KW - Peer Assessment KW - Teamarbeit KW - eLearning Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-471830 ER - TY - CHAP A1 - Jacqmin, Julien A1 - Özdemir, Paker Doğu A1 - Fell Kurban, Caroline A1 - Tunç Pekkan, Zelha A1 - Koskinen, Johanna A1 - Suonpää, Maija A1 - Seng, Cheyvuth A1 - Carlon, May Kristine Jonson A1 - Gayed, John Maurice A1 - Cross, Jeffrey S. A1 - Langseth, Inger A1 - Jacobsen, Dan Yngve A1 - Haugsbakken, Halvdan A1 - Bethge, Joseph A1 - Serth, Sebastian A1 - Staubitz, Thomas A1 - Wuttke, Tobias A1 - Nordemann, Oliver A1 - Das, Partha-Pratim A1 - Meinel, Christoph A1 - Ponce, Eva A1 - Srinath, Sindhu A1 - Allegue, Laura A1 - Perach, Shai A1 - Alexandron, Giora A1 - Corti, Paola A1 - Baudo, Valeria A1 - Turró, Carlos A1 - Moura Santos, Ana A1 - Nilsson, Charlotta A1 - Maldonado-Mahauad, Jorge A1 - Valdiviezo, Javier A1 - Carvallo, Juan Pablo A1 - Samaniego-Erazo, Nicolay A1 - Poce, Antonella A1 - Re, Maria Rosaria A1 - Valente, Mara A1 - Karp Gershon, Sa’ar A1 - Ruipérez-Valiente, José A. A1 - Despujol, Ignacio A1 - Busquets, Jaime A1 - Kerr, John A1 - Lorenz, Anja A1 - Schön, Sandra A1 - Ebner, Martin A1 - Wittke, Andreas A1 - Beirne, Elaine A1 - Nic Giolla Mhichíl, Mairéad A1 - Brown, Mark A1 - Mac Lochlainn, Conchúr A1 - Topali, Paraskevi A1 - Chounta, Irene-Angelica A1 - Ortega-Arranz, Alejandro A1 - Villagrá-Sobrino, Sara L. A1 - Martínez-Monés, Alejandra A1 - Blackwell, Virginia Katherine A1 - Wiltrout, Mary Ellen A1 - Rami Gaddem, Mohamed A1 - Hernández Reyes, César Augusto A1 - Nagahama, Toru A1 - Buchem, Ilona A1 - Okatan, Ebru A1 - Khalil, Mohammad A1 - Casiraghi, Daniela A1 - Sancassani, Susanna A1 - Brambilla, Federica A1 - Mihaescu, Vlad A1 - Andone, Diana A1 - Vasiu, Radu A1 - Şahin, Muhittin A1 - Egloffstein, Marc A1 - Bothe, Max A1 - Rohloff, Tobias A1 - Schenk, Nathanael A1 - Schwerer, Florian A1 - Ifenthaler, Dirk A1 - Hense, Julia A1 - Bernd, Mike ED - Meinel, Christoph ED - Staubitz, Thomas ED - Schweiger, Stefanie ED - Friedl, Christian ED - Kiers, Janine ED - Ebner, Martin ED - Lorenz, Anja ED - Ubachs, George ED - Mongenet, Catherine ED - Ruipérez-Valiente, José A. ED - Cortes Mendez, Manoel T1 - EMOOCs 2021 N2 - From June 22 to June 24, 2021, Hasso Plattner Institute, Potsdam, hosted the seventh European MOOC Stakeholder Summit (EMOOCs 2021) together with the eighth ACM Learning@Scale Conference. Due to the COVID-19 situation, the conference was held fully online. The boost in digital education worldwide as a result of the pandemic was also one of the main topics of this year’s EMOOCs. All institutions of learning have been forced to transform and redesign their educational methods, moving from traditional models to hybrid or completely online models at scale. The learnings, derived from practical experience and research, have been explored in EMOOCs 2021 in six tracks and additional workshops, covering various aspects of this field. In this publication, we present papers from the conference’s Experience Track, the Policy Track, the Business Track, the International Track, and the Workshops. KW - e-learning KW - microcredential KW - MOOC KW - digital education KW - experience KW - online course design KW - online course creation KW - higher education Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-510300 SN - 978-3-86956-512-5 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Gamage, Dilrukshi A1 - Staubitz, Thomas A1 - Whiting, Mark T1 - Peer assessment in MOOCs BT - Systematic literature review JF - Distance education N2 - We report on a systematic review of the landscape of peer assessment in massive open online courses (MOOCs) with papers from 2014 to 2020 in 20 leading education technology publication venues across four databases containing education technology-related papers, addressing three research issues: the evolution of peer assessment in MOOCs during the period 2014 to 2020, the methods used in MOOCs to assess peers, and the challenges of and future directions in MOOC peer assessment. We provide summary statistics and a review of methods across the corpus and highlight three directions for improving the use of peer assessment in MOOCs: the need for focusing on scaling learning through peer evaluations, the need for scaling and optimizing team submissions in team peer assessments, and the need for embedding a social process for peer assessment. KW - MOOC KW - peer assessment KW - peer evaluation KW - peer review KW - literature review KW - social interaction Y1 - 2021 U6 - https://doi.org/10.1080/01587919.2021.1911626 SN - 0158-7919 SN - 1475-0198 VL - 42 IS - 2 SP - 268 EP - 289 PB - Routledge, Taylor & Francis Group CY - Abingdon ER - TY - THES A1 - Teusner, Ralf T1 - Situational interventions and peer feedback in massive open online courses T1 - Situationsabhängige Interventionen und Peer-Feedback in Massive Open Online Courses BT - narrowing the gap between learners and instructors in online programming education N2 - Massive Open Online Courses (MOOCs) open up new opportunities to learn a wide variety of skills online and are thus well suited for individual education, especially where proffcient teachers are not available locally. At the same time, modern society is undergoing a digital transformation, requiring the training of large numbers of current and future employees. Abstract thinking, logical reasoning, and the need to formulate instructions for computers are becoming increasingly relevant. A holistic way to train these skills is to learn how to program. Programming, in addition to being a mental discipline, is also considered a craft, and practical training is required to achieve mastery. In order to effectively convey programming skills in MOOCs, practical exercises are incorporated into the course curriculum to offer students the necessary hands-on experience to reach an in-depth understanding of the programming concepts presented. Our preliminary analysis showed that while being an integral and rewarding part of courses, practical exercises bear the risk of overburdening students who are struggling with conceptual misunderstandings and unknown syntax. In this thesis, we develop, implement, and evaluate different interventions with the aim to improve the learning experience, sustainability, and success of online programming courses. Data from four programming MOOCs, with a total of over 60,000 participants, are employed to determine criteria for practical programming exercises best suited for a given audience. Based on over five million executions and scoring runs from students' task submissions, we deduce exercise difficulties, students' patterns in approaching the exercises, and potential flaws in exercise descriptions as well as preparatory videos. The primary issue in online learning is that students face a social gap caused by their isolated physical situation. Each individual student usually learns alone in front of a computer and suffers from the absence of a pre-determined time structure as provided in traditional school classes. Furthermore, online learning usually presses students into a one-size-fits-all curriculum, which presents the same content to all students, regardless of their individual needs and learning styles. Any means of a personalization of content or individual feedback regarding problems they encounter are mostly ruled out by the discrepancy between the number of learners and the number of instructors. This results in a high demand for self-motivation and determination of MOOC participants. Social distance exists between individual students as well as between students and course instructors. It decreases engagement and poses a threat to learning success. Within this research, we approach the identified issues within MOOCs and suggest scalable technical solutions, improving social interaction and balancing content difficulty. Our contributions include situational interventions, approaches for personalizing educational content as well as concepts for fostering collaborative problem-solving. With these approaches, we reduce counterproductive struggles and create a universal improvement for future programming MOOCs. We evaluate our approaches and methods in detail to improve programming courses for students as well as instructors and to advance the state of knowledge in online education. Data gathered from our experiments show that receiving peer feedback on one's programming problems improves overall course scores by up to 17%. Merely the act of phrasing a question about one's problem improved overall scores by about 14%. The rate of students reaching out for help was significantly improved by situational just-in-time interventions. Request for Comment interventions increased the share of students asking for help by up to 158%. Data from our four MOOCs further provide detailed insight into the learning behavior of students. We outline additional significant findings with regard to student behavior and demographic factors. Our approaches, the technical infrastructure, the numerous educational resources developed, and the data collected provide a solid foundation for future research. N2 - MOOCs (Massive Open Online Courses) ermöglichen es jedem Interessierten sich in verschiedenen Fachrichtungen online weiterzubilden. Sie fördern die persönliche individuelle Entwicklung und ermöglichen lebenslanges Lernen auch dort, wo geeignete Lehrer nicht verfügbar sind. Unsere Gesellschaft befindet sich derzeit in der sogenannten "digitalen Transformation". Von vielen Arbeitnehmern werden in diesem Zusammenhang zunehmend Fähigkeiten wie abstraktes Denken und logisches Schlussfolgern erwartet. Das Erlernen einer Programmiersprache ist eine geeignete Möglichkeit, diese Fähigkeiten zu erlangen. Obwohl Programmieren als geistige Disziplin angesehen wird, ist es zu einem gewissen Grad auch ein Handwerk, bei dem sich das individuelle Können insbesondere durch stetige praktische Anwendung entwickelt. Um Programmierkenntnisse effektiv in einem MOOC zu vermitteln, sollten daher praktische Aufgaben von vornherein in den Lehrstoff des Kurses integriert werden, um die vorgestellten Konzepte geeignet zu vertiefen und zu festigen. Neben den positiven Aspekten für die Lernenden weisen praktische Programmieraufgaben jedoch auch ein erhöhtes Frustpotential auf. Kryptische Fehlermeldungen und teils unbekannte Syntax überfordern insbesondere diejenigen Teilnehmer, welche zusätzlich mit konzeptionellen Missverständnissen zu kämpfen haben. Im Rahmen dieser Arbeit entwickeln und analysieren wir mehrere Interventionsmöglichkeiten um die Lernerfahrung und den Lernerfolg von Teilnehmern in Programmier-MOOCs zu verbessern. Daten von über 60.000 Teilnehmern aus vier Programmier-MOOCs bilden die Grundlage für eine Analyse von Kriterien für geeignete Programmieraufgaben für spezifische Teilnehmergruppen. Auf Basis von 5 Millionen Codeausführungen von Teilnehmern leiten wir Schwachstellen in Aufgaben und typische Herangehensweisen der Teilnehmer ab. Die Hauptschwierigkeit beim Lernen in einer virtuellen Umgebung ist die durch physische Isolation hervorgerufene soziale Entkopplung. Jeder Teilnehmer lernt alleine vor einem Bildschirm, ein gemeinsamer Stundenplan wie im klassischen Schulunterricht fehlt. Weiterhin präsentieren bestehende online Kurse den Teilnehmern in der Regel lediglich universell einsetzbare Lerninhalte, welche in keiner Weise auf die jeweiligen Bedürfnisse und Vorerfahrungen der individuellen Teilnehmer angepasst sind. Personalisierte Lerninhalte bzw. individuelles Feedback sind in MOOCs aufgrund der großen Anzahl an Teilnehmern und der nur kleinen Anzahl an Lehrenden oft nur schwer bzw. gar nicht zu realisieren. Daraus resultieren wiederum hohe Anforderungen an das individuelle Durchhaltevermögen und die Selbstmotivation der MOOC-Teilnehmer. Die soziale Entkopplung manifestiert sich sowohl zwischen den Teilnehmern untereinander als auch zwischen den Lehrenden und den Teilnehmern. Negative Folgen sind ein häufig verringertes Engagement und damit eine Gefährdung des Lernerfolgs. In dieser Arbeit schlagen wir als Gegenmaßnahme skalierbare technische Lösungen vor, um die soziale Interaktion zu verbessern und inhaltliche Schwierigkeiten zu überwinden. Unsere wissenschaftlichen Beiträge umfassen situationsabhängige Interventionen, Ansätze zur Personalisierung von Lerninhalten, sowie Konzepte und Anreize zur Verbesserung der Kollaboration der Teilnehmer untereinander. Mit diesen Maßnahmen schaffen wir es, kontraproduktive Blockaden beim Lernen zu lösen und stellen damit einen universell einsetzbaren Ansatz zur Verbesserung von zukünftigen Progammier-MOOCs bereit. Die aus unseren Experimenten gesammelten Daten zeigen, dass bei Programmierproblemen gewährtes Feedback von anderen Teilnehmern die Gesamtpunktzahl innerhalb des Teilnehmerfeldes durchschnittlich um bis zu 17% verbessert. Bereits das Formulieren des jeweiligen individuellen Problems verbesserte die Gesamtpunktzahl um etwa 14%. Durch situative Interventionen konnte weiterhin der Anteil der Teilnehmer, die nach Hilfe fragen, um bis zu 158% gesteigert werden. Die gesammelten Daten aus unseren vier MOOCs ermöglichen darüber hinaus detaillierte Einblicke in das Lernverhalten der Teilnehmer. Wir zeigen zusätzlich Erkenntnisse in Bezug auf das Verhalten der Teilnehmer und zu demografischen Faktoren auf. Die in dieser Arbeit beschriebenen Ansätze, die geschaffene technische Infrastruktur, das entworfene Lehrmaterial, sowie der umfangreiche gesammelte Datenbestand bilden darüber hinaus eine vielversprechende Grundlage für weitere zukünftige Forschung. KW - programming KW - MOOC KW - intervention KW - collaboration KW - peer feedback KW - Programmierung KW - MOOC KW - Interventionen KW - Kollaboration KW - Peer-feedback Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-507587 ER - TY - CHAP A1 - Rüdian, Sylvio Leo A1 - Haase, Jennifer A1 - Pinkwart, Niels T1 - The relation of convergent thinking and trace data in an online course T2 - Die 19. Fachtagung Bildungstechnologien (DELFI) / Lecture Notes in Informatics (LNI) N2 - Many prediction tasks can be done based on users’ trace data. In this paper, we explored convergent thinking as a personality-related attribute and its relation to features gathered in interactive and non-interactive tasks of an online course. This is an under-utilized attribute that could be used for adapting online courses according to the creativity level to enhance the motivation of learners. Therefore, we used the logfile data of a 60 minutes Moodle course with N=128 learners, combined with the Remote Associates Test (RAT). We explored the trace data and found a weak correlation between interactive tasks and the RAT score, which was the highest considering the overall dataset. We trained a Random Forest Regressor to predict convergent thinking based on the trace data and analyzed the feature importance. The result has shown that the interactive tasks have the highest importance in prediction, but the accuracy is very low. We discuss the potential for personalizing online courses and address further steps to improve the applicability. KW - Convergent thinking KW - creativity KW - online course KW - MOOC KW - prediction Y1 - 2021 UR - https://dl.gi.de/bitstream/handle/20.500.12116/37008/DELFI_2021_181-186.pdf?sequence=1 SP - 181 EP - 186 PB - Gesellschaft für Informatik CY - Bonn ER - TY - BOOK A1 - Meinel, Christoph A1 - Willems, Christian A1 - Staubitz, Thomas A1 - Sauer, Dominic A1 - Hagedorn, Christiane T1 - openHPI T1 - openHPI BT - 10 Years of MOOCs at the Hasso Plattner Institute BT - 10 Jahre MOOCs am Hasso-Plattner-Institut N2 - On the occasion of the 10th openHPI anniversary, this technical report provides information about the HPI MOOC platform, including its core features, technology, and architecture. In an introduction, the platform family with all partner platforms is presented; these now amount to nine platforms, including openHPI. This section introduces openHPI as an advisor and research partner in various projects. In the second chapter, the functionalities and common course formats of the platform are presented. The functionalities are divided into learner and admin features. The learner features section provides detailed information about performance records, courses, and the learning materials of which a course is composed: videos, texts, and quizzes. In addition, the learning materials can be enriched by adding external exercise tools that communicate with the HPI MOOC platform via the Learning Tools Interoperability (LTI) standard. Furthermore, the concept of peer assessments completed the possible learning materials. The section then proceeds with further information on the discussion forum, a fundamental concept of MOOCs compared to traditional e-learning offers. The section is concluded with a description of the quiz recap, learning objectives, mobile applications, gameful learning, and the help desk. The next part of this chapter deals with the admin features. The described functionality is restricted to describing the news and announcements, dashboards and statistics, reporting capabilities, research options with A/B testing, the course feed, and the TransPipe tool to support the process of creating automated or manual subtitles. The platform supports a large variety of additional features, but a detailed description of these features goes beyond the scope of this report. The chapter then elaborates on common course formats and openHPI teaching activities at the HPI. The chapter concludes with some best practices for course design and delivery. The third chapter provides insights into the technology and architecture behind openHPI. A special characteristic of the openHPI project is the conscious decision to operate the complete application from bare metal to platform development. Hence, the chapter starts with a section about the openHPI Cloud, including detailed information about the data center and devices, the used cloud software OpenStack and Ceph, as well as the openHPI Cloud Service provided for the HPI. Afterward, a section on the application technology stack and development tooling describes the application infrastructure components, the used automation, the deployment pipeline, and the tools used for monitoring and alerting. The chapter is concluded with detailed information about the technology stack and concrete platform implementation details. The section describes the service-oriented Ruby on Rails application, inter-service communication, and public APIs. It also provides more information on the design system and components used in the application. The section concludes with a discussion of the original microservice architecture, where we share our insights and reasoning for migrating back to a monolithic application. The last chapter provides a summary and an outlook on the future of digital education. N2 - Anlässlich des 10-jährigen Jubiläums von openHPI informiert dieser technische Bericht über die HPI-MOOC-Plattform einschließlich ihrer Kernfunktionen, Technologie und Architektur. In einer Einleitung wird die Plattformfamilie mit allen Partnerplattformen vorgestellt; diese belaufen sich inklusive openHPI aktuell auf neun Plattformen. In diesem Abschnitt wird außerdem gezeigt, wie openHPI als Berater und Forschungspartner in verschiedenen Projekten fungiert. Im zweiten Kapitel werden die Funktionalitäten und gängigen Kursformate der Plattform präsentiert. Die Funktionalitäten sind in Lerner- und Admin-Funktionen unterteilt. Der Bereich Lernerfunktionen bietet detaillierte Informationen zu Leistungsnachweisen, Kursen und den Lernmaterialien, aus denen sich ein Kurs zusammensetzt: Videos, Texte und Quiz. Darüber hinaus können die Lernmaterialien durch externe Übungstools angereichert werden, die über den Standard Learning Tools Interoperability (LTI) mit der HPI MOOC-Plattform kommunizieren. Das Konzept der Peer-Assessments rundet die möglichen Lernmaterialien ab. Der Abschnitt geht dann weiter auf das Diskussionsforum ein, das einen grundlegenden Unterschied von MOOCs im Vergleich zu traditionellen E-Learning-Angeboten darstellt. Zum Abschluss des Abschnitts folgen eine Beschreibung von Quiz-Recap, Lernzielen, mobilen Anwendungen, spielerischen Lernens und dem Helpdesk. Der nächste Teil dieses Kapitels beschäftigt sich mit den Admin-Funktionen. Die Funktionalitätsbeschreibung beschränkt sich Neuigkeiten und Ankündigungen, Dashboards und Statistiken, Berichtsfunktionen, Forschungsoptionen mit A/B-Tests, den Kurs-Feed und das TransPipe-Tool zur Unterstützung beim Erstellen von automatischen oder manuellen Untertiteln. Die Plattform unterstützt außerdem eine Vielzahl zusätzlicher Funktionen, doch eine detaillierte Beschreibung dieser Funktionen würde den Rahmen des Berichts sprengen. Das Kapitel geht dann auf gängige Kursformate und openHPI-Lehrveranstaltungen am HPI ein, bevor es mit einigen Best Practices für die Gestaltung und Durchführung von Kursen schließt. Zum Abschluss des technischen Berichts gibt das letzte Kapitel eine Zusammenfassung und einen Ausblick auf die Zukunft der digitalen Bildung. Ein besonderes Merkmal des openHPI-Projekts ist die bewusste Entscheidung, die komplette Anwendung von den physischen Netzwerkkomponenten bis zur Plattformentwicklung eigenständig zu betreiben. Bei der vorliegenden deutschen Variante handelt es sich um eine gekürzte Übersetzung des technischen Berichts 148, bei der kein Einblick in die Technologien und Architektur von openHPI gegeben wird. Interessierte Leser:innen können im technischen Bericht 148 (vollständige englische Version) detaillierte Informationen zum Rechenzentrum und den Geräten, der Cloud-Software und dem openHPI Cloud Service aber auch zu Infrastruktur-Anwendungskomponenten wie Entwicklungstools, Automatisierung, Deployment-Pipeline und Monitoring erhalten. Außerdem finden sich dort weitere Informationen über den Technologiestack und konkrete Implementierungsdetails der Plattform inklusive der serviceorientierten Ruby on Rails-Anwendung, die Kommunikation zwischen den Diensten, öffentliche APIs, sowie Designsystem und -komponenten. Der Abschnitt schließt mit einer Diskussion über die ursprüngliche Microservice-Architektur und die Migration zu einer monolithischen Anwendung. T3 - Technische Berichte des Hasso-Plattner-Instituts für Digital Engineering an der Universität Potsdam - 148 KW - openHPI KW - MOOC KW - digital learning platform KW - digital enlightenment KW - lifelong learning KW - openHPI KW - MOOC KW - digitale Lernplattform KW - digitale Aufklärung KW - lebenslanges Lernen Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-560208 SN - 978-3-86956-544-6 SN - 1613-5652 SN - 2191-1665 IS - 148 PB - Universitätsverlag Potsdam CY - Potsdam ER -